TÜRKIYE AT THE FRONTIER Human Capital Utilization, Jobs and Equity TECHNICAL DIAGNOSTIC © 2024 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy, completeness, or currency of the data included in this work and does not assume responsibility for any errors, omissions, or discrepancies in the information, or liability with respect to the use of or failure to use the information, methods, processes, or conclusions set forth. 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Design: Will Kemp, GCS, World Bank Group Contents Acknowledgements ix Executive Summary xi 1 Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 1 Aim, Motivation and Framework 2 Context and Overall Benchmarking: Türkiye and Global Trends 10 Institutions 22 2 Labor Capital: Activating Markets 27 Getting Skills to Work 28 Restructuring Labor Markets 42 Leveraging Labor Policies and Programs 70 3 Financial Capital: Expanding Resilience and Assets 83 Assessing Firms and Employment Resilience to Shocks 84 Adapting Firms and Jobs to the Green Transition 87 Leveling Financial Services Inclusion and Entrepreneurship 91 4 Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 103 Evolving Household Time Use and Roles 104 From National to Local Public Representation 113 E-Service Delivery and Outreach for Economic Inclusion 116 5 Outlook: Holistic Systems for Equitable Utilization 125 Maximizing Whole-of-Government Action for Outreach 126 Integrated Human Capital and Jobs Framework 128 Annex 135 Trends in World Bank Portfolio on Gender-Tagged Investment Projects 135 Mapping of Selected Projects Supported by International Partners 136 E-Systems for Addressing Labor Market Vulnerability 141 Tables Table ES-1.  Ten key achievements and frontier challenges to gender-inclusive human capital and jobs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii Table ES-2.  Integrated human capital and jobs framework: Ten measures for overall and gender equity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Table 1.  Global benchmarking, selected proxy indicators: holistic gender-inclusive human capital utilization over time. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Table 2.  Vocational and technical secondary enrollment among total and women's populations, Türkiye, selected countries, 2005 versus 2017 % secondary enrollment). . . . . . . . . . . . 30 Table 3.  Children registered in schools whose parents are seasonal agricultural workers. . . . . . 35 Table 4.  Employment rates by regional zone by gender, aged 25–34 years, 2010 versus 2022 (% and percentage change). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Table 5.  Most vulnerable sectors, by gender. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 Table 6.  Vulnerability components across selected sectors, 2021. . . . . . . . . . . . . . . . . . . . . . . . 86 Table 7.  Selected grouped indicators, World Bank Women Business and the Law, Türkiye, 2000 versus 2023 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Table 8.  Selected detailed indicators, World Bank Women Business and the Law, Türkiye, 2023. 92 Table 9.  Summary of e-METIP features. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Table 10.  E-METIP: summary of relevant global models and complementary features. . . . . . . . . 123 Table 11.  Ten achievements and frontier challenges to gender-inclusive human capital and jobs. 132 Table 12.  Integrated human capital and jobs framework: ten measures for overall and gender equity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Table 13.  Summary of internationally financed jobs projects by target and type. . . . . . . . . . . . . . 136 Table 14.  Detailed description of internationally financed jobs projects. . . . . . . . . . . . . . . . . . . . 137 Figures Figure 1.  Proposed conceptual framework: multidimensional human capital utilization for equitable growth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Figure 2.  Poverty and social exclusion composite index by gender, national data, At-Risk-of- Poverty or Social Exclusion (AROPE) rate (%) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Figure 3.  Human capital index versus share of youth not in employment, education or training (NEET). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Figure 4.  Labor force participation rates by gender, female versus male, Türkiye and global, 2020–2021 (%) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Figure 5.  Social expenditures (SOCX) and human capital index (HCI), Türkiye and global. . . . . . . 17 Figure 6.  Institutions: Scaleable economic gender inclusion programs, social services and pilots in Turkiye, implemented 2016–2023. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Figure 7.  Secondary schooling rate among girls, 2010 versus 2021 (net, %). . . . . . . . . . . . . . . . . 29 Figure 8.  Literacy rates, by gender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Figure 9.  School enrollment, primary and secondary (gross), gender parity index (GPI). . . . . . . . . 30 Figure 10.  Share of youth neither in employment nor in education (NEET) over time, by gender (%). . 30 Figure 11.  TIMSS: Average math and science scores for fifth and eighth graders by gender, 2019 . . 33 Figure 12.  Total number of most disadvantaged students by region (NUTS–170), 2022 . . . . . . . . . . 34 Figure 13.  Percentage of most disadvantaged students by region and grade level (NUTS–171). . . . 34 Figure 14.  Children contributing to household chores by weekly hours and gender. . . . . . . . . . . . 36 Figure 15.  Employment rate among children by age group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Figure 16.  Regional PISA scores, (NUTS–1), 2018 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Figure 17.  TIMSS (2019) regional Differences (NUTS–1), 2019. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Figure 18.  PISA 2018 scores by school type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Figure 19.  Experiments versus TIMSS science scores. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Figure 20.  Profile of the working age population in Türkiye, as of 2022 (millions, %). . . . . . . . . . . . 43 Figure 21.  Labor force participation rates by gender over time (%). . . . . . . . . . . . . . . . . . . . . . . . . . 46 Figure 22.  Labor force participation versus human capital index among women, Türkiye, global . . 46 Figure 23.  Selected labor indicators, by age group and gender, 2022. . . . . . . . . . . . . . . . . . . . . . . 47 Figure 24.  Labor force participation by gender and education, 2014 versus 2022 (thousands). . . . 47 Figure 25.  Labor force participation rate among women (aged 15+ years) by regional zone, 2010 versus 2022. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Figure 26.  Unemployment (thousands) by gender and education, 2014 versus 2022 . . . . . . . . . . . 48 Figure 27.  Unemployment rates over time by gender (aged 15+ years) . . . . . . . . . . . . . . . . . . . . . . 49 Figure 28.  Youth unemployment rates over time by gender (aged 15–24) . . . . . . . . . . . . . . . . . . . . 49 Figure 29.  Unemployment rate by gender and education, 2014 versus 2022 . . . . . . . . . . . . . . . . 50 Figure 30.  Registered unemployed by occupation and gender, 2021 (%). . . . . . . . . . . . . . . . . . . . 50 Figure 31.  Employment rates by regional zone among women, 2022 (%) . . . . . . . . . . . . . . . . . . . 52 Figure 32.  Share of employment by category and by gender over time (%) . . . . . . . . . . . . . . . . . . . 53 Figure 33.  Educational composition of the adult employed population by gender, 2021–22 (aged 25–64 yrs). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 Figure 34.  Share of jobs and job growth by regional zone, 2010 versus 2022. . . . . . . . . . . . . . . . 55 Figure 35.  Share of jobs by sector across regional zones, 2022. . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Figure 36.  Change in jobs by sector and regional zone, 2014 versus 2022. . . . . . . . . . . . . . . . . . 56 Figure 37.  Sectoral employment distribution by gender over time. . . . . . . . . . . . . . . . . . . . . . . . . 56 Figure 38.  Jobs by economic activity and gender (thousands), 2014–2022. . . . . . . . . . . . . . . . . . . 57 Figure 39.  Job growth by economic activity and gender, 2022 versus 2014 (percentage change). . . 57 Figure 40.  Share of informal and formal employment by worker profile 2020 (%) . . . . . . . . . . . . . 58 Figure 41.  Informal overall employment rates over time among agricultural versus non- agricultural workers (%). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Figure 42.  Overall rate of informal employment by gender over time (%). . . . . . . . . . . . . . . . . . . . 59 Figure 43.  Nominal gender income gap over time by employment category (percentage difference of men's average income relative to women's). . . . . . . . . . . . . . . . . . . . . . . 62 Figure 44.  Real income by sector versus real minimum wage over time (real average annual income as a share of minimum wage, percentage difference). . . . . . . . . . . . . . . . . . . . 62 Figure 45.  Average annual wages among full-time employees across OECD countries during 2018–2022 (US$ PPP) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Figure 46.  Determinants of employment type on wages [odds p (wage informal)/p (wage formal)]. . . 64 Figure 47.  Determinants of labor income among formal wage employment (LN (income) | wage formal). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Figure 48.  Determinants of labor income among informal wage employment (LN (income) | wage informal). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Figure 49.  Determinants of labor income among formal self-employment (LN (income) | Self- employed formal) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 Figure 50.  Determinants of labor income among informal self-employment (LN (income) | Self- employed informal). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Figure 51.  Share of all individuals not working covered under labor programs by gender, 2022 (%). . 70 Figure 52.  Coverage of national labor programs overall and by gender over time (% of registered unemployed) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Figure 53.  Distribution of internationally-financed jobs projects by target group (gender) and type in Turkiye, 2015–2024 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Figure 54.  Jobseeker demand for on-the-job training by occupation (OJT, İŞKUR programs), 2010 versus 2020 (% of registered unemployed). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Figure 55.  Distribution of total vacancy rates for 2010 and 2020 versus the share of women's job placement rate for 2020, 2010 versus 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Figure 56.  Mapping of sectoral job vacancies, unfilled rate and female placement (panels A–C), 2020. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 Figure 57.  Illustrative mapping of employment vulnerability by sectoral vulnerability, 2018–2021 . . 85 Figure 58.  Share of jobs that will require upskilling due to greening by province, 2019 (NUTS–2). . . 88 Figure 59.  Gender and age distribution by green job categories, 2019 . . . . . . . . . . . . . . . . . . . . . 89 Figure 60.  Wide variance in sub-sectoral jobs (NACE 2-digit classification of types of jobs affected by greening and use of green skills, 2019). . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 Figure 61.  Green jobs by educational level and share of green jobs by education level, 2019 (%). . . 91 Figure 62.  Financial inclusion indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Figure 63.  Association between financial accounts ownership and wage employment among women, global, 2005–2022. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Figure 64.  Relationship between financial accounts and labor force participation among women, Türkiye and global (2005–2022) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Figure 65.  Share of employers by gender, 2011–2022 (%). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Figure 66.  Proportion of individuals in senior or middle management positions by gender (%). . . . 97 Figure 67.  Women employers as share of women’s employment by regional zone (NUTS–2), 2021 (%). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 Figure 68.  Women senior officials, managers and professionals as share of total by regional zone (NUTS2), 2021 (%). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Figure 69.  Full- and part-time work by gender, 2010 versus 2022 (thousands, % of wage employment). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Figure 70.  Time use on household care versus employment by gender among ages 15+ years, 2006 and 2015 (number of hours) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Figure 71.  Time use for household care and employment by gender and education, 2015 (number of hours) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Figure 72.  Association between age at first marriage and labor force participation rates (LFPR) across provinces by gender, 2022. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Figure 73.  Time spent on paid and unpaid work by gender, Türkiye and OECD. . . . . . . . . . . . . . 107 Figure 74.  Perceptions of women’s work by demographics over time . . . . . . . . . . . . . . . . . . . . . . 108 Figure 75.  Nursery rate among children by region over time, 2006 and 2016 (% of children) . . . . . 111 Figure 76.  Public and private education expenditures by educational level and by household quintile over time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 Figure 77.  Representation in national parliaments (proportion of seats held by women), Türkiye and selected countries, 2021 (%). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 Figure 78.  Representation in assembly by gender, Türkiye, 1999–2022 (%). . . . . . . . . . . . . . . . . . 114 Figure 79.  Women’s representation in regional development agencies, 2020–2021 (% of staff who are women). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Figure 80.  Regional development agencies by region, 2021. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Figure 81.  Türkiye: Stylized typology of human capital utilization across occupational profiles. . . 127 Figure 82.  World Bank-financed project approvals tagged as gender-inclusive in Türkiye and global regions over time, 2017–2023. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Figure 83.  World Bank-financed project approvals tagged as gender-inclusive in Türkiye by theme, 2017–2023 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Boxes Box 1.  Selected women’s national economic inclusion policy framework and selected programs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Box 2.  Internal migration, refugees and jobs for women and men on the move. . . . . . . . . . . . . 44 Box 3.  Gender occupational choice perceptions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Box 4.  Applying Türkiye’s e-learning platform EBA model for vulnerable adults and youth neet . 117 Box 5.  Relevant examples of approaches to supporting gender equity in economic inclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 Türkiye in Transition: Next-­Generation Human Capital Investments for Inclusive Jobs Acknowledgements This technical note was prepared as part of the World Bank’s Türkiye Human Capital Dialogue with the Government of Türkiye over 2019–2023 and Public Financial Review, serving as background for the World Bank’s forthcoming Country Partnership Framework and Systematic Country Diagnostic. The team comprises Heba Elgazzar (Lead Economist, Program Leader, Human Development and Social Protection and Jobs), Aysenur Acar (Economic Consultant), Ahmet Anil (Operations Consultant), Joel Reyes (Senior Institutional Development Specialist, Education), Mattia Makovec (Senior Economist, Social Protection and Jobs), Alina Petric (Social Protection Specialist), Efsan Ozen (Economist, Social Protection and Jobs), Sirma Seker (Senior Economist, Social Protection and Jobs), Daniel Garotte (Economist, Social Protection and Jobs), Laurent Bossavie (Senior Economist, Social Protection and Jobs), Derya Barlak (Program Assistant), Secil Paker (Program Assistant), Dhushyanth Raju (Lead Economist, Social Protection and Jobs), Husein Abdul-Hamid (Senior Education Specialist), Imren Arsanoglu (Operations), Bilgen Kahraman (Communications), Ayse Ozge Bayram (Communications), Sandra Sargent (Senior Digital Development Specialist), Kasia Jakimowicz (Digital Development, Consultant), Claire Hollweg (Senior Economist, Macroeconomics and Trade), Ali Abukumail (Senior Private Sector Specialist), Stefka Slavova (Lead Economist, Private Sector/ Innovation), Gunhild Berg (Lead Financial Sector Economist), Etkin Ozen (Senior Financial Sector Specialist), Murat Onur (Social Development Specialist), Natacha Lemasle (Senior Social Development Specialist) and Rene Leon Solano (Lead Economist, Program Leader, Human Development). The work benefited from helpful inputs and discussions with Tunya Celasin (Senior External Affairs Officer), Indira Chand (Senior External Affairs Officer), Mirey Ovadiya (Senior Social Protection Specialist), Safir Sumer (Human Development Specialist), Nadwa Rafeh (Senior Health Economist), Fisun Altinbas (Executive Assistant), Aaron Buchsbaum (Senior Knowledge Management Officer), Indira Chand (Senior External Affairs Officer), Mustafa Alver (Senior Country Officer), Selcuk Ruscuklu (Senior Program Assistant, Portfolio Monitoring), Eavan O’Halloran (Country Program Coordinator), Hans Beck (Program Leader, Equitable Growth, Finance and Institutions), Laurent Debroux (Program Leader, Sustainable Development) and Stephan Garnier (Program Leader, Infrastructure), Laura Rawlings (Lead Economist, Gender), Diego Javier Ubfal (Senior Economist, Gender), Tazeen Hasan (Senior Operations Officer, Gender), Abhilasha Sahay (Economist, Gender), Cigdem Celik (Economist, Poverty), Samuel Freije-Rodriguez (Lead Economist, Poverty), Sammar Essmat (Senior Officer, Gender, IFC), Juliana Victor (Senior Operations Officer, Development Effectiveness), Besa Rizvanolli (Operations, Development Effectiveness), Michael Weber (Senior Economist, Human Capital), Federica Saliola (Lead Economist and Manager, Jobs Group) and Arnaud Dupoizat (Country Manager, IFC). The team appreciates the helpful feedback and advice by peer reviewers Truman Packard (Practice Leader and Lead Economist, Human Development, Latin America and Caribbean), Elena Ianchovichina (Deputy Chief Economist, Chief Economist’s Office, Latin America and Caribbean), and Tom Farole (Lead Economist, Sustainable Development). The team sincerely thanks Will Kemp, Designer, Global Publications Support, and team for publication support. Acknowledgements ix The work benefited from overall guidance by Humberto Lopez (Country Director, Türkiye), Michal Rutkowski (Regional Director, Human Development, Europe and Central Asia, recent Global Director, Social Protection and Jobs), Fadia Saadah (recent Regional Director, Human Development, Europe and Central Asia), Paolo Belli (Practice Manager, Social Protection and Jobs, Europe and Central Asia), Cem Mete (Practice Manager, Social Protection and Jobs), Hana Brixi (Global Director, Gender Group), Iffath Sharif (Global Director, Social Protection and Jobs, recent Manager, Human Capital Project), and global initiatives by the World Bank’s Social Protection and Jobs Global Practice, Human Capital Project, and Gender Group. The work accompanies the World Bank’s Türkiye Human Capital skills and jobs knowledge- sharing series (2019–2023), including Women, Business and the Law in Turkey: Unlocking Jobs; Labor Returns to Education and the Green Transition; Informality, Productivity and Risk-Sharing for a Green Economy; Supporting Firms in Creating Formal Jobs: Emerging Opportunities for Turkey; Gender, Human Capital and Jobs Consultations and Jobs Forum Workshops; and the associated components of the analysis released during preparation, including Much ado about nothing? The next generation of human capital investments, skill; and labor in Turkey and beyond1; Back to the future: Harnessing women’s capital for new growth in Turkey2; Can shocks accelerate human capital and jobs transformation in Türkiye?3. The work assesses historical trends and global benchmarking; it is not intended to necessarily capture real-time aspects by the time of publication, which future work may evaluate. As of 2022, “Türkiye” has become the official country name and all efforts have been made to replace “Turkey” in this note where possible, with any possible errors or omissions remaining inadvertent. The findings reflect analysis conducted by the authors based on data and information available. The team wholeheartedly thanks the Government of Türkiye for helpful discussions and the availability of survey and administrative data published routinely by national agencies, notably the Turkish Statistical Institute (TURKSTAT/TUIK), Ministry of Treasury and Finance, Ministry of National Education, Ministry of Labor and Social Security, Turkish Employment Agency (ISKUR), Turkish Social Security Institute (SGK), Ministry of Family and Social Services, and other relevant agencies. The team also appreciates non-governmental national and international stakeholders for invaluable discussions and inputs. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. 1 See https://blogs.worldbank.org/europeandcentralasia/the-next-generation-of-human-capital-investments-skills​ -and-labor-in-Turkey-and-beyond 2 See https://blogs.worldbank.org/europeandcentralasia/back-future-harnessing-womens-capital-new-growth-turkey 3 See https://blogs.worldbank.org/europeandcentralasia/can-shocks-accelerate-human-capital-and-jobs​ -transformation-turkiye x Türkiye in Transition: Next-­Generation Human Capital Investments for Inclusive Jobs Executive Summary This note aims to assess human capital utilization in terms of inclusive jobs in Türkiye towards broadening economic resilience, with a focus on gender equity given the profile of the vulnerable labor force. Türkiye’s early human capital foundations have paved the way for poverty reduction and labor force participation, today facing new multi-dimensional challenges. Türkiye’s investments have historically helped diversify and increase aggregate growth, propelling it to upper middle-income status. Yet relative to overall growth more recently, human capital utilization in terms of jobs and have not necessarily kept pace. Over half the population remains either out of the labor force or employed in informal, relatively low- paying jobs, most of whom have been women. Economic vulnerabilities remain following the Coronavirus pandemic (COVID) and the 2023 earthquakes in southeastern Türkiye, compounded by long-term effects of global financial crises and regional conflicts since 2008. Helping vulnerable workers, largely comprising women, adapt to a changing labor market will be needed to sustain a broad, productive workforce for future broad-based growth. As Türkiye embarks on its forthcoming Twelfth Five-Year National Development Plan, a diagnostic of human capital and jobs programs and policies in terms of gender equity is timely for informing future needs. In addition, a review of Türkiye’s experience will equally help provide global knowledge for other countries facing similar challenges. This note aims to assess human capital utilization in terms of inclusive jobs and gender equity in Türkiye towards broadening economic resilience following shocks. Human capital utilization in this note refers to labor market outcomes including labor force participation, employment and job quality-related outcomes such as earnings, labor support and social risk protection. Building on public expenditure analysis, the note primarily examines the role of multi-dimensional labor market policies for supporting the most vulnerable populations in general as well as gender equity. The assessment adopts a novel holistic framework that focuses maximizing human capital utilization through inclusive labor markets in terms of Executive Summary xi three inter-linked dimensions: labor capital and associated financial capital and social capital dimensions. The analysis complements other work on broader issues in depth outside the scope of this note. The work takes stock of key national and international literature to date and incorporates global benchmarking and original analysis using national statistical data. The note culminates by distilling a typology of profiles and policy recommendations into an integrated human capital and jobs framework, including both overall and gender-specific measures. Türkiye’s foundational human capital and labor policies have historically been comprehensive yet pending gaps in gender equity remain, suggesting adaptation to evolving needs lags. Over the past century, Türkiye has invested in foundational legislative and public service delivery systems that have helped accelerate gender-inclusive human capital accumulation. Türkiye was among the first nations to ratify laws that codified gender equity, from suffrage to civil code, and its progress continues to be held as an example for other countries in many ways. Parity has been achieved in basic learning outcomes over grades K through 12, with a Human Capital Index (HCI) among women that is on par with that of : 0.66 vs 0.64, respectively4. In terms of laws, policy measures and programs, international assessments show that Türkiye is advanced in terms of national legal provisions compiled by Women, Business and the Law5 and FinDex6 financial inclusion indicators. This work also shows that while foundations are generally comprehensive, selected gaps remain in access to banking and credit, labor regulations (discouraging work in selected sectors), social insurance benefits and equal pay. Today, however, addressing gaps in labor underutilization between women and men remains a key frontier towards boosting earnings and employment-based human capital gains equitably. Over the last generation (1990–2022), Türkiye’s human capital utilization among women in terms of labor force participation rate was initially at 37 percent in 1990, decreased to 23.3 by 2005 (34.1 percent and 21.3 percent, respectively, based on updated national data provided by the Turkish Statistical Institute, TUIK/TURKSTAT), and rose to nearly 35 percent by 2020–2022. This compares modestly to countries discussed later like Chile and Mexico that started at lower levels in 1990 but reached over 45 and 41 percent, respectively, by 2020–2022 nearly in line with OECD levels7. Over 2014–2022, Türkiye saw an expansion of the labor underutilization rate overall from 14 to 17 percent8 but nearly double among women, particularly reflecting the COVID pandemic and labor market contraction. Women’s labor force participation overall in Türkiye lags that of men by a factor of at least 2:1, aggravated due to COVID and global uncertainty facing growth. Labor market underutilization therefore remains a key challenge, particularly among women. 4 World Bank Development Indicators. 5 World Bank (2022). Women, Business and the Law: Türkiye. Washington DC: World Bank. 6 World Bank (2022). The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington DC: World Bank. 7 World Development Indicators accessed June 2023. 8 Based on analysis by the national Turkish Statistical Institute (TUIK/TURKSTAT), Annual supplementary indicators, https://data.tuik.gov.tr/Bulten/Index?p=Labour-Force-Statistics-2022-49390 xii Türkiye in Transition: Next-­Generation Human Capital Investments for Inclusive Jobs Overall, Türkiye has progressed significantly over the past fifteen years in 18 out of 22 dimensions of jobs-related human capital utilization and gender equity outcomes used for this analysis, although regional disparities remain. Global benchmarking of 22 indicators highlights the following stylized gender equity patterns to date in Türkiye: 1. Women’s labor force participation has increased modestly over this period. Nevertheless, vulnerable employment remains relatively high notably in peri-urban zones, and Southeastern and Central Anatolia. 2. Women’s work in industry has been steady. Generally, the share of higher-educated women working in industry has been in line with OECD average over this period, sustaining the share. 3. Agriculture accounts for less and services for more of women’s jobs, but informality remains high. The share of women working in agriculture has decreased, while the share of women entering the labor force with secondary or primary education into services has increased. Since vulnerable employment remains high at 30 percent as noted, most of this movement has been into informal or temporary short-term employment. 4. Job growth has not necessarily meant formal job growth for women. While vulnerable employment has decreased modestly, the quality of jobs in services may not have improved as quickly as the availability of jobs (low-wage, informal jobs particularly in hospitality, food, retail, and domestic services). 5. Youth NEET has decreased but remains higher than the OECD, ECA and high-income average. Youth NEET has decreased among Turkish women. However, it remains relatively high compared to the OECD, building on historically high initial rates. As will be shown subsequently, this is largely driven by persistently high rates in certain provinces in middle and southeastern Anatolian regions. 6. Semi-advanced and advanced job skills among adults significantly lags the OECD average. The low share of women (like men) with advanced competencies for technology-rich environments indicates that expansion into services coupled with vulnerable employment was driven by low-skilled, low-productivity employment. 7. Financial inclusion is improving though a wider gender gap remains in Türkiye than in other upper and high middle-income countries. There is also a role for certain labor and financial sector regulations to facilitate this in terms of removing barriers to/ introducing balanced incentives for alleviating implicit and explicit occupational and sectoral segregation and segmented financial inclusion services, such as financial literacy education that includes practical access to services at an early age and fostering early entrepreneurship skills locally and firm ownership/representation at the local level across different size firms, sectors, and regions. Executive Summary xiii 8. Women’s household roles are relatively more pronounced in Türkiye but has been lessening over time as access to opportunities and children’s early childhood development/education (ECD/E) enrollment have expanded notably in urban areas. This suggests more and more women are becoming active (particularly in informal markets) outside the home. Pending differences in social security benefits coverage, labor regulations and access to early childhood education remain. Access to older care services over the long-term will also provide enhanced support. 9. Pending gaps over the short run suggest a need to boost the quality of existing jobs through improved, targeted benefits and expand coverage of labor market programs which reach nearly 8 percent of the total potential labor force. Over the short run, the pending focus is on improving the quality of those available jobs desired by women in the short run. This means social protection measures embedded in jobs, maternity and paternity benefits, flexibility, competitive wages, and long-term productive potential. 10. Pending gaps over the long run suggest a need to expand competitiveness among the labor force and job creation in frontier green and digital sectors. Over the long run, strengthening advanced skills and competencies among intermediate-skilled women for acquiring more productive jobs in services and industry will be critical, while making more accessible ECD/E to lower-skilled households and women. This note, in line with previous work, further shows that multiple factors explain these labor outcomes by gender in Türkiye–grouped as labor capital, financial capital and social capital. These include, inter alia, (i) job-related skills associated with technological shifts in production processes in services, manufacturing and agriculture, (ii) access to finance, banking services, entrepreneurship, (iii) access to employment support services and networks, from school-age through adulthood, (iv) access to and quality of early childhood education, and (v) perceptions regarding occupational, social and public roles and representation9 10 11. As a result, this note shows that to accelerate gender-inclusive labor markets, a simultaneous, integrated, or interlinked, approach to addressing issues is needed. The rest of the note proposes a framework which addresses multiple constraints holistically. While unidimensional interventions to address specific constraints have helped modestly, multi-dimensional interventions will be needed to address more complex, underlying issues. 9 Aldan A and Öztürk S (2019). Determinants of the Rise in Female Labor Force Participation Rate: Identifying Cohort Effects. Central Bank of the Republic of Turkiye (CBRT) Working Paper No: 19/05. https://www.tcmb.gov.tr/wps/wcm/connect/EN/TCMB+EN/Main+Menu/Publications/Research/ Working+Paperss/2019/19-05 10 Dayıoğlu M and Kırdar M (2010). Determinants of and Trends in Labor Force Participation of Women in Turkey. State Planning Organization of the Republic of Turkey and World Bank, Welfare and Social Policy Analytical Work Program Working Paper Number 5. http://ideas.econ.boun.edu.tr/content/wp/EC2019_02.pdf 11 Tatoğlu T (2022). Drivers of Low Female Labor Force Participation in Türkiye. BBVA Working Paper No. 22/13, December 2022. Banco Bilbao Vizcaya Argentaria, S.A. (BBVA), Madrid/Mexico City (BBVA Research) https://www.bbvaresearch.com/wp-content/uploads/2022/12/WP_22_13_Drivers_of_Low_Female_Labor_Force_ Participation_in_Turkiye.pdf xiv Türkiye in Transition: Next-­Generation Human Capital Investments for Inclusive Jobs Moving forward, Türkiye can strengthen human capital utilization and jobs for women and men equitably by scaling up holistic investments tailored to different profiles, needed to expand coverage and adapt to evolving labor market needs. Türkiye can reinforce its human capital and labor market foundations in main two ways, as discussed in detail in the note: 1. First, it can apply the spirit of its Constitution and Eleventh and Twelfth NDP in expanding existing institutional foundations to semi-urban and rural regions, including ongoing effective programs at the local level in regions and communities such as peri-urban zones and Southeastern and Central Anatolia. 2. Second, it can introduce new investments, programs and policies to ensure policies and programs are implemented at scale. For a gradual increase of up to 2–4 percent of GDP12, returns on expanding investment in programs that work are exponential, potentially outweighing other alternative uses of public resources given that Türkiye boasts one of the most competitive, global outreach infrastructure systems in the world. This includes labor market interventions to alleviate distortions and market failures, inherent to most countries, that will otherwise continuing lagging. In line with the World Bank’s Global Gender Strategy, these proposed approaches can incorporate gender into economic transition from the outset, so women do not get left further behind and economic resilience of vulnerable households is compromised. Based on this two-pronged integrated approach, this note consolidates Türkiye’s achievements and ten main frontier areas (Table ES–1), with recommendations for an integrated human capital and jobs framework tailored to women and men (Table ES–2). Policy and program examples from Türkiye and global experience have demonstrated effective approaches that can be scaled up further and combined for maximizing impact. In addition to Türkiye’s examples discussed in this note, global experience shows that holistic approaches are most effective and long-lasting. This would imply combining at least two of three challenges from among labor, financial and/or social capital needs per measure, with a package of different options targeting different profiles from the four stylized profiles. The key is to scale-up coverage, program design, incentives, and financing. Türkiye is ready to reach new frontiers in equitable growth; how far it will go depends on how far and fast its policies are willing to go–for women and men alike. 12 World Bank (2022). Türkiye in Transition: Next-Generation Human Capital Investments for Inclusive Growth. Washington DC: World Bank. Executive Summary xv Table ES-1.  Ten key achievements and frontier challenges to gender-inclusive human capital and jobs Pillar Foundational Advanced (i) HCI and NEET: High Women’s Human Capital Index (iii) Women’s Labor Force Participation and Informality: (0.66), HCI Gender Gap closed (−3%). Female NEET Women’s LFPR has increased (23 to 33% in 15 yrs). high, has halved in 15 yrs. Frontier: 30% more work in vulnerable informal Frontier: Female NEET still twice ECA average (32%). jobs than do men (37 vs 28%). MEX and CHL faster (23 to 45 and 42%, resp.). Constraints: Limited early career counseling, social perceptions. Constraints: Private sector stimulation for labor- versus capital-intensive job creation, associated (ii) ALMP Coverage and Effectiveness: Coverage of market failures (information asymmetry on job profile ALMPs (14% of registered unemployed, excluding needs, labor market coordination and matching informal workers) has been increasing over time with job seekers) and firm dynamics (economies of and vocational formal secondary education scale, productivity, green transition); adjustments coverage gender gap has closed. needed for enhancing labor regulation flexibility/ Capital Labor Frontier: ALMP enrollment among women contract types for informal workers, parental and remains 30 percent lower than men for OJT and social insurance benefits parity, sectoral barriers Vocational Courses, and occupational and sectoral (construction, mining)/spillovers. segregation persists in ALMP and job placement. (iv) Gender Wage and Occupational Gap: Higher Govt. spending on labor support modest (est. educated women’s share of jobs in industry well 1.0% GDP), but double coverage among highest advanced (17%), nearly on par with OECD. income quintile vs lowest. ALMP spending relatively low compared to high labor underutilization Frontier: Advanced skills on digital lacking OECD, rates notably in rural and peri-urban areas (youth and informally structured services and agriculture unemployment, women’s unemployment, low labor market widest gender gap (up to 50%) and lower force participation, high informality). wages than OECD average. Constraints: Financing to expand coverage, Constraints: Occupational perceptions, employer targeting, design (additional incentives), and bias, advanced skills levels (OJT). access to information and outreach. (v) Financial Inclusion: Women’s financial inclusion (vi) Entrepreneurship: Women Business and Law Index is (banking) doubled over 15 yrs to 63%. high on par with HIC and improving (score 83/100). Financial Capital Frontier: Still lower than men and women’s OECD Frontier: Women’s firm ownership still one-fourth avg. (98%). OECD avg (11 vs 40%, respectively). Constraints: Awareness, social perceptions, Constraints: Occupational perceptions, financial dedicated programs (financing and design). sector bias, networks, advanced skills levels (OJT). (vii) Role Perceptions: Highly favorable perceptions of (ix) Early Childhood Development Programs: ECD women’s work among certain regions and higher enrollment among younger than 5 years has education levels up to 90%. increased 4-fold over 15 yrs (10 to 40%). Govt. spending on ECD has modestly increased over Frontier: Little change over decade or age groups. decade (reaching 0.29% GDP). On avg. 1 out of 5 unfavorable. Lower average perceptions (70%) in central and southeastern Frontier: Enrollment and spending remains half regions) and among women vs men (78 vs 91%, of OECD. respectively), and less than secondary education. Constraints: Limited locally adaptable models, Capital Social Constraints: Information and social beliefs. financing, quality regulation. (viii) Time Use: Gender time use and roles on (x) Representation: Women’s senior leadership has household care (child, older care) vs employment increased modestly over 15 yrs (14 to 20%). shifting over decade modestly. Frontier: Wide regional variation (10 to 35%). Frontier: Household care by women remains up Constraints: Information and social beliefs. to 4 times time use of men, and higher than OECD gender gap. Constraints: Information, services, expectations. Source: World Bank staff authors in consultation with Government of Türkiye and stakeholders. xvi Türkiye in Transition: Next-­Generation Human Capital Investments for Inclusive Jobs Table ES-2.  Integrated human capital and jobs framework: Ten measures for overall and gender equity Pillar Short-Term Long-Term (i) Develop Jobs Financing System at scale with (iii) Reform labor and social security policies to close gender equity targets, including: (a) jobs- inclusion and gender gaps for the most vulnerable, conditional MSME financing (credits/grants) specifically: (a) remove gender-based differences through MoLSS/İŞKUR- MOIT-KOSGEB and private in labor code policies such as hiring (ie. restrictions sector partnership (national development finance in construction, mining, other), (b) remove gender- institutions, Organizational Industrial Zones, based differences in social security policies Chambers of Commerce); (b) national labor (retirement age, duration of maternity and paternity market e-registry/geospatial tracking, targeting benefits); (c) introduce new independent workers and services platform, linking and adapting accounts with gradual subsidies for vulnerable MoLSS e-METIP (to broader profiles), İŞKUR informal workers, ensuring gender targeting and ALMPs (job matching, counseling, training), ISAS using existing e-Government system for payments; (MoFSS) and MOIT Enterprise Database as inter- (d) introduce greater coverage of flexible/part-time operable registry of firms and vulnerable workers; work including for the informal sector; (e) conduct (c) consolidation and targeting of existing in-depth labor and social security policy inclusion and Capital Labor multiple employment incentives/wage subsidies financial diagnostic with tri-partite social dialogue to (İŞKUR/SGK), expanding coverage to low- and inform these and other reforms. semi-skilled informal workers in low-employment, peri-urban and rural regions. (iv) Develop secondary schools’ school-to-work case management system targeting vulnerable girls and (ii) Develop performance-based financing and boys (low-income, rural and peri-urban) jointly with coverage at-scale for joint job training and private sector. Boost fiscal space and counseling employment services system with gender equity training to expand coverage of full-time school job targets: comprising private sector vocational counselors particularly for youth NEET and informal training (MoNE) and on-the-job training (MoLSS/ households. İŞKUR, linking MoNE Vocational Training-İŞKUR On the Job Programs. Expand eligibility to continuing/retraining for NEET and informal workers targeting high demand occupations and peri-urban and rural regions. (v) Develop targeted outreach and subsidies for (vi) Expand at-scale pre-entrepreneurship and self- expanding e-bank accounts and e-financial employment support system for the most vulnerable services equitably to vulnerable women and (low-income, youth, peri-urban and rural regions) men: Strengthen investments in financial literacy, with gender equity targets, including: MoLSS/ Financial accounts and nominal in-kind subsidies, digital İŞKUR-KOSGEB partnership to target high-value Capital payment accounts, and savings outreach through added private enterprises and social cooperatives, inter-Governmental partnerships (notably İŞKUR linked to e-registry platform above (i), including local bureaus and MoFSS social worker outreach, nascent İŞKUR entrepreneurship support scheme, joint with KOSGEB, Central Bank, other agencies). early creditworthiness counseling through mentor firms and entrepreneurship OJT, seed financing, and e-commerce platform for market access. (vii) Develop locally-adapted, early childhood (ix) Develop early childhood education accreditation/ education public-private delivery models with quality assurance system with performance- targeted financial household support: with based contracting. Ensure high quality assurance private sector and social cooperatives, unified systems and financing arrangements (public, private, quality assurance, performance-based subsidies cooperatives, or PPP providers) for expansion, to providers, and conditional cash transfers for introducing performance-based grants/subsidies. Capital Social vulnerable informal women working linked to ECE enrolment, with MoNE, MoFSS, municipalities. (x) Develop outreach on gender-inclusive civic representation and participation at local and (viii) Scale up outreach on occupational gender national levels: with MoFSS, MoNE, regional inclusion among households and youth: authorities, local community groups. with MoFSS, MoNE, regional authorities, local community groups. Source: World Bank staff authors in consultation with Government of Türkiye and stakeholders. Executive Summary xvii Türkiye in Transition: Next-­Generation Human Capital Investments for Inclusive Jobs 1 Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs “The Equal Opportunities Model aims to create a level playing field for men and women in professional life. Increasing women’s employment raises productivity in the workplace and improves overall economic performance.” President, Women Entrepreneurs Association of Türkiye (KAGIDER), Gender Certification Program Launch13. World Bank-KAGIDER Memorandum of Understanding14. Taking a holistic perspective of labor, financial and social factors related to inclusive human capital utilization, this part provides the overall framework and context in Türkiye for the analysis. It describes the underlying theoretical and empirical basis for the framework, key indicators and global benchmarks, and the institutional landscape of governmental and non-governmental stakeholders related to key national policies and programs. 13 The KAGIDER Gender Certification Program, launched in 2011 with World Bank technical assistance, is a private sector equal opportunity initiative adopted by Turkish development financial institutions and large, small, and medium enterprises. World Bank Press Release, 2011 https://www.worldbank.org/en/news/press-release/2011/07/20/kagider​ -and-the-world-bank-sign-memorandum-of-understanding-in-support-of-turkeys-gender-certification-program 14 KAGIDER Gender Certification Program, Overview https://kagider.org/en/projects/equal-opportunities-model​-fem-a-gender-equality-certification Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 1 Aim, Motivation and Framework This note aims to assess human capital utilization in terms of inclusive jobs in Türkiye towards broadening economic resilience, with a focus on gender equity given the profile of the vulnerable labor force. Türkiye’s early human capital foundations have paved the way for poverty reduction and labor force participation, today facing new multi-dimensional challenges. Türkiye’s investments have historically helped diversify and increase aggregate growth, propelling it to upper middle-income status. Yet relative to overall growth more recently, human capital utilization in terms of jobs and have not necessarily kept pace. Over half the population remains either out of the labor force or employed in informal, relatively low- paying jobs, most of whom have been women. Economic vulnerabilities remain following the Coronavirus pandemic (COVID) and the 2023 earthquakes in southeastern Türkiye, compounded by long-term effects of global financial crises and regional conflicts since 2008. Helping vulnerable workers, largely comprising women, adapt to a changing labor market will be needed to sustain a broad, productive workforce for future broad-based growth. As Türkiye embarks on its forthcoming Twelfth Five-Year National Development Plan, a diagnostic of human capital and jobs programs and policies in terms of gender equity is timely for informing future needs. In addition, a review of Türkiye’s experience will equally help provide global knowledge for other countries facing similar challenges. This note aims to assess human capital utilization in terms of inclusive jobs and gender equity in Türkiye towards broadening economic resilience following shocks. Human capital utilization in this note refers to labor market outcomes including labor force participation, employment and job quality-related outcomes such as earnings, labor support and social risk protection. Building on public expenditure analysis, the note primarily examines the role of multi-dimensional labor market policies for supporting the most vulnerable populations in general as well as gender equity. The assessment adopts a novel holistic framework that focuses maximizing human capital utilization through inclusive labor markets in terms of three inter-linked dimensions: labor capital and associated financial capital and social capital dimensions. The analysis complements other work on broader issues in depth outside the scope of this note. The work takes stock of key national and international literature to date and incorporates global benchmarking and original analysis using national statistical data. The note culminates by distilling a typology of profiles and policy recommendations into an integrated human capital and jobs framework, including both overall and gender-specific measures. Türkiye’s foundational human capital and labor policies have historically been comprehensive yet pending gaps in gender equity remain, suggesting adaptation to evolving needs lags. Over the past century, Türkiye has invested in foundational legislative and public service delivery systems that have helped accelerate gender-inclusive human capital accumulation. Türkiye was among the first nations to ratify laws that codified gender equity, from suffrage to civil code, and its progress continues to be held as an example for other 2 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity countries in many ways. Gender-inclusive human capital and jobs are also espoused in Türkiye’s national development strategies. These include the Eleventh Development Plan (NDP), with the Twelfth National Development Plan under preparation, and the Climate Action Plan. It has in place a platform for intra-government and private and civil society gender action, ranging from national strategies to initiatives by economic coalitions like chambers of commerce15. Parity has been achieved in basic learning outcomes over grades K through 12, with a Human Capital Index (HCI) among women that is on par with that of men: 0.66 vs 0.64, respectively16. In terms of laws, policy measures and programs, international assessments show that Türkiye is advanced in terms of national legal provisions compiled by Women, Business and the Law17 and FinDex18 financial inclusion indicators. This work also shows that while foundations are generally comprehensive, selected gaps remain in access to banking and credit, labor regulations (discouraging work in selected sectors), social insurance benefits and equal pay. Today, however, addressing gaps in labor underutilization between women and men remains a key frontier towards boosting earnings and employment-based human capital gains equitably. Over the last generation (1990–2022), Türkiye’s human capital utilization among women in terms of labor force participation rate was initially at 37 percent in 1990, decreased to 23.3 by 2005 (34.1 percent and 21.3 percent, respectively, based on updated national data provided by the Turkish Statistical Institute, TUIK/TURKSTAT), and rose to nearly 35 percent by 2020–2022. This compares modestly to countries discussed later like Chile and Mexico that started at lower levels in 1990 but reached over 45 and 41 percent, respectively, by 2020–2022 nearly in line with OECD levels19. Over 2014–2022, Türkiye saw an expansion of the labor underutilization rate overall from 14 to 17 percent20 but nearly double among women, particularly reflecting the COVID pandemic and labor market contraction. This shows that overall labor force participation and formal sector job rate is generally lower in Türkiye than in OECD countries, and even lower among women. This also translates to a utilization-adjusted human capital index (U-HCI) of 0.34 overall, and 0.45 among men compared to 0.22 among women21. Women’s labor force participation in Türkiye lags that of men by a factor of at least 2:1, aggravated due to COVID and global uncertainty facing growth. 15 Gender action across agencies is discussed later in the note. It ranges from inter-ministerial coordination across agencies by the Ministry of Family and Social Services to economic initiatives by the Ministry of Industry and Technology and its agency KOSGEB, and the Ministries of Labor and Social Security (including IŞKÜR national employment agency and SGK national social security institution), Agriculture, Trade, and other key ministries, in addition to major national chambers of commerce and private sector bodies such as TÜBİTAK, TÖBB, TÜSAİD, national development financial institutions such as TSKB and TKYB, among others. 16 World Bank Development Indicators. 17 World Bank (2022). Women, Business and the Law: Türkiye. Washington DC: World Bank. 18 World Bank (2022). The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington DC: World Bank. 19 World Development Indicators accessed June 2023. 20 Based on analysis by the national Turkish Statistical Institute (TUIK/TURKSTAT), Annual supplementary indicators, https://data.tuik.gov.tr/Bulten/Index?p=Labour-Force-Statistics-2022-49390 21 World Bank (2020). Utilization-adjusted Human Capital Index. Washington DC: World Bank. https://www.worldbank.org/en/publication/human-capital#Index Using basic utilization-adjusted rate reflecting labor force participation rate. Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 3 This note, in line with previous work, further shows that multiple factors explain human capital utilization and jobs outcomes by gender in Türkiye–grouped as labor capital, financial capital and social capital. These include, inter alia, (i) job-related skills associated with technological shifts in production processes in services, manufacturing and agriculture; (ii) access to finance, banking services, entrepreneurship; (iii) access to employment support services and networks, from school-age through adulthood; (iv) access to and quality of early childhood education; and (v) perceptions regarding occupational, social and public roles and representation22 23 24. As a result, this note shows that to accelerate gender-inclusive labor markets, a simultaneous, integrated, or interlinked, approach to addressing pending issues is needed. The rest of the note proposes a framework which addresses multiple constraints holistically. While unidimensional interventions to address specific constraints have helped modestly, multi-dimensional interventions will be needed to address more complex, underlying issues. Complementing literature to date, this assessment adopts a multidimensional framework to evaluating human capital utilization, jobs and gender equity. Broad-based growth and equity, including gender equity, are inextricably linked. At a global level, economic gender equity has been associated with 20 percent greater growth and welfare (income) on average through direct and indirect channels at the individual, intergenerational, and societal levels25. Ianchovichina and Leipziger (2019)26 find that for Türkiye, the most critical constraints to overall growth are also those that impact gender equity. These include underdeveloped financial markets, low women’s labor force participation (itself determined by multiple economic and social factors), and low technology absorption and innovation, i.e., productivity, diffusion, and advanced skills. 22 Aldan A and Öztürk S (2019). Determinants of the Rise in Female Labor Force Participation Rate: Identifying Cohort Effects. Central Bank of the Republic of Turkiye (CBRT) Working Paper No: 19/05. https://www.tcmb.gov.tr/wps/wcm/connect/EN/TCMB+EN/Main+Menu/Publications/Research/ Working+Paperss/2019/19-05 23 Dayıoğlu M and Kırdar M (2010). Determinants of and Trends in Labor Force Participation of Women in Turkey. State Planning Organization of the Republic of Turkey and World Bank, Welfare and Social Policy Analytical Work Program Working Paper Number 5. http://ideas.econ.boun.edu.tr/content/wp/EC2019_02.pdf 24 Tatoğlu T (2022). Drivers of Low Female Labor Force Participation in Türkiye. BBVA Working Paper No. 22/13, December 2022. Banco Bilbao Vizcaya Argentaria, S.A. (BBVA), Madrid/Mexico City (BBVA Research) https://www.bbvaresearch.com/wp-content/uploads/2022/12/WP_22_13_Drivers_of_Low_Female_Labor_Force_ Participation_in_Turkiye.pdf 25 Orstey et al (2018). IMF Working Paper; IMF (2022). Background to IMF Gender Strategy. World Bank Gender Strategy. 26 Ianchovichina and Leipziger (2019). Combining Growth and Gender Diagnostics for the Benefit of Both. World Economics 20(4): 177-203. 4 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Human capital accumulation and access to opportunities for utilizing it have been associated with holistic individual, societal and legislative factors, influencing gender equity. Gender equity in access to opportunities is especially sensitive to these factors. An analysis over 48 countries in Europe and Central Asia, including Türkiye, over twenty years shows that an increase in gender-inclusive parliamentary representation is positively correlated with GDP growth, transparency in governance, and inclusive labor policy27, observed elsewhere as well28 29. In addition, globally the role of legislation and policies on gender equity has been shown to bridge gaps in economic outcomes over a forty-year period since the 1970s30. The bi-directional, mutually reinforcing relationship between gender-equitable public participation and growth and employment, tied to social and political structures and expected gender roles, with evidence that this can change over time31. The dual relationship is explained both by the direct effect of gender equity in public participation (such as official leadership roles in parliament and government) on the design of inclusive public policy and programs, and the indirect effect on social expectations and roles that influence labor market participation32 33. Recent national assessments provide a comprehensive overview of legislative and policy measures adopted over time in Türkiye. The Government’s annual review, Women in Türkiye, prepared by the then-Ministry of Family, Labor and Social Security (currently two ministries at the time of writing), compiles highlights from national legislation across different aspects and provides a regulatory basis for areas this assessment34. It provides a general overview of key articles related to, inter alia, the civil code and the personal status of women, labor code, penal code, revenue and taxes, and protection against gender-based violence. Finally, analysis by academics and think tank institutions has explored selected issues related to employment choice, income, and implicit bias in occupational sorting. Global work highlights trends in policies and programs for economic gender inclusion internationally and in Türkiye. A recent IMF global survey benchmarks national policies for public financial management, showing that Türkiye does not have as many federal, explicit measures for gender-related expenditure management relative to comparable 27 Mirziyoyeva Z and Salahodjaev R (2023). © 2023 Mirziyoyeva and Salahodjaev. Does representation of women in parliament promote economic growth? Considering evidence from Europe and Central Asia. Frontiers in Political Science. 28 April 2023: 01-10. 28 Priyanka S (2020). Do female politicians matter for female labor market outcomes? Evidence from state legislative elections in India. Labour Economics. 64 (2020) 101822. 29 Kauhanen A (2022). Gender differences in corporate hierarchies. IZA World of Labor 2022: 358v2. 30 Sever C (2022). Legal Gender Equality as a Catalyst for Convergence. IMF Working Paper WP/22/155. Washington DC: International Monetary Fund. 31 Milazzo A and Goldstein M (2019). Governance and Women’s Economic and Political Participation: Power Inequalities, Formal Constraints and Norms. World Bank Research Observer. 34(1): 34–64. 32 Iversen T and Rosenbluth F (2008). Work and Power: The Connection Between Female Labor Force Participation and Female Political Representation. Annual Review of Political Science 2008(11): 479–95. 33 Council of Europe (2017). Regional study on women’s political representation in the Eastern Partnership countries. Strasbourg: Council of Europe. 34 Republic of Türkiye (2021). Women in Turkey. Ministry of Family, Labor and Social Services. Ankara: Republic of Türkiye. Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 5 countries35. Further, Türkiye is benchmarked in the recent 2022 Global Gender Gap Report by the World Economic Forum regarding general trends in health and survival, educational attainment, political participation, and broad economic opportunities. The Gender Initiative by the Organisation for Economic Cooperation and Development (OECD) benchmarks also provides selected benchmarking along similar parameters, notably the wage gap. Recent work by the World Bank has reviewed Türkiye’s key achievements and pending challenges in terms of poverty, shared prosperity, and women’s economic empowerment. At a global level, the World Bank’s Global Gender Strategy36 and forthcoming 2024–2030 Update highlights key domains for women’s economic participation and global lessons learned, incorporating experience and consultations from Türkiye. The World Bank’s 2016 Türkiye Systematic Country Diagnostic37 reviewed trends in labor force participation, poverty, and equity, with descriptive overall trends based on household budget surveys and gender gap analysis in educational levels, employment rates overall, access to banking, and use of judicial and legal services. In addition, the Bank’s 2017 Türkiye Country Gender Assessment38 provided a review of general key trends, including descriptive information focusing on health, fertility and labor, gender-based social norms, gender-based violence, and gaps and implications for childcare support. The scope and conceptual framework of this note focuses on human capital utilization for boosting inclusive growth in terms of three dimensions: labor capital, financial capital and social capital. This diagnostic contributes to recent evidence in three ways. First, while compiling and synthesizing all key evidence to date in one place, it will also raise areas which have not yet been assessed in-depth in terms of policies, programs and determinants related to labor, financial and social capital. Second, it will include more extensive global benchmarking than has previously been done. Third, it will incorporate expenditure and policy mapping, building on recent public financial review analysis completed as part of an earlier volume of this work39. It will therefore contribute to the evidence by providing a stress-test of key institutional measures and investments for inclusive growth and resilience to economic shocks with a specific gender filter. 35 International Monetary Fund (2021). Gender Budgeting in G20 Countries. Report No. WP/21/269. Washington DC: IMF. 36 World Bank Group (2015). World Bank Group Gender Strategy (FY16-23): Gender Equality, Poverty Reduction and Inclusive Growth. Washington DC: World Bank Group. https://www.worldbank.org/en/topic/gender/brief/gender​-strategy-update-2024-30-accelerating-equality-and- empowerment-for-all#1 37 World Bank (2016). Turkey’s Future Transitions. Republic of Turkey Systematic Country Diagnostic. Report No. 112785-TR. World Bank Group. 38 World Bank (2018). Türkiye Country Gender Assessment 2017. Washington DC: World Bank. 39 World Bank (2022). Türkiye in Transition: Next-Generation Human Capital Investments for Inclusive Jobs. Washington DC: World Bank. 6 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Key policy questions and scope for the analysis include: 1. Profiles: How can women and men’s human capital utilization in Türkiye be characterized into a policy-relevant typology, based on profiles and constraints for purposes of designing and better targeting policies and programs? 2. Performance: To what extent have existing public investments fostered human capital utilization (labor) and jobs among women and men over the last decade in Türkiye, with a focus on labor capital, financial capital, and social capital dimensions? 3. Proposals: What are key policy and program recommendations in terms of existing and/or new options that can be scaled up or introduced over the coming decade to enhance gender-equitable human capital utilization? The scope of this compendium note focuses on strengthening human capital utilization in terms of access to and quality of jobs in Türkiye among the most vulnerable, most of whom are women. The analysis includes both general and gender-specific analyses to design integrated recommendations with gender-specific measures to maximize impact for all in an inclusive way. Of primary interest is access to viable, sustainable jobs, defined as jobs that are likely to be needed over the mid- to long-term and that provide risk protection coverage with at least a basic package of social protection and labor benefits (i.e., either formal sector jobs or basic social protection benefits for informal workers). The note focuses on key issues related to selected economic market failures related to labor, financial and social capital, given these factors are directly or indirectly associated with human capital utilization40. Financial inclusion has direct financial impacts and indirect, positive externality effects on savings and e-commerce through digital payments. Social capital dimensions (defined broadly), such as household roles and public representation, impact time use and social externalities such as networks, access to information and mobility. The conceptual framework frames human capital utilization for equitable growth in terms of jobs, driven by labor capital, financial capital and social capital (Figure 1). To stimulate efficient labor markets that match demand and supply efficiently, all three dimensions of human capital utilization are needed. The framework adapts key aspects from the World Bank’s World Development Report: Jobs (2013) and the World Development Report: Gender Equality (2012). In addition, the World Bank Global Human Capital Project, the World Bank Global Social Protection and Jobs Compass, and the World Bank Global Gender Strategy highlight the need for scaling up existing skills, labor investments and risk-protection mechanisms for reaching the last mile in men and women’s inclusion. Specifically, the conceptual framework links human capital utilization in terms of employment outcomes (by gender) to labor, financial and social capital investments. As an illustrative framework, let Ε(f,m) represent the demand for employment (formal 40 Elgazzar H (2021). Back to the future: Harnessing women’s capital for new growth in Turkey (2021) and roundtable event (2021) https://blogs.worldbank.org/europeandcentralasia/back-future-harnessing-womens-capital​-new-growth-turkey Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 7 versus informal) by gender (women, men); Υ represent a given level of growth; Χ represent demographic characteristics (defined as age, gender, marital status, geographic setting, province/regional zone); Η represent the vector of human capital characteristics (defined as the stock of skills including educational level, digital competencies and labor-oriented competencies, health status and prior use of employment and social security services); F represent financial capital (defined as financial literacy and use of financial inclusion services such as formal bank accounts, access to credit and firm ownership); S represent social capital (defined as household roles, time use and public representation); α, β, ϕ, λ represent parameter estimates, t represent a given time; and ε represent a vector of error terms, where: Reflecting the framework of human, financial and social capital factors, this work thus reviews trends in employment (formal and informal) and gender equity as a function of different domains. Figure 1.  Proposed conceptual framework: multidimensional human capital utilization for equitable growth LONG-TERM EQUITABLE GROWTH HUMAN CAPITAL UTILIZATION (Employment) LABOR FINANCIAL SOCIAL CAPITAL CAPITAL CAPITAL Broadening jobs Broadening Broadening opportunity coverage representation Source: World Bank staff authors with inputs from World Development Report: Jobs (2013), World Development Report: Gender Equality (2012), World Bank Global Gender Strategy. The methodology used for the analysis focuses on a review of recent secondary research, administrative documentation, and primary quantitative descriptive and econometric analysis, including: 1. a review of key evidence on outcomes related to labor markets over time by sector and region, with special attention to the evolution of green jobs (including educational and skills trends); 8 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity 2. a review of key evidence on financial inclusion as well as entrepreneurship outcomes over time; 3. a review of representation in formal institutions over time; and 4. an analysis of policies, coverage and expenditures related to labor markets, coupled with stakeholder insights, national documentation, and relevant recent literature. Data used for selected new analysis includes national household survey and administrative and regulatory policies and program data at the national level and province-level where available. A core set of indicators and a consistent set of global benchmarks will be used to capture strengths and pending gaps, data permitting. This includes statistical survey data; administrative data sourced from line ministries; international survey and globally compiled national accounts data (based on World Development Indicators, OECD, ILO, World Values Survey, and other relevant sources); and qualitative appraisals by World Bank staff authors based on national policy and program documents, discussions with key stakeholders from the public sector, and insights from key non-state agencies, think tanks and international partners cited throughout the report where included. Stakeholder engagement and consultations have also informed the work, with a focus on labor-related institutions that directly implement labor regulations, policies and programs. Key institutions include the Ministry of Labor and Social Security and associated agencies such as the National Employment Agency (İŞKUR) and the Social Security Institution (SGK), coordinated with the Ministry of Industry and Technology on sectoral private sector firm support, the Ministry of Trade on social cooperatives and Fair-Trade certification and development finance institutions. Dialogue has also included the World Bank Türkiye Human Capital Roundtable Series and engagement through a virtual Jobs Forum with primary Government counterparts, civil society (notably academics, think tanks, and social cooperatives), and ongoing dialogue with international partners through ongoing projects in which gender is examined, notably the European Union, United Nations Agencies including the ILO, and other international financial institutions such as the EBRD. The Jobs Forum program focuses on four key areas of interventions initially assessed in the Human Capital Expenditures for Inclusive Jobs analysis: (i) targeting job creation; (ii) modernizing skills and job training; (iii) facilitating labor entry and mobility; and (iv) adapting risk and resilience. In addition, following the February 2023 earthquakes, a consultative workshop was organized with university researchers was organized to discuss welfare monitoring approaches, data needs and options for interim vulnerability analyses. The work is complemented by selected just-in-time technical background notes. The accompanying background notes discuss earthquake recovery; vulnerable jobs following shocks such as COVID and the earthquake; green skills and green jobs segmentation analysis; critical occupational and higher order skills gaps to boost resilience during transitions; and a literature review of selected employment trends and measures in Türkiye by global and Turkish researchers. Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 9 The note is structured as follows. It is divided into five main parts: an Overview (first part) and an Outlook (concluding part), with three detailed parts focusing each on Labor Capital (human capital accumulation and labor market trends), Financial Capital (financial inclusion, private sector growth and entrepreneurship), and Social Capital (household roles, representation, and service delivery for economic inclusion). Finally, the final section discusses key findings and proposes a policy matrix on areas for potential measures or adjustments to existing programs to facilitate inclusive access to jobs, including performance-based approaches, with a focus on youth, women, and the green transition. It will aim to reinforce key instruments to connect the demand-, supply- and policy (institutional infrastructure) sides. The latter focuses on information/delivery systems for profiling and registering, jobs investments and restructuring existing wage subsidies, and the roll-out of a new human capital benefits package for jobseekers (including, inter alia, financial literacy, critical higher-order, and digital skills). Limitations: Key limitations of the work include (i) selectivity in the scope with a focus on economic-related issues, complementing work on broader issues outside this note; (ii) data availability for quantitative, observable data for international benchmarking are based on available sources that can be readily accessed and analyzed directly, thereby excluding other data sources, and (iii) timing and resources, whereby broader analysis that may require additional time or prospective survey data collection has been excluded. These limitations represent opportunities for future work and data efforts as a regular, thematic, and more in-depth follow-up to the present work as needed. Context and Overall Benchmarking: Türkiye and Global Trends Türkiye has outpaced peers on growth and opportunities at an aggregate level on various dimensions. Türkiye has outpaced peers in economic progress since the 2000s, among the fastest growth rates globally with strong income convergence, notwithstanding recent emerging challenges.41 Türkiye’s high growth has been accompanied by high inflation and other imbalances exacerbated during COVID, impacting vulnerability among middle- and low-income households and workers. In recent years Türkiye has witnessed a decline in net FDI inflows, averaging 0.8 percent of GDP since 2019; most FDI during this period has shifted to largely comprise real estate. Importantly, the share of employee compensation in national income has declined from nearly 33 percent in 2019 to 26 percent by 2022. 41 World Bank (2023). Macroeconomic and Poverty Outlook, Annual Meetings, April 2023. 10 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity The challenge of earthquake reconstruction has come on the heels of post-COVID recovery. Looking back to post-COVID recovery, while Türkiye’s economy grew 7.5 percent year-on-year by the first half of 2022, soaring inflation, a weakening currency and a widening current account deficit exacerbated vulnerabilities42. GDP growth is expected to moderate to 4.7 percent in 2022–3, but private investor confidence has been constrained notably in manufacturing, services and retail. The authorities are expected to continue policies to stimulate private sector demand in following the presidential elections held during May 2023. However, poverty and income inequality continue to disproportionately affect women (Figure 2). Poverty since COVID was estimated to have increased to approximately 11–12 percent based on World Bank methodology using consumption expenditure41, now receding though slower than expected due rising energy and food price pressures on households. Based on national data using equivalized household disposable income (relative to 50 percent of national medium income), 14.4 percent of households are considered at risk of poverty as of 2022 with no change since 202143. Official data shows the gini coefficient has increased every year from 0.391 in 2014 to 0.415 in 202244, also reflecting the declining share of labor income in gross national value of output. Figure 2.  Poverty and social exclusion composite index by gender, national data, At-Risk-of- Poverty or Social Exclusion (AROPE) rate (%) 38 18 36 16 34 32 14 30 12 28 26 10 24 8 22 20 6 2015 2016 2017 2018 2019 2020 2021 2022 Total Men Women Gender gap (percentage difference) Source: World Bank staff authors based on nationally-developed AROPE rate using TUIK Poverty and Living Conditions Statistics 202243 42 Macroeconomic and Poverty Outlook, Annual Meetings, October 2022. 43 TUIK Poverty and Living Conditions Statistics 2022, most recent data released May 2023 https://data.tuik.gov.tr/Bulten/Index?p=Poverty-and-Living-Conditions-Statistics-2022-49746 44 TUIK regional statistics database https://biruni.tuik.gov.tr/bolgeselistatistik/degiskenlerUzerindenSorgula.do# Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 11 Official data show higher rates of poverty and social exclusion among women on average. Poverty rates have been higher among women particularly since 2019, particularly among women (and men) with a secondary education, rising to 19.6 percent among women versus 17.4 among men using a national poverty threshold of 60 percent the medium national income45. This is also the cohort with the widest wage gap as shown later. National data also shows the at-risk-of poverty or social exclusion rates (AROPE) the gap by gender has grown over nearly a decade, with 14 percent more women by 2022. Per capita income is the second lowest among single-parent households who make up nearly 16 percent46 of all households (making an average mean income of nearly 84,600 Turkish lira47 115). This is 14 percent less than the national mean (98,400 Turkish lira), with women making up 77 percent of those households. Post-COVID labor market recovery was seen in 2022, though unemployment and informality rates remain high notably among women and youth48. Employment increased by 1.5 million (5.2 percent) between July 2021 and July 2022 as COVID restrictions eased. While women and youth (ages 15–24) employment expanded slightly faster than average, their respective unemployment rates still exceed national averages considerably, at 13.1 and 19.1 percent, respectively, compared to 10.1. Türkiye’s jobs recovery challenge is mainly a vulnerable women’s jobs challenge in terms of the level of vulnerability and magnitude. This means that beyond the quantity of jobs created, the quality (vulnerability) of those jobs and access (equitable distribution) matter. Labor force participation recorded its highest level in the first half of 2022 since the start of the pandemic, reaching 53.1 percent in July. Some jobs recovery among women and youth post-COVID was largely driven by recovery of some employment lost among these cohorts as hospitality and services pick up. The gross wages/salaries index for formal employees in industry, construction, trade, and services increased in line with CPI inflation by the second quarter of 2022. For Türkiye to absorb all inactive, able workers who are either out of the labor force or unemployed, let alone improve conditions for vulnerable working people, it will likely need to create almost double the number of jobs it has today. Given rates of job creation per quarter currently, it may need to accelerate this rate up to 5 times to get ahead of the green transition. Women account for nearly 23 million jobs of the 33.9 that need to be created, or nearly 68 percent. 45 TUIK Women in Statistics 2022 most recent data released March 2023 https://data.tuik.gov.tr/Bulten/Index?p=Women-in-Statistics-2022-49668 and pg 161, full report https://www.tuik.gov.tr/media/announcements/toplumsal_cinsiyet_istatistikleri.pdf 46 TUIK Statistics on Family, 2022 most recent data released May 2023 https://data.tuik.gov.tr/Bulten/Index?p=Statistics-on-Family-2022-49683 47 TUIK Income Distribution Statistics 2022 most recent data released May 2023 https://data.tuik.gov.tr/Bulten/Index?p=Income-Distribution-Statistics-2022-49745 48 Macroeconomic and Poverty Outlook, Annual Meetings, October 2022, based on TURKSTAT national labor force data. 12 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity The green transition risks leaving women further behind owing to their current labor trends. Currently the share of green jobs in Türkiye is lower than the average in ECA, with a higher share of current brown jobs and jobs requiring upskilling for the green transition49. This finding highlights the need to invest in green skills to smooth the green transition and mitigate the risks of increasing structural unemployment. Workers with basic and secondary education form the bulk of the labor force in current brown jobs, including predominately women in the informal sector, who will likely need to be targeted for retraining. 62 percent of workers in brown jobs and 55 percent of workers in jobs that need upskilling have attained basic or secondary education. Foundational human capital accumulation has been high for women and men, but youth and adult outcomes show disparities. Turkish women and men’s foundational human capital growth is relatively advanced, notwithstanding labor participation challenges. Türkiye’s Human Capital Index (HCI) among women is on par with that of men: 0.66 vs 0.64, respectively50. This indicates that Türkiye’s long-standing infant, child and maternal health achievements, basic math, literacy and reading skills and nutritional outcomes are on par or ahead of most upper-middle income countries. At the same time, school-to-work transition lags for its level of HCI, notably among women. Türkiye has rates of youth of education, employment, or training for its HCI level (Figure 3). Despite overall gender parity in learning outcomes over grades K through 12 and HCI, NEET among women is also far higher for women’s HCI than the relationship for men. As discussed later, this is largely driven by women’s NEET rates, reflecting Türkiye’s labor force participation among women that is also lower for its HCI level. Female labor force participation has long hovered at around 30 percent, less than half that of men at over 70 percent. This is also particularly low compared to an OECD average of 44 percent, 45 percent among Central Europe and the Baltics, and over 40 percent among East Asia and the Pacific and Latin America and the Caribbean51 (Figure 4). Among inactive women not looking for a job in Türkiye, 46 percent have left the labor force due to household reasons52, compared to zero percent among men. Women also bore the majority of COVID-19 job losses in Türkiye at nearly 60 percent. 49 World Bank (2022). Türkiye Country Climate and Development Report and Climate, Welfare, and the Just Transition. Washington DC: World Bank Group. With analysis by M. Makovec and D. Garotte Sanchez. 50 World Bank Development Indicators. 51 World Development Indicators. 52 Turkish Statistical Institute, Labor Force Statistics for September 2020 Quarterly Data, December 2020. https://data.tuik.gov.tr/Bulten/Index?p=Labour-Force-Statistics-September-2020-33793 Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 13 Figure 3.  Human capital index versus share of youth not in employment, education or training (NEET) 50% 45% 40% Share of Youth NEET 2019/2020 35% 30% 25% 20% 15% 10% 5% 0% 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 −5% Human Capital Index (0 to 1, 2020) Source: World Bank staff authors using World Development Indicators, latest available corresponding data. Figure 4.  Labor force participation rates by gender, female versus male, Türkiye and global , 2020–2021 (%) 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% rs an ia as tia ia ico e da ly va ka y a ke in ec Ita As on be ur do n oa be an ex ov r La e nd ed Tu em l Cr Gr ol Rw rib M ra eg i M Ho ac Sr nt M Ca rz M Ce He D & EC rth & ica d No O an pe er ro ia Am Eu sn Bo tin Women Men La Source: World Bank staff authors using World Development Indicators. 14 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Shocks such as COVID and the February 2023 earthquakes exacerbate employment risks and resilience facing vulnerable semi-skilled women, youth, and lower-growth regions. Following the 2023 earthquakes in southern Türkiye, the risk of denting human capital and poverty gains looms large. Key vulnerable groups such as women, youth, older persons, and low-income households are especially at risk. Homes have been destroyed, jobs have been lost, and learning has been disrupted. Yet such a shock has the potential to accelerate Türkiye’s vision to adapt human capital to climate change, digitalization, economic shifts, and natural disasters. The earthquakes hit a region that was already vulnerable. The 11 provinces most impacted by the earthquake span an enormous geographic area that is largely inland. The earthquake-affected provinces bore 14 million Turkish citizens (16.4 percent of the national population) plus 1.8 million Syrians under Temporary Protection (SuTPs)53, and accounted for 9.4 percent of Turkish gross domestic product (GDP) and 8.6 percent of exports in 2022. Official data show that the region’s annual income per capita (about 44,000 Turkish lira) is nearly half the national average (about 87,000 Turkish lira), women’s labor force participation is far lower (21 percent versus 33 percent) and average household size is much bigger (4.5 versus 3.2 people). The region’s population is also relatively younger, comprising nearly 4 million children ages 0 to 14 years and a youth dependency ratio of about 45 percent as of December 2022—almost double the national average. The 1.5 million poor households living in the affected region prior to the earthquake may fall deeper into poverty, while the vulnerability will have increased among the displaced destitute. The scale of the damage surpasses any in Türkiye’s modern history since its founding in 1923. Over 4 million people are either sheltering in the affected provinces or have been evacuated. Direct physical damage alone was estimated at over $34 billion soon after the earthquakes by the World Bank, excluding economic costs, and total losses at over $100 billion based on Government estimates. With the collapse of housing, health care facilities and schools and the loss of livelihoods, the risk of destitution and long-term scarring is high, especially among vulnerable groups, such as low-income women, children, older citizens, and refugees. The Government’s emergency social support package of cash transfers, housing and employment protection support introduced following the earthquakes will help stem some of these impacts for those covered, building on the country’s long-standing social protection and labor programs. Public investment in human capital over the past three decades has been steady, yet coverage and efficiency will need to be adjusted in the face of evolving shocks. Türkiye has activated a robust public service delivery system to respond to emergency needs, with a need to further expand coverage among the 30 percent informal, primarily women. Overall public spending in human capital in Türkiye, encompassing the broad spectrum of social policies and programs to support households and workers, have 53 https://www.goc.gov.tr/gecici-koruma5638, February 2, 2023 Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 15 remained constant over the past ten years, yet remain modest in the face of post-COVID challenges to welfare and jobs. The cost of managing the impact of COVID-related shocks on households and workers while addressing underlying vulnerabilities is expected to be significant, with a need to ensure efficiency and equity. The COVID-related shock also provides an important opportunity to reform economic and social welfare policies early and implement “early alert adaptive” systems. The choice of instruments is key to striking a balance between supporting immediate needs and building long-term resilience. Türkiye spends a considerable share of GDP on social investments at approximately 16 percent as of 2020–2022, which has remained stable for over a decade, benefiting women and men alike54. Total social expenditures represented the single largest share of public expenditures at approximately 40 percent as of 2020, up from 38 percent in 2007, indicating that the share has been remained relatively constant. As a share of GDP, social expenditures saw a spike of nearly 2 percentage points over 2007–2009 (11 to 13 percent), subsequently decreasing somewhat until COVID-19, when the Government’s fiscal stimulus benefiting households and workers is estimated to have been the equivalent of 0.5 to 1 percent of GDP given modest amounts and coverage. Türkiye’s human capital expenditures by component are generally in line with comparable countries, with some differences. As of 2020–2022, pensions accounts for the bulk of public social expenditures (an estimated 5.6 percent of GDP). This is followed by estimated expenditures on education (4.5 percent of GDP), health (3.4 percent), survivor benefits (1.4 percent), wage subsidies (0.6 percent), unemployment benefits (0.2 percent), active labor market programs (0.2 percent), and non-contributory social assistance and in- kind services (0.06 percent).55 Türkiye’s contributory social insurance policies are financed mainly through employer contributions, employee contributions, and public transfers (for non-contributory programs such as social assistance and health insurance subsidies). However, the relatively low level of labor market program spending that tends to favor the highest 20 percent of the income distribution means that semi-skilled women outside the labor force are particularly disadvantaged. 54 World Bank (2022). Türkiye in transition: next-generation human capital investments for inclusive jobs. Washington DC: World Bank. 55 World Bank staff authors estimates based on detailed definitions of programmatic and thematic expenditures irrespective of agency implementation, using Government of Turkey data and OECD Social Expenditures database, 2020, including several long-standing social assistance and newer household income programs for the most vulnerable particularly benefiting women and children. Additional detail on beneficiary incidence and gender include data provided by the Ministry of Family and Social Services, Directorate of Social Assistance, showing that 61 percent of social assistance beneficiaries were women among a wide range of programs including the Conditional Cash Transfer Programs (for children's school attendance, and for maternal nutrition), Regular Cash Assistance Program for Widowed Women, Assistance Program for Needy Family with Men in Compulsory Military Services, and, most recently as of 2022, the Family Support Program, as well as employment incentives to social assistance women beneficiaries. 16 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity At an aggregate level, for its level of social expenditures, the allocative efficiency of Türkiye’s human capital spending since 2018 is somewhat lower than comparable countries (Figure 5). In terms of basic HCI, Türkiye’s outcomes are somewhat lower than comparable countries. HCI-utilizaton, or overall labor force participation rate (LFPR), is lower than expected for its level of social spending, driven mainly by women’s lower rates. This suggest that value for spending and likely broader factors such as demand-side (private investment) and social dynamics are at play. Similarly, youth LFPR, similar to youth unemployment, is lower in Türkiye than expected for its level of HCI. Examining higher-level aspects of human capital further reveal inefficiens regarding public spending in three main areas: (i) boosting competitive skills, (ii) faciliating labor market entry and (iii) matching with the demand side, especially for women. Figure 5.  Social expenditures (SOCX) and human capital index (HCI), Türkiye and global 0.9 0.8 0.7 HCI, 2017 ( 0 to 1) 0.6 0.5 0.4 0.3 0 5 10 15 20 25 30 35 SOCX % GDP Source: World Bank World Development Indicators Overall, Türkiye has progressed significantly over the past fifteen years in 18 out of 22 dimensions of jobs-related human capital utilization and gender equity outcomes used for this analysis, although regional disparities remain. Using the organizing framework, initial aggregate benchmarking of 24 selected indicators indicates how human capital utilization has progressed among women in Türkiye and global regions (Table 1). Proxy indicators from a global database are used to benchmark gender-inclusive labor, financial and social capital. As described earlier, this includes Η, human and labor capital characteristics (defined as the stock of skills including educational level, digital competencies and labor-oriented competencies, health status Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 17 and prior use of employment and social security services); F, financial capital (defined as financial literacy and use of banking services such as formal bank accounts, access to credit and firm ownership); S, social capital (defined as household roles, time use and public representation). More detailed national indicators and within-country gender comparisons between men and women are described in subsequent chapters. Overall, Turkish women have advanced in most domains over fifteen years. Relatively moderate to high and improving levels are seen in 14 out of 18 indicators which previously lagged OECD averages, with an additional four indicators that have been maintained on par, between 2005–2021. Progress shows especially fast achievement in many areas. Three areas did not advance as much or remain lagging: young women’s unemployment (among the formal sector), firms’ women’s ownership (despite an increase to 40 percent just after GFC in 2010, dipped back to pre-levels), and OECD PIAAC adult skills levels in technology- rich contexts (noting only a baseline value exists as the survey was conducted once). Global benchmarking highlights stylized gender equity patterns to date in Türkiye: 1. Women’s labor force participation has increased modestly over this period. Nevertheless, vulnerable employment remains relatively high. 2. Women’s work in industry has been steady. Generally, the share of higher-educated women working in industry has been in line with OECD average over this period, sustaining the share. 3. Agriculture accounts for less and services for more of women’s jobs, but informality remains high. The share of women working in agriculture has decreased, while the share of women entering the labor force with secondary or primary education into services has increased. Since vulnerable employment remains high at 30 percent as noted, most of this movement has been into informal or temporary short-term employment. 4. Job growth has not necessarily meant formal job growth for women. While vulnerable employment has decreased modestly, the quality of jobs in services may not have improved as quickly as the availability of jobs (low-wage, informal jobs particularly in hospitality, food, retail, and domestic services). 5. Youth NEET has decreased but remains higher than the OECD, ECA and high- income average. Youth NEET has decreased among Turkish women. However, it remains relatively high compared to the OECD, building on historically high initial rates. As will be shown subsequently, this is largely driven by persistently high rates in certain provinces in middle and southeastern Anatolian regions. 18 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity 6. Semi-advanced and advanced job skills among adults significantly lags the OECD average. The low share of women (like men) with advanced competencies for technology-rich environments indicates that expansion into services coupled with vulnerable employment was driven by low-skilled, low-productivity employment. 7. Financial inclusion is improving. There is also a role for certain labor and financial sector regulations to facilitate this in terms of removing barriers to/introducing balanced incentives for alleviating implicit and explicit occupational and sectoral segregation and segmented financial inclusion services, such as financial literacy education that includes practical access to services at an early age and fostering early entrepreneurship skills locally and firm ownership/representation at the local level across different size firms, sectors, and regions. 8. Women’s household roles are relatively more pronounced in Türkiye but has been lessening over time as access to opportunities and children’s early childhood development/education (ECD/E) enrolment have expanded. This suggests more and more women are becoming active (particularly in informal markets) outside the home. Pending differences in social security benefits coverage, labor regulations and access to early childhood education remain. Access to older care services over the long-term will also provide enhanced support. 9. Pending gaps, over the short run, suggest a need to boost the quality of existing jobs: Over the short run, the pending focus is on improving the quality of those available jobs desired by women in the short run. This means social protection measures embedded in jobs, maternity and paternity benefits, flexibility, competitive wages, and long-term productive potential. 10. Pending gaps, over the long run, suggest a need to expand competitiveness among the labor force and job creation in frontier green and digital sectors: Over the long run, strengthening advanced skills and competencies among intermediate-skilled women for more productive jobs in services and industry will be critical, while making more accessible ECD/E to lower-skilled households and women. Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 19 20 Table 1.  Global benchmarking, selected proxy indicators: holistic gender-inclusive human capital utilization over time Europe & OECD East Asia & Pillar Dimension Proxy Indicator Year Türkiye Central HIC MIC LIC Members Pacific Asia Country Level only to Madagascar Country Türkiye Georgia Poland Indonesia Korea Argentina Madagascar 1. Human Capital Index (HCI), women 2020 0.66 0.61 0.79 0.56 0.81 0.61 0.40 (0–1) Composite Human Capital 2. HCI gender gap, men relative to women (percentage, %) −3 −13 −8 −6 −4 −4 −6 3. Mortality from CVD, cancer, diabetes or 2005 12.7 15.3 10.9 16.8 10.8 18.9 24.7 Health CRD, ages 30–70 years, female (%) 2019 10.8 11.4 9.1 12.5 9.0 15.7 22.0 4. Adjusted net enrollment rate, primary, 2006 96.2 95.6 96.9 n/a 95.9 n/a 69.2 female (% of primary school age children) 2017 94.5 97.0 97.1 95.7 96.8 90.9 78.4 5. Lower secondary completion rate, 2005 85.6 88.6 92.0 89.2 93.9 68.6 22.9 female (% of relevant age group) 2021 93.0 91.2 96.5 96.6 96.7 80.8 38.2 6. Share of youth not in education, 2005 57.5 21.0 21.7 n/a 14.3 n/a n/a employment or training (NEET), female 2021 (% of female youth population) 32.4 15.3 17.4 n/a 12.6 n/a n/a (2019 ECA) 7. Secondary education, vocational pupils 2005 37.3 42.7 44.8 48.6 43.9 46.0 37.6 (% female) 2017 45.0 43.8 45.5 43.2 43.1 42.9 40.0 Labor Capital Human Capital / 8. Percentage of adults at each Skills proficiency level in problem solving in 2012–2018 5.6 n/a 23.6 n/a n/a n/a n/a technology-rich environments, Level 2, women (PIAAC, OECD) 9. Labor force with basic education, 2005 20.2 35.0 34.5 n/a 34.3 n/a n/a female (% of female working-age population with basic education) 2021 26.5 24.0 30.4 n/a 29.4 n/a n/a 10. Labor force with intermediate 2005 30.2 62.5 59.2 n/a 60.6 n/a n/a education, female (% of female working-age population with 2021 34.8 55.8 52.5 n/a 53.1 n/a n/a intermediate education) 11. Labor force with advanced education, 2005 69.1 78.9 75.6 n/a 75.9 n/a n/a female (% of female working-age population with advanced education) 2021 67.6 71.6 71.5 n/a 71.9 n/a n/a Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Europe & OECD East Asia & Pillar Dimension Proxy Indicator Year Türkiye Central HIC MIC LIC Members Pacific Asia 12. Labor force participation rate, female (% 2005 23.3 50.0 50.3 n/a 52.2 n/a n/a of female population ages 15+) (national estimate) 2021 32.8 50.6 51.9 n/a 53.5 n/a n/a 13. Labor force participation rate for ages 2005 24.5 37.2 44.6 n/a 47.2 n/a n/a 15–24, female (%) (national estimate) 2021 29.7 33.7 43.0 n/a 44.4 n/a n/a 14. Unemployment, youth female (% of 2005 20.5 19.6 15.2 n/a 15.0 n/a n/a female labor force ages 15–24) (national estimate) 2021 28.7 20.4 14.6 n/a 13.7 n/a n/a Labor 15. Employment in agriculture, female (% of 2005 46.5 11.0 4.2 37.8 3.6 41.4 74.3 Participation female employment) (modeled ILO) 2021 22.3 6.6 2.9 20.4 2.1 27.7 61.7 16. Employment in services, female (% of 2005 36.9 73.1 82.2 40.1 82.9 39.6 20.1 Labor Capital female employment) (modeled ILO) Human Capital / 2021 61.1 80.2 85.6 58.2 86.8 53.9 30.9 17. Employment in industry, female (% of 2005 16.5 15.9 13.6 22.1 13.4 19.0 5.6 female employment) (modeled ILO) 2021 16.6 13.2 11.5 21.4 11.1 18.4 7.4 18. Vulnerable employment, female (% of 2005 51.0 14.5 12.7 57.4 10.0 60.2 90.4 female employment) (modeled ILO) 2021 28.3 10.7 11.0 42.2 7.7 49.3 87.4 19. Women Business and the Law Index Score 2005 77.5 81.2 n/a 75.8 n/a 50.8 Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs Institutions (scale 1–100) (labor, financial pillars) 2021 82.5 91.1 n/a 86.9 n/a 66.1 20. Account ownership at financial institution 2011 32.7 66.5 88.2 57.5 86.2 38.5 7.6 Financial or with mobile-money-service provider, Inclusion 2021 62.6 88.0 97.7 81.4 96.7 69.6 34.5 female (% of population ages 15+) Capital Financial 21. Firms with female participation in 2021 Entrepreneurs 11.3 34.8 39.7 45.7 39.5 33.7 24.1 ownership (% of firms) (2019 TUR) Public 22. Proportion of seats held by women in 2005 4.4 19.2 20.7 16.9 20.1 14.6 17.4 Participation national parliaments (%) 2022 17.4 30.9 32.5 21.9 30.8 25.1 26.4 23. Contributing family workers, female 2005 39.9 4.6 4.2 29.7 3.2 28.5 47.7 Household (% of female employment) (modeled Enterprises Social 2021 19.4 2.7 2.3 15.7 1.4 18.0 37.5 Capital ILO estimate) Early 24. School enrollment, preprimary (% gross) 2005 10.9 65.1 73.7 n/a n/a n/a n/a Childhood Education 2020 39.7 78.3 80.8 n/a n/a n/a n/a Source: World Bank staff authors based on comparable available data from World Development Indicators as of May 2023 , selected updated data. Note: HIC = high income countries; MIC = middle income countries; LIC = low income countries. Ministry of National Education Türkiye, gross schooling rate, 3–5 years: 43.3% (2019/20) and 56.4 (2021/2022). 21 Institutions Türkiye’s achievements to date have been supported by successive institutional investments, with a role for renewing whole-of-government coordination on gender equity moving forward. A range of institutions have been historically central to Türkiye’s push and pull efforts - pushing frontiers and pulling women actively into labor markets (Figure 6). Türkiye’s policy fundamentals have laid some of the foundations for women’s economic empowerment. Its long-standing commitment to maximizing human capital potential and gainful employment for women and men is enshrined in a whole-of-government approach and successive five-year national development plans. Türkiye’s Eleventh NDP (2019–2023), followed by its forthcoming Twelfth NDP, includes specific sections for “women’s advancement to raise Türkiye’s international position”56. It calls for “preventing all kinds of discrimination against women and to ensure that women benefit and strengthen equal rights and opportunities in all spheres of social life”. Relatedly, the Government’s Specific policies and programs have long existed or have been introduced to meet targets included in the Eleventh NDP. It stated that by the end of 2023, targets include: 1. female labor force participation rate increased to 38.5 percent, 2. female employment rate to 34 percent, 3. the rate of women among self-employed to 20 percent, and 4. the rate of women among those working as employers to 10 percent. To achieve these targets, at the national level the Ministry of Family and Social Services’ General Directorate on the Status of Women (GDSW) coordinates several intra- governmental initiatives, with potential for scale-up. GDSW’s annual Women in Türkiye reviews highlight key legislative, reform and program measures adopted regularly across agencies57 in line with international conventions. Key legislation and reforms include articles in the Constitution on personal status; the Turkish civil code; family courts, the Turkish penal code and protection against gender-based violence; extensive reproductive health, counseling and monitoring support (through the Ministry of Health); early childhood, K through 12, vocational, and tertiary education programs and policies (through the Ministry of National Education and Higher Education Council); the Labor Code; civil service employment and law; income and corporate tax legislation; and social security and universal health insurance, including efforts to extend to the agricultural sector accounting for a high share of women’s employment. In terms of specific programs, most ministries and major national bodies have range of economic inclusion and social services and pilot programs, addressing demand- and 56 This section summarizes legal and policy reforms, progress, projects and activities, with a more detailed list available from the Government. See MoFSS Women in Turkiye annual editions. Latest: Women in Türkiye January 2023 https://www.aile.gov.tr/media/130403/wowen-tr.docx 57 See MoFSS Women in Turkiye annual editions. Latest: Women in Türkiye January 2023 https://www.aile.gov.tr/media/130403/wowen-tr.docx 22 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity supply-sides (Box 1). In addition to the NDP, two national strategies are particularly relevant to women’s employment. The National Employment Strategy 2014–2023 (coordinated by the Ministry of Labor and Social Security)58 aims to strengthen Türkiye’s jobs and competitiveness outlook, with attention to the school-to-work transition, flexicurity and formal employment among the agricultural sector, women’s participation (with a goal of reaching 41 percent) and vulnerability including persons with disabilities and child labor. This is complemented by the National Youth Employment Action Plan led by İŞKUR with a particular focus on expanding active labor market programs, vocational training and employment incentives for firms jointly with the Social Security Institution (SGK)59. The National Women’s Empowerment Strategy Document and Action Plan 2018–2023 (coordinated by the Ministry of Family and Social Services)60 addresses gender-specific education, employment, decision-making representation, mitigating against gender-based violence, and women’s entrepreneurship. There is room to expand ongoing initiatives while introducing new measures. While many of the economic inclusion and jobs programs address a range of demand- and supply-side needs, some remain at the pilot level and can be scaled up or adapted further for greater impact. Subsequent sections will examine human capital utilization trends within Türkiye in more detail to identify areas of particularly high potential. Figure 6.  Institutions: Scaleable economic gender inclusion programs, social services and pilots in Turkiye, implemented 2016–2023 Presidency Strategy and budget office; parliamentary committees National development plans; targets; gender budgeting Ministry of Industry and Technology Ministry of Treasury and Finance KOSGEB; regional development Mid-term expenditure frameworks agencies; entrepreneurship Ministry of Labor and Social Security İŞKUR programs; social security institution Ministry of Trade programs; vulnerable labor registry Social cooperatives ‘E-METIP’; climate Ministry of National Education Ministry of Agriculture and Forestry & Higher Education Council Livelihoods & agri-cooperatives ECD; K-12 education; vocational & technical training centers; tertiary Ministry of Health Ministry of Family and Social Services Reproductive health; General Directorate on Status of Women family health centers Social information registry; cash social assistance; in-kind services; ECD Source: World Bank staff authors based on Government background documentation and information. ECD: early childhood education. 58 Ministry of Labor and Social Security. http://www.uis.gov.tr/Media/Books/UIS-en.pdf 59 Ministry of Labor and Social Security (İŞKUR) https://media.iskur.gov.tr/13507/national-youth-employment-action-plan.pdf 60 Ministry of Family and Social Services. https://www.aile.gov.tr/media/6315/kad%C4%B1n%C4%B1n​ -gue%C3%A7lenmesi-strajesi-belgesi-ve-eylem-plan%C4%B1-2018-2023.pdf Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 23 Box 1.  Selected women’s national economic inclusion policy framework and selected programs Several agencies in Türkiye have economic inclusion and employment programs that target women’s demand- and/or supply-side labor market needs. As described in the Government’s WiT 2023, recent examples include: Demand-side (firms) • Firms’ financial grant incentives to women employers to hire women workers (WOMEN-UP) project supported by the Social Security Institution and funded by the EU. The project targets 4,000 employers and 4,000 workers in seven provinces. • Firms’ employment incentives (tax and social security premiums) supported by the Turkish Employment Agency (İŞKUR) Incentives for Women, joint with the Social Security Institution. Support is provided typically for 18 months for women, young men, and persons with disabilities. Up to approximately 516,000 women beneficiaries (nearly half the total) reached in 2022. • Firms’ women’s entrepreneurship as well as strengthening firms’ incentives to hire qualified women is supported by KOSGEB. Its Applied Entrepreneurship Trainings comprises 46 percent women beneficiaries and Enterprise Development Support Program provides financial incentives for hiring qualified women. The Union of Chambers and Commodity Exchanges of Türkiye (TOBB) established "Entrepreneurship Information System" supporting 6,500 women entrepreneurs across 81 provinces. • Social cooperatives projects supported by Ministry of Agriculture and Forestry and Ministry of Trade. These aim to strengthen women’s cooperatives through technical, financial and entrepreneurship support. Up to 40,000 beneficiaries across 81 provinces. Further projects have been supported by the World Bank. Supply-side (workers) • On-the-job training and vocational skills courses are supported by İŞKUR. Up to 170,000 women beneficiaries (nearly half of total) reached in 2022, in addition to 13,000 under projects financed by EU and supported by World Bank. İŞKUR job counselling services supported 950,855 women in 2022. • Half-time work allowance supported by İŞKUR is available under certain conditions for women, benefiting up to 4,000 women beneficiaries in 2022. • Financial literacy projects supported by the Ministry of Family and Social Services. Seminars focus on money management, income, spending, assets, debt, savings, investment instruments, and the private pension system. Up to 746,000 beneficiaries reached across 81 provinces. 24 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity • Girls’ STEM (science, technology, engineering, and mathematics) projects supported by the Ministry of Family and Social Services, Ministry, Ministry of National Education, United Nations Development Program (UNDP) and Limak Foundation. Targeting university (770 beneficiaries) and high school students (54,000 beneficiaries). • Organized Industrial Zones (OIZ)s Nursery Care supported by the Ministry of Family and Social Services, Ministry of Industry and Technology (formally Science, Industry and Technology) and Borusan Holding Inc. OIZ in four provinces were supported. Ministry of Family and Social Services’ “Survey on the Supply and Demand of Child Care and Early Childhood Education Services in Türkiye” (2016) further highlighted the need to invest in expanding services. • Women’s employment and institutional childcare services (INST-CARE) supported by the Social Security Institution. The project (funded by the European Union) targeted 17,000 women with monthly childcare stipends (EUR 100) for 29 months for children attending a facility approved by Ministry of Education or Ministry of Family and Social Services. A similar project targeting Educated Childminders (EDU-CARE) focused on professionalization of trained babysitters through financial stipends. • Gender-responsive budgeting supported by the Ministry of Family and Social Services, the Presidency Strategy and Budget Office, with Parliamentary Plan and Budget Committee and Equal Opportunity Commission for Women and Men. Up to 900 beneficiaries. Source: World Bank staff authors summary based on the Government’s Women in Türkiye, 202357 Overview: Holistic Human Capital Utilization, Gender-Inclusive Jobs 25 26 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity 2 Labor Capital: Activating Markets “We work with women from different backgrounds. We have work permits; we work in equal and fair conditions.” Women Social Entrepreneurs, HALKA Cooperative, Strengthening Economic Opportunities Project, World Bank staff mission, November 2022. To understand Türkiye’s human capital foundations to date, this part takes stock of educational and labor market policies and programs for fostering inclusion and gender equity. It examines Türkiye’s basic skills progress over time, showing that girls’ and boys’ outcomes have converged over time within the educational system, but diverge once entering the labor market. The findings suggest that adapting educational and labor market programs to an evolving economic landscape will need to be accelerated, together with increased measures targeted to gender equity. Labor Capital: Activating Markets 27 Getting Skills to Work Türkiye has continued to strengthen basic skills over time, notwithstanding regional differences in school leavers among girls. Türkiye’s enrollment and learning outcomes for school-age girls and boys, excluding higher rates of drop out among girls, have progressed significantly over time in line with average levels for upper middle-income countries. Türkiye has largely closed the gender K–12 enrollment and learning gap on basic math, reading and science (Figures 7–9). At the same time, differences remain at the regional level across household socioeconomic level. Vocational and technical secondary school enrollment shows that Türkiye, in line with other OECD countries like Poland, has increased the total and women’s share as a percent of total secondary enrollment (Table 2). Enrollment rates are similar among men and women, indicating equitable access. The choice of which vocational programs and subsequent job placement by gender shows some occupational and sectoral segregation, which is not necessarily unique to Türkiye but may be more marked, given the higher share in agricultural activities and low rates of job placement in manufacturing, administration, and real estate. The share of youth (aged between 15 and 24) neither in employment nor in education (NEET) shows wide regional differences by gender. Figure 10 shows the trend for NEET population in Türkiye. Even though the share of NEET population decreased for the last two years, long-term numbers show that it remained stagnant from 2014 to 2022. An increase for both genders was observed in 2020 mostly due to lockdown during COVID pandemic. From 2014 to 2022, NEET population among women decreased but still twice higher of men. This shows that they are not contributing to the economy or improving their own skills to be able to contribute in the near future. Like comparable countries where geography and income play a role regarding gender differences, the challenge for the education system is to continuously innovate at the local level. School leavers remain an issue particularly among informal workers’ households, the agricultural sector and in certain regions, with girls more at risk. Internationally, Türkiye’s performance in international learning assessments is one of the fastest-improving globally. In the last TIMSS application, for fourth-grade level math, Türkiye outperformed 28 countries, including Croatia, France, Slovakia, and Spain. At the eighth-grade level, Türkiye performed higher than 18 countries including France and Romania. In science, at the fourth-grade level, Türkiye has performed significantly higher than the 29 countries including Belgium (Flemish Region), France, Italy, Portugal, and Spain. At the eighth-grade level, Türkiye has achieved higher success than 17 countries, including France, Italy, Norway, and Romania. 28 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity However, international assessments also show that Türkiye remains “trapped” in the middle range of learning scores in reading and mathematics and needs to emphasize further high-order cognitive skills. There is also the need to move students above basic proficiency levels. In upper secondary, 26 percent of students who participated in PISA 2018 could not attain basic proficiency (level 2), and 37 percent did not attain it in math. Although no longitudinal studies follow the same student cohort, the higher percentage of students falling below the basic reading and math benchmarks in higher grades may show that the problem is compounding from deficiencies in earlier grades. Figure 7.  Secondary schooling rate among girls, 2010 versus 2021 (net, %) 100 % 100 % 90 % 90 % 80 % 80 % 70 % 70 % Schooling rate (%) 60 % 60 % % Change 50 % 50 % 40 % 40 % 30 % 30 % 20 % 20 % 10 % 10 % 0% 0% rn ia ia e an a ia an ul a lia a a ar ar Se Se iy ol ol ol nb te to ne ge rk m m at at at as na ta ck k Tü rra ar ar Ae An An An ac he Is la tA tM M te Bl tB ut st st e st es ia dl es st ea ea So es Ea ed W id Ea W dl th W M M id or 2010 2021 Change M N Source: World Bank staff authors calculations based on TurkStat regional database. https://biruni.tuik.gov.tr/bolgeselistatistik/degiskenlerUzerindenSorgula.do?d-4326216-p=1 Figure 8.  Literacy rates, by gender 100 95 90 Percent 85 Literacy rate, adult women 80 (% of females ages 15 and above) Literacy rate, adult men 75 (% of males ages 15 and above) 70 2004 2005 2006 2007 2009 2010 2011 2012 2013 2014 2015 2016 2017 2019 Source: World Bank staff authors illustration based on WDI data. Labor Capital: Activating Markets 29 Figure 9.  School enrollment, primary and secondary (gross), gender parity index (GPI) School Enrollment, primary 1.00 Gender Party Index (GPI) and secondary (Gross), 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60 1971 1974 1978 1984 1991 1994 1999 2002 2005 2008 2011 2014 2017 2020 Source: World Bank staff authors using WDI/UNESCO61. Table 2.  Vocational and technical secondary enrollment among total and women's populations, Türkiye, selected countries, 2005 versus 2017 % secondary enrollment) Vocational and technical enrollment (% of total secondary enrollment) Year Türkiye Indonesia Poland Brazil Tunisia Women Total Women Total Women Total Women Total Women Total Women 2005 13.7 16.4 11.7 13.5 18.0 23.6 3.0 3.0 6.4 8.3 2017 22.4 23.8 16.8 19.3 22.9 28.4 4.5 4.1 6.5 9.1 Source: World Bank Gender Data Portal, UNESCO Institute for Statistics (UIS). Note: this indicator is a general, non-age specific indicator; other data sources may vary due to definitions. For example, OECD Stat for enrollment specifically among 15–19 years, Türkiye: 43% (2021). Most recent data for Tunisia is 2016. https://genderdata.worldbank.org/indicators/se-sec-enrl-vo-zs/?geos=TUR_ OED_ECS_EAS&view=trend; Figure 10.  Share of youth neither in employment nor in education (NEET) over time, by gender (%) 40.0 35.0 30.0 25.0 20.0 15.0 10.0 2014 2015 2016 2017 2018 2019 2020 2021 2022 Total Men Women Source: World Bank staff authors illustration based on TUIK data https://data.tuik.gov.tr/Bulten/DownloadIstatistikselTablo?p=C3oZ87zEoyk2AHTSzq/ QFGcAoU6VSOlMpb0yTQYFVOD7Trac6ZHhrDwbWFh9XqB6 61 Note: The Gender Parity Index (GPI) indicates parity between girls and boys. A GPI of less than 1 suggests girls are more disadvantaged than boys in learning opportunities and a GPI of greater than 1 suggests the other way around 30 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Most students participating in TIMSS and PISA place at the intermediate higher order cognitive (HOC) competency level. TIMSS, for fourth graders, found 55 percent in math and 63 percent in science, and for eighth graders, 44 percent in math and 53 percent science. For PISA, 40 percent of Turkish students have reached this level in reading, 31 percent in math and 40 percent in science. Although these students may have good subject content and use more complex strategies to organize and analyze data (comparing, synthesizing, conceptualizing), they may still require higher-order skills to help them apply knowledge and solve problems in more complex and unfamiliar contexts. The percentage of students that have reached only the minimum or basic HOC competency is low. TIMSS, for fourth grade, found 18 percent at this level in math and 15 percent in science, and for eighth grade, 24 percent in math and 22 percent in science. In PISA, 30 percent of Turkish students reached only this level in reading, 27 percent in math, and 33 percent in science. These students may be overlying in memorization and recall and do not have a full set of higher-order skills that would help them learn more efficiently, while synthesizing and conceptualizing knowledge and inferring relations and outcomes, which would help them to solve complex problems and in non-familiar situations. Overall, more Turkish students are scoring at the advanced level of learning, characterized by high-order cognitive skills such as conceptualizing, inferring, and using knowledge to solve real-world problems. However, most students place at the basic and intermediate levels still showing reliance on memorization and information recall and more limited application of knowledge. A smaller, and decreasing, percentage do not reach basic achievement levels. Türkiye’s learning achievements are also equitable across gender, but gaps exist based on socioeconomic status (SES) and for students living in vulnerable contexts. Learning needs to be protected for the most vulnerable students and during crises. To close these learning gaps, the country needs to accelerate improvements in the quality of learning for all and protect learning in vulnerable situations, including during crises. The overall percentages of students categorized in each HOC level, based on the proficiency benchmarks in TIMSS and PISA, as proxies. The Turkish education system has built a resilient response model for mitigating to the extent possible learning loss impacts during emergencies for girls and boys. It has been developing a digital platform, school profiles, nation-wide monitoring, evaluations and research, after-school courses, and a well-functioning teacher support network. It also has programs to support disadvantaged schools with infrastructure, compensatory services, and remedial education (including learning catch-up and tutoring programs).62 These and other efforts need to pay attention to, at least, three aspects of learning: (i) foundational learning skills (cognitive, social, emotional, and early literacy and numeracy); (ii) skills for a technological and green transitions; and (iii) specific content and industry skills. 62 See also: MoNE 2022, "10 Thousand Schools in Basic Education Project Finalized" https://www.meb.gov.tr/10-thousand-schools-in-basic-education-project-finalized/haber/28323/en; and Ozer M (2022). The universalization of education in Türkiye and new orientations. November 2022. Istanbul: TRT World Research Centre. https://researchcentre.trtworld.com/wp-content/uploads/2022/11/New-Orientations_V8.pdf Labor Capital: Activating Markets 31 The next frontier includes expanding equitable early quality foundational learning and advanced skills. Although Türkiye’s educational achievement has been increasing as national averages, it is important to disaggregate these outcomes across some indicators of equity. This includes socioeconomic status (SES), gender, vulnerabilities, mobility, geographical locations, school types, and crises affected. This analysis would identify any equity gaps and needed targeted investments to improve the quality of learning overall. This chapter also includes information on risks confronted by disadvantaged students, such as child labor, early marriage, and displacement/forced migration. Türkiye has advanced in narrowing inequity in educational outcomes substantially relative to OECD average indicators. PISA reading performance SES differences (76 points) are less than the OECD average (89 points)63. The average OECD equity gap has not improved since 2009 (87 points)64. Considering “academic resilience,” meaning “the percentage of disadvantaged students who score in the top quarter of performance with their own country,” it is an average of 11 percent across OECD countries and 15 percent in Türkiye.65 Still, SES-related differences in learning are high. In Türkiye, although 9 percent of advantaged Turkish students place among top performers, only 1 percent of disadvantaged students place at the highest benchmarks characterized by HoC skills. In PISA 2019, socioeconomically advantaged Turkish students outperformed disadvantaged students in reading by 76 points, equivalent to two years of schooling and learning.66 This gap has closed as compared to 2009, when the difference was 92 points. Türkiye has achieved largely gender equality in basic learning outcomes (Figure 11). The following scores correspond roughly to achievement benchmarks in TIMSS: 400 (low), 475 (intermediate), 550 (high), and 625 (advanced). Girls score slightly higher than boys in the upper grades. In mathematics, fourth-grade boys (525) performed slightly better than girls (521), but girls (501) performed better than boys (490) at the eighth-grade level.67 In science fourth-grade boys (529) again performed better than girls (524), but eight- grade girls (520) were more successful than boys (510). PISA reflects similar equitable performance. In 2018 girls significantly outperformed boys in reading (by 25 points) and science (by 7 points). In math girls and boys showed similar performance. 63 OECD Programme for International Student Assessment https://www.oecd.org/pisa/ 64 OECD, 2019: PISA 2018 Results (Volume I): What Students Know and Can Do. Organisation for Economic Co-operation and Development, Paris. https://www.oecd.org/education/pisa-2018-results-volume-i-5f07c754-en.htm. Also: PISA 2018 Results (Volume II): Where All Students Can Succeed. Organisation for Economic Co-operation and Development, Paris. https://www.oecd-ilibrary.org/education/pisa-2018-results-volume-ii_b5fd1b8f-en. See also: PISA 2018 Results (Volume III): What School Life Means for Students’ Lives. Organisation for Economic Co-operation and Development, Paris. https://www.oecd-ilibrary.org/docserver/acd78851-en. pdf?expires=1637058908&id=id&accname=guest&checksum=A1708FFF34FFF0C823840D1BC02B8659. 65 OECD (2019). PISA 2018 Results Turkey Country Note. Organisation for Economic Co-operation and Development, Paris. https://www.oecd.org/pisa/publications/PISA2018_CN_ TUR.pdf. 66 PISA scores between 30 and 40 points represent approximately one year of learning (the actual score is country dependent) (World Bank 2020; OECD 2014). 67 These differences are not statistically significant. 32 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 11.  TIMSS: Average math and science scores for fourth and eighth graders by gender, 2019 550 540 529 530 525 520 520 524 521 510 501 510 500 490 490 480 470 460 Mathematics Science Mathematics Science Grade 5 Grade 8 Boys Girls Source: World Bank staff authors using Mullis et al. 2020. Türkiye shows slightly less gender-related differences across SES than the OECD average. Among the highest SES quartile in OECD countries, the PISA reading differences between boys and girls were 29.73 points (compared to 25.23 scores in Türkiye). For the lowest SES quartile, the OECD average gender difference is 27.13 score points (compared to 26.74 points in Türkiye).68 Less differences are seen in mathematics and science. Almost half a million students attend basic education in lower socioeconomic regions to the east in Türkiye, the focus of major programs by the Government such as the "10,000 Schools in Basic Education Program" launched in 2021.69 These include 48,007 pre-school students, 198,017 primary schoolers, and 171,877 middle school students. Across all three grade levels, the lowest educational achievement outcomes are found mainly in Southeast Anatolia, Middle East Anatolia, and Northeast Anatolia, respectively (Figure 12). Further, regions with the highest student-to-teacher ratios are found in Northeast Anatolia and Middle East Anatolia across all grade levels (Figure 13). 68 MoNE. 2020. TIMSS 2019 Turkey Preliminary Report. Reports Series No. 15. Directorate General for Measurement, Assessment and Examination Services, Ministry of National Education, Ankara. http://odsgm.meb.gov.tr/meb_iys_dosyalar/2020_12/10175514_TIMSS_2019_ Turkiye_On_Raporu_.pdf. 69 Based on MoNE’s identification of 10,000 schools in rural areas determined as the most disadvantaged by the Ministry of National Education. See also: MoNE 2022, "10 Thousand Schools in Basic Education Project Finalized" https://www.meb.gov.tr/10-thousand-schools-in-basic-education-project-finalized/haber/28323/en; and Ozer M (2022). The universalization of education in Türkiye and new orientations. November 2022. Istanbul: TRT World Research Centre. https://researchcentre.trtworld.com/wp-content/uploads/2022/11/New-Orientations_V8.pdf Labor Capital: Activating Markets 33 Figure 12.  Total number of most disadvantaged students by region (NUTS–170), 2022 120000 100000 Number of students 80000 60000 40000 20000 0 lia a a a an n lia a ia ia lia ar Se ar Se ea ol ol to to to ne m m at at Ag na na na k ck rra ar ar An An ac la tA lA tA tM M ite Bl tB st st ra st es as es ed st ea Ea es Ea nt he W Ea W M rth Ce W e ut dl No So id M ECE Primary school Middle school Total Source: World Bank staff authors using data from MoNE as of 2022. Figure 13.  Percentage of most disadvantaged students by region and grade level (NUTS–171) 30 25 20 Percentage 15 10 5 0 lia a a a an n lia a ia ia lia ar Se ar Se ea ol ol to to to ne m m at at Ag na na na k ck rra ar ar An An ac la tA lA tA tM M ite Bl tB st st ra st es as es ed st ea Ea es Ea nt he W Ea W M rth Ce W e ut dl No So id M ECE Primary school Middle school Source: World Bank staff authors using data from MoNE as of 2022. Note: Comprises 10,000 schools in rural areas (villages) designated by MoNE. 70 Except for Istanbul. 71 Except for Istanbul. 34 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Vulnerability is associated with child labor at 4 percent and over 700,000 children in Türkiye, particularly among girls in agricultural zones. In Türkiye, around 221,000 children (30.8 percent of working children in general) in total join the agricultural workforce. Of these, 64.1 percent are between the ages of 5 and 14 and 22.3 percent are between the ages of 15 and 17.72 The majority of these children may not be enrolled in school. In addition, at harvest time, more than a million agricultural workers—and their school-age children—migrate from one province to another; they are accommodated in tents.73 Here 13,250 children are identified as registered in one school and transferred to another one due to their parents’ seasonal work responsibilities. Most of these children are in Southeast Anatolia and the Mediterranean regions (Table 3). Table 3.  Children registered in schools whose parents are seasonal agricultural workers Number of childrena Percentage of childrenb Region ECEC Primary Middle ECE Primary Middle Istanbul 3 35 27 0.002% 0.004% 0.004% West Marmara 1 112 67 0.002 0.07 0.05 Aegean 10 324 281 0.01 0.06 0.06 East Marmara 6 216 110 0.01 0.05 0.03 West Anatolia 0 156 141 0.00 0.03 0.04 Mediterranean 50 1,198 1,075 0.03 0.16 0.17 Central Anatolia 10 158 148 0.02 0.07 0.08 West Black Sea 5 189 99 0.01 0.09 0.06 East Black Sea 9 77 87 0.03 0.06 0.09 Northeast Anatolia 31 453 275 0.07 0.30 0.21 Middle East Anatolia 9 375 199 0.01 0.13 0.08 Southeast Anatolia 217 4,014 3,091 0.11 0.44 0.44 Source: World Bank staff authors using data from MoNE as of 2022. Note: (a) Data obtained from e-school management information system, January 2022. (b) The ratio of the number of children of families who are seasonal agricultural workers to the general number of preschool, primary, and secondary school students affiliated with the General Directorate of Basic Education. (c) Represents children from independent kindergarten and kindergarten in primary education institutions. 72 TUIK, 2020. 73 UNICEF. Labor Capital: Activating Markets 35 Poverty-related work responsibilities in or out of home are negatively affecting students learning. Poverty, at approximately 11–12 percent in Türkiye based on national estimates, can lead to limited access to education services, unemployment of adult family members, employers’ demand for cheap child labor, and irregular migration.74 Türkiye has monitored child labor since 1994, and the year 2018 was declared as “The Year of Elimination of Child Labor.”75 In Türkiye the number of children aged 5–17 working in an economic activity is 720,000 (4 percent of this age group): 80 percent in the 15–17 age group, 16 percent of 12–14-year-olds, and 4 percent under the age of 11 (Figure 14). Of these, 66 percent continued their schooling and 34 percent did not. According to age groups, 72 percent of the age group under 14 and 64 percent of the 15–17 age group continue their education (Figure 15). The main reasons cited in national surveys for children working include: (i) helping household’s economic activity (36 percent), (ii) building skills for a job and having a profession (34 percent), (iii) contributing to household income (23 percent), and (iv) meeting their own needs (6 percent). Children working outside their homes did so mostly in the following sectors: service (46 percent), agriculture (31 percent), and industry (24 percent). Those who helped only their families76 spent an average 5.8 hours a week on household chores such as shopping, laundry and dishwashing, ironing, cooking, cleaning, etc. (44 percent); taking care of younger children (23 percent); and helping their families to care for an elderly, disabled, and/or sick relative (5 percent). Figure 14.  Children contributing to household chores by weekly hours and gender 50 Total Boys Girls 48 40 Percentage of students 40 37 36 38 30 34 20 17 15 11 10 5 7 4 4 3 1 0 0–2 3–7 8–14 15–20 21 + Weekly hours range Source: World Bank staff authors using data from MoNE as of 2022. 74 MoLSS (2017). National Program on the Elimination of Child Labor (2017–2023)., Ankara: Directorate General of Labor, Ministry of Labor and Social Security. Note: poverty rates subject to regular national data updates following the time of writing. 75 MoLSS (2017). National Program on the Elimination of Child Labor (2017–2023)., Ankara: Directorate General of Labor, Ministry of Labor and Social Security. 76 These children do not engage in any economic activity. 36 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 15.  Employment rate among children by age group 5–11 Years 4% 12–14 Years 16% 15–17 Years 80% Source: World Bank staff authors using data from MoNE as of 2022. Note: Comprises 10,000 schools in rural areas (villages) designated by MoNE. Pending learning gaps remain on differences in higher-order skills across regions, in part due to limited early childhood education coverage. Average national PISA scores increased significantly in reading, math, and science; however, regional PISA scores are lower in the eastern regions of Türkiye (in comparison to the west). PISA, as well as TIMSS, considers a score of 500 an average score across OECD countries (Roser, Nagdy, and Ortiz-Ospina 2013). In Türkiye, West Marmara achieved the highest results, both in reading (501) and in science (489), and East Marmara achieved the highest score in math (476). The lowest scores in reading (409), science (424), and math (407) belong to students from Middle East Anatolia.Students’ performance in the West Marmara, East Marmara, West Anatolia, and West Black Sea regions was relatively higher than in other regions. Scores for East Black Sea, Central Anatolia, Southeast Anatolia, Northeast Anatolia, and Middle East Anatolia are lower than Türkiye’s reading, math, and science average scores (Figure 16). Labor Capital: Activating Markets 37 Figure 16.  Regional PISA scores, (NUTS–1), 2018 500 480 460 Test score 440 420 400 a a a ul lia n an a lia lia ia ia ar Se ar Se ea ol ol nb to to to ne m m at at Ag na na na ta ck k rra ar ar An An ac Is la tA lA tA tM M ite Bl tB st st ra st es as es ed st ea Ea es Ea nt he W Ea W M th Ce W e ut dl or So id N M Reading Math Science Reading average Source: World Bank staff authors using data from MoNE 2019a. Figure 17.  TIMSS (2019) regional Differences (NUTS–1), 2019 570 550 530 Test score 510 490 470 450 an a a ul a ia n a ia ia lia lia Se ar ar Se ea l ol ol nb to to ne to m m at at Ag na na ta ck ck na rra ar ar An An Is la a tA tA tM M lA ite Bl tB st st st es as tra es ed st Ea ea es Ea he W Ea n W M th W Ce e ut dl or So id N M 8th-Grade 8th-Grade 4th-Grade 4th-Grade Average 8-Grade Math Science Math Science Math Source: World Bank staff authors using data from MoNE 2020a. 38 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Similarly, in TIMSS, although an increase in scores is seen in all regions compared to the 2015 cycle, major differences are found across regions. For example, East Marmara has the highest scores in eighth-grade mathematics and science assessments. For eighth graders, the lowest achievement in both fields is in Southeast Anatolia (Figure 17). For fourth graders the scores in the more developed regions are approximately the equivalent of more than two years of learning.77 This is a score difference of 83 in math and of 87 between East Marmara, where success is highest, and Southeast Anatolia, where it is lowest. Also, considering the difference of 75 points between each benchmark, there is more than one proficiency level difference. As noted earlier, proficiency levels imply differences in high- order cognitive skills of students. Learning differences are apparent across advantaged and disadvantaged schools. At the primary and lower secondary levels, almost half of the Turkish students participating in TIMSS (fourth- and eighth-grade assessment) belong to schools in socioeconomically disadvantaged contexts (fourth graders: 44 percent; eighth graders: 45 percent). The average score points difference between advantaged and disadvantaged schools is, approximately, the equivalent of one year and a half of learning in math and science (fourth grade: 64 and 55 points, respectively; eighth grade: 66 and 56 points, respectively). This score difference between schools in Türkiye is higher than the general average of other participating countries.78 Türkiye is one of the ten countries where the gap between schools in reading skills is the highest, as shown by PISA 2018 scores (testing 15–year-old students).79 Anatolian high schools performed higher than Imam Hatip high schools and technical and vocational high schools. Multiprogram high schools show the lowest achievement in all subjects (Figure 18). Furthermore, science high schools are the top performers in reading, math, and science. Science high schools and social sciences high schools performed above the OECD average.80 In terms of achievement benchmarks, the approximately 600 score average of science high schools is level 4 of proficiency (out of 6, the highest), and the approximately 400 score average of multiprogram high schools is level 2.81 However, experiment-based instruction is still limited, associated with lower TIMSS scores (Figure 19). Only 38 percent of Turkish fourth graders and 15 percent of eight graders conducted experiments at least once a week in science lessons, and 24 percent of fifth graders and 45 percent of eighth graders experiment a few times a year or never. 77 TIMSS is a grade-specific assessment and more difficult to estimates “years of learning” related to score points. However, it does correlate with PISA, and, thus, a similar estimate is used: 40 score points equal one year of learning. 78 Mullis et al, 2020 79 MoNE (2020). TIMSS 2019 Turkey Preliminary Report. Reports Series No. 15. Directorate General for Measurement, Assessment and Examination Services, Ministry of National Education, Ankara. http://odsgm.meb.gov.tr/meb_iys_dosyalar/2020_12/10175514_TIMSS_2019_ Turkiye_On_Raporu_.pdf. 80 MoNE (2020). TIMSS 2019 Turkey Preliminary Report. Reports Series No. 15. Directorate General for Measurement, Assessment and Examination Services, Ministry of National Education, Ankara. http://odsgm.meb.gov. tr/meb_iys_dosyalar/2020_12/10175514_TIMSS_2019_ Turkiye_On_Raporu_.pdf. 81 The cutoffs for the PISA levels are Level 1.C (below or equal to 262); Level 1B (higher than 262); Level 1A (higher than 335); Level 2 (higher than 407); Level 3 (higher than 480); Level 4 (higher than 553); Level 5 (higher than 625); Level 6 (higher than 698) (Roser, Nagdy, and Ortiz-Ospina 2013). Labor Capital: Activating Markets 39 Figure 18.  PISA 2018 scores by school type 700 Reading Math Science 600 500 Test score 400 300 200 100 0 ol ol ol .. l... ol ol ol h. ho ho ho ho ho ho ica g Hi Sc Sc Sc Sc Sc Sc n ch ip gh gh gh ts gh e Te dl at Ar Hi Hi Hi Hi id M nd ne M e e n am am nc nc ia la Fi ol gr Im ie cie na n at ro Sc ia n tio lS An tip ol ia ca cia at ol ul An at Vo M So An Source: World Banks staff using PISA data from MoNE 2019a. Figure 19.  Experiments versus TIMSS science scores 560 550 540 530 520 Test score 510 500 490 480 470 460 At least once Once or twice A few times Never a week a month a year 5th grade science 8th grade science Source: World Bank staff authors using TIMSS data from Mullis et al. 2020 Türkiye is implementing various programs to reduce the learning gap between schools. These include creating school profiles; nation-wide monitoring, evaluation, and research; restructuring after-school courses and establishing teacher support centers; and positive discrimination to support disadvantaged schools with infrastructure, compensatory services, and remedial education programs.82 82 MoNE (2020). TIMSS 2019 Turkey Preliminary Report. Reports Series No. 15. Directorate General for Measurement, Assessment and Examination Services, Ministry of National Education, Ankara. http://odsgm.meb.gov. tr/meb_iys_dosyalar/2020_12/10175514_TIMSS_2019_ Turkiye_On_Raporu_.pdf. 40 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity The Ministry of National Education (MoNE) transitioned into remote education shortly after the onset of the COVID-19 pandemic. However, as in many other countries, the transition into remote learning generated uneven results–due to pre-existing gaps in technology and connectivity gaps. In Türkiye, only 50.8 percent of the households had access to internet via fixed broadband connection (ADSL, cable internet, fiber etc) based on TUIK national data. Sixty-seven percent of students reported having a computer for school work, which is lower than the OECD average (89 percent) as of 2020. Another pre-existing vulnerabilty was the large population of refugee children and youth (1.4 million, 5–17 years of age), 900,000 (68 percent) of whom attend Turkish schools.83 Adapting MoNE’s education policies and investments can contribute to strengthening learning quality further. Existing education policies and programs in Türkiye are considered assets that can be strengthened and complemented to accelerate and protect learning. Türkiye has developed its own roadmap to improve learning in a holistic way, detailed in the country’s Eleventh Development Plan 2019–2023, Education Strategy Plan 2019–2023, and Türkiye’s Education Vision (EV) 2023. For these, the available evidence (associated learning factors, brain science learning process, and international examples) provide useful recommendations to accelerate and protect learning. Finally, in terms of education levels, a review of Türkiye’s learning achievements and existing gaps points to three priorities, with specific impacts for girls and women. These include focusing on expanding: (i) early childhood education universalization and quality; (ii) foundational literacy and numeracy in early grades of primary education; and (iii) upper secondary education programs. In addition, MoNE's Lifelong Learning Programs, which currently provides over 3,700 different course programs across 75 fields, of which 2,600 are TVET programs, represent a critical instrument for facilitating training for employment. Further strengthening the practical design of and expanding access to lifelong learning bears high potential in untapped regions, particularly for boosting digital and green transition-relevant occupations amongst vulnerable groups that facilitate equal opportunity to education for all, especially technical and vocational education and training (TVET) and Open Education as a second opportunity program, including introducing earlier career development classes, practical training and private sector-led models84 based on performance-contracting, and dedicated counselors on-site that ensure girls and boys are enrolled in programs, notably at-risk NEET students. These education levels require investments in access and retention, quality of learning (HOCs and SEL), as well as equity compensatory investments to support at-risk students living in vulnerable contexts and/or during emergencies. Overall, in terms of human capital, economic contraction during recent shocks has increased the risk of school dropouts, particularly for girls, prompting efforts to increase the resilience of the education system. These include modalities that blended quality face- to-face education with education technology (EdTech) support. The public national education 83 MoNE. 2021b. 2021–2022 Education Year Data (October 2021). Directorate General for Lifelong Learning, Department of Education in Migration and Emergency Situations, Ministry of National Education, Ankara. https://hbogm.meb.gov.tr/meb_iys_dosyalar/2021_11/05171729_ekim3.pdf. 84 Ozer M (2020). The Contribution of the Strengthened Capacity of Vocational Education and Training System in Turkey to the Fight against Covid-19. Journal of Higher Education (Turkey). 10(2): 134–140. Labor Capital: Activating Markets 41 platform, EBA, is being enhanced further with World Bank-supported Türkiye Safe Schooling and Distance Education Project to expand information technology capacity so that no child is left behind, especially girls, low-income households and non-native Turkish students85. Restructuring Labor Markets Türkiye’s labor force participation has grown over time, largely driven by that of more highly-educated women in selected regions. Türkiye’s labor force participation rate among women has increased over time (from 21 percent in 2005 to nearly 35 percent over 2022–3), but the gender gap remains salient. As an illustration, for Türkiye to absorb all inactive but working-age able workers who are either out of the labor force or unemployed, it will likely need to create almost double the number of jobs per year which, given rates of job creation today, may need to be accelerated by up to 5 times. Representing the scale of the challenge using a stylized example, up to nearly 23 million jobs would ultimately need to be created to absorb women alone who are either out of the labor force or unemployed, compared to the existing nearly 31 million jobs. Türkiye’s overall labor force participation rate has hovered between 49–50 percent86 since 1990, below the OECD average over that period of nearly 60 percent.87 The overall working-age population (15+ years) comprises nearly 64 million people, of whom nearly 33 million (51 percent) are active labor force participants (Figures 20–22). Of the inactive labor force, most are women at 70 percent. This may skew the perception of registered unemployment and self-employment (informality) figures since only those who are active labor force participants are reflected. Nonetheless, 41 percent of all registered unemployed are women. Of the active labor force, 29 million are employed (45 percent of the working age population), while 4 million (12 percent) are unemployed. 35 percent of informal self-employed workers are women. Türkiye also has an estimated 740,000 foreign residents, (excluding refugees) and an estimated 3.5 million registered Syrians under Temporary Protection (SuTP). Among SuTP, nearly 62 percent of men over 18 are employed, compared to 6 percent among women, with over 98 percent overall being informal workers88 (Box 2). 85 World Bank Türkiye Safe Schooling and Distance Education Project, Project Appraisal Document, June 2020. Based on MoNE, the Project, supporting the national EBA system, prioritized reaching students from disadvantaged groups during COVID-19 and future needs. It also seeks to ensure that all content is accessible to students with hearing and visual impairments and that disadvantaged students as a priority is maintained. (MoNE correspondence) 86 TUIK Annual Labor Force Statistics released March 2023. https://data.tuik.gov.tr/Bulten/Index?p=Labour-Force-Statistics-2022-49390 87 World Development Indicators. 88 Testaverde, Hari and Ozen/World Bank, 2022 working paper (forthcoming), Identifying the Constraints Among Syrian Refugee Workers in Accessing Better Employment Opportunities in and Outside Agriculture, based on Turkey Demographic and Health Survey 2018 from Demirci and (2021). Labor Market Integration of Syrian Refugees in Turkey. Center for Research and Analysis of Migration Discussion Papers No. 38/21. 42 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity The gender gap in labor force participation has declined gradually over the last three decades yet remains wider than other comparable countries. On a global scale, the share of women in the labor force participation (LFP) in Türkiye at 35 percent remains low for its level of HCI among women at 0.66. In line with global trends, however, the bulk of labor force losses during COVID were borne largely by women, youth ages 15–24 and semi- skilled workers. Overall, labor force participation losses over the period of November 2019 to November 2020 were nearly equivalent to the gains in employment since 2016. The labor force participation rate decreased to 49.3 percent, versus 52.5 percent in November 2019. Since the start of the post-COVID jobs recovery as of 2021, LFPR remains highest among the most highly educated (higher education), and lowest among the low- to mid- skilled (high school or just below high school). Prior research by the Central Bank of the Republic of Türkiye (CBRT) demonstrates that labor force participation responds positive during GDP expansion for post-shock recovery for men, but negatively for women including during recovery, as women second earners leave once economic activity resumes.89 Figure 20.  Profile of the working age population in Türkiye, as of 2022 (millions, %) WORKING AGE POPULATION 64.7 million (M) (Women: 33M, 51%) LABOR FORCE NOT IN LABOR FORCE 34.3M, 53.1% 30.3M, 46.8% (Women: 11.5M, 35.1%) (Women: 21.2M, 64%) EMPLOYED UNEMPLOYED 30.8M, 47.5% 3.6M, UR 10.4% (Women: 9.9M, 30.4%) (Women: 1.5M 3.4%) WAGE EMPLOYED 21.7M, 70.5% (Women: 7.0M, 70.7%) EMPLOYER 1.4M, 4.5% (Women: 0.2M / 2%, 12% of all employers) SELF-EMPLOYED / UNPAID FAMILY WORKER 5.0M / 2.7M (16% / 9%) (Women: 0.9M / 1.8M; 3% / 6% of all employed) Source: World Bank staff authors, TUIK Annual Labor Force Statistics released March 2023. Total national population: 85.3 million. https://data.tuik.gov.tr/Bulten/Index?p=Labour-Force-Statistics-2022-49390. Note: rates shown among women unless otherwise indicated. 89 Coşar and Yavuz (2021). Okun’s Law under the Demographic Dynamics of the Turkish Labor Market. Central Bank of the Republic of Türkiye. https://www.tcmb.gov.tr/wps/wcm/connect/5fb15659-032a-4b2c-94af-5a2c6d7cc71b/ wp2108.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-5fb15659-032a-4b2c-94af-5a2c6d7cc71b-nx5rYnI Labor Capital: Activating Markets 43 For over a decade, women exiting the labor force have cited “household responsibilities” as the main driver in labor force surveys. Exit from the labor force was dominated by household responsibilities accounting for 31 percent and driven by women; 46 percent of women who leave the labor force cited this as the factor, compared to zero percent among men. This represents 9.8 million work-able women; were these women to work, this would represent an increase of nearly 30 percent of the labor force. Leading reasons cited in national surveys include “discouragement due to a lack of job offers” and “retirement” and showed an increase relative to pre-COVID levels, notably among women. In terms of age, among men, labor force participation and employment figures show a reversed U-shape, with LFP peaking at middle age for men (Figure 23). By contrast, women show a gradual increase until their early 30s, with a lower level of LFP than men in all age groups. For both men and women, participation sharply decreases near retirement-eligible ages. Box 2.  Internal migration, refugees and jobs for women and men on the move Striking the balance between access to jobs for vulnerable internal national and foreign migrants has been a balancing act in Türkiye given the scale of the challenge. Türkiye has in place dedicated institutions for supporting welfare of migrant workers, both intra-regional domestic (nationals) and foreign. In terms of intra-regional nationals as seasonal agricultural workers, policies in place seek to ensure their access to social protection, health, and education, including for children otherwise at risk of child labor. The Ministry of Labor and Social Security has in place policy frameworks for seasonal agricultural workers and child labor, including monitoring systems such as E-METIP discussed later. Migration also represents a welfare priority in terms of irregular international migration into Türkiye. This is defined in Türkiye as border crossings without prerequisite immigration processes, including most refugees and people entering fleeing from other contexts who may not be officially designated as refugees in Türkiye. The Ministry’s International Labor Force framework supports a range of instruments from e-work permits to active labor market program coordination with İŞKUR. Syrians fleeing conflict represent the single largest foreign migrant group, designated as Syrians under Temporary Protection (SuTP). Almost a decade since their initial arrival and an estimated 3.5 million SuTP individuals90 later, their labor market integration has been a key determinant of their welfare. Most have settled and remained in Türkiye, acquiring language and cultural skills thanks to a variety of integration programs at the local level. SuTP migrants who register receive an identification card with designated residency in a specific province without recourse to travel or seek employment in other provinces91. In addition to Government support to essential health, education and other services, international support has supported national efforts. Financing, programs, and projects have been supported by multi- and bilateral international financing institutions, the European Union, the United Nations- 90 Data obtained from Presidency Office of Migration Management, as of 2023 https://en.goc.gov.tr/temporary​ -protection27 91 Testaverde, Hari and Ozen/World Bank, 2022 working paper (forthcoming), Identifying the Constraints Among Syrian Refugee Workers in Accessing Better Employment Opportunities in and Outside Agriculture. 44 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity coordinated agencies as part of the Refugee Response and Resilience Plan (3RP) and international bilateral cooperation. This support has targeted humanitarian and development needs. The EU- financed Emergency Social Safety Net (ESSN) Program, one of the first large-scale responses (2016 to date), finances targeted pro-poor cash transfers through a digital payments card, plus, increasingly, referrals to viable jobs pending options to avoid an abrupt halt to transfers. Managed by the Turkish Red Crescent (Kizilay), it has reached 1.54 million vulnerable beneficiaries to date (largely stable annually in recent years), of whom 1.49 million are Syrian and 53 percent are women92. Regular monitoring, evaluations and in-depth analyses of livelihoods are routinely published93 including by the World Bank94, outside the scope of this note. On balance, access to opportunities, integration in host communities and government support have made Türkiye among the most desirable destinations for vulnerable Syrians and other nationalities fleeing conflict for over a decade. Some areas can be strengthened to alleviate labor market inefficiencies facing host and refugee communities alike, including broader work permit coverage and entrepreneurship in regions that can stimulate growth in regions such as Southeastern and Central Anatolia provinces. On average, employment is 62 percent among Syrian men, compared to only 6 percent among Syrian women, compared to the rate among Turkish women at 30 percent. Most Syrian workers are employed informally (as high as 98 percent among married workers based on available data), up to triple the national average. This is especially the case in agriculture but also textiles and clothing, and construction. Child labor is evident, particularly among boys at up to 45 percent as of 2018. Türkiye’s well-developed work permit system and language integration has helped facilitate opportunity for vulnerable migrant women, with room to expand coverage. Of the 1.6 million working age (19–64-year-old) SuTP migrants in 2021, 91,500 had received work permits, or 5.5 percent. While women comprise 46 percent of all SuTP migrants including working age, only 5,335 women received work permits, or 6 percent of all SuTP work permits. Managed by the Ministry of Labor and Social Security’s Directorate General for International Labor Force work permit system95, a work permit is required for formal employment in line with standard practice elsewhere. However, applications can only be made with an employer sponsorship (a condition that is usually associated with having a prerequisite, established local network, which most foreign migrants naturally lack as newcomers). SuTP migrants are also required to have spent at least six months as a registered SuTP in Türkiye, and there are hiring quota limits whereby refugees can account for no more than 10 percent of any given firm’s workforce. While the introduction of access to work was granted in 2016, scale has been limited, impinging on the possibility of self-sufficiency96. 92 Turkish Red Crescent (Kizilay), Emergency Social Safety Net Program Monthly Report, Issue 34: April 2023 most recent at the time of writing https://platform.kizilaykart.org/en/Doc/rapor/2023-04_ESSNMonthlyReport.pdf 93 See Kizilay and partner reports https://platform.kizilaykart.org/en/rapor.html 94 See, for example, poverty monitoring in Cuevas et al/World Bank (2019), Vulnerability and Protection of Refugees in Turkey https://documents1.worldbank.org/curated/en/298891560175692951/pdf/Vulnerability-and-Protection-of-Refugees-in​ -Turkey-Findings-from-the-Rollout-of-the-Largest-Humanitarian-Cash-Assistance-Program-in-the-World.pdf (among others) 95 Directorate General of International Labor Force https://www.csgb.gov.tr/uigm/yayinlar/istatistikler/ and full report at https://www.csgb.gov.tr/media/90062/yabanciizin2021.pdf 96 İzmirli and İzmirli (2022). Work of foreigners under temporary protection in Turkey and main problems regarding the work of Syrians under temporary protection. Dokuz Eylül University Law Faculty Journal / Dokuz Eylül Üniversitesi Hukuk Fakültesi Dergisi, Cilt: 24, Sayı: 1, 2022, s. 123–165 / Volume 24, Number 1, 2022, pg 123–165. Labor Capital: Activating Markets 45 There are some work permit registration exemptions for agriculture, making it relatively easier to integrate. İŞKUR job counseling, language and vocational training and access to the on-the-job training are also available to Syrian migrant workers assuming they can register formally into the system with requisite identification and residency status. Reforming some of these measures may alleviate hiring potential of Turkish firms in provinces in which vulnerable refugee women can significantly contribute as critical labor, including in agriculture (as more Turkish women move to services), early childhood education (assuming provider training) and other services. Source: World Bank staff authors. Figure 21.  Labor force participation rates by gender over time (%) 80% 70% 60% 50% 40% 30% 20% 10% Total Men Women 0% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2019 2018 2019 2020 2021 2022 Source: World Bank staff authors calculations based on Household Labor Force Survey Figure 22.  Labor force participation versus human capital index among women, Türkiye, global 100 0.1835 90 80 Labor Force Participation Rate, 70 Female 2019-2020 (%) 60 50 40 30 20 10 0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Human Capital Index, 2020 (0 to 1) Source: World Bank staff authors using Turkstat data and (for female labor force comparisons) and World Development Indicators data. 46 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 23.  Selected labor indicators, by age group and gender, 2022 Men 100% 80% 60% 40% 19% 20% 18% 4% 0% Ages 15-19 Ages 20-24 Ages 25-29 Ages 30-34 Ages 35-39 Ages 40-44 Ages 45-49 Ages 50-54 Ages 55-59 Ages 60-64 Ages 65+ Women 100% 80% 60% 40% 20% 5% 5% 0% 1% Ages 15-19 Ages 20-24 Ages 25-29 Ages 30-34 Ages 35-39 Ages 40-44 Ages 45-49 Ages 50-54 Ages 55-59 Ages 60-64 Ages 65+ Unemployment rate Labor force participation rate Employment rate Source: World Bank staff authors calculations based on Household Labor Force Survey Figure 24.  Labor force participation by gender and education, 2014 versus 2022 (thousands) 34,334 40,000 Higher education 35,000 28,786 Vocational school at secondary level Secondary school 30,000 Less than secondary school 22,852 Total 15+ 25,000 20,057 20,000 15,000 11,473 8,729 10,000 5,000 0 2014 2022 2014 2022 2014 2022 Total Women Men Source: World Bank staff authors calculations based on TurkStat statistical database. https://biruni.tuik.gov.tr/medas/?kn=141&locale=en Labor Capital: Activating Markets 47 Figure 25.  Labor force participation rate among women (aged 15+ years) by regional zone, 2010 versus 2022 50 100% 45 80% Labor force participation rate (%) 40 Percentage change (%) 35 60% 30 25 40% 20 20% 15 10 0% 5 0 -20% ol rn ul a ia ia lia ye an a an a ia a ar ar Se Se ia ol ol ol nb at te to ki ge ne rm m nt at at Aneas Tü na ta ck k rra ar Ae An An A ac a Is a tA M tM h st ite l Bl tB ut e st Ea st es dl es ed st ea So es Ea W id Ea e W M th W dl M or id N 2010 2022 % Change M Source: World Bank staff authors calculations based on TurkStat regional database. https://biruni.tuik.gov.tr/bolgeselistatistik/degiskenlerUzerindenSorgula.do# Figure 26.  Unemployment (thousands) by gender and education, 2014 versus 2022 4,000 3,582 3,500 Higher education Vocational school at secondary level 3,000 2,853 Secondary school Less than secondary school 2,500 Total 15+ 2,044 2,000 1,813 1,538 1,500 1,040 1,000 500 0 2014 2022 2014 2022 2014 2022 Total Women Men Source: World Bank staff authors calculations based on TurkStat indicators database. https://biruni.tuik.gov.tr/medas/?kn=141&locale=en 48 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity The unemployed are predominantly low-skilled women and first-time job seekers (Figures 24–30). Unemployment has decreased to 10 percent as of 2023, down from 13.1 percent as of November 2020 at the COVID peak, compared to 13.6 percent in November 2019 just before COVID. It remains higher at 13 percent among women. However, unemployment rates masked, on the one hand, substantive labor force exits and, on the other, certain job protections provided for the formal sector during COVID. Unemployment previously increased significantly during 2007–2009 from 9.2 percent to 13.1 percent and has essentially remained high since. During the COVID peak, unemployment rose to 15 percent among women compared to 12.2 percent among men, and 25 percent among youth. Figure 27.  Unemployment rates over time by gender (aged 15+ years) 18% 16% 16% 14% 14% 13% 12% 12% 10% 10% 8% 9% 6% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Total Men Women Figure 28.  Youth unemployment rates over time by gender (aged 15–24) 36% 31% 25% 26% 21% 19% 16% 16% 11% 6% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Youth (Aged 15–24) Youth, Women (Aged 15–24) Youth, Men (Aged 15–24) Source: World Bank staff authors calculations based on Household Labor Force Survey Labor Capital: Activating Markets 49 50 0 5 10 15 20 25 30 35 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Babysitter/babysiting staff Child development & 2014 Secretary Dietitian Patient advisor Total Medical documentation Turkish philology teacher 2022 Food engineer Advisory teacher Front accountants Haircutter Call center personnel Customer representative Clinic support 2014 Accounting assistant Accounting professionalsist Office staff First and emergency aid Women Administrative office Men Sales counselor/expert 2022 Labourer Store attendant https://biruni.tuik.gov.tr/bolgeselistatistik/degiskenlerUzerindenSorgula.do# Source: World Bank staff authors calculations based on İŞKUR annual data. Designer, graphic Cook Women Market personnel Occupations not requiring Source: World Bank staff authors calculations based on TurkStat indicators database. 2014 Business manager Security officer Figure 30.  Registered unemployed by occupation and gender, 2021 (%) Sales representative Men Guard, security Figure 29.  Unemployment rate by gender and education, 2014 versus 2022 Other nursery workers Other related handicraft 2022 Shoe manufacturer Construction engineer Gardener Mechanical engineer Warehouse attendant Fuel sales staff Electrical technician Motorcycle courier Total 15-24 Official chauffeur Primary school Welder, gas Higher education Driver - transportation Vocational school Secundary school at secondary level Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Employment rates across regions and sectors vary widely, with larger occupational and sectoral gender segmentation among low-wage, semi-skilled jobs in services sectors. Labor force participation and employment among women and men has been shifting over the past decade, and following COVID has started to recover in some sectors and regions faster than others. As of 2022 and early 2023, men’s employment rate hovered at 82 percent, twice that of women at 42 percent, with wide regional variation (Table 4 and Figure 31). Yet women’s employment rate has increased by nearly 37 percent over the past decade while that of men has remained largely the same, indicating convergence. Some of the recent increase represents women returning to the workforce following COVID as those sectors resumed, particularly services. Similarly, over the past decade women’s wage employment has also nearly caught up to that of men’s at around 70 percent of employment (Figure 32). However, predominantly informal unpaid family work among women is still high at 18 percent despite slowly decreasing, compared to 4 percent among men. This means that home-based domestic work accounts for nearly 1 out of every 5 working women. Notwithstanding higher dropout rate among women from the labor force during COVID, employment rate losses were similar by gender and an assessment down the line will be needed to fully understand long-term effects. Overall employment in Türkiye fell during COVID by nearly by 1.5 million between December 2019 and 202097, Employment rates declined from 63 percent in 2019 to 60 percent in 2020 for men, and from 29 percent in 2019 to 26 percent in 2020 for women. Employment losses experienced during the pandemic exacerbated long-term structural vulnerabilities such as high rates of NEET, pre-existing low labor force participation, and low labor underutilization particularly among women. Some regions have seen a faster rate of improvement in gender equity in employment rates than others, notably those regions that continue to have lower women’s employment rates in eastern Türkiye. Southeastern, Middle East and Middle Anatolia saw increases in women’s employment rates of between 34 to 90 percent over the past decade. While women’s employment is still nearly 30 percent below the national average, it shows shifting patterns as services gain ground, discussed later in this section. 97 Data based on Turkish Statistical Institute (TUIK) Labor Force Survey annual and quarterly monitoring. Labor Capital: Activating Markets 51 Table 4.  Employment rates by regional zone by gender, aged 25–34 years, 2010 versus 2022 (% and percentage change) Men Women Region 2010 2022 Percentage change 2010 2022 Percentage change Southeastern Anatolia 73.3 72.3 −1.4% 15.1 28.8 90.7% Middle East Anatolia 75.5 74.6 −1.2% 20.5 32.1 56.6% Middle Anatolia 81.5 83.6 2.6% 26.2 35.1 34.0% Northeast Anatolia 82.4 76.4 −7.3% 36.7 37.9 3.3% Mediterranean 81.4 81.5 0.1% 34.9 40.1 14.9% West Anatolia 85.1 84.8 −0.4% 33.3 42.4 27.3% Türkiye 83.1 82.7 −0.5% 31.2 42.8 37.2% East Black Sea 81.5 78.8 −3.3% 49.7 45.2 −9.1% West Black Sea 82.6 82.9 0.4% 39.9 45.5 14.0% East Marmara 85.8 85.9 0.1% 29.1 46.7 60.5% West Marmara 88.5 87.3 −1.4% 39.5 47.6 20.5% Aegean 84.7 85.3 0.7% 37.6 48.7 29.5% Istanbul 86.3 86.2 −0.1% 28.8 49.5 71.9% Source: World Bank staff authors calculations based on TurkStat regional database. https://biruni.tuik.gov.tr/bolgeselistatistik/degiskenlerUzerindenSorgula.do# Figure 31.  Employment rates by regional zone among women, 2022 (%) Source: World Bank staff authors calculations based on TurkStat regional database and using mapchart.net https://biruni.tuik.gov.tr/bolgeselistatistik/degiskenlerUzerindenSorgula.do# 52 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 32.  Share of employment by category and by gender over time (%) Women 2022 2021 2020 2019 2018 2017 2016 2015 2014 0% 20% 40% 60% 80% 100% Men 2022 2021 2020 2019 2018 2017 2016 2015 2014 0% 20% 40% 60% 80% 100% Wage and salaried Employed Self - Employed Unpaid familly workers worker Source: World Bank staff authors calculations based on Household Labor Force Survey. As they move into the labor force and employment, Turkish women have increasingly filled semi-skilled service jobs despite similar educational levels. A higher share of employed women have completed university education than have men, but the jobs they hold do not necessarily reflect educational attainment (Figures 33–36). Most working women hold jobs that require medium skill levels, meaning that they are mostly clerks, service workers and shop and market sales workers, skilled agricultural and fishery workers, craft and related trades workers and plant and machine operators and assemblers (Figure 37). Men show a similar pattern with different magnitudes. However, a lower share of men holds low-skilled jobs than women. Labor Capital: Activating Markets 53 Figure 33.  Educational composition of the adult employed population by gender, 2021–22 (aged 25–64 yrs) 45% Men Women 40% 35% 30% 25% 20% 15% 10% 5% 0% Less than Secondary High school Vocational University primary high school Source: World Bank staff authors calculations based on Household Labor Force Survey The share of employment in agriculture has decreased over the last decade, while the share in services has increased, particularly among women (Figures 34–39). These trends hold true across the country including in eastern regions, which may have pulled women in who are otherwise outside the labor force. Industry and construction sectors remain male- dominated sectors, but more and more women have entered areas such as manufacturing (particularly administrative roles). Around 60 percent of employed women are working in services, while 23 percent of the women are employed in agriculture sector and an estimated 17 percent in manufacturing98. Over the past decade, in terms of services, public administration, health and education have also pulled in women. Agriculture production in Türkiye remains dominated by traditional household enterprises who largely lack modern technology available to more advanced cooperatives within Türkiye, reflected by a high share of unpaid family (and female) workers. 79 percent of the women are working as unpaid family workers in agriculture as their primary job and 76 percent of them are not registered in social security. The quality of jobs in the agriculture and service sectors are hampered by the precarious nature of temporary work and low productivity99. Jobs in the service sector in Türkiye span a large spectrum in terms of quality, in line with other upper middle-income countries. A large share of employment in services provides temporary, low-wage and informal jobs that lack social protection. Nearly 82 percent of the employed women in service sector comprises informal workers and 58 percent of the employed women in service sector work in low or medium skill jobs. While services sectors have boosted women’s employment, the quality and productivity of jobs lags. Historically, literature suggests that urbanization since 1988 has increased (rural) women’s labor force participation in Türkiye towards service sectors but skills and 98 TUIK data. Figures reflect data across 2021-early 2023, subject to minor annual changes since then. 99 See Genc S and Sengul G (2015). On the Future of Female Employment in Turkey. Working Paper. Central Bank of the Republic of Türkiye. 54 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity productivity have not kept pace100. While services have provided opportunities for women to enter the labor market, services expansion alone will likely not improve the quality of jobs in the absence of productivity gains for boosting earnings and associated labor and social protection coverage101. Figure 34.  Share of jobs and job growth by regional zone, 2010 versus 2022 25% 70% Share of Total Jobs Nationwide (%) Job growth percentage change (%) 60% 20% 50% 15% 40% 10% 30% 20% 5% 10% 0% 0% ia ia ia ul a an a lia ia an a a ar ar Se Se ol ol ol ol nb to ge ne m m at at at at na ta ck k rra ar ar Ae An An An An ac Is la tA tM M ite Bl tB st st rn e st es dl es ed st ea Ea te es Ea W id Ea W as M th W le M or he de N ut id 2010 2022 Job growth percentage change (%) So M Figure 35.  Share of jobs by sector across regional zones, 2022 100 75 50 25 0 e lia lia ia ul a an a lia ia an a a ar ar Se Se iy ol ol nb to to to ge ne rk m m at at a a na ta ck k Tü rra ar ar Ae An An An An ac Is la tA tM M ite Bl tB st st rn e st es dl es ed st ea Ea te es Ea W id Ea W as M th W le M or he d id N ut Agriculture Industry Service M So Source: World Bank staff authors calculations based on TurkStat regional database. https://biruni.tuik.gov.tr/bolgeselistatistik/degiskenlerUzerindenSorgula.do# 100 Dayıoğlu M and Kırdar M (2010). Determinants of and Trends in Labor Force Participation of Women in Turkey. State Planning Organization of the Republic of Turkey and World Bank Welfare and Social Policy Analytical Work Program Working Paper Number 5. Ankara. 101 İleri and Şengül (2017). Rise of Services and Female Employment: Strength of the Relationship. Central Bank of the Republic of Türkiye https://www.tcmb.gov.tr/wps/wcm/connect/237e8657-33c1-4821-a0b4-a61db333dd00/ wp1702.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-237e8657-33c1-4821-a0b4-a61db333dd00-m3fw6jq Labor Capital: Activating Markets 55 Figure 36.  Change in jobs by sector and regional zone, 2014 versus 2022 East Black Sea West Black Sea Mediterranean Middle Anatolia West Anatolia East Marmara Aegean West Marmara Istanbul Southeastern Anatolia Middle East Anatolia Northeast Anatolia Türkiye −60 % −40 % −20 % 0% 20 % 40 % 60 % Service Jobs Agriculture Jobs Industry Jobs Change 2014 vs 2022 Change 2014 vs 2022 Change 2014 vs 2022 Source: World Bank staff authors calculations based on TurkStat regional database. https://biruni.tuik.gov.tr/bolgeselistatistik/degiskenlerUzerindenSorgula.do# Figure 37.  Sectoral employment distribution by gender over time Women Men 100% 100% Public administration, 90% 90% community, social and other services and 80% 80% activities 70% 70% Trade, tramsportation, accommodation and 60% 60% food, and business and administrative services 50% 50% Industry 40% 40% Agriculture 30% 30% 20% 20% 10% 10% 0% 0% 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Source: World Bank staff authors calculations based on TUIK and ILOSTAT data. 56 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 38.  Jobs by economic activity and gender (thousands), 2014–2022 35,000 Electricity, gas, steam, water, sewerage 30,000 Real estate Financial and insurance 25,000 Information and communication Mining and quarrying Manufacturing 20,000 Agriculture, forestry and fishing Wholesale and retail trade Public administration and defence 15,000 Education Construction Human health and social work 10,000 Accommodation and food service Transportation and storage 5,000 Administrative and support service Other social, community service Professional, scientific and technical 0 Arts, entertainment and recreation 2014 2022 2014 2022 2014 2022 Total Men Female Source: World Bank staff authors calculations based on TurkStat statistical database. Figure 39.  Job growth by economic activity and gender, 2022 versus 2014 (percentage change) Manufacturing Agriculture, forestry and fishing Female Wholesale and retail trade Male Total Public administration and defence Education Construction Human health and social work Accommodation and food service Transportation and storage Administrative and support service Other social, community service Professional, scientific and technical Electricity, gas, steam, water, sewerage Real estate Financial and insurance Information and communication Mining and quarrying Arts, entertainment and recreation Total −50 % 0% 50 % 100 % 150 % 200 % 250 % Source: World Bank staff authors calculations based on TurkStat statistical database. Labor Capital: Activating Markets 57 Informality and the gender wage gap in Türkiye are marked and intertwined notably among semi-skilled workers. Informality remains especially prevalent among low- and semi-skilled women, although the Government has put in place several measures that have gradually helped increase coverage of social security (Figures 40–42). Informality overall steadily decreased by 21 percentage points (from 48 percent to 27 percent) between 2005 and 2022 in part as the share of services, effectiveness of national Social Security Institution SGK services particularly since comprehensive reforms in 2008 regarding incentives, awareness programs and cross- checks, and a more highly educated workforce increased102. As expected, informality is higher in the agriculture sector, with non-agricultural informality having gradually decreased until 2019, decreasing more rapidly since. As of 2022, 16.8 percent of employment in non- agriculture was informal. Informality among wage and casual workers in non-agriculture has decreased from 22 percent in 2005 to 9.4 percent in 2022. While informality seems to have declined during 2020 due to COVID including among women, this was driven by losses to labor force participation rates. Among women, the sharpest decline was in accommodation and food services, wholesale and retail, administrative support, and manufacturing (between 3 to 7 percentage points decline in informality rates). Among men, the sharpest decline is in construction, manufacturing, accommodation and food services, wholesale and retail and arts, entertainment, and recreation (between 3 to 10 percentage points decline). Lower demand for labor in certain sectors with high informality due to depressed consumer demand may have led to major exit by workers, particularly in services which tend to be less productive. In addition, firms may have formalized previously informal workers to benefit from pandemic-related subsidies, yet to be evaluated fully. Figure 40.  Share of informal and formal employment by worker profile 2020 (%) 100% 80% 60% 40% 20% 0% Men Women 15 - 24 25 - 64 65+ Literate but not... Primary school (5 years) Secondary High school University Agriculture Manufacturing Construction Trade Services Industry Formal Informal Gender Age Education Economic sector Source: World Bank staff authors calculations based on LFS. Note: trends are largely similar over the period 2020–2023. 102 Source: Correspondence from Turkiye Social Security Institution SGK, and https://www.sgk.gov.tr/Download/ DownloadFileStatics?f=reform_sonrasi_sosyal_guvenlik.pdf&d=YAYINLARIMIZ. Note that data on labor force participation and informality rates compiled by SGK may differ from national data compiled by national labor force surveys due to data collection differences. An in-depth analysis of all factors, policies and measures impacting employment and informality is outside the scope of this analysis. See also: Bağır, Küçükbayrak and Torun (2021). Declining Labor Market Informality in Turkey: Unregistered Employment and Wage Underreporting. Working Paper No: 21/19. Central Bank of the Republic of Türkiye. https://www.tcmb.gov​.tr/wps/wcm/connect/c9f5851d-d1d2-42ee-86bf-f75044b0ba26/wp2119.pdf?MOD=AJPERES &CACHEID=ROOTWORKSPACE-c9f5851d-d1d2-42ee-86bf-f75044b0ba26-nIaKNw0 58 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 41.  Informal overall employment rates over time among agricultural versus non-agricultural workers (%) 60% 48.0% 50% 40% 34.3% 30% 27.0% 22.0% 20% 16.8% 10% 9.4% 0% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2019 2018 2019 2020 2021 2022 Total informality rate Non-agricultural informality rate Informality rate for wage and paid workers in non-agriculture Source: World Bank staff authors calculations based on Household Labor Force Survey. Figure 42.  Overall rate of informal employment by gender over time (%) 70% 65% 65% 60% 55% 50% 45% 42% 40% 34% 35% 30% 25% 23% 20% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2019 2018 2019 2020 2021 2022 Women Men Source: World Bank staff authors calculations based on Household Labor Force Survey. Labor Capital: Activating Markets 59 Informality in Türkiye likely persists due to several reasons outside the scope of this work, including, inter alia, reservation wage103, minimum wage shifts, labor regulations’ enforcement, tax policy and certain social security extended benefits to dependents, and exemptions102. Self-employed agricultural workers, spouses, dependents, and paid agricultural workers who work with temporary service contracts are exempt the law from mandatory social security registration. Informal employment is also prevalent among retired people mostly related to the early retirement age policies in the 1990s. Retirees continue to work as informally since their additional premium after retirement does not affect retirement pension, thereby both firms and retirees may prefer to be attached in informal employment104. As a high supply of workers willing to work at low wages has remained, firms are more likely to underreport or evade altogether declaring wages or worker registration to the national social security institution (Sosyal Güvenlik Kurumu/SGK). The influx of migration and refugees, notably after the Syrian conflict, has likely reduced formal low-skilled job vacancies on aggregate notably in agriculture as more migrants move into the sector at even lower pay105. For Turkish women working informally in low-skilled jobs, this means they have likely accepted informal job opportunities instead. Informality is closely tied to the gender wage gap in Türkiye (Figures 43–45). First, in terms of crude income (wages plus additional direct monetary benefits or assets), the largest crude gender income gap appears among predominantly informal self-employed and informal casual workers, hovering between 70–90 percent106. Based on analysis that covers all workers (informal and formal workers), the gender gap also widened modestly on average between 2014 and 2020. This has possibly been driven by more pronounced wage stagnation and/or job exits in services sectors with a relatively high rate of women’s participation. As Türkiye’s aggregate gender gap may mask relatively low wages in general for men and women, the gender pay gap also reflects labor market segmentation in occupations, jobs, and sectors. This may not necessarily only wage differences within the same job. In construction, the few women found are mainly managerial, highly skilled workers, with a gender wage gap favoring women by roughly 19 percent107. By contrast, in sectors such as health services in which a higher share of advanced medical professionals is largely male, the gender wage gap is highest at nearly 22 percent. Average nominal wages increased steadily between 2014–2022 but real wages have not kept up with spiking inflation. The Government has introduced regular annual and semi-annual minimum wage increases. Previous work showed that hikes during 2015–2016 tended to increase informality notably among low- productivity, low-profit firms108. While this has disproportionate implications for women, this also 103 Lowest wage at which a worker is willing to work (for less or more) relative to wages on offer. 104 Number of Informally working retirees is 3.5 million in 2018 in Türkiye (Bagir et al, 2021). 105 Begen, Mercan and Barlin (2023). Immigration, job vacancies, and Beveridge Curve: Evidence from Syrian refugees in Turkey. Economic and Labour Relations Review (2023), 1–20. https://www.cambridge.org/core/journals/ the-economic-and-labour-relations-review/article/immigration-job-vacancies-and-beveridge-curve-evidence-from​ -syrian-refugees-in-turkey/C94FBF38A67B9BD4BC9285FCBECED743 106 World Bank staff authors calculations using Household Labor Force Survey Data. 107 TUIK Structure of Earnings Survey (every four years, 2006–2018). Values reflect 2018 released 2020, covering establishments with at least 10 employees. Excludes agriculture as a result, typically earning at or below minimum wage. 108 Acar, Bossavie and Makovec (2019). Do Firms Exit the Formal Economy after a Minimum Wage Hike? Quasi- Experimental Evidence from Turkey. World Bank Policy Research Working Paper 8749. Washington DC: World Bank. 60 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity has the effect of spurring their economic activity especially for women who may otherwise not have opportunities, informal or not. The balance depends on the broader national vision. The informal gender wage gap rises to nearly 25 percent compared to 11 percent among formal sector workers, based on TUIK and ILO analysis. Recent joint work by TUIK and ILO (2020)109 estimates the average gender wage gap by profile using household plus enterprise data, showing an average overall gap of 15.6 percent as of 2018 in Türkiye. The pay gap was also found to increase with age. Women working in services and sales face highest wage gap (43.5 percent), followed by health and social services, and the remainder. Working mothers tend to earn less than both working non-mothers and working fathers (11 percent and 19 percent, respectively). Similarly, among full-time wage workers, the OECD estimates the average gender gap to be 11 percent as of 2018, compared to an OECD average of 12110, noting that this excludes self-employed, part-time, informal work which constitutes 40 percent of Türkiye’s female labor force. The OECD and global averages are also driven by a large share of low-average wage countries, showing that globally the gender gap remains a concern given labor market segmentation in job types. Adjusting for purchasing power parity (PPP), average real annual wages in Türkiye for full-time wage employees (a subset) were estimated at US$ 31,000, compared to an OECD average of US$ 53,000111. Despite social spending, Türkiye’s average wages appear lower than in comparable countries, disproportionately hitting sectors employing women thee most. Although Türkiye also has a relatively broad social benefits and services system (for example, spending nearly 7.5 percent of GDP on pensions alone as of 2019), average wages appear lower than in comparable countries with similar systems such as Chile (3.1 percent) and Poland (10.9 percent)112. In Türkiye, employee compensation as a share of gross value added is also among the lowest in the OECD across all sectors113. It is also lowest for agriculture, a high women’s employer, followed by industry and services. To note, some of the lowest wage gender gap countries in the OECD are also some of the lowest-wage earners, and vice-versa, highlighting the nature of the economy and jobs at play. Türkiye has implemented several strategies to reduce informality with varying degrees of effectiveness. Embodied within its Five-Year Development Plans, multiple national strategies have included measures for reducing vulnerable employment, including the National Employment Strategies, Action Plan to Fight Against Informal Employment and 109 https://www.ilo.org/wcmsp5/groups/public/---europe/---ro-geneva/---ilo-ankara/documents/publication/ wcms_756660.pdf 110 OECD Gender wage gap data, most recently globally comparable database based on TUIK data https://data.oecd.org/earnwage/gender-wage-gap.htm 111 OECD Average wages data, most recently globally comparable database based on TUIK data https://data.oecd.org/earnwage/average-wages.htm#indicator-chart 112 OECD Pension spending data, most recently globally comparable database based on TUIK data https://data.oecd.org/socialexp/pension-spending.htm 113 OECD Employee compensation data, most recently globally comparable database based on TUIK data https://data.oecd.org/earnwage/employee-compensation-by-activity.htm#indicator-chart Labor Capital: Activating Markets 61 the SGK Annual Central Action Plans. The first main large campaign and action plan (Fight Against Informal Employment) was launched in 2005 by the Ministry of Labor and Social Security with participation of key government institutions. Other instruments have been used such as labor audits, incentives to firms, and awareness raising at a societal level. The key may lie more in implicit and explicit incentives facing workers and firms in terms of occupational and sectoral segregation, economies of scale given the bulk of employment dominated by relatively small size SMEs, and household roles discussed later. Figure 43.  Nominal gender income gap over time by employment category (percentage difference of men's average income relative to women's) 150% 125% 100% 75% 50% 25% 0% −25% 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Total Employer Regular employee Self employed Casual employee Source: World Bank staff authors calculations based on TUIK annual labor force statistics March 2023, most recent at time of writing.114 Note: calculated as the percentage difference between men and women using on annual mean income. Figure 44.  Real income by sector versus real minimum wage over time (real average annual income as a share of minimum wage, percentage difference) 160% 120% 80% 40% 0% −40% 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Total Services Industry Construction Agriculture Minimum wage Source: World Bank staff authors calculations based on TUIK Income and Living Standards Survey, Presidency information on 115 minimum wage 2022,116 and Eurostat.117 114 Gender gap calculated by World Bank staff based on data from: TUIK Income and Living Standards Survey released May 2023 https://data.tuik.gov.tr/Bulten/Index?p=Income-Distribution-Statistics-2022-49745 115 TUIK Income and Living Standards Survey released May 2023 https://data.tuik.gov.tr/Bulten/Index?p=Income-Distribution-Statistics-2022-49745 116 Presidency of the Republic of Türkiye, 2022 Minimum Wage https://www.tccb.gov.tr/en/news/542/133891/-minimum-wage-will-be-tl-4-250-in-2022- 117 Eurostat, Minimum wage data (local currency and Purchasing Power Standard $PPP) https://ec.europa.eu/eurostat/databrowser/view/EARN_MW_CUR__custom_6613344/default/table?lang=en 62 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 45.  Average annual wages among full-time employees across OECD countries during 2018–2022 (US$ PPP) 90,000 80,000 70,000 60,000 50,000 40,000 30,000 20,000 10,000 0 Mexico Colombia Greece Slovak Republic Hungary Costa Rica Türkiye Portugal Chile Czech Republic Latvia Estonia Poland Japan Spain Lithuania Israel Italy Slovenia Korea Sweden New Zeland Finland Ireland France OECD - Total Norway United Kingdom Germany Canada Australia Netherlands Austria Denmark Belgium Switzerland United States Luxembourg Iceland Source: World Bank staff authors based on OECD Average wages data111. All else held equal, formal employment rates are highest among highly skilled men, with the highest earnings in administration, mining, and manufacturing. Multi-factor regression118 shows that low-skilled women are significantly at a disadvantage in terms of formal wage employment rates, all else held equal.Illustrative analysis developed for this section applies the conceptual framework on the demand for human capital utilization (employment) as a function of labor, financial and social capital. It assesses selected factors over a ten-year period for various employment outcomes based on available data and using proxy indicators. This is a stylized illustration and not an exhaustive analysis; future work can more rigorously untangle geographic, public representation and financial effects due to possible endogeneity and adjusted instruments needed beyond crude measures readily available. This longitudinal analysis covers the 2007–2019 period until COVID, excluding subsequent shocks which will require future work to understand labor mobility and effects over a subsequent 5–10-year period. Over this period, the share of formal wage employment increased from 42 percent in 2007 to 60 percent in 2019 just prior to COVID. At the same time, the percentage of formal self-employed individuals remained constant at 9 percent. Informal wage employment represents an estimated 13 percent of total employment and informal self-employment 9 percent. There are also 9 percent of employed workers who work for their families with no remuneration. 118 Prepared by authors. The multi-factor regression analysis was prepared using multi-year Türkiye Survey on Living Conditions (SILC) and Labor Force Survey (LFS) over 2007–2019. Labor Capital: Activating Markets 63 Figure 46.  Determinants of employment type on wages [odds p (wage informal)/p (wage formal)] Male HH head Age Age sq. Education (REF, litarate) Literate High school Higher education Marital (REF, single) Married Widowed Divorced Econ, Activity (REF, agriculture) Mining and quarrying Manufacturing Electricity, gas, steam, water supply, sewage Construction Whole-sale and retail trade Transportation and storage Accommodation and food service activities Information and communication Financial and insurance activities Real estate activities Professional, scientific and technical activity Administrative and support service activity Public administration and defence Education Human health and social work activities Art, entertainment and recreation Other social, community and personal services Occupation (REF, Managers) Professionals Technicians and associate professionals Clerical support workers Service and sales workers Skilled agricultural and fishery workers Crafts and related trades workers Plant and machine operators and assembly Elementary occupations Year (REF, 2007) 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 −35% −30% −25% −20% −15% −10% −5% 0% 5% 10% Source: Prepared as background to World Bank Türkiye Public Financial Review, 2022–2022. Adapted by World Bank staff authors based on TUIK LFS 2007–2019 and World Bank/Packard et al 2019119, Palacios and Robalino (2020) and Robalino, Romero and Walker (2020). 119 World Bank/Packard et al (2019). Risk-Sharing in a Diverse and Diversifying World of Work. Social Protection and Jobs White Paper. Washington DC: World Bank. https://openknowledge.worldbank.org/entities/publication/5a09ca98-f1a7-5289-b2e6-7e06c63b0391 64 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Regression results show that the likelihood of formal employment, all else held equal, has been significantly higher among highly skilled men relative to other profiles over the past decade (Figures 46–50). In addition, other key factors include adults older than 25 years, and heads of households, and significantly lowest among divorced and widowed workers. Similar determinants are seen with respect to formal self-employment versus informal self-employment. In terms of economic sector, all else held equal, informality is significantly higher in agriculture than any other sector. The determinants of labor income over a decade show that earnings’ growth among the lowest-income households are attributed to labor productivity and hours worked. Earnings declined with working hours and increased with productivity, favoring high-income households. All deciles witnessed a modest boost from switching to more productive sectors and to formal jobs. As mentioned, the Government has in place several outreach programs which can be further scaled-up to improve awareness and facilitate registration for women and men, including existing approaches through local community leaders, field visits and household outreach targeted to agricultural zones. Likewise, changes in labor income over the same period show that low-income households were highly sensitive to changes in productivity and working hours. COVID has had a significantly higher impact on employment and earnings, all else held equal, on women, youth, unskilled and informal sector workers, regardless of sector. Informal work bears out as a function of individual profile (age, demographic, skills), the type of occupation, and the economic sector. Overall, as seen in earlier descriptive findings, controlling for all else, the likelihood of informal wage employment relative to formal wage employment has been gradually declining for women and men. With every higher level of education, the likelihood of informality drops gradually, all else equal. Gender plays a significant role in earnings, controlling for all else. This analysis shows that men’s earnings are 51 percent higher than women’s among informal wage employment and 108 percent higher among informal self-employed workers. Earnings are also largely a function of economic sector both formal and informal jobs among women and men. Among formal wage jobs, the highest earnings, all else equal, are found in public administration, mining, manufacturing, and the health sector, while the lowest earnings are observed in science and technology services, education, and agriculture. Education plays a modest role in earnings for formal wage employment and self-employment (formal and informal), but hardly any role in informal wage employment. Labor Capital: Activating Markets 65 Figure 47.  Determinants of labor income among formal wage employment ( LN (income) | wage formal) Male HH head Age Age sq. Education (REF, litarate) Primary school High school Higher education Marital (REF, single) Married Widowed Divorced Econ, Activity (REF, agriculture) Mining and quarrying Manufacturing Electricity, gas, steam, water supply, sewage Construction Whole-sale and retail trade Transportation and storage Accommodation and food service activities Information and communication Financial and insurance activities Real estate activities Professional, scientific and technical activity Administrative and support service activity Public administration and defence Education Human health and social work activities Art, entertainment and recreation Other social, community and personal services Year (REF, 2007) 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 −3% −2% −1% 0 1% 2% 3% 4% 5% 6% Source: Prepared as background to World Bank Türkiye Public Financial Review, 2022–2022. Adapted by World Bank staff authors based on TUIK LFS 2007–2019 and World Bank/Packard et al 2019, Palacios and Robalino (2020) and Robalino, Romero and Walker (2020). 66 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 48.  Determinants of labor income among informal wage employment ( LN (income) | wage informal) Male HH head Age Age sq. Education (REF, litarate) Primary school High school Higher education Marital (REF, single) Married Widowed Divorced Econ, Activity (REF, agriculture) Mining and quarrying Manufacturing Electricity, gas, steam, water supply, sewage Construction Whole-sale and retail trade Transportation and storage Accommodation and food service activities Information and communication Financial and insurance activities Real estate activities Professional, scientific and technical activity Administrative and support service activity Public administration and defence Education Human health and social work activities Art, entertainment and recreation Other social, community and personal services Year (REF, 2007) 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 −1% 0% 1% Source: Prepared as background to World Bank Türkiye Public Financial Review, 2022–2022. Adapted by World Bank staff authors based on TUIK LFS 2007–2019 and World Bank/Packard et al 2019, Palacios and Robalino (2020) and Robalino, Romero and Walker (2020). Labor Capital: Activating Markets 67 Figure 49.  Determinants of labor income among formal self-employment (LN (income) | Self- employed formal) Male Age Age sq. Education (REF, litarate) Literate but not a graduate Primary school Secondary, vocational secondary or primary High school Vocational or technical high school Faculty/university, college or higher education Marital (REF, single) Married Widowed Divorced Public sector Econ, Activity (REF, agriculture) Manufacturing Construction Whole-sale and retail trade Administrative and support service activity Public administration and defence Other social, community and personal services Occupation (REF, Managers) Professionals Technicians and associate professionals Clerical support workers Service and sales workers Skilled agricultural and fishery workers Crafts and related trades workers Plant and machine operators and assembly Elementary occupations Year (REF, 2007) 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 −6% −4% −2% 0 2% 4% 6% Source: Prepared as background to World Bank Türkiye Public Financial Review, 2022–2022. Adapted by World Bank staff authors based on TUIK LFS 2007–2019 and World Bank/Packard et al 2019, Palacios and Robalino (2020) and Robalino, Romero and Walker (2020). 68 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 50.  Determinants of labor income among informal self-employment (LN (income) | Self- employed informal) Male HH head Age Age sq. Education (REF, litarate) Primary school High school Higher education Marital (REF, single) Married Widowed Divorced Econ, Activity (REF, agriculture) Mining and quarrying Manufacturing Electricity, gas, steam, water supply, sewage Construction Whole-sale and retail trade Transportation and storage Accommodation and food service activities Information and communication Financial and insurance activities Real estate activities Professional, scientific and technical activity Administrative and support service activity Public administration and defence Education Human health and social work activities Art, entertainment and recreation Other social, community and personal services Year (REF, 2007) 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 −0.5% 0% 0.5% 1% 1.5% 2% Source: Prepared as background to World Bank Türkiye Public Financial Review, 2022–2022. Adapted by World Bank staff authors based on TUIK LFS 2007–2019 and World Bank/Packard et al 2019, Palacios and Robalino (2020) and Robalino, Romero and Walker (2020). Labor Capital: Activating Markets 69 Leveraging Labor Policies and Programs The shift of women and men to new sectors, the growth of wage employment and the protection of formal sector workers from shocks seen in Türkiye has been supported by a range of well-established labor market institutions. These include labor regulations, policies and active labor market programs, totaling nearly 1.0–1.5 percent of GDP annually over 2019–2021, compared to an OECD average of nearly 2.5 percent120. Key labor market programs assessed in this section include wage subsidies (largely managed by the national social security fund, SGK) and active labor market programs (ALMP) such as vocational training and on-the-job training programs (multiple types) led by the national employment agency, İş Kurumu/İŞKUR. Overall, these reach roughly 8 percent of all working-able individuals not working, defined as registered unemployed or out of the labor force, where 4 percent of women are covered compared to 15 percent of men (Figures 51–52). Figure 51.  Share of all individuals not working covered under labor programs by gender, 2022 (%) 40,000,000 100% Percent share of coverage as a percent (%) 80% 30,000,000 Number of individuals 60% 20,000,000 40% 10,000,000 20% 0 0% Men Women Total Registered unemployed Out of labor force + Registered unemployed Share of out of labor force plus registered Share of registered unemployed as a % unemployed covered by labor programs (%) covered by labor programs (%) Source: World Bank staff authors using Turkish National Employment Agency (İŞKUR) and TUIK Labor Force Statistics114. 120 OECD Public expenditure of labor market programs, https://stats.oecd.org/Index.aspx?QueryId=49447# 70 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity İŞKUR manages national and donor-financed employment programs in Türkiye as the main national employment agency, with an increasing focus on women. It had an annual domestic budget of nearly 14 billion Turkish Lira (as of 2022, US$ 500 million equivalent) covering programs administered by 81 provincial offices121. Earlier work elsewhere includes more detailed public expenditure analysis of social protection and labor programs outside the scope of this analysis122 123. In addition, İŞKUR, has been implementing 20 percent of all internationally financed jobs-related projects in Türkiye over the period 2015–2024 (Figure 53). This comprises the equivalent of US $248.5 million out of an estimated US$ 1.26 billion jobs projects (including 32 projects focusing on ALMPs totaling US$ 536 million and two entrepreneurship financing projects funded by loans totaling $730 million). Of the 34 projects, nearly 30 percent of the number and share of financing target women solely (Annex). The rest target the general or youth population often with gender quotas of around one-third women. In total, these 34 projects will have targeted a total of 270,000 job seekers over a 10-year period, or an estimated 1 percent of the total stock of out of work population as of today (36.9 million). This shows that coverage can be scale-up further of several promising projects that on average range from US$ 5–35 million per project and typically 1,000–20,000 beneficiaries. In addition, only an estimated 7 percent adopt mixed approaches combining demand- (firms) and supply-side (job seekers) support, whose share can be increased further for greater effectiveness, discussed below. To date, women make up nearly 40 percent of all domestically-financed İŞKUR ALMP programs. ALMP coverage in Türkiye has been increasing to catch up with wage subsidies and unemployment benefits’ coverage, noting that eligibility criteria for all programs is linked to the formal sector. COVID and the 2023 earthquakes saw the temporary expansion of wage subsidies in 2019 and other job protections (layoff freeze during both periods increased coverage temporarily, while unemployment benefit coverage has fluctuated. The decrease in unemployment benefits is closely correlated with the significant decrease in labor force participation, early retirement, and the COVID layoff freeze during 2020. 121 İŞKUR Annual Report for 2022 https://media.iskur.gov.tr/58449/2022-yili-kurumsal-mali-durum-ve-beklentiler-raporu.pdf 122 This analysis is based on data available at the tim e of writing, covering through early 2021. This analysis will be updated as needed in future work outside the scope of this paper, as the main emphasis of the policy note is trends and implications over time which remain largely unchanged in spite of modest changes in data and indicators. 123 See Elgazzar et al/World Bank (2022). Türkiye in Transition: Next-Generation Human Capital Investments for Inclusive Jobs. World Bank: Washington DC. Labor Capital: Activating Markets 71 Figure 52.  Coverage of national labor programs overall and by gender over time (% of registered unemployed) 70% (a) Overall coverage Share of registered unemployed (%) 60% 50% 40% 30% 20% 10% 0% 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 % ALMP % UB % Wage subs 250,000 Doctorate (b) Coverage of ALMP by type, gender and education Post Graduate 200,000 License Associate Degree Secondary Education 150,000 (High school and equivalent) Primary Education Literate 100,000 Illiterate 50,000 0 Male Female Male Female Male Female Vocational On-the-job All ALMPs 100% (c) Share of beneficiaries of ALMPs who are women over time 75% 50% 25% 0% 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Vocational training programs Unemployment benefits Registered unemployed Entrepreneurship training program Job placement All programs On-the-job training programs Source: World Bank staff authors using Turkish National Employment Agency (İŞKUR) and National Social Security Institution (SGK) Statistics. Note: ALMP: active labor market programs. For (a) and (b) prepared using data through 2020 in advance; patterns for 2020 similar through 2022. Entrepreneurship Training Scheme remains available but since 2020 not under implementation. 72 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 53.  Distribution of internationally-financed jobs projects by target group (gender) and type in Turkiye, 2015–2024 Financing by Target Group Financing by Project Type (% of Total) (% of Total) Institutional Mixed (Firms + support 5% Both women/men Women-only Job seekers) 6% 11% 37% Job seeker services 21% Quota 52% Firms’ support 68% Source: World Bank staff authors’ mapping and calculations on based on published program documentation and Ministry of Labor and Social Security Directorate of European Union and Financial Assistance https://www.ikg.gov.tr/?lang=en Of note, depending on how they are designed, labor market programs can help mitigate market failures for the most vulnerable based on global and Türkiye-specific evidence. A series of two seminal global meta-analyses in 2016–19124 and 2022125 show that active labor market programs for youth can have significantly large effects on employment. This is especially the case when targeting the most vulnerable youth with a holistic benefits package with private sector implementation. These combine financial support or incentives to employers and/or entrepreneurship financing on the demand-side with supply-side measures for workers, ie. to facilitate job search, case management to ensure participation, and targeted skills upgrade per beneficiary profile. Critically, no one specific intervention or package is a magic bullet alone; the principle is to ensure specific profiling of a specific beneficiary’s main constraints and tailoring a package. This holds for young women and men from lower-income settings particularly. 124 Kluve, Puerto, Robalino et al/World Bank, ILO (2019). Do youth employment programs improve labor market outcomes? A quantitative review. World Development 114 (2019) 237–253 https://www.sciencedirect.com/science/ article/pii/S0305750X18303905 and at Kluve, Puerto, Robalino et al/IZA (2016). IZA DP No. 10263 https://www.iza.org/ publications/dp/10263/do-youth-employment-programs-improve-labor-market-outcomes-a-systematic-review 125 Puerto, Weber et al/ILO, World Bank, Government of Netherlands (2022). Report — Systematic review on the effects of youth-oriented active labour market programmes https://english.iob-evaluatie.nl/results/youth-unemployment Labor Capital: Activating Markets 73 In Türkiye, work to date has shown the positive impact of labor market programs managed by İŞKUR depending on which programs and design. An enhanced İŞKUR On-the-Job Training Program, complemented by skills development and, for non-Turkish speakers, language and work permits, supported by a recent project to expand coverage and incentives to employers, was associated with an employment placement rate of 64.5 percent, with 67 percent among men and 52 percent among women126. Syrian SuTP beneficiaries comprising at least half of total beneficiaries of this program showed similar outcomes, resulting in even higher marginal benefits among Syrian women. This shows the importance of these programs on nearly doubling women’s labor utilization rate. Vocational training courses contracted through competition to private providers were found to have a significantly large effect, particularly among providers facing more competition (in terms of prior selection based on demonstrating effectiveness on employment)127. Wage subsidies (employment incentives) have tended to expand immediately after the onset of shocks in Türkiye, such as post-2008, post-2018 and COVID. Up to thirteen employment subsidies have been introduced in Türkiye over the past two decades (some replacing or consolidating others), targeting different populations and firms and different parameters regarding duration and benefits. While some of these programs were introduced before 2008, several were introduced following the 2008 global financial crisis. Among the registered unemployed, subsidies to cover wages and social security contributions are afforded to apprentices, interns and trainees not covered by full-time job contracts, amounting to an estimated 1.5 million individuals as of first quarter 2020, which increased temporarily during COVID and following the 2023 earthquakes to certain firms, but coverage remained largely stable over this period. Effects analyzed to date have shown positive outcomes particularly among the most vulnerable workers who would otherwise work informally. Evaluations are ongoing of different subsidies. To date, recent evidence by Aşık, Bossavie, et al (2022)128 from Türkiye suggest some subsidies targeting social security contributions paid by firms (tax wedge) may not necessarily increase job creation on aggregate, but they improve the quality of jobs offered by firms and access to women and youth (positive distributional effects). This was especially the case among low- and medium- skilled women as evaluated by Balkan, Baskaya and Tumen (2016)129 following the global financial crisis of 2008. 126 World Bank (in press). Employment Support Project for Syrians Under Temporary Protection and Turkish Citizens Project, ID P161670. Implementation Completion and Results Report. 127 World Bank (2013). Turkey: Evaluating the impact of İŞKUR’s vocational trainign programs. Washington: World Bank https://documents1.worldbank.org/curated/en/954771468318313306/ pdf/823060P12051400h0final0report0small.pdf 128 Aşık G, Bossavie L, Kluve J, Özen SE, Nebiler M, Oviedo AM/World Bank (2022). The Effects of Subsidizing Social Security Contributions Job creation or Informality Reduction? Policy Research Working Paper 9904. Washington DC: World Bank https://documents1.worldbank.org/curated/en/685191642611488161/pdf/The-Effects-of​ -Subsidizing-Social-Security-Contributions-Job-creation-or-Informality-Reduction.pdf 129 Balkan B, Baskaya YS and Tumen S (2016). Evaluating the Impact of the Post-2008 Employment Subsidy Program in Turkey. IZA Discussion Paper No. 9993 74 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Of the employment incentives provided for full-time formal sector jobs, one main subsidy scheme predominates, Scheme 5510 (or Five-Points Scheme), benefiting nearly 70 percent of all firms receiving employment subsidies. Employment subsidies are primarily financed through the Unemployment Insurance Fund and the Ministry of Treasury and Finance, administered through İŞKUR and the Social Security Institution (SGK), hovering at approximately 0.5–0.7 percent of GDP as of 2017–2022. The four largest schemes reached a total of over 1.5 million firms (out of an estimated 3.5 million active SMEs, representing 99.8 percent of all registered enterprises)130 and 9 million workers over 2019–2021 (out of nearly 28 million)131. COVID-associated expansions of employment subsidies in terms of wage protection and social security premia broadened the scope of beneficiary firms serving workers, excluding the large share of informal working women. In terms of the impact of employment subsidies on employment, previous work has shown that formal employment in small firms has tended to increase through the formalization of existing informal jobs, particularly for women and youth132. Effects also tend to be larger in sector such as construction and manufacturing. Adjusting subsidies to support to reach more vulnerable women workers, notably first-time job seekers, would further improve efficiency and employment impacts. That said, the duration of impacts depends on productivity gains and labor costs over the mid-term perceived by firms. Active labor market programs (ALMPs) in terms of employability paid and unpaid training programs Türkiye covered almost 15 percent of the registered unemployed133 almost equally across gender over 2019–2022, modestly up from 14 percent in 2020. Coverage has generally increased anti-cyclically since 2007, notably expanding during the 2008–2009 global financial crisis and similar shocks. Prior to COVID in 2019, ALMPs accounted for over 568,000 beneficiaries (15 percent of the unemployed), compared to 1.013 million recipients of unemployment benefits (26 percent of the unemployed). Coverage expanded temporarily to address COVID and related shocks but has largely remained stable to date. Since 2020 and of the over 423,000 beneficiaries enrolled in ALMPs, the national On-the-Job Training Program (OJT) remained the dominant choice (80 percent), with the Vocational and Technical Courses Program (VT) accounting for 20 percent particularly among women. Among the nearly 1,400 VT courses on offer, clothing and textiles was the most common occupational skill in demand, accounting for nearly one out of three beneficiaries (26 percent). Among nearly 34,000 OJT programs on offer, nearly one in three beneficiaries were in sales or retail occupations (26 percent), followed 130 Union of Chambers and Commodity Exchanges of Türkiye (TOBB), https://www.tobb.org.tr/KobiArastirma/ Sayfalar/Eng/SMEsinTurkey.php. Accessed March 24, 2020. 131 World Bank (forthcoming), Evaluation of employment subsidy schemes, from progress reviews for June 2019 and February 2020. 132 Betcherman et al., 2020; World Bank, forthcoming. 133 Registered unemployed defined as those registered with the Turkish national employment agency, İŞKUR. On average, İŞKUR data capture approximately 80 percent of the total unemployed estimated through national labor force surveys conducted by the Turkish national statistics institute, TUIK. Labor Capital: Activating Markets 75 by clothing and textile-related occupations (14 percent), with the remainder split nearly equally across trades (metallurgy, furniture), hospitality, and other services. Over the past decade, the demand for OJT by occupation has evolved, with a shift towards more skilled manufacturing workers at mid-level and client services. ALMPs tend to cover younger, less-skilled workers and serve as a pathway to re-skilling and facilitating the transition to new jobs and sectors. Most ALMP beneficiaries are young adults under the age of 34 years (77 percent), heavily concentrated among 20–24-year-olds (33 percent). The majority of ALMP beneficiaries continue hold a primary or secondary education (71 percent), although vocational courses are skewed towards primary-schooled workers than secondary (51 versus 27, respectively). By gender, while no major differences are seen overall and among on-the-job training, vocational course enrollment is skewed towards women relative to men (69 versus 31 percent, respectively). These patterns have been generally constant over time. The impact of ALMPs is tied to how responsive they are to the demand by firms for certain occupational skills at the local level. Their effectiveness is also tied to keeping up with shifts expected following shocks and within the context of the green transition will heighten the need for demand-driven training. Administrative and online job vacancy data highlights the need for social as well as technical skills in the formal sector and across regions134. The demand for skills may have shifted pre- and post-COVID, as the need for service sector workers has declined and that for construction, for example, has increased, although it is unclear whether the latter is specifically due to COVID. Occupations in demand have shifted over a decade, retaining manual trades but increasingly comprising diversified services as more women enter ALMPs in textiles, office work and call centers (Figure 54). Occupations including routine tasks (such as machine operators, call center information clerks and product graders and testers) and occupations requiring non-routine manual tasks (such as customer service) have historically been in high demand, with wide variations across provinces. Increasingly, IT-related and social skills (such as software knowledge, communication and teamwork skills) and professionalism (discipline, time management) also tend to be in high demand, particularly in regions with higher economic activity. As greater attention is given to building back better and the green economy as part COVID-recovery, targeting skills retraining to youth and first- time job seekers, particularly women, may be especially cost-effective. 134 World Bank, forthcoming; Turkish Employment Agency data. 76 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 54.  Jobseeker demand for on-the-job training by occupation (OJT, İŞKUR programs), 2010 versus 2020 (% of registered unemployed) OJT, 2010 Manual worker 14.1% Computer manager 6.9% Janitor 3.8% Business manager 2.9% Machine operator, Sewing/Clothing 2.7% Labourer, Manufacturing/Readymade 2.4% Office staff 2.2% Marketers 2.2% Mechanic, Sewing 1.8% Patient Advisor 1.8% Costumer service officer 1.7% Cooking Assistant 1.7% Designer, Web 1.5% Mechanic, Electronic/Computor 1.3% Designer, computer-aided 1.0% OJT, 2020 Marketers 12.3% Manual labor, Manufacturing/Readymade 7.9% Receptionist/Front office staff 6.0% Mechanic, Sewing 3.5.9% Sewing machine operator-clothing 3.4% Customer service officer/Assistant 3.2% Patient Advisor 3.2% Call center personnel 2.7% Officer worker 2.6% Waiter 2.5% Market Personnel 1.6% Laborer, Plastic/Manufacturing fitter basic 1.5% Manufacturing/Machinery 1.4% Assembler, Metal products 1.2% Source: World Banks staff calculations, İŞKUR data, most recent available data the time of initial analysis through COVID; post-COVID analysis to follow in next 5–10 year period to account for adjustments over time. Labor Capital: Activating Markets 77 Job search data (among formal sector jobs) shows that over a decade, women’s job placement rate has increased, although not necessarily evenly across sectors (Figures 55–56). Overall job search patterns since COVID recovery and following earthquakes may be driven by regional labor force participation dynamics, matching efficiency between available competencies and occupational skills most in demand over time, and regional changes in the demand for jobs. Women appear to be competing for a relatively small share of job openings, despite higher numbers of job openings and unfilled vacancy rates in other sectors. While unfilled vacancies among women be due to jobseekers’ choice and real or perceived job quality, high rates indicate labor mismatches. Once again, manufacturing stands out as the sector which appears to have the greatest gaps in terms of manpower matching, which comprised around 43 percent of all job openings as of 2020–2021. Women’s placement rates in manufacturing have only increased from 25 to 33 percent over the past decade. By contrast, education accounted for around 2 percent of all job vacancies, and women’s placement has almost doubled over the same period from 37 to 63 percent. In terms of absolute numbers, more women are working in manufacturing, but this illustrates that latent demand is likely higher in certain sectors like industry given high rates of unfilled vacancies while millions more women are out of the workforce. Figure 55.  Distribution of total vacancy rates for 2010 and 2020 versus the share of women's job placement rate for 2020, 2010 versus 2022 100% 50% 0% l iv ing Su nst air n es or d se al es ge es Ed ces n Fo /De T , a Min ry/F e g ng te ply T te go cre e s/ tion es ta io io nc c IC M W r co ng/ shin ic ta c tio rvic ic ic t/R an To ep th tora i p of ppo uct at r su tion rry G an /Fo chn i vi fe a s om ctu od ion serv oc erv rv su M en sur e uc r er i a Se r e S nt nan eal ut ufa u e s ls g n/ ou inm l/In e Q /T in rt lth er n as ia ot R st Co an o od al io a /W re i at ta M c O i /S i r ly d n ist s pp n io ld e/ es sp l/A e/ Ag min Fi at ho ea ur a tiv i t ta t er se H Pr l ad i ra Tr er u e m ric /R ist at am ic m ,e le in H bl co ts sa te m Pu Ac Ar ,s Ad le ho as ,g W ty ci tri ec El 2010 2020 Share of all vacancies (%), 2020 Source: World Bank staff authors, data from Türkiye National Employment Agency (İŞKUR). 78 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 56.  Mapping of sectoral job vacancies, unfilled rate and female placement (panels A–C), 2020 100% (A) Share of all Formal Job Vacancies (İŞKUR) versus Rate Unfilled Household goods/Sercices Rate of unfilled job vacancies (%) Real estate Professional/Technical Other services 50% ICT Electricity, gas, steam, air Financial/Insurance conditioning supply Water supply/waste Manufacturing MGMT Wholesale/Retail/ Arts/Entertainment Automotive repair Transportation/storage Construction Mining/Quarryng Accommodation/ Food services Education Administrative/ Support services Health/Social services Agriculture/ Forestry/Fishing 0% 0% 25% 50% Share of all vacancies (%) 100% (B) Share of All Formal Job Vacancies (İŞKUR) versus Female Placement Rate Health/Social services Female placement rate (%) Education Financial/Insurance 50% Agriculrure/Forestry/Fishing ICT Wholesale/Retail/Automotive ... Arts/Entertainment Professional/Technical Accommodation/Food services Real estate Manufacturing Administrative/ Other services Support services Household goods/Services Transportation/Storage Water supply/Waste MGMT Mining/Quarrying Construction Electricity, gas, steam, air conditioning supply 0% 0% 25% 50% Share of all vacancies (%) Source: World Bank staff authors calculations, İŞKUR data. Labor Capital: Activating Markets 79 100% (C) Rate of Unfilled Vacancies versus Female Placement Rate Health/Social services Female placement rate (%) Education Agriculture/Forestry/Fishing Financial/Insurance 50% Wholesale/Retail/Automotive repair Arts/Entertainment ICT Professional/Technical Accommodation/ Food services Manufacturing Real estate Administrative/ Other services Transportation/Storage Household goods/Services Support services Water supply/Waste MGMT Construction Electricity, gas, steam, air conditioning supply Mining/Quarrying 0% 0% 50% 100% Share of unfilled vacancies (%) Source: World Bank staff authors calculations, İŞKUR data. Key Implications Taken together, Türkiye’s labor market programs provide a prime platform that can be adjusted and expanded further into a jobs system, connecting private sector targeted financing, active labor market programs and e-profiling systems to include vulnerable informal and youth NEET women and men. Specifically: 1. Adjusting Türkiye’s active labor market programs to a greater emphasis on combining capacity development with demand-side incentives for the same jobseeker may help boost effectiveness. Globally, effects tend to be highest for the most vulnerable workers who benefit from direct job creation or entrepreneurship support in tandem with capacity-building, job placement and counseling services as discussed earlier in the note. 2. Relatedly, active labor market programs that step up mentorship and counseling for women for boosting self-confidence and self-efficacy are considered particularly effective. Adjustments to traditional vocational training and innovative approaches such as assessments to target training needs for women, bolstering socio-emotional skills, certification of training, providing a variety of logistics to access training (transportation, digitization, local provision), allowing women to bring a friend to the training, and providing childcare services have been found to be effective135. 135 Halim, O’Sullivan, Sahay/World Bank (2023). Increasing female labor force participation. World Bank Gender Thematic Policy Note. Washington DC: World Bank. 80 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity 3. World Bank 2019119 highlights the role of labor regulation for improving the quality of new, temporary work arrangements in reducing vulnerability, balancing security with flexibility and mobility. Inadequate, commensurate support to non- traditional forms of work can further impinge productivity and increase job turnover, especially trapping female workers in low skilled jobs. Ensuring equal treatment for all workers regardless of contract type, expanding affordable social security coverage for temporary work arrangements, and providing public care services including maternity and paternity leave are among key measures. Overall, key areas moving forward include: (i) expanding a national jobs system that includes targeted jobs financing and job matching services in partnership with the private sector through financing and regional outreach services; (ii) targeting reforms to more transparently identify and include excluded vulnerable informal workers and women in vocational, on-the-job training and wage subsidy programs, particularly in more productive and green sectors; (iii) developing integrated labor market case management services to register and provide routine job counseling to poorer households and vulnerable informal workers; and (iv) consolidating and harmonizing benefit levels across wage subsidy and unemployment benefit programs to ensure more equitable and efficient investments towards boosting job outcomes. Labor Capital: Activating Markets 81 82 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity 3 Financial Capital: Expanding Resilience and Assets “We take the decisions; we talk and discuss, and partners take a decision. We are independent in our work.” Women Social Entrepreneurs, EKIP Cooperative, Strengthening Economic Opportunities Project, World Bank staff mission, November 2022. To better adapt labor market policies for inclusion and gender equity discussed in the previous part, this part of the note focuses on financial capital in terms of firms’ and individuals’ capacity to stimulate and access job opportunities. This part first examines disparities in the demand for labor by firms and associated growth factors, including how the green transition is expected to impact jobs and skills demand. The rest of the analysis assesses entrepreneurship, access to finance and financial inclusion in terms of gender equity, highlighting that pending disparities will exacerbate inequities as economies transform further. Financial Capital: Expanding Resilience and Assets 83 Assessing Firms and Employment Resilience to Shocks Disparities in jobs across regions and sectors reflects differences in intra-regional and intra-sectoral growth, equally impacting gender equity in jobs. Work by Farole and et al (2018)136 highlights that in the EU, for example, intra-regional growth differences stem essentially from stagnating growth in advanced economies or low productivity within growing countries. The most effective approach would be to maximize regional potential rather than seek to achieve equally high outcomes, a bar that may be insurmountable due to factors beyond the control of policy like natural geographic endowments. Women who live in these regions in Türkiye face similar hurdles: how to work in vulnerable labor markets that are constrained by broader factors. This section applies this framing to a sectoral analysis of vulnerability. Certain sectors and firms may be particularly vulnerable during shocks due to labor market structure, productivity, financial and market constraints, particularly among women-led firms and in certain regions. Critical factors also include credit constraints, supply chain and consumer purchasing power disruptions that may disproportionately impact women-led firms and women’s jobs. Considering the recent earthquakes, this section begins by examining firms, sectors, and jobs most at risk of financial and labor losses during shocks such as the recent COVID pandemic and natural disasters. Though shocks differ in nature, extending recent work in Türkiye, this section provides an illustrative resilience analysis of sectors and jobs by constructing a vulnerability index to examine gender implications137. The index considers several aspects of employment vulnerability, including higher economic vulnerability in the sector, vulnerabilities due to deficiencies in worker protection and income generation capability of workers, as well as education and skills levels of workers. Illustrative analyses show that sectors that bear the highest employment vulnerability include firms operating in various manufacturing and trades sectors. This includes manufacture of textile and apparel, manufacture of leather, manufacture of furniture, accommodation and food, wood and paper products and agriculture (Figure 57 and Tables 5–6). By contrast, ICT, finance, education, and public administration sectors have low employment vulnerability results by nature of their characteristics as being relatively less dependent upon economic supply chains and physical requirements. These sectors are generally characterized by high-skilled workers, non-routine jobs and high protection and earnings. 136 Farole et al/World Bank (2018). Rethinking lagging regions: Using Cohesion Policy to deliver on the potential of Europe’s regions. Washington DC: World Bank. https://thedocs.worldbank.org/en/doc/739811525697535701​ -0080022018/original/RLRFULLonline20180501.pdf 137 The analysis builds on the Employment Vulnerability Index generated for Türkiye in an earlier work (Demir Seker, Nas Ozen and Acar Erdogan, 2020) and discusses employment vulnerability in Türkiye’s sectors with emphasis on the regional and gender differences in vulnerability. 84 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity The degree to which employment within a given sector is vulnerable generally does not differ by gender, but the scale of impact may differ depending on shares. Textile, leather, accommodation, and food are the most vulnerable sectors for both women and men. Small differences in the ordering of the most vulnerable sectors can be attributed to the employment shares of the two genders in the sectors. For example, employing about 23 percent of total women in employment, agriculture is found to be a more vulnerable sector for women than men. At the same time, the furniture sector appears as a relatively more vulnerable sector for men and less so for women, as the number of women in the sector seems negligible. Similarly, with a share of 95 percent male workers, construction is among the top five sectors with the highest vulnerability for men. There is sectoral vulnerability segregation by gender, over 30 percent more women working in vulnerable jobs than do men. Among employed women, nearly 37 percent work in the most vulnerable six sectors while the same rate is 28 percent for men. Shocks during COVID disproportionately impacted women. This is in line with findings from recent studies138 where data from household phone surveys in 40 countries showed that employment shocks during the COVID pandemic disproportionately hurt women’s employment, in addition to variations across age and education, with younger, less-skilled workers at a disadvantage. Figure 57.  Illustrative mapping of employment vulnerability by sectoral vulnerability, 2018–2021 0.80 Employment Vulnerability by Sectoral Vulnerability Indices Textile, apparel Wood & paper products Accom. & food Furniture Leather Agriculture Construction Food, beverage, tobacco Other non-metallic mineral Fabricated metal Basic metals Transport & storage Rubber and plastic motor vehicles Sectoral vulnerability index Wholesale & retail Transport veh. Arts, entertainment and recreation Machinery and equipt. Electrical and Other services computer Real estate Mining 0.40 Electricity, water & gas Coke and petroleum Health Printing recorded media Prof. admin & support Chemicals Pharmaceutical products Public admin Education ITC Finance 0.00 0.50 1.50 2.50 Employment vulnerability index Source: World Bank staff authors calculations based on Türkiye HLFS (2018–2021), Türkiye PIAAC, Employment Vulnerability and Sectoral Vulnerability Index analysis137 138 See Kugler et al 2021; Khatiwada et al 2021, Schotte et al 2021. Financial Capital: Expanding Resilience and Assets 85 Table 5.  Most vulnerable sectors, by gender Most vulnerable sectors for women Most vulnerable sectors for men 1. Textile, apparel 1. Textile, apparel 2. Accommodation and food 2. Leather 3. Wood & paper products 3. Furniture 4. Leather 4. Accommodation and food 5. Agriculture 5. Wood & paper products 6. Furniture 6. Construction Source: World Bank staff authors calculations based on Türkiye HLFS (2021) Table 6.  Vulnerability components across selected sectors, 2021 Worker profile (%) Share of jobs (%) Less Self- Earning than Routine Of Of Vulnerability empl. or Part- less than second. skills Of all women’s men’s index unpaid time Informal 80% mw ed. jobs jobs jobs jobs level Textile, apparel 11 10 21 63 69 81 5.6 8 5 Highest Leather 9 4 30 68 69 86 0.4 0.4 0.4 Highest Furniture 12 5 20 59 64 74 1.1 0.4 2 Highest Accom. & Food 15 6 25 69 56 8 4.9 5 5 High Wood & paper 8 4 12 57 54 62 0.8 0.3 1 High Agriculture 86 24 85 81 84 1 17.2 23 15 High Sub-total 30 37.1 28.4 highest Education 1 14 2 12 9 5 6.3 12 4 Low Public admin 0 1 0 8 18 17 6.9 4 8 Low Pharmaceuticals 1 1 3 30 12 36 0.2 0.1 0.2 Low Health 0.01 0.04 0.3 30 0.4 0.1 6 12 3 Low Ict 10 5 8 21 9 16 0.9 1 1 Lowest Finance 5 2 3 14 7 43 1 1 1 Lowest Sub-total 21.3 30.1 17.2 lowest Source: World Bank staff authors calculations based on Türkiye HLFS (2021). Health profile constant 2018–2021. 86 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Given especially low female entrepreneurship and employment in the earthquake zones, the risk that women-led firms and women’s labor force participation are hampered is high. For example, textile and apparel sector is the most vulnerable sector for both genders, with women accounting for 30 percent of employment compared to 45 percent nationally. Any further job losses following the earthquakes puts these modest hard-earned gains at risk of reversal. Employment vulnerability by sector in the earthquake regions is similar to national averages, with a higher share of vulnerable employment. A higher share of women and men in the earthquake zones work in vulnerable sectors than elsewhere. Textile and apparel, furniture, and the accommodation and food sectors are the most vulnerable sectors, while education, ICT and finance are the least vulnerable sectors in the earthquake regions. 42 percent of total employment is in the six most vulnerable sectors (accommodation and food, agriculture, construction, furniture, textile and apparel, and wood and paper products) according to the 2021 Household Labor Force Survey. It is yet too early to determine the full labor market impacts of the earthquake at the time of writing, however, preliminary field assessments as mentioned earlier already show significant losses and/or displacement among firms and workers. Women and women-led firms remain especially at risk of further labor force exits and/or barriers to entry during recovery. Adapting Firms and Jobs to the Green Transition Similarly, the challenge of jobs (re)creation in the earthquake zone provides an opportunity to green pre-existing and new firms, given some areas in the earthquake zone were at risk of green job shifts. In a similar vein, this section captures the extent to which firms and their associated jobs are considered “green” in terms of occupational skills used and greenhouse gas emissions. Using a global methodology, a “Green Skills Index” is constructed based on applying a global database of occupational skills to the Turkish context by sub-sector, adjusted for educational levels139. Though there are overlaps across categorization of green firms and jobs, up to estimated 18 percent of today’s labor force in Türkiye may be vulnerable to job shifts, particularly women and low-skilled workers. The share of green versus brown jobs has remained relatively stable over the past decade, but wide regional variations are evident (Figure 58). Both brown jobs and jobs requiring upskilling are geographically concentrated. There is a higher concentration of these jobs in western provinces, which reflects the relative importance of jobs in energy, transport and high-GHGs emission manufacturing sectors in these areas. 139 Makovec M and Garotte D/World Bank staff authors calculations based on Vona et al (2018) and TUIK LFS 2019. Prepared for and see World Bank Türkiye Country Climate and Development Report, 2022, for details. Financial Capital: Expanding Resilience and Assets 87 The demand by firms for green skills is growing, shaping entrepreneurship expectations. The share of sub-sectors, jobs requiring green upskilling has been increasing with the shift towards services and, to a lesser extent, manufacturing. The lag in the share of occupations with skills needed for the green transition, and therefore the need for upskilling, has therefore increased. This has likely been due to a lag in green skills in growing green sectors, exacerbated by a lag general in learning outcomes discussed earlier. This has been compounded by the shift to capital-intensive technologies and labor force participation stagnation, despite modest increases, due to economic shocks since 2016. In terms of gender differences, women have lower green skills levels as measured by the Green Skills index than men on average due to the sectors and firms in which they predominantly work. This is driven both by lower labor force participation and lower rates of employment in green jobs to begin with. As a corollary, the incidence of both brown jobs and jobs requiring upskilling on total employment is higher among men than women (6 versus 3 percent and 16 versus. 6 percent, respectively, Figure 59), which follows higher rates of employment. In terms of age, 48 percent of “brown jobs” employ workers below 34 years old, and 42 percent between 35 and 50. In addition to supply-side implications, this also means that demand-side expectations of new entrants to the labor force will increasingly focus on relatively rare skills. This has potential implications for the equilibrium between capital and labor over the short-run, and potential deleterious effects over the long-run in the absence of both demand- and supply-side stimulation measures. Figure 58.  Share of jobs that will require upskilling due to greening by province, 2019 (NUTS–2) Source: Makovec M and Garotte D/World Bank staff authors calculations based on Vona et al (2018) and TUIK LFS 2019. Prepared for World Bank Türkiye Country Climate and Development Report, 2022. 88 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 59.  Gender and age distribution by green job categories, 2019 18% 0.37 16% 0.36 14% 0.35 12% Green skills index (0–1) 0.34 Share of jobs (%) 10% 8% 0.33 6% 0.32 4% 0.31 2% 0% 0.30 Male Female Brown jobs Green jobs Need upskilling Green skills 25% 0.38 0.37 20% 0.36 15% 0.35 Green skills index (0–1) Share of jobs (%) 0.34 10% 0.33 0.32 5% 0.31 0% 0.30 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 Age group Brown jobs Green jobs Need upskilling Green skills Source: Makovec M and Garotte D/World Bank staff authors calculations based on Vona et al (2018) an TUIK LFS 2019. Prepared for World Bank Türkiye Country Climate and Development Report, 2022. Financial Capital: Expanding Resilience and Assets 89 The increasing demand by firms for green skills will require measures in advance to smooth the transition for vulnerable women and balance (green) capital versus labor, notably in manufacturing and agriculture (Figures 60 and 61). The manufacturing sector is characterized by a particularly high number of sub-sectors and occupations with high share of brown, low and semi-skilled jobs. Workers with basic and secondary education, notably women, form the bulk of the labor force in current brown jobs who will likely need to be targeted for retraining. 62 percent of workers in brown jobs and 55 percent of workers in jobs that need upskilling have attained basic or secondary education. These trends are important to keep in mind as more women with lower educational background have been entering the labor market over time. Figure 60.  Wide variance in sub-sectoral jobs (NACE 2-digit classification of types of jobs affected by greening and use of green skills, 2019) 0.50 50% 45% 0.45 40% 0.40 35% Green skills index (0–1) 0.35 Share of jobs (%) 30% 25% 0.30 20% 0.25 15% 0.20 10% 0.15 5% 0% 0.10 A B C DE G H I J K LM N OPQ R S TU Sectors (NACE 2-digit) Need upskilling Source: Makovec M and Garotte D/World Bank staff authors calculations based on Vona et al (2018) and TUIK LFS 2019. Prepared for World Bank Türkiye Country Climate and Development Report, 2022. 90 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 61.  Green jobs by educational level and share of green jobs by education level, 2019 (%) 100% 90% educational level (%) 80% Share of jobs by 70% 60% 50% 40% 30% 20% 10% 0% Total jobs Brown jobs Green jobs Jobs need upskilling Low education Mid education High education 0.38 Green skills index (0–1) 16% 0.37 14% Share of jobs (%) 0.36 12% 0.35 10% 8% 0.34 6% 0.33 4% 0.32 2% 0.31 0% 0.30 Low Middle High Education Level Brown jobs Green jobs Need upskilling Green skills Source: Makovec M and Garotte D/World Bank staff authors calculations based on Vona et al (2018) an TUIK LFS 2019. Prepared for World Bank Türkiye Country Climate and Development Report, 2022. Leveling Financial Services Inclusion and Entrepreneurship Relatively strong legislation on labor and financial markets has helped boost women’s access to financial services, notwithstanding high gaps. Against this backdrop, the need to ensure financial capital across cycles is ever-more critical to firm recovery and women’s participation. Expanding Türkiye’s new growth into frontier sectors such as green and digital industries will depend on casting a viable financial net as widely as possible. In the realm of labor and financial policies, the World Bank’s Women, Business and the Law, 2021 Edition, shows that Türkiye’s gender legislation is relatively comprehensive, with selected areas that show gaps. Its index hovers at the average for Europe and Central Asia, at 82.5 out of 100, versus the regional average of 84.2, having improved by doubling over the last two decades (Table 7). Despite generally favorable legislation, in some cases measures are lacking regarding provisions related to marriage, pensions, occupational barriers to entry (notably jobs in mining and occupations deemed hazardous), equal pay, part-time work and parental leave56 (Table 8). In other cases, implementation of existing laws related to flexible work and access to finance lag due to broader blind spots. Financial Capital: Expanding Resilience and Assets 91 Table 7.  Selected grouped indicators, World Bank Women Business and the Law, Türkiye, 2000 versus 2023 Year Wbl total index Mobility Workplace Pay Marriage Parenthood Entrepreneurship Assets Pension 2000 48.8 75 25 25 40 20 75 80 50 2023 82.5 100 100 75 80 80 75 100 50 Source: World Bank staff authors adaptation based on World Bank Women Business and the Law, Türkiye 2023 indicators. Table 8.  Selected detailed indicators, World Bank Women Business and the Law, Türkiye, 2023 Selected topics and Pending indicators Is the age at which Are periods of Is the age at which Is the mandatory men and women can absence due to Pension men and women can retirement age for retire with partial childcare accounted score retire with full pension men and women the pension benefits the for in pension benefits the same? same? same? benefits? 50 No Yes Yes No Does the law prohibit Can a woman sign a Can a woman register Can a woman open a Entrepreneurship discrimination in contract in the same a business in the bank account in the score access to credit based way as a man? same way as a man? same way as a man? on gender? 75 No Yes Yes Yes Is dismissal of Parenthood Length of paid Length of paid Is there paid parental pregnant workers score maternity leave paternity leave leave? prohibited? 80 112 7 No Yes Does the law mandate Can a woman work Can a woman work at Can a woman work in Pay equal remuneration in a job deemed night in the same way an industrial job in the score for work of equal dangerous in the as a man? same way as a man? value? same way as a man? 75 Yes Yes Yes No Are there criminal Does the law prohibit Can a woman get a Is there legislation on penalties or civil Workplace discrimination in job in the same way sexual harassment in remedies for sexual score employment based on as a man? employment? harassment in gender? employment? 100 Yes Yes Yes Yes Source: World Bank staff authors adaptation based on Women, Business and the Law, Türkiye 2023 indicators. 92 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Empowering women through financial inclusion and education has been found to improve productive opportunities and resilience, particularly through digital payment accounts to facilitate (e-commerce and savings140 141. These principles equally apply to firms facing recovery challenges following shocks or preparing to remain viable for the green transition. Overall financial literacy rates (measuring concepts and excluding coverage of financial services) does not differ significantly between men and women in Türkiye. The average is 24 percent in Türkiye based on areas assessed in the S&P Global Financial Literacy Survey, compared to 40–65 percent among upper middle- and high-income averages. The OECD score142 for Türkiye is 12.5 (on a scale of 1–21), putting it in the bottom third out of 31 countries and somewhat lower than the OECD average of 13.7. Financial literacy is low for both at 7 percent in Türkiye based on areas assessed in the Turkish Central Bank’s Methods for Payment Survey143, among the lowest three out of 15 mainly high-income countries (and two middle-income) assessed in previous surveys over 2007–2014. These trends show that like closing the gender gap in human capital accumulation, capacity potential in terms of cognitive skills do not necessarily trail men’s regarding financial concepts. The same was seen as discussed earlier regarding digital gender skills gaps in terms of capacity potential, where levels are overall low in Türkiye but do not differ significantly by gender. There remains a large gender gap in financial inclusion in terms of bank accounts in Türkiye, with lower financial inclusion correlated with lower wage employment globally (Figures 62–64). While the account ownership among women have been increasing over time, the gap between genders remained the same, in a range between 20 and 30 percentage points, driven largely by low-skilled, informal workers. Coverage modestly increased by 2021 as shown earlier, but as of 2017, 83 percent of men while 54 percent of women had bank accounts, a 30-percentage point gender gap with has narrowed somewhat, still higher than the low- and middle-income average gap of 9 percentage points144. The correlation with wage employment may reflect a bi-directional relationship for further exploration outside the scope of this work. In addition to lagging inclusion in banking services, gaps in accessing credit are evident. Women-run businesses may lack the asset base to access credit; 58 percent of loans require collateral when the business is managed by a woman, versus 37 percent when the business is run by a man145. The Inclusive Access to Finance Project shows that 42 percent of beneficiary firms are women-led as of 2020146, compared to a national estimate of 4 percent, to be expanded further under a newly- launched Formal Employment Creation Project. 140 Asli et al, 2017 https://documents1.worldbank.org/curated/en/403611493134249446/pdf/WPS8040.pdf 141 Duvendack and Mader, 2019 https://opendocs.ids.ac.uk/opendocs/bitstream/handle/20.500.12413/14269/ Impact%20of%20financial%20inclusion%20in%20low-%20and%20middle-income.pdf?sequence=1&isAllowed=y 142 OECD INFE Survey on Adult Financial Literacy, 2016 https://www.oecd.org/finance/OECD-INFE-International​ -Survey-of-Adult-Financial-Literacy-Competencies.pdf 143 Belici and Cevik (2022). Financial literacy and cash holdings in Turkey. Working Paper 20/02. Central Bank of the Republic of Turkey. https://www.tcmb.gov.tr/wps/wcm/connect/a44693ab-6a07-4818-81aa​ -ed168a3044dc/2202wp.pdf? MOD=AJPERES&CACHEID=ROOTWORKSPACE-a44693ab-6a07-4818-81aa​-ed168a3044dc-o1QhLXi 144 World Bank FinDex Survey, 2021 and 2017. 145 World Development Indicators, World Bank Enterprise Survey 2019. 146 World Bank Türkiye Inclusive Access to Finance Project, Implementation and Status Report, September 2020. Financial Capital: Expanding Resilience and Assets 93 Figure 62.  Financial inclusion indicators 150.0 100.0 50.0 0.0 Turkeys OECD AVG Indonesia Argentina Tunisia South Africa Account ownership at a financial institution or with a mobile-money-service provider (% of population ages 15+) Account ownership at a financial institution or with a mobile-money-service provider, female (% of population ages 15+) Account ownership at a financial institution or with a mobile-money-service provider, male (% of population ages 15+) Account ownership at a financial institution or with a mobile-money-service provider, poorest 40% (% of population ages 15+) Source: World Bank FINDEX data, 2017. Data for 2021 show modest increases while similar global benchmarking trends. Women-led enterprises face additional vulnerabilities in terms of green financing.147 Currently, available financing for green investments is not sufficient and too short-term in general. Given Türkiye’s weakly diversified financial sector, domestic debt financing alone will not be sufficient for firms’ decarbonization given its short-term nature and coverage.148 Access to long-term finance via diversified sources is challenging for SMEs and, within that group, women-led or managed firms. This is mainly driven by financial institutions’ perceptions of women-led firms as being higher risk.149 Reflecting this, firms managed by women are less likely to have a loan or line of credit than those managed by men (25 versus 35 percent), face stricter collateral requirements, and are more likely to have their loan application rejected, based on 2019 Enterprise Survey data. Women-managed firms are also significantly more likely to report access to finance as their biggest obstacle (41.6 compared to 28.4 percent). 147 Berg G and Ozen E. in World Bank (2023). Türkiye Green Finance Project. Project Appraisal Document Report No. PAD5380. World Bank: Washington DC. 148 80 percent of domestic debt securities issued by non-financial corporations are short term by remaining maturity, while this number is 85 percent for financial institutions. 149 World Bank Türkiye 2019 Enterprise Survey 94 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity In line with experience from high-income countries, some of these constraints to financial inclusion and access among women (and men) can be addressed by scaling-up demand- and supply-side interventions. These range from training, public programs to finance account-opening and outreach, incentives and behavioral nudges for the use of financial services, digital and mobile money payment systems (including government-to-citizen and vice-versa systems used by e-Government in Türkiye, discussed later), savings, retirement planning and long-term wealth accumulation150. Certain programs have been found to be more effective than others particularly on more significant financial decision-making related to retirement savings, investments and business151. Micro-enterprise support programs include financial counseling, mentorship, regular meetings. Country-tailored approaches have been found to be most effective to reaching women, accounting for differences in needs, learning contexts, take-up opportunities and local factors. Approaches will need fine-tuning different contexts within Türkiye, given regional and social variations discussed earlier. Figure 63.  Association between financial accounts ownership and wage employment among women, global, 2005–2022 100 ARE QAT SAUSAU KWT ARE KWT SAU JOR JOR JOR BHR BLR BHR BLR BHR ARE KWT BLR R = 0.5398 Share of employment in wage and salaried work, women (%) OMN RUS USA HKG USA HKG USAHKGNOR EST DNK RUS RUS MLTMLTEST SWE EST HUN ISR IRL LUX LUX FRA IRL DEU 90 IRQ BGR BGRPRI HUN HUN BGR LTU SVK LTU LTU SVKHRV SVK ISR FRA LVA CYPLVA IRL ISRFRA LVA SGP MLT SGP GBR JPN BEL AUT AUT DEU LUX FIN JPN FIN AUT SGP GBR MNE ZAF CYP ESP JPN GBR BEL NLD CAN SVN CAN NZL UKR ZAF CZE CZE CZE HRVCYP PRT ESP CHE NZL AUS NLD CHE NLD SVN LBNTUN LBN UKR ZAF MNE MUS PRT MNETTO TTO MUS MUS POL ITA SVNNZL SYR TUN CRI ITA POL PRT ARG ITA 80 UKR ARG CRI CRIMYS POL MKD HRV BIH ARG KAZ MKD KOR MDADZAPAN URY ROU BIH CHLURY BRA MKD MYS KOR PSE URY DZA CHL DZA BIH BWA SRB BRA SRB CHL MYS KOR IRQ MDA BWABRA KAZ SRB 70 KGZ PAN MDA BLZ DOM GRC BWA MEX DOM GRC GRC DOMMEX PAN ROU JAM JAM KGZ ROU KAZ PSE MEX VEN TJK VEN MDV IRQ PSE EGY GAB TKM UZB TUR LBY GAB 60 TJK GABKGZ PHL ARM TUR UZB NAM VEN NAM TJK UZB IRN IRN ARM SLV PHL PRY LKA LKA TKM EGY DJI GTM PHL IRN LKA MNGMNG SLV EGY ARM PRYSLV NIC TURGTM CHN CHN 50 NIC NIC COL COL GTM ECU CHN GEO THA HND COL ECU THA MNG KHM HND ALB GEO LSO ALBGEO HNDECU IDN THA KEN 40 MAR KHM PER IDN PER PER MMR VNM LSO IDN KEN MMR ALB YEM SDN MWIMWI BOL MWI 30 YEM SDN MRT VNM BGD BOL KEN AZE VNM AZE SEN BOL PAK KHM PAK SEN COM MRT AZE BGD ZWE ZWE ZWE MRT 20 PAKSEN RWA RWA IND BGD RWAHTI IND GHA HTI HTI GMB LAO CIV AGO GHA CMR AGO NGA BTN IND GHA CMR CIV NGA UGA ZMB UGA BDI CMR UGA BDI NGA LAOETH ZMB MLI NPL 10 COG BFA MLI MLI COD COG LBRMDG COG TGO ETH NPL ZMB COD LBR NPL BFA TZA TGO TZA NER CODMDGAFGMDGBFA TZA TGO AFG CAF BENSLE BEN BEN MOZ AFGSSD CAF SLE SLE SOM GIN GIN NER TCD NER TCD GIN TCD 0 0 10 20 30 40 50 60 70 80 90 100 Financial account ownership, women (%) Source: World Bank staff authors calculations using World Development Indicators and FinDex. 150 World Bank (2021). Building a Financial Education Approach. Financial Inclusion Support Framework. Washington DC: World Bank. https://openknowledge.worldbank.org/server/api/core/bitstreams/ba4aa1f7-c7b8-5177​ -a1c3-75f7e6df15a1/content 151 See multiple global meta-analysis reviews on financial literacy interventions discussed at: McKenzie D/World Bank (2022). Do financial literacy interventions actually work better than I think they do? (and thoughts about meta-analyses) Washington DC: World Bank https://blogs.worldbank.org/impactevaluations/do-financial-literacy​ -interventions-actually-work-better-i-think-they-do-and Financial Capital: Expanding Resilience and Assets 95 Figure 64.  Relationship between financial accounts and labor force participation among women, Türkiye and global (2005–2022) 100 R = 0.0094 90 EST 80 Labor force participation rate, women (%) MKD LUX MMR BFA NIC UGA 70 SLV CRI PRT FRA MLT TJK KAZ NAM TUR GAB ECU SAU SVK CZE ESP LVA ITA GBR AFG MMR ARE EST SLV ETH UGA CHL TZA NPL MDA KWT IRN MLT HKG SWE NZL 60 ALB MDA PER ZMBRWA KGZ PAN ROU NPL RUS IDN SAU BHR JAM IND CYP THA SGPJPN LUX AUS SWE SVN NER IRQBEN KHMURY ALB TJK SRB MUS NLD AUT SDN CIV MARGTM ZWE BEN ARG BIH DOM KEN POL KWT ESP BEL MDG CMR PSE LSO NGA NGA COD PER COL UZB TUR MWI RWA MYS LKA MNE LTU CZE LTU HRV CHNCYP SVK MNG BEL MLTSWE CAF COM MOZ VEN TKM TUR BRA JAM BIH MDV HRV NZL CHE DNK TZA GABECU LAO URY VEN HRV ZAF SGPJPN AUT 50 TGO LBR JOR SLEGHAHND DOM ZMB BLZ NAM BGR MKD CYP USA IRL IRL USACAN SAU NER AZE TCDMDA RWA PHL HND PAN CHN MKD HUNTHA KEN GBR GBR ISL NZL BEL PAK IRQ SLV CMR GEOROU GEO SVK LTU IRN JPNDNK MDG TCD PAN CMR MEX CIV TGOPHL URY SVK AUS PSE ARM MWI GIN DZA VNM UZBALB LVA KOR FRA MLIEGY ARM RUS NOR DNK HTI COG LVA FRA CAN 40 DJI BFA DZA GEO MNE DOM TUR UKR MYS FIN DEU SEN CHE TJK BOL LBR ETH COG SOM JOR SEN NAM 30 BRA MUS BEL KHM ROU ITA MLI LBY TTO KAZ EST LVA BIH JPN HND XKX ECU CHN SVN 20 BTN AGO HKG IND QAT PRIPOL ISR BDI GIN HUN GRC AZE BFA KGZ GHA MYS 10 BWA 0 0 10 20 30 40 50 60 70 80 90 100 Financial account ownership, women (%) Source: World Bank staff authors calculations using World Development Indicators and FinDex. Real and perceived constraints to women’s access to SME finance have been easing gradually over time, but more is needed to accelerate women-led enterprises for resilience. In addition to financial inclusion gaps, female-led firms and women managers remain limited (Figures 65–68). Female employers represented only 1.25 percent of all employers in Türkiye as of 2019 just prior to COVID, reaching 2 percent by 2021. Wide regional variation exists, from a high of nearly 4 percent in Izmir and Istanbul to less than 0.5 percent in eastern-most provinces. While the national average of firms with female participation in ownership was 11.3 percent in 2019 and the national average of firms with a female top manager was 3.9 percent in the same year,152 the share of women-owned or led MSMEs in the earthquake-affected provinces is expected to be lower. Selected ongoing programs shed hope with ever-higher shares of women-led firms and women hired. Forthcoming insights from the Ministry of Industry and Technology’s Small and Medium Enterprises Development Organization (Küçük ve Orta Ölçekli İşletmeleri Geliştirme ve Destekleme İdaresi Başkanlığı/KOSGEB) show that a significant share of beneficiaries from emergency programs have been women153. The recent World Bank-financed SME 152 World Bank Enterprise Survey, Türkiye (2019) 153 Abukumail A and Slavova S, World Bank. (2020). Turkey Emergency Firm Support Project. Project Appraisal Document Report No. PAD3960. Washington DC: World Bank. https://documents.worldbank.org/en/publication/ documents-reports/documentdetail/123821598925756490/turkey-emergency-firm-support-project 96 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity COVID recovery operation shows that women account for 60.9 percent of new workers hired by beneficiary firms and 15.4 percent of firm ownership. Future work will highlight sectoral, geographic and demographic distribution. While the program had emphasized sectors that have higher shares of women initially, the project is a good case study for improving female participation when public incentives are well aligned. In addition, an upcoming 2023 Enterprise Survey follow-up among 700 firms across Türkiye focuses on climate and will evaluate correlations related to female leadership and green agenda progress. Figure 65.  Share of employers by gender, 2011–2022 (%) 8.0 7.0 6.8 5.8 Share employed (%) 6.0 5.2 5.0 4.5 4.0 3.0 2.0 1.7 1.2 1.0 0.0 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Total Men Women Source: TurkStat, Household Labor Force Survey (HLFS), 2011–2022154 Figure 66.  Proportion of individuals in senior or middle management positions by gender (%) 100% 85.6 79.3 Share of all managers (%) 80% 60% 40% 20.7 20% 14.4 0% 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Men Women Source: TurkStat, Household Labor Force Survey (HLFS), 2012–2021, and Women in Statistics 154 Note: As of 2021, the series may not be directly comparable to previous years due to the adjustments in the definition, scope and design of the survey. Financial Capital: Expanding Resilience and Assets 97 A previous World Bank (2015) assessment found that women’s limited access to financial and other resources, and weak networks are found as important barriers to women’s entrepreneurship. According to the 2021 Turkish Household Labor Survey, the share of women employers in total employment is 2 percent (6 percent among men). Women employers are well represented in the service sector (84 percent), while the share in manufacturing is 12 percent. In terms of firm size, 89 percent of females employers operate as largely informal, subsistence micro firms with 1–9 employees. Like women-led firms, jobs for women in various services sub-sectors that account for a high share of employment but are not equally productive have increased rapidly over the past decade. Mining, accounting for a small share of employment, has nonetheless seen growth in women’s employment as well. These trends show that the quality of women-led firms and job growth is as if not more important than the quantity of firms and jobs created. Figure 67.  Women employers as share of women’s employment by regional zone (NUTS–2), 2021 (%) TR31 (İzmir) 3.73 TR10 (İstanbul) 2.95 TR81 (Zonguldak, Karanbük) 2.64 TR22 (Balikersir, Çanakkale) 2.59 TR51 (Ankara) 2.17 TR41 (Bursa, Eskişehir, Bilecik) 2.15 TR61 (Antalya, Isparta) 2.07 TR21 (Tekirdağ, Edirne) 2.00 TR62 (Adana, Mersin) 1.99 Total 1.93 TR32 (Aydin, Denizli, Muğla) 1.81 TR72 (Kayseri, Sivas, Yozgat) 1.78 TR71 (Kirikkale, Aksaray) 1.72 TR42 (Kocaeli, Sakarya) 1.54 TRB1 (Malatya, Elaziğ) 1.18 TRC1 (Gaziantep, Adiyaman) 1.18 TR83 (Samsun, Tokat, Çorum) 1.04 TR52 (Konya, Karaman) 1.01 TR33 (Manisa, Afyon) 0.94 TR63 (Haytay) 0.87 TR90 (Trabzon, Ordu) 0.86 TR82 (Kastamonu, Çankiri) 0.80 TRA1 (Erzurum, Erzincan) 0.67 TRB2 (Van, Muş, Bitlis, Hakkari) 0.48 TRA2 (Ağri, Kars, Iğdir) 0.19 TRC2 (Şanliurfa, Diyarbakir) 0.19 TRC3(Mardin, Batman) 0.06 Source: World Bank staff authors calculations based on HLFS, 2021. Noe: Senior officials and managers Total average not shown: 20.7%. 98 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 68.  Women senior officials, managers and professionals as share of total by regional zone (NUTS2), 2021 (%) TRS1 (Ankara) 35% TR10 (İstanbul) 31% TR31 (İzmir) 26% TR41 (Busa, Eskişehir, Bilecik) 23% TRC1 (Gaziantep, Adiyaman) 21% TR72 (Kayseri, Sivas, Yazgat) 21% TRC3 (Mardin, Batman) 21% TRA1 (Erzurum, Erzincan) 20% TR63 (Hatay) 20% TRB1 (Malatya, Elaziğ) 20% TR61 (Antalya, Isparta) 20% TR62 (Adana, Mersin) 20% TRC2 (Şanliurfa, Diyarbakir) 20% TR42 (Kocaeli, Sakarya) 19% TR71 (Kirikkale, Aksaray) 18% TR32 (Aydin, Denizli, Muğla) 18% TR21 (Tekirdağ, Edirne) 18% TR81 (Zonguldak, Karabük) 17% TRS2 (Konya, Karaman) 16% TR22 (Balakesir,Canakkale) 15% TR90 (Trabzon, Ordu) 15% TRA2 (Ağri, Kars, Iğdir) 13% TR33 (Manisa, Afyon) 13% TR83 (Samsun, Tokat) 12% TRB2 (Van, Muş Bitlis) 11% TR82 (Kastamonu, Çankiri) 10% Source: World Bank staff authors calculations based on HLFS, 2021. Note: Senior officials and managers Total average not shown: 20.7%. Trends in Türkiye reflect a significant global gender gap in SME growth as well as access to finance (Alibhai S et al, 2019)155. Equal opportunities in access to finance can facilitate women’s employment both as heads of firms and employers of other women and men (IMF, 2019). Cross-country evidence shows that having limited access to finance, gender bias in banking credit sector, inadequate skills and networks, limited prevalence of technology usage among women have also resulted in a low number of female entrepreneurs and women-led businesses (Ubfal, 2023). Globally, policy has increasingly focused on increasing the share of growth-oriented enterprises rather than increasing the number of startups per se that may not be as productive (Ubfal, 2023). This means traditional self-employment in Türkiye will increasingly need to be strengthened. 155 https://openknowledge.worldbank.org/entities/publication/a0d7bc31-df7e-566a-995f-5589fb29398e Financial Capital: Expanding Resilience and Assets 99 Internationally, a holistic approach has been most effective in promoting productive women-led firms and access to finance. These include training programs that emphasize socio-emotional cognitive entrepreneurship skills (rather than conventional entrepreneurship technical training alone) have been key to shifting potential women entrepreneurs towards higher productivity sectors. Other measures include gender-oriented training, access to secure and convenient savings instruments, promoting and raising awareness among women to shift to male-led sectors, technology uptake and market expansion, mentorship, and consulting services among women, and increasing access to finance opportunities (such as reducing gender bias in banking sector and promoting blended finance) as effective policy interventions (Ubfal, 2023). Targets, outreach, and capacity-building have helped support increasing coverage in recent years in Türkiye, including initiatives by the private sector. Notably, KOSGEB has had successive programs aimed at increasing targets for women as mentioned. The Turkish Union of Chambers of Commerce and Commodity Exchanges (TOBB) publishes a regional Gender Equality Scorecard across 81 provinces156. With a mandate to promote R&D-led private sector growth, the Scientific and Technological Research Council (TÜBİTAK)157 also has in place a 2022–2025 Gender Equality Plan (GEP)158 to foster women-led firms through outreach and services. Importantly, the share of female-owned or led projects funded by TÜBİTAK averaged 17.8 percent over 2019–2023, higher than the national average of 11.3. Key Implications In Türkiye, demand- and supply-side measures can help alleviate barriers to financial inclusion, capital and women-led enterprises. Supply-side measures range from awareness-raising to scaling-up multi-dimensional capacity and practical training. Specifically: 1. Formal and informal outreach and incentives on financial literacy and banking, including digital services, targeting vulnerable groups at scale can be expanded. Educational policy can consider reinforcing financial literacy, entrepreneurship and management teaching early at the formal secondary, vocational, and tertiary education levels, as well as non-formal systems at the local or community level. 2. Given the preponderance of traditional self-employment, awareness, and sensitization especially among women with entrepreneurial goals are important; promotion of female entrepreneurs’ success stories and success rate of women-owned SME loans have been seen as useful. 156 https://tobb.org.tr/Sayfalar/Eng/Detay.php?rid=10304&lst=Haberler 157 Slavova S and Abukumail A. in World Bank (2023). Türkiye Green Industry Project. Project Appraisal Document Report No. PAD5349, May 2023. World Bank: Washington DC. 158 https://www.tubitak.gov.tr/en/news/policy-principles-for-increasing-the-participation-of-women-researchers-in​ -tubitak-processes-are and full document https://tubitak.gov.tr/sites/default/files/18842/gep_actionplan.pdf 100 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity 3. Business training programs offering skills and economic opportunities for women and that are combined with financial support such as cash grants to start a business can be effective. On the demand-side: 1. Reforms would include regulations to rationally reduce collateral requirements, simplify legislation and procedures for SME loans, and sanction against the use of women’s loans by male family members (Cebeci and Essmat, 2015). 2. To reduce gender bias in SME lending, technical trainings among loan officers on how to accurately assess loan worthiness may induce better female entrepreneurship outcomes. 3. Financial incentives in terms of tax or preferential credit terms for a certain time frame, conditional on performance and potentially social benefits such as broader public externalities, can further boost access to productive entrepreneurship among vulnerable women and men. Financial Capital: Expanding Resilience and Assets 101 102 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity 4 Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion “Leaving the house for work, even the feeling of missing my home and my children during work, is exciting for me.” Women social entrepreneurs, HALKA Cooperative, Strengthening Economic Opportunities Project, World Bank staff mission, November 2022. Taking a holistic perspective of labor, financial and social factors related to inclusive human capital utilization, this part provides the overall framework and context in Türkiye for the analysis. It describes the underlying theoretical and empirical basis for the framework, key indicators and global benchmarks, and the institutional landscape of governmental and non-governmental stakeholders related to key national policies and programs. Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 103 Evolving Household Time Use and Roles Building on labor and financial capital, Türkiye’s social capital among women and men has also played a role in human capital utilization. Upholding labor legislation protecting and balancing women and men’s workplace flexibilities, rights, and access to jobs as new entrants and parents will be key. Continuing to foster household awareness of options to optimize women and men’s household time use and responsibilities can help. Although outside the focus of this note, continuing to maximize Türkiye’s broad public and social outlets for improving awareness at the local level on safe public spaces and gender-based violence is key. Türkiye’s initiatives can serve as a global example, with calls by private sector leaders in Türkiye emphasizing the importance of ensuring the requisite investments and outreach to protect women from all forms of harassment159. Over the past decade, women and men’s time use has gradually changed, with women spending more time on employment. In line with modest increases in women’s labor force participation, household time use has evolved over a decade by gender in Türkiye (Figures 69–73). National time use surveys conducted by the Turkish Statistical Institute160 show some changes in self-reported patterns over a decade (2006 versus 2015). While men continue to report spending nearly three times as many hours as women per day on employment on average, a slight increase in the amount of time women devote is seen since 2006. By contrast, time spent by women on household care continues to dwarf that of men at nearly 5 times, but this has decreased since 2006. These patterns hold by educational level. At the same time, more highly educated women devote almost equal time to employment and household, while secondary educated women’s time is largely devoted to household. In addition, part-time employment is higher among women than men (45 percent versus 15 percent, respectively). Most part- time workers are also informally employed, at 74 percent among part-time women. Since the data used does not include information explaining these patterns directly, further work is needed to understand factors influencing these part-time work patterns, such as necessity, personal preferences, flexible work arrangements available, or other aspects. Household roles and labor force participation are closely tied to household structure, particularly among women and certain regions. While a relationship between age at first marriage and labor force participation is not seen among men, earlier average marriage age appears associated with lower labor force participation on average for a given province among women. Of note, a high share of women (and men) Türkiye are 159 As described by Women in Türkiye by Ministry of Family and Social Services and earlier sections on financial capital, several national chambers of commerce and private sector bodies have in place gender action and safety initiatives. For example, TUSAID has called for Türkiye to rejoin the Istanbul Convention after its exit in 2021, while acknowledging national laws in place (Law No. 6284) in the fight against gender-based violence. See https://tusiad.org/en/press-releases/item/10739-the-withdrawal-from-the-istanbul-convention-fosters-a-damaging​ -mindset-which-encourages-violence-against-women 160 TUIK Time Use Survey, which was carried out in 2006 at the first time, was reapplied in the 2014–2015 period. Analysis by TUIK shows the distribution of time allocation for individuals according to their age, gender, education level, income level, employment status. 104 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity married (60 percent of those aged 15 and over) and most women in general have children (including those who are divorced or widowed). The average age of first marriage is relatively young in Türkiye, hovering between 24 and 27 years. Younger first marriages are generally seen in the southeastern and middle Anatolian provinces, while older first marriages are seen in Istanbul, Izmir, and other western provinces. Similarly, on average, married women’s labor force participation rate is lower than single and never married women (42 percent versus 33 percent) as of 2021–22. This division of labor is not unique to Türkiye but more marked than the OECD average. Figure 69.  Full- and part-time work by gender, 2010 versus 2022 (thousands, % of wage employment) Number of wage employees (thousands) 35,000 30,000 90% Full time 25,000 Part time 20,000 89% 93% 15,000 93% 10,000 84% 5,000 77% 0 2010 2022 2010 2022 2010 2022 Total Men Women Source: World Bank staff authors calculations based on TurkStat indicators database. Figure 70.  Time use on household care versus employment by gender among ages 15+ years, 2006 and 2015 (number of hours) 5.28 4.58 4.45 4.40 3.08 2.78 2.75 2.80 1.13 1.27 0.85 0.88 2005 2015 2005 2015 2005 2015 Total Women Men Household and family care Employment Source: World Bank staff authors using TurkStat https://biruni.tuik.gov.tr/medas/?kn=141&locale=en Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 105 Figure 71.  Time use for household care and employment by gender and education, 2015 (number of hours) 5.03 4.93 4.35 4.12 3.63 3.60 3.02 2.32 2.12 1.70 1.03 0.83 Total Men Women Total Men Women Sencondary or vocational school Higher education Employment Household and family care Source: World Bank staff authors using TurkStat https://biruni.tuik.gov.tr/medas/?kn=141&locale=en Figure 72.  Association between age at first marriage and labor force participation rates (LFPR) across provinces by gender, 2022 45 Women 40 0.4315 LFPR, Women (%) 35 30 25 20 15 23 24 25 26 27 Average age at first marriage, female (years) 80 Men 75 0.0426 LFPR, Men (%) 70 65 60 55 26.5 27 27.5 28 28.5 29 29.5 Average age at first marriage, male (years) Source: World Bank staff authors using TurkStat regional statistics accessed May 8, 2023. https://biruni.tuik.gov.tr/bolgeselistatistik/degiskenlerUzerindenSorgula.do# 106 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 73.  Time spent on paid and unpaid work by gender, Türkiye and OECD 9.0 Türkiye OECD - Average 8.0 8.0 Number of hours spent per day 7.6 7.3 7.0 7.1 6.0 6.0 5.1 5.3 5.0 4.4 4.0 3.6 3.0 2.0 2.3 2.2 1.0 1.1 0.0 Men Women Men Women Men Women Time spent in unpaid work, by sex Time spent in paid work, by sex Time spent in total work, by sex Source: World Bank staff illustration based on 2021 OECD compilation using most recent data for Türkiye for 2015161 https://stats.oecd.org/index.aspx?queryid=54757 Social roles and perceptions contribute to differences in labor force participation in Türkiye, in line with global variations. Turkish survey data shows beliefs regarding women and men’s employment have been constant over roughly the past decade with some regional and educational differences (Figure 74). In both 2016 and 2022, nearly 83–85 percent of surveyed respondents in Türkiye had a favorable view of women’s employment outside the home, based on work by the Turkish Statistical Institute and Ministry of Family and Social Service’s Family Structure Survey. Interestingly, little difference is seen across age groups on average, suggesting beliefs are formed as early as the 15–20-year-old age group surveyed. The largest differences were seen not by gender but by region. The most favorable perceptions were generally to the west, almost exactly mirroring regions with the highest to the lowest women’s employment rates. The central and southeastern Anatolian regions had the lowest perceptions of women’s work, and in many regions, dipped even lower from 2016 to 2022. This is likely associated with the economic downturns and COVID effects when women were more likely to exit the labor force or switch to informal work. Evidence from Türkiye shows that unobserved characteristics such as underlying gender beliefs influence employment outcomes. As the time use data and the relationship between age of first marriage and employment analysis shows, a large share of women either does not enter or drops out early from the labor force to divert time to household roles, including child and older care. While this may be due to affordable alternatives to support household responsibilities, this may also be due to long-held beliefs. Recent evidence is also emerging on inherent occupational bias regarding women (and men’s) 161 Note, OECD: Unpaid work includes routine housework; shopping; care for household members; child care; adult care; care for non-household members; volunteering; travel related to household activities; other unpaid activities. Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 107 choice of profession in Türkiye, showing a bias among men and women towards certain professions for women and men as explored by Avcı et al (2019162) and Ulas and Demirtas- Zorbas (2016)163 (Box 3). Figure 74.  Perceptions of women’s work by demographics over time (a) Share with positive perception of women having a job, 2016 versus 2022, 100 by gender and region (% of respondents) 91.5 90.6 84.9 85.6 83.5 85.8 85.4 76.8 81.4 80 82.6 78.9 75.8 73.8 71.5 68.1 60 40 20 0 l en en ul a an a lia an lia a a ia lia ia ta ar ar Se Se ol ol nb to to to To ge ne M om m m at at na na na ta ck k rra ar ar Ae An an ac W Is la tA lA tA tM M ire Bl tB st st ra st es as es Ea ed st Ea es Ea nt 2016 2022 lE W Ea W M Ce h W th ra ut or nt So N Ce (b) Share with positive perception of women having a job 100 by age and education, 2022 (% of respondents) 93.2 86.1 82.4 78.2 80 60 40 20 0 ol ol y l n 0 5 0 5 0 5 0 5 0 5 + na ar tio 65 –2 –3 –4 –5 –6 –2 –3 –4 –5 –6 ho ho tio im ca 30 40 25 35 20 50 60 19 45 55 sc sc Pr ca du o y Vo ar N rE im y/ he ar Pr ig nd H co Se Source: World Bank staff authors using TurkStat, Türkiye Family Structure Survey, 2015–2016 and 2021–2022. 162 Based on World Bank staff authors’ consultations with Avci O based on Avci O, Tozar M, Hasret Y, YİĞİT S, ÖZDEMİR E (2019). Development of the "Attitude Towards Gender Based Choice of Profession Scale - Female Form. Pamukkale Üniversitesi Eğitim Fakültesi Dergisi (PAU Journal of Education) 45: 252–266, https://avesis.hacettepe.edu.tr/publication/details/2598d994-05d7-4343-8333-1eb9f76bafdc/development-of-the- attitude-towards-gender-based​-choice-of-profession-scale-female-form 163 Ulas O and Demirtas-Zorbaz S (2016).P Perception of various professions in Turkey. Journal of Teaching and Education. 5(01):739–744 (2016) https://www.researchgate.net/publication/303813528_PERCEPTION_OF_VARIOUS_PROFESSIONS_IN_TURKEY 108 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Box 3.  Gender occupational choice perceptions Gender-based occupational and sectoral segregation is seen in Türkiye and globally, reflecting informed choice but often less informed bias. While the aim is not to necessarily ensure the same matching across sectors, alleviating inefficiencies in otherwise informed choices can help improve women’s jobs outcomes in terms of access and quality. Information asymmetry may be an important determinant of these biases, filtering women and men into certain sectors and occupations. A previous global review by Das and Kotikula/World Bank (2019)164 found that occupational gender segregation can be linked to limited knowledge on potential job options and their relative returns, which in turn reduces their aspirations, educational investments, and entry into particular occupations. The earlier volume to this note123 demonstrated the role of early school, full-time career counselors. It showed that the rate of dedicated, full-time in-school career counselors (not teachers who both teach and counsel) at early secondary school levels in Türkiye was lower than most of the OECD, for example. Recent efforts have started in Türkiye to develop job counseling centers. Practicum experience is also generally lower among secondary school students in Türkiye as shown earlier in this note, notably among vulnerable regions. Together with social beliefs at the community level, evidence by Avci et al (2019) also shows that inherent attitudes and biases exist as early as secondary school years in Türkiye, as seen elsewhere to different extents. Work by Ulas and Demirtas-Zorbas (2016) and shows that among secondary school students equally male and female, the top five professions rated most appropriate for men were construction engineers, mechanical engineers, electric-electronic engineers, computer engineers and district attorneys (in order of share of respondents from 47 to 17 percent). By contrast, the top five professions rated most appropriate for women were nurses, dietician/nutritionists, elementary school teachers, counselors, and human resources (ranging from 40 to 13 percent of respondents). Some of these biases are learned as early as pre-school, showing the power of early childhood education for foundational and advanced skills. Interventions to both increase the quantity and skills of full- time, dedicated early career counseling and practical programs at an early age (early secondary) and national outreach campaigns through multiple channels can have strong impacts. Source: World Bank staff authors compilation based on works cited. 164 Das S and Kotikula A/World Bank (2019). Gender-based Employment Segregation: Understanding Causes and Policy .org/curated/ Interventions. Jobs Working Paper Issue No. 26. Washington DC: World Bank https://documents1.worldbank​ en/483621554129720460/pdf/Gender-Based-Employment-Segregation​-Understanding-Causes-and​-Policy-Interventions.pdf Locally adaptable, affordable, quality early childhood education is key in Türkiye for strengthening human capital, labor outcomes and gender equity alike. Women’s labor force participation in Türkiye as cited earlier is influenced by household responsibilities including family care, with women’s labor force participation lower than in comparable countries with similar rates of marriage, aging and fertility as shown in earlier global benchmarking. Reasons include personal preferences, choices, perceptions, Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 109 and biases related to social care, supply of services, and/or financial considerations. Of note, Turkish women’s LFPR among single women who have never been married aged between 25 and 64 years old is 64 percent, dropping to 35 percent among married women as of 2021, unlikely to rebound. Similarly, the participation rate among women with at least one young child (less than 6 years) is 32 percent. Ilkkaracan (2010) finds that education also plays a role. Among women with a primary education, marriage decreases average labor force from 50 percent among unmarried to 20 percent among married, the lowest rate among all women. As education increases, the drop is evident though rates do not decrease to the same low levels. Secondary-educated women who are unmarried have a 67 percent participation rate, compared to 30 percent among unmarried women. This means that nearly 1 out of 2 women are likely to leave the labor force following marriage, with many not returning. Both public and private pre-primary early childhood and nursery services are available in Türkiye but enrollment relatively limited. Türkiye has a long tradition of developing pre- primary school services since the foundation of the Republic, although enrollment particularly in nursery school has tended to miss national development plan targets165. As of 2022–23, nearly 64 percent of pre-primary schools (kindergarten) are public, the remaining 36 percent being private166. This translates to 82 percent of students enrolled in public institutions and 18 percent in private. In addition, among nursery services largely managed by the Ministry of Family and Social Services in addition to the Ministry of National Education and community centers, over 90 percent of services and enrollment are in public institutions. Türkiye’s pre-primary school enrollment rate (defined as enrollment among 3–5 year olds) has been increasing, reaching nearly 40 percent, which is half of OECD average at nearly 80 percent. Among 5 year olds, the rate in Türkiye is 95 percent as of the 2022–2023 academic year. Similarly, over the decade 2006–2016, national survey data shows that the use of nursery schools increased from less than 1 percent to nearly 3 percent (Figure 75). This trend has been driven mainly by Istanbul, West Anatolia, Marmara and Mediterranean regions, but lower in the same regions where women’s labor force is also lowest in eastern regions. While regulations governing the provision of pre-primary services exist, more has been proposed for expanding enrollment and developing systems, teacher training and quality assurance further. However, access to sufficient numbers of locally adaptable, quality early childhood education services may be a constraint, particularly among lower earners. Using 2014–15 Turkish Time Use Survey, Memis and Kongar (2020) also find that 43 percent of households in the top income quintile use nursery and childcare services, compared to only 1 percent of the households in the bottom quintile. Previous work has found that a particularly high likelihood that women leave the labor force permanently after marriage and childbirth in Türkiye (Ilkkaracan et al., 2021). These trends may suggest demand and/or supply side issues that need further detailed exploration outside the scope of this work. Türkiye has modestly increased spending and supply of early childhood over the past decade123. Creating conducive environments for trusted, reputable, and locally adaptable 165 Aral N, Kadan G and Aysu B (2023). Preschool Education in Türkiye from Past to Present. Theory and Practice in Child Development. 3(1): 138–164. 166 Ministry of National Education Statistics 2022–2023, https://sgb.meb.gov.tr/www/icerik_goruntule.php?KNO=508 110 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity models for early childhood education programs can contribute to pulling more parents into the labor force. Evidence from the most recent related meta-analysis by the Central Bank of the Republic of Türkiye on the topic highlights that while other factors play as equal a role, alleviating childcare constraints such as financial barriers can alleviate women’s employment barriers to an extent167. Measures like ensuring part-time and other flexible work arrangements also tend to help significantly for women and men alike. Figure 75.  Nursery rate among children by region over time, 2006 and 2016 (% of children) 7.6 4.8 4.3 3.4 3.5 2.8 2.7 2.8 1.6 1.0 1.1 1.2 0.9 0.8 0.8 0.9 0.6 0.5 0.3 0.7 0.6 0.4 0 0 0 0 2006 2006 2006 2006 2006 2006 2006 2006 2006 2006 2006 2006 2006 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 Aegean Central Central East East İstanbul Medite- North South Turkey West West West Anatolia East Black Marmara rranean East East Anatolia Black Marmara Anatolia Sea Anatolia Anatolia Sea Source: World Bank staff authors using TurkStat https://biruni.tuik.gov.tr/medas/?kn=141&locale=en As public spending on pre-primary has increased modestly, private spending has decreased on average (Figure 76). Overall public expenditure on education as percent of GDP has largely been stable in Türkiye since 2011, reaching approximately 4.3 to 4.6 percent of GDP as of 2020–2022, compared to the OECD average of approximately 5.6 to 6 percent. As of 2017–2020, Turkiye spent approximately 0.25 percent of GDP on early childhood education, compared to 0.23 percent in 2013. By contrast, the EU average was 0.68 to 0.69 percent over the same period. While a slight increase, this helps explain the increasing rise in early childhood enrolment discussed as part of global benchmarking. While public spending has generally been stable, private spending on education by households has doubled over the past two decades since 2002168, but not necessarily on early childhood (Figure 76). Most of this spending has gone to upper educational levels. This pattern may reflect changes in preferences and/or the relatively lower public expenditure on secondary education, as tertiary education has absorbed more resources over the same period. Out-of-pocket expenditure on education has gone from 1.3 to 2.5 percent between 2002 and 2019, driven by higher-income households. These differences may partially explain the socioeconomic differences in learning outcomes such as PISA in Türkiye and its higher HCI- health outcomes as compared to HCI-education relative to comparable countries. 167 Akgündüz and Platenga (2016). Childcare Prices and Maternal Employment: A Meta-Analysis. Central Bank of the Republic of Türkiye https://www.tcmb.gov.tr/wps/wcm/connect/8474165c-43c9-40e6-9acc-50824ea7e2e6/ wp1626.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-8474165c-43c9-40e6-9acc-50824ea7e2e6-m3fw6jo 168 TURKSTAT Household Budget Survey, 2011–2019. Most readily available data at the time of preparation and largely consistent with values through 2021–2022. Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 111 In line with recent efforts in Türkiye, boosting investments in the supply of quality and affordable childcare in public facilities and providing incentives can accelerate trends in growing coverage. Local community services can play an important role, such as municipalities and firm incentives to offer on-site or nearby childcare. Similarly, incentives targeted to low-income parents can alleviate financial barriers assuming local supply is readily available. Given a high share of childcare providers are women, the returns to women’s employment in childcare are an additional benefit. As initiated in selected Organizational Industrial Zones in Türkiye56, expanding and improving industrial zones can help improve women’s access to secure work environments with childcare facilities and transportation, triggering positive externalities that pull more women in (Cebeci, 2015). Figure 76.  Public and private education expenditures by educational level and by household quintile over time Public Education EXP 1.8% Tertiary 1.29% 1.6% Lower EXP as % of GDP 1.4% Secondary 0.82% 1.2% 1.0% Primary 0.79% 0.8% Vocational and 0.6% technical upper secondary 0.66% 0.4% 0.2% General upper 0.0% secondary 0.40% 2011 2012 2013 2014 2015 2016 2017 2018 2019 Pre-primary 0.29% Private Household EXP 0.35% General upper secondary 0.30% 0.30% Lower EXP as % of GDP 0.25% Secondary 0.29% 0.20% Tertiary 0.27% 0.15% Primary 0.21% 0.10% Vocational and 0.05% technical upper secondary 0.10% 0.00% 2011 2012 2013 2014 2015 2016 2017 2018 2019 Pre-primary 0.04% 4.5 Share of household expenditure (%) 4.0 3.5 3.0 Total 2.5 Quintile 1 (lowest 20%) 2.0 Quintile 2 1.5 Quintile 3 1.0 0.5 Quintile 4 0.0 Quintile 5 (highest 20%) 2002 2010 2019 Source: World Bank staff authors calculations, Education Expenditure Statistics per educational level, TURKSTAT Household Budget Survey for household expenditure on education by consumption expenditure quintiles. Based on most readily available data at the time of preparation. 112 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity From National to Local Public Representation Turkish women’s public representation has increased over a decade, particularly at the local level and in certain provinces. Women’s public voice and representation have also been expanding at a modest rate, with regional variation. Public voice, participation, and representation in public administration can provide direct and indirect effects on pulling more women into the workforce. Currently, 17 percent of national parliamentary seats are held by women, compared to an OECD average of 32 percent (Figures 77 and 78). In Türkiye the rate increased sharply from nearly 4 percent in 1999 to 14 percent in 2011 and has only modestly increased since then. Affirmative action measures such as quotas for the number of seats held by women such as that used in Türkiye169, all else equal, have been instrumental in increasing women’s parliamentary representation. At the regional level, Regional Development Agencies (DAs) within the Ministry of Industry and Technology provide an example of women’s public representation and participatory processes that can be scaled up170. The DAs comprise 26 agencies comprising province groupings per agency. With a national investment budget of nearly US$ 339 million171 as of 2021, the DAs target local development through a participatory and citizen engagement process, emphasizing youth and women’s livelihoods. The DAs provide support to various entities including public institutions, private sector, and non- governmental organizations such as associations, foundations, and producer unions, often with dedicated calls and/or targets for women- and youth-led initiatives. Responsible for identifying and fostering local economic development opportunities, over a decade the DAs have increased women’s staff representation nearly in line with national labor force participation rates (Figures 79 and 80). Collectively they employ over 1,200 employees, including 695 specialists. Most DA staff have graduate degrees and an average of 10 years of experience. On aggregate, women’s representation has gone from 26 percent in 2010 to 33 percent by 2021172, or a jump of nearly 27 percent. The share of women’s representation in DAs varies by region and in some cases is higher than the local employment rate. In general, regional variation mimics overall regional employment variation, in that regions with the highest share of women’s participation are also those with the highest labor force and employment rates among women. 169 Taşkın B (2021). Political Representation of Women in Turkey. Institutional Opportunities versus Cultural Constraints. Open Gender Journal, 5. https://opengenderjournal.de/article/view/106 170 Onur M and Lemasle N/World Bank (forthcoming). Türkiye Social Inclusive Green Transition Project. Project Appraisal Document. 171 MoIT, Development Agencies Annual Report 2021; MoIT DG of Development Agencies. US$ values calculated based on the average US$-TL exchange rate per year. 172 MoIT, Development Agencies Annual Report for 2021. https://ka.gov.tr/sayfalar/faaliyet-raporlari--28 Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 113 Participatory investments with women’s inclusion as a key focus that are overseen by the DAs can provide lessons learned through future evaluations. Financing needs identified by local communities are funded through calls for proposals that target certain themes and populations170. The DAs provide financial and technical assistance through different incentive and financing schemes to local development ideas from local enterprises and cooperatives that are aligned with regional development plans. The DAs focus on various thematic areas under social and economic development, small-scale infrastructure, investment promotion and cooperation for development in the regions. Most DAs specialize in and focus on specific issues according to the potential in their regions. Entrepreneurship, low carbon economy, renewable energy, social inclusion and cohesion, agriculture and rural development are among the most supported areas. The investment and technical assistance priorities of the DAs are determined in the 5-year regional development plans, which are prepared in an inclusive manner through local citizen engagement, including women’s outreach. Figure 77.  Representation in national parliaments (proportion of seats held by women), Türkiye and selected countries, 2021 (%) 45 32 26 21 17 16 15 14 e be CD sia il a a nd sia as in di iy rs la ne ni rk nt In em OE Br ai Tu Tu ge do Th Ar In M Source: World Bank staff authors using World Development Indicators based on Turkstat for Türkiye. Figure 78.  Representation in assembly by gender, Türkiye, 1999–2022 (%) 100 Men Women 90 80 70 60 50 40 30 20 10 0 1999 2002 2007 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Source: TURKSTAT, Women in Statistics, data on Grand National Assembly of Türkiye, 1999–2022, https://data.tuik.gov.tr/Bulten/Index?p=Istatistiklerle-Kadin-2022-49668 114 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Figure 79.  Women’s representation in regional development agencies, 2020–2021 (% of staff who are women) Total 32% Kudaka FKA Karacadağ Mevka Daka Kuzka Zafer Dіka Ahіka Serhat Oka İka Marka Doğaka Bakka Baka Oran Gmka Geka Ankaraka İstka Doka Çka Trakyaka Bebka İzka 0% 10% 20% 30% 40% 50% 60% Source: World Bank staff authors using MoIT data, 2021171. Figure 80.  Regional development agencies by region, 2021 Source: MoIT, 2021171. Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 115 E-Service Delivery and Outreach for Economic Inclusion Building upon these trends, social inclusion and voice for vulnerable women can be scaled-up further through innovative ways, including leveraging outreach through Türkiye’s advanced digital e-government platform173. The platform has become one of the largest e-government systems globally. As a public service delivery system, it has helped expand coverage and accelerate service delivery, strengthening inclusion and as a result social capital. It includes inter-agency services from civil records to health system monitoring used during COVID, with selected inter-operability between agencies and digital records for citizen-centric services. This includes: 1. On the social protection side, the national Integrated Social Assistance System (ISAS)174 can be further expanded to other populations (including informal workers and youth NEET) and connected through new modules with social security and labor services. ISAS is a broad social information system for targeting the most vulnerable in terms of social protection and labor programs and associated needs such as housing, health care, municipal and civic services. 2. On the education side, the national online e-platform teaching system managed by the Ministry of National Education, can be applied to other needs through additional investments (Box 4). The Education Digital Network, EBA (Eğitim Bilişim Ağı), EBA, originally designed for K–12 learning, was instrumental during COVID for distance learning and can be used to address out-of-school challenges and adult learning for vulnerable women and men, including foundations for financial literacy, entrepreneurship, and public participation in coordination with relevant expert agencies. MoNE has also launched an online teacher training platform. This comprises forty-one online professional development courses delivered on the Teacher Information Network (ÖBA( platform to improve digital competencies of teachers and school leaders. 3. On the labor and financial capital side for vulnerable groups, the Government’s nascent e-METIP managed by the Ministry of Labor and Social Security can be developed further, the focus of the rest of this section. E-METIP, initially a digital monitoring system for early alert regarding risks facing vulnerable seasonal agricultural workers, could be adapted further. The system, launched in 2016, includes features that could readily be adapted to deliver labor, financial inclusion and social capital outreach, sensitization, case management and services at the local level. Coordination with local municipalities, government programs and Regional Development Agencies can be enhanced through expanding inter-operable digital systems and program design. 173 Türkiye e-Devlet (e-Government) Platform https://www.turkiye.gov.tr/non-citizens 174 Ministry of Family and Social Services (Policy) and World Bank, 2017, https://www.aile.gov.tr/SYGM/PDF/Turkeys_integrated_social_assistance_system.pdf 116 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Box 4.  Applying Türkiye’s e-learning platform EBA model for vulnerable adults and youth neet Türkiye’s current national EBA online distance education system aims to reach girls and boys equitably. The Government has been increasing EBA investments needed to diversify mobile digital options for non-connected groups, including vulnerable women. Boys and girls in Türkiye on average have similar access to computers and internet (61 percent for girls and 62 percent for boys) and have similar usage of computers at home according to PISA 2018 data. COVID renewed Türkiye’s commit- ment to consolidate its national reform for education technology, under the FATIH175 program and related legislative framework for distance education. MONE’s strategy is two-pronged: To expand access to distance education, both on-line and TV, with required materials, teacher training, and parental guidance (both curricular and to mitigate COVID risks). The second part of its strategy is to complete earlier investments in the education technology while modernizing EBA through a new platform, that is resilient to climate related natural disasters, and create the organizational and virtual structures for innovative digital education materials for teachers and students. Such a resilient system can be useful during stable education periods and for emergency preparedness and response. Future areas that can be considered include scaling-up approaches to integrate and adapt the digital platform to other delivery modalities, learning and labor needs, including financial literacy, most accessible to low-income households, notably women (TV, mobile phones and tablets, etc.). Specifi- cally, as described by MoNE, in terms of content design and management, high-quality and up-to-date digital content has been integrated into EBA for each student. The process is coordinated by MoNE's Department of Content Development and Management using a three-part structure: (i) in-house production with content teams, (ii) acquisition of quality standards-compliant content from non-govern- mental organizations and other institutions through grants, and (iii) procurement. Currently, to manage these processes systematically, a strategic assessment has been conducted to ensure students have been reached without facing barriers. Digital content standards are thus emphasized and processes established according to global Web Content and Accessibility Guidelines (WCAG). The EBA approach provides important architectural and accessibility lessons learned for future programs and needs. Source: Ministry of National Education, and Reyes S, Sargent S and Abdul-Hamid H/World Bank (2020). Türkiye Safe Schooling and Distance Education Project. Project Appraisal Document Report No. PAD3962. Washington DC: World Bank. 175 Within "Turkey Vision 2023 E-transformation" policies, the FATIH Project (Firsatlari Arttirma ve Teknolojiyi Iyilestirme Hareketi = Movement of Enhancing Opportunities and Improving Technology) was initiated by MoNE in 2010. It had four components (i) Interactive White Board, (ii) Infrastructure and Access, (iii) Teacher Training, and (iv) Content (the EBA education platform). FATIH’s goals where to set up an information technology to support teaching-learning, including Interactive blackboards (IWB) in all classrooms; provide tablet computers to all teachers and lower secondary and high school students, and to create software and digital content and z-books (to be used with IWB and tablets). The program also aimed to set up the required internet infrastructure and train teachers to combine incorporate digital tools into their pedagogical processes. Assessment of the e-METIP monitoring platform shows ways to serve broader vulnerable groups. As a nascent system, this section serves as a summary overview of the potential for further digital development expansion of the Government’s existing labor market tracking system (e-METIP)176. The aim is to identify existing strengths and areas for 176 See full supplemental World Bank assessment note/Jakimowicz K. Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 117 developing it into a broader online labor vulnerability monitoring for case management for vulnerable groups, notably women, during major structural transitions and shocks (including earthquakes/ natural disasters, climate/green transition, pandemics, major economic/ financial crises, and other needs). E-METIP has a strong women’s dimension by virtue of its initial focus on informal workers in agriculture. The Second Seasonal Agricultural Information System (e-METIP) was launched within the framework of the Seasonal Agricultural Workers Project (METIP) in 2017. The initial system was established in 2008. The system is administered by the Ministry of Labor and Social Security in cooperation with the Ministry of Interior and the Ministry of Health and Ministry of National Education. Its initial design is to monitor seasonal agricultural workers, their juveniles and children, and their children’s compulsory school attendance and relevant information coming from the Ministry of Health, across all of Türkiye. As such it has a strong gender dimension since women are highly represented in agriculture. Its structure and components are versatile and readily adaptable to support additional groups, including broader informal vulnerable women workers in other sectors. The primary focus of e-METIP is comprehensive reporting and monitoring system is to enable real-time alerts regarding workers’ vulnerabilities. It is designed to enable monitoring and data collection on seasonal agricultural workers understood as a labor workforce that is currently excluded from the social security system, and their children to: • Effectively register them into a social security system; • Increase children’s school attendance and awareness of existing schooling options (such as distance learning etc.) and other respective measures; • Manage the reporting of the local administration budgetary needs pertaining to seasonal workers on the level of the city/settlement (such as housing, clean water, and electricity needs), which are then further evaluated by the ministry using a set of predefined criteria; and • Generate data insights that can feed further policy recommendations/action in the identified areas. Key features include: 1. Data collection/capture and reporting. Data is collected via self-reporting by the local agencies as well as via extraction from the interoperable systems of the Ministries of National Education, Health, and Interior. The system allows for the generation of reports as a map visualization, excel, word, or in .pdf format. No real-time monitoring function is available. 2. Demographics and labor mobility monitoring. The system offers data visualization and aggregation & disaggregation based on predefined filters. It provides information on the total number of seasonal e/migrants and children. Migrants are understood as domestic workers (citizens) who move from province to province, including 118 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity international seasonal workers. Data can be disaggregated by demographics (gender, age, nationality) and location (district and 10 biggest cities level), non/residential address and point of origin. In the future, the Ministry plans to expand the information on the child labor data with age breaks (such as 6–12, 12–14) and add the wage information of the workers. The system provides information and map visualization on the movement of migrant workers (movement from/where to, secondary movement), by cities and provinces (movement from/where to). 3. Budgeting/needs costing at the provincial level. E-METIP enables a detailed reporting of budgetary needs’ projections and requested support per local government in the form of action plans, detailed info on temporary settlement area (size, population capacity, type of building, electricity, water, etc), as well as management of budget and action plan approval process. For the reporting process, the Ministry works closely with local governments. Local governments define their needs and budget to fulfill their needs. The Ministry defines criteria to finance the needs of local governments and on their basis approves the action plans. 4. Interoperability/referral services. E-METIP is based on open-source software and is interoperable with the system of: • the Ministry of National Education (integration with e-school - E-METIP can share data with E-School on children’s enrollment to the schools. A child of the seasonal worker is allowed to register at the school of the city in which the seasonal worker works), • the Ministry of Health (extraction of data based on the national ID), and • the Ministry of Interior (integration module with law enforcement). Key findings from a rapid assessment of key opportunities for developing the e-METIP follows below (Table 9). The assessment uses the ISPA M&E Data Collection Framework to evaluate the degree to which the platform has sufficient monitoring and evaluation protocols in place to track results and impacts of the program, and whether sufficient mechanisms are established to promote transparency and reduce error, fraud, and corruption. The assessment of the features of the current e-METIP platform reveals that the platform has a potential for future improvements 1) in terms of functionalities of the current system, as well as 2) its potential for further development for the purpose of the comprehensive online labor vulnerability monitoring platform. Monitoring & Evaluation System. Though the e-METIP system allows for comprehensive reporting of the budgetary needs and action plans at the provincial governorship level, it is unclear if the M&E plan is in place and/or is fully implemented in the platform. The platform constitutes a Management Information System that allows to process and generate reports and basic evaluations (progress on the number of migrants registered and children attendance or degree of budgetary spending on a provincial level). Nevertheless, the system, and accompanying platform, do not offer impact evaluations and scorecards, focusing on inputs and outputs indicators that are not fully elaborated in the platform (as Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 119 compared to the overall objectives of the program run in collaboration with the ILO). The outcome and impact indicators related to direct, indirect, and induced effects (e.g., social, economic and environmental) are not available. The system serves as a tool for internal administration and is very well-developed in terms of financial audit / provincial action plans and budgetary spending monitoring. However, the dashboard does not offer indicators and analytics functionality regarding the cost-efficiency & their comparison across provincial governorships. The system allows direct access to provincial administrators, the platform does not offer the final beneficiary interface, nor the community feedback is available. E-METIP could be further enhanced by the development and introduction of the monitoring and evaluation scorecard that allows for more elaborated performance, output and impact indicators, cost/efficiency tracking and comparison across provinces. Data Collection, Dissemination, and Use. The portal enables data collection/capture via online forms for provinces and through interoperability with several ministries. However, the portal could be further enhanced by the introduction of the beneficiaries-facing interface and app and a case-management system with real-time insights into field activities. E-METIP portal provides a dashboard that could be further elaborated by connecting it to a border range of demographic indicators (eg. income, occupation, education level) and to job employment/counseling services for the parents. In addition, the system could be enhanced by introducing an AI-enabled advanced decision-making tool that could help target the most vulnerable beneficiaries. Table 9.  Summary of e-METIP features Monitoring and Yes/No/ Notes / evaluation system Partially Comments Is there an m&e plan in place and An online monitoring dashboard impact evaluation potential to be n/a E.1 implemented? developed (TBD) Interoperable with other ministries, based on open-source • MIS n/a components • Process reports and evaluations n/a Comprehensive reporting section E.2 • Impact evaluation n/a TBD. Reports focused on inputs and outputs. • Community feedback (E.G., Social Provincial governments can update the information. The system c audits, score cards) does not offer direct connection/ information to final beneficiaries • Financial audit n/a Budgetary needs and spending monitoring available. Is baseline data available? Yes 2018 Onwards E.3 From what year? Yes, within the program log frame developed with the ilo. However, Is there a log frame to guide monitoring Partially the online log frame focuses on provincial budgetary needs. No E.4 and evaluation? Explain. fully developed log frame is available 120 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Monitoring and Yes/No/ Notes / evaluation system Partially Comments The output indicators presented in the online system are limited as compared to the overall ilo outputs reported, eg: Does the system have output indicators? • No. of children • No. of children prevented from seasonal agricultural work E.5 List the indicators (E.G., Number of n/a through protective, preventive services and referred to people employed, no. Of wells built). educational activities. • No. of children and families, men, women registered into the service system • No. of families were outreached. Does the system have outcome and • Elimination of child labour in seasonal agriculture in Türkiye impact indicators for all objectives, • Strengthening capacities of national and local institutions. E.6 relating to direct, indirect and induced n/a • Improving livelihoods of seasonal agricultural worker families and effects? List the indicators (E.G., Social, their children, via improving their access to public services, and economic and environmental). to education (for children) E-metip allows for tracking of budgetary spending. However, direct Does the system have cost-efficiency n/a analytics regarding the cost-efficiency and comparison of provincial E.7 indicators? List the indicators. governorships performance is not available Is the data required to measure these Yes. System allows for additional data to be easily added and E.8 n/a indicators easily available? presented What means does the system use to inform about program performance and No direct info and gateway to the final beneficiaries as it is meant E.20 n/a eligibility criteria (E.G., The media, civil as an internal administrative management system. To be evaluated society, etc)? Source: World Bank staff authors. Excerpt based on World Bank CODI assessment tool for monitoring and evaluation systems of social protection and labor programs. See full supplemental World Bank assessment note/Jakimowicz K. n/a: not available. TBD: to be determined. Potential for Inter-Agency Operability. Finally, the open-source nature of the platform and its interoperability with selected other ministries allows for its further expansion in scope and functionalities. Based on the already existing infrastructure, e-METIP has the potential to be expanded to support all labor force population irrespective of their employment status including women, youth dropouts, child labor vulnerabilities and other challenges, allowing for: • Comprehensive understanding of the labor market’s condition and service delivery provision over time for more effective policymaking in the area of social protection and jobs; • Increased efficiency of organizational processes and effective allocation and use of resources; • Enhancement of the accuracy, transparency and accountability of third-party monitoring (TPM) of the M&E; • Flexible and faster delivery of assistance (cash transfers, educational trainings, job assistance) and services to the population; • Better multi-stakeholder engagement (perception or feedback surveys) and understanding of local dynamics for an informed decision-making process. Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 121 To strengthen the E-METIP system and expand its use for addressing labor market vulnerabilities including gender gaps, the following recommended steps can be taken (Table 10): 1. Upgrading systems for real-time community-based data collection and monitoring capacity: this includes integration of data collection through physical means directly from the field with satellite imagery for identifying vulnerable households and areas and risks. Examples include the Geo-Enabling Initiative for Monitoring and Supervision (GEMS) and the associated open-source technology KoBo Toolbox, an initiative that has been implemented in over 100 countries to improve monitoring and evaluation (M&E) of field activities while also increasing operation effectiveness on the ground via the use of digital data collection and analysis. 2. Detailing information collected on labor market vulnerabilities and profiling for decision- and policy-making process: this entails the development of a comprehensive Vulnerability Welfare Assessment Index methodology (including an Employment Resilience Assessment) and dataset. Examples include welfare tracking assessments such as those used in Indonesia and Estonia. In Indonesia, systems such as the Welfare Tracking in the Aftermath of Crisis (WelTrAC) tool employs an interactive, detailed web-based monitoring dashboard to track impacts, household characteristics, coping mechanisms, and labor mobility, and to target responses, which can be adapted and used for non-emergency settings as well. The Estonian Unemployment Insurance Fund (EUIF) has adopted smart technology through a partnership with private sector technology firms to develop an AI-powered decision support tool (OTT) that predicts the risk of long-term unemployment, supporting fiscal and service delivery needs analysis. 3. Developing robust case management systems and service delivery for holistically addressing labor market and social vulnerabilities: this entails building case management information systems (CMIS) to support all phases of service delivery, including for field-based social workers and monitoring support to vulnerable beneficiaries. Examples include systems used in Colombia, Italy, Romania, Germany, Zambia, Nepal and other countries, ranging from jobseeker services, social insurance payments and basic income schemes to non-contributory household transfers and child protection services. Packages like the World Bank’s Case Compass and CORE- MIS technology tools can help introduce these systems. 4. Consolidating service delivery into a single point of user contact (one-stop shop) for efficiency of organizational processes, resources and beneficiary engagement: this includes maximizing e-Government platforms for managing a consolidated package of services and outreach. Examples are the use of a Digital Family-Job Card and other unique identification-based schemes to support education, jobs, social protection, financial, justice, medical and social services in countries such as Kazakhstan and India. 122 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Table 10.  E-METIP: summary of relevant global models and complementary features Based on “G.E.M.S./Kobotool” Based on and WELTRAC methodology “CORE-MIS” Enhancing real-time community-level data collection and monitoring capacity via in-field data collection & remote sensing. Improving case management and service delivery via Case Objective Improving understanding of labor market Management Information Systems (CMIS) that support the conditions for decision & policy making delivery of cash transfers & inclusion programs. process via the creation of a Vulnerability Assessment Index. A digital platform based on the use of a low- cost open-source technology, KoBoToolbox A user-friendly web-based application, developed using and smartphone app, and an integration exclusively free and open-source tools, that can be quickly Description of geo-tagged field data that automatically adapted and deployed to support the delivery of cash transfers feeds into a centralized M&E system to gain & inclusion programs. real-time insights on local dynamics. • Real-time M&E Dashboard • Task management with notifications (inl. bulk SMS notifications) • Case management life cycle • Real-time M&E Dashboard • Beneficiary detailed view & household view • Screening / Profiling/ Assessment/ Pre- • Cash transfer and inclusion programs distribution (service Functions enrollment provision, training tracking) • Vulnerability Assessment • Payment management (Payments management (generation of payrolls, repeated payment cycle support, multi-level approval • Email notifications workflow, support for over-the-counter offline payment (dedicated android app), advanced reconciliation with proof of payments (e.g. photo evidence)) • GRM (Grievance Redress Module) • Time and payroll management • Public administration Institutional / • Public administration • Field/case workers Users • Field/case workers • Beneficiaries • In-field via digital questionnaires • Mixed - surveys in-field, phone calls, public registries (customized templates) • Online & offline data collection • Online & offline data collection • GPS coordinates (geo-tracking) via KoboToolbox extension Data • GPS coordinates (geo-tracking) • Document upload collection / • Remote sensing (satellite imaginary) • Document upload • Multiple data sources beyond text (photos, audio, videos, time Sources and date stamps) • Multiple data sources beyond text (photos, • Interoperability with other public registries for additional data audio, videos, time, and date stamps) population • Interoperability with other public registries • Data cleaning tool for additional data population Access Android app, tablets & web browser Smartphones, tablets & web browser • Open source • Open source • Low-cost/free • Low-cost/free • Fast deployment • Fast deployment • 15 Modules operational including integration with • Customization available IT KoboToolbox (customization available) Architecture Additional technology to be deployed Integration of the AI-powered tool into the M&E and case management system to help predict the risk of long- term unemployment or vulnerability (supporting the Vulnerability Assessment Index) at the micro and micro level and serve as a decision-support tool for public administration and case workers. Source: World Bank staff authors. Excerpt. See full supplemental World Bank assessment note/Jakimowicz K. Social Capital: Roles, Public Representation, and Service Delivery for Economic Inclusion 123 Key Implications Türkiye’s social capital landscape in terms of gender equity in time use, use of key services, and public representation shows shifts over time, with wide regional differences. 1. These align with patterns seen in labor capital and financial capital, suggesting that collectively these three dimensions influence human capital utilization patterns. 2. While some of these social capital patterns require further analysis to identify detailed underlying factors, awareness and service delivery can help bridge regional differences in the short term in terms of gender-related employment beliefs, occupational choices, coverage of early childhood education services and public office representation. 3. E-government systems provide a mechanism for supporting these aims especially in a country as geographically large as Türkiye, building on its existing e-government systems. 124 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity 5 Outlook: Holistic Systems for Equitable Utilization “It makes commercial sense. We’re in it for the 82 percent: The masses of unserved women of rural or lower socioeconomic background. This is where we can impact.” Women-led firm CEO 177, IFC Banking on Women Program178 Compiling Türkiye’s achievements and pending gaps, this part summarizes key profiles for addressing greater inclusion and gender equity, and links these to a holistic approach to policy recommendations. It highlights that Türkiye has continued to progress but to accelerate, existing policies and programs can be expanded for coverage in vulnerable regions. In addition, greater performance- based approaches and reforms to labor market and social protection policies can level the playing field for vulnerable women and men alike, particularly informal workers. Maximizing integrated human capital and jobs systems with robust demand- and supply-side measures and e-government services can help Türkiye’s most vulnerable women and men strengthen resilience ahead of future shocks. 177 IFC, “A Helping Hand for Turkey’s Women Entrepreneurs”, https://www.ifc.org/wps/wcm/connect/news_ext_ content/ifc_external_corporate_site/news+and+events/news/turkeys+women+entrepreneurs 178 Ongoing 2023 IFC program. IFC (2016). Profit with Purpose: Making Banking on Women Impactful. Washington DC: IFC https://www.ifc.org/wps/wcm/connect/6bc3f55b-51ad-4b84-b6e2-9ed874bcb346/ MakingBankingonWomenImpactful_191016.pdf?MOD=AJPERES&CVID=lvDs7GW Outlook: Holistic Systems for Equitable Utilization 125 Maximizing Whole-of-Government Action for Outreach Türkiye has progressed in laying the foundations of human capital, with frontier areas in utilization remaining in greater outreach, labor productivity and financial and social capital inclusion. Overall, a paradox of performance appears in Türkiye regarding human capital utilization and economic inclusion in terms of gender equity. Türkiye has performed well, on balance, in putting in place foundations: legislative, human capital, investments, and institutional platforms with a vision of universal coverage and equitable opportunity. The paradox is pending gaps appear to be disproportionate to those foundations. Coverage appears to be one of the over-arching missing links, whereby some regions and cohorts benefit more from those strong foundations than others. Türkiye’s human and economic institutions have historically enabled labor utilization, but macroeconomic challenges put those gains at risk particularly among vulnerable women. Türkiye’s development has leap-frogged in many ways compared to comparable economies. Yet since the global financial crisis (2007–8), COVID and its 2023 earthquakes, new challenges have emerged. These regularly beg constant innovation in program and policy design for safeguarding Turkish women and men’s hard-earned gains to date. The challenge now is to push those frontiers radically to keep pace with demand and aspirations. Analysis from this note on Türkiye’s progress on human capital utilization and gender equity over 2005–2022 points to three general trends: 1. Highly advanced primary human capital accumulation: Some of its progress has been due to major reforms and measures taken over the past two decades, like universal education, universal health insurance reforms, wage subsidy programs introduced, and minimum wage hikes. 2. Gradual progress on more advanced human capital, labor and financial inclusion: Many areas of progress were due to more gradual reforms and measures. These include a gradual shift in expenditures towards secondary and vocational education and ECD, from agriculture to services especially hospitality and domestic services, in the growth of formal firms, and legal reforms regarding part-time work and other flexibilities. 3. Slower progress on expanding productivity and social capital-enhancing measures: In other areas, reforms and/or implementation has been more limited. These include measures needed to radically ramp up social security and formal jobs for women, aligning parental benefits, sectoral and occupational segmentation, pre-early childhood education and nursery care, and women-led firms and ownership. 126 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity The findings from labor, financial and social capital analysis in this note can be grouped into a typology of human capital utilization profiles for designing targeted programs (Figure 81). Ranging from low- to highly skilled, less to more readily connected to different occupations, and with less to greater access to services, these profiles can support designing more nuanced “gender equity” strategies. As this note has shown, constraints due to market failures distort access to information, services, incentives for the private sector, and selection bias in networks for the most vulnerable workers, impacting women of different profiles differently. Since human capital accumulation does not automatically translate to labor utilization, policies and programs, particularly integrated labor systems, can help address labor market failures that can leave vulnerable groups and women behind. Labor programs and associated financial and social measures can better target those readily modifiable constraints and market failures, such as information asymmetry, selection bias, opportunity costs, and financing for public goods and positive externalities where markets have lower direct incentives to intervene (including women’s equity, vulnerable regions, and early childhood education). Figure 81.  Türkiye: Stylized typology of human capital utilization across occupational profiles Traditional and domestic trades | 50–60% of labor force • Basic or lower secondary education or youth NEET • Lack financial accounts/skills, • High labor force exit among women, high informality, far lower among women occupational segregation • Ages 15–35 • Over 90% of women primary home caregivers, • Semi-urban and rural low early childhood education Vocational trades | 20–30% of labor force • Secondary education, basic job skills • May lack financial accounts/skills, • In labor force, informal or unemployed, far lower among women notably among women • Ages 25–45 • Over 90% of women primary home caregiver, • Semi-urban and semi-rural low early childhood education Technical and commercial services | 10–20% of labor force • Secondary or higher education, semi-advanced job skills • Likely some financial account/skills; but • In labor force but unemployed, in precarious jobs or • weak access to credit, networks, markets weak self-employment • Ages 25–45 • Over 80% of women primary home caregiver, • Urban and semi-urban few early childhood education Professional services | 5–10% of labor force • Higher education, advanced skills • May have access to financial • In labor force, employed, entrepreneurs, accounts/skills, but wide gender gaps but occupational/sectoral segregation in access to credit, networks, markets • Over 70% of women primary home caregiver, • Ages 35–55 likely early childhood education Source: World Bank staff authors. Outlook: Holistic Systems for Equitable Utilization 127 Integrated Human Capital and Jobs Framework Moving forward, Türkiye can strengthen human capital utilization and jobs for women and men equitably by scaling up holistic investments tailored to different profiles. Alleviating lagging human capital utilization and gender equity can be tackled at scale through holistic approaches tailored to profiles. In addition to Türkiye’s examples discussed in this note, global experience shows that while the challenges are complex, holistic approaches are likely to be most effective moving forward (Box 5). This would imply combining at least two of three challenges from among labor, financial and/or social capital needs per measure, with a package of different options targeting different profiles from the four stylized profiles. The frontier is to build upon Türkiye’s strong base and scale-up: in coverage, program design, incentives, and financing. Türkiye can reinforce its human capital and labor market foundations in main two ways, as discussed in detail in the note: 1. First, it can apply the spirit of its Constitution and 11th and 12th NDP in expanding existing institutional foundations to semi-urban and rural regions, including ongoing effective programs at the local level in regions and communities such as peri-urban zones and Southeastern and Central Anatolia. 2. Second, it can introduce complementary spending and measures to facilitate this implementation at the local level. For a marginal increase, returns on expanding investment in effective programs are exponential, outweighing other alternative uses of public resources given that Türkiye boasts one of the most competitive, global outreach infrastructure systems in the world. The earlier volume of this work on public expenditures analysis showed an illustrative costing of between 2–4 percent of GDP needed for targeted social expenditures to close gaps in coverage123. This includes labor market interventions to alleviate distortions and market failures, inherent to most countries, that will otherwise continuing lagging. Using this two-pronged approach, this note consolidates Türkiye’s achievements and ten main frontier areas, with recommendations for an integrated human capital and jobs framework tailored to women and men (Tables 11 and 12). Specifically, ongoing newer initiatives to date can be scaled-up through innovative designs capitalizing on technological outreach and linkages to market networks more proactively. Strengthened investments are needed for hard-to-reach youth and women NEET, out of labor force cohorts, and informal sector workers. Delivery systems through enhanced registries and case management provide one avenue. There is also more scope to expand effective, ongoing areas that have already gradually started, especially through performance and results incentives, while introducing radical new measures and reforms to leapfrog and accelerate. Unprecedented global economic contraction during shocks on family incomes has increased the risk of school dropouts, particularly for girls. The public national online education platform, EBA, is being enhanced further with World Bank-supported Türkiye Safe Schooling and 128 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Distance Education Project to expand information technology capacity so that no child is left behind, especially girls, low-income households and non-native Turkish students179. New mechanisms developed by the Turkish National Employment Agency, İŞKUR, the Ministry of Trade, firms, and social cooperatives, with World Bank and European Union support have helped improve job placement among women as well as social integration, with 60 percent of women finding jobs following skills upgrade180. Innovative platforms under this engagement such as the Social Entrepreneurship Community of Practice further help reach the most vulnerable, remote men and women. An integrated human capital and jobs framework that addresses inclusion and gender equity would bring together Türkiye’s existing programs and adjust performance and scale, built around a holistic jobs system. Türkiye has espoused employment, inclusion of vulnerable populations and gender equity in its five-year National Development Plans and associated Women’s Empowerment Strategy and National Employment Strategy, with several institutions in place that can be adapted further for reaching impact at scale: 1. On the supply-side, a range of ministries support outreach services and monitoring vulnerability. The Ministry of Family and Social Services coordinates intra-governmentally, also responsible for direct-to-citizen social services, case management and outreach. The Ministry of Labor and Social Security, including İŞKUR and SGK, have robust foundations for key labor and social protection programs, social dialogue, and monitoring vulnerability. The Ministry of National Education has been ever-expanding educational technology and systems strengthening to improve future school-to-work transition. Scale remains the next frontier. 2. On the demand side, several actors have launched gender equality of opportunity incentives and targeted programs that serve as examples to be enhanced and scaled-up jointly with supply-side institutions. The Ministry of Industry and Technology, including KOSGEB and Regional Development Agencies, has wide reach to firms and enterprises at the regional levels. The Ministry of Trade is actively involved in facilitating social cooperatives with the potential to reach the most vulnerable communities. Finally, national private sector associations, chambers of commerce, labor, and trade groups such as TUSAID, TUBITAK, TOBB, KAGIDER and other groups all espouse gender action plans for greater competitiveness. The landscape is ripe for extending these initiatives far broader. In addition, an effective investment for gender equity is expanding information and awareness measures at the household level. Addressing information asymmetries through expanding mentorship, community networks and access to information on earnings across jobs and sectors can shift women’s preferences. Promoting a more equal division of labor at home through education campaigns and introduction of paternal leave can be important levers for alleviating opportunity costs (IMF, 2019). Engaging men, boys, and extended household members at an early age and throughout through regular behavioral nudging 179 World Bank Türkiye Safe Schooling and Distance Education Project, Project Appraisal Document, June 2020. 180 World Bank and European Union Employment Support Project, İŞKUR database, October 2020. Outlook: Holistic Systems for Equitable Utilization 129 and awareness-raising of women’s success stories at the local level is equally effective. Expanding women’s work outside the home can positively boost economic resilience following shocks while strengthening women’s human capital. Further, the positive spillover effects and community contagion that encourages other households to encourage women’s participation in the labor force cannot be overstated (IMF, 2019). As the labor market evolves with the green transition, climate action and gender equity can also be developed together from the outset, in line with the World Bank’s Global Gender Strategy36. Support such as targeted subsidies to firms for on-the-job training or re-skilling, vouchers to pre-labor market entrants and new entrants for upskilling, unemployment support measures, safety net programs and pre-graduate education system skills programs can help new entrants to the labor market and pre-graduates at younger ages. For older workers with current “brown jobs”, early retirement policies and/or reskilling as climate-friendly self-employed or entrepreneurs might help tackle the bulk of labor market effects. Box 5.  Relevant examples of approaches to supporting gender equity in economic inclusion What works for vulnerable women’s economic inclusion is what works for most vulnerable groups: cohesive approaches. While there is a tendency to consider “gender interventions” or “women’s only” programs as discrete, surgical interventions to turn the tide, often the most effective approaches are holistic, including both men and women. Combining human and labor capital, financial resources, and socio-behavioral awareness-raising jointly build effectiveness. Measures work synergistically. As an illustration, Chile and Mexico are likely the only two countries worldwide whose female labor force participation was similar or lower than Türkiye’s in 2005 but that surpassed its levels by 2020–2022. Recent World Bank Global Gender Thematic Notes and other global reviews point to some factors. 1. Gender-Inclusive Fiscal Policies, Social Protection and Labor Programs, and Financial Inclusion: A global review181 highlights the role of ever-innovative, progressive tax policies that address specific constraints to women’s employment (such as low-wage earners and informal agricultural workers in Türkiye) and equitable social expenditure measures (adjusting pension benefits an retirement policies accordingly, spending on early childhood, active labor market programs and equitable parental benefits) can alleviate high binding constraints and disincentives for formal work among firms and workers. Importantly, for financial inclusion and access to credit, the review finds that alternative sources of collateral and new non-traditional ways of validating creditworthiness is key to otherwise high-potential, vulnerable women who lack assets or credit history. 2. Joint Behavioral and Financial Entrepreneurship Support: In Mexico, programs combining personal initiative training (risk-taking, leadership behavior, assertive and self-confidence) with traditional business training had stronger positive impacts on business outcomes than traditional 181 IMF (2022). IMF Strategy Towards Mainstreaming Gender–Background Paper. July 2022. Washington DC: International Monetary Fund. 130 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity training or finance alone (World Bank 2023/Ubfal based on LACGIL 2021)182. Of note, Mexico’s rate of women’s firm ownership is over double that of Turkiye’s, at over 26 percent versus 11, respectively185. A global review by Revenga and Dooley (2020)183 of over 50 programs from 27 countries supports the importance of bundled packages, particularly emphasizing networks: “Evidence suggests that training + relatively low-cost things such as mentorship are more effective than training alone, and that training + finance is more effective than training or finance alone. However, female entrepreneurs likely need further supporting interventions that tackle other barriers, such as market access or time constraints due to child/home responsibilities. We also may need interventions that encourage women to enter male dominated sectors, where firms seem to be more profitable.” While Turkiye has in place strong approaches for more highly educated women in larger urban, western provinces, expanding investments in central and southeastern provinces could be relevant. 3. Early Childhood Education Expansion: In Chile, reforms and measures that increased the duration of school hours and afterschool care at zero cost increased mothers’ labor force participation (World Bank 2023184 based on Contreras et al 2012; Berthelon et al 2015; Martinez and Perticara 2017). Chile has also had a steady pre-primary school enrolment rate 80–85 percent during 1990–2022, compared to Türkiye at 4–40 percent185. 4. Combining General and Women-Targeted Measures, Including Qualified Leadership Quotas: A global review finds that as gender inequity becomes more subtle and via indirect channels, measures that specifically target women and gender gaps will be needed (Shang/IMF 2022)186. For example, positive externalities of qualified gender quotas in political leadership include influencing girls’ career aspirations through role models (IMF 2022 based on Beaman and others, 2012; Pande and Ford, 2012). Male role models play an equally important role in encouraging choices. Source: World Bank staff authors. 182 Ubfal/World Bank (2023). What works in supporting women-led businesses? World Bank Gender Thematic Policy Note. Washington DC: World Bank. 183 Ravenga and Dooley/Brookings Institution (2020). What works for women microentrepreneurs? A meta-analysis of recent evaluations to support female entrepreneurship. Global Working Paper #142. Washington DC: Brookings Institution. 184 Halim, O’Sullivan, Sahay/World Bank (2023). Increasing female labor force participation. World Bank Gender Thematic Policy Note. Washington DC: World Bank. 185 World Development Indicators. 186 Shang/IMF (2022). Tackling Gender Inequality: Definitions, Trends, and Policy Designs. IMF Working Paper. WP/22/232. Washington DC: International Monetary Fund. https://www.elibrary.imf.org/view/ journals/001/2022/232/001.2022.issue-232-en.xml Outlook: Holistic Systems for Equitable Utilization 131 Table 11.  Ten achievements and frontier challenges to gender-inclusive human capital and jobs Pillar Foundational Advanced (i) HCI and NEET: High Women’s Human Capital (iii) Women’s Labor Force Participation and Informality: Index (0.66), HCI Gender Gap closed (−3%). Women’s LFPR has increased (23 to 33% in 15 yrs). Female NEET high, has halved in 15 yrs. Frontier: 30% more work in vulnerable informal Frontier: Female NEET still twice ECA average (32%). jobs than do men (37 vs 28%). MEX and CHL faster (23 to 45 and 42%, resp.). Constraints: Limited early career counseling, social perceptions. Constraints: Private sector stimulation for labor- versus capital-intensive job creation, associated (ii) ALMP Coverage and Effectiveness: Coverage of market failures (information asymmetry on job profile ALMPs (14% of registered unemployed, excluding needs, labor market coordination and matching informal workers) has been increasing over time with job seekers) and firm dynamics (economies of and vocational formal secondary education scale, productivity, green transition); adjustments coverage gender gap has closed. needed for enhancing labor regulation flexibility/ Capital Labor Frontier: ALMP enrollment among women contract types for informal workers, parental and remains 30 percent lower than men for OJT and social insurance benefits parity, sectoral barriers Vocational Courses, and occupational and sectoral (construction, mining)/spillovers. segregation persists in ALMP and job placement. (iv) Gender Wage and Occupational Gap: Higher Govt. spending on labor support modest (est. educated women’s share of jobs in industry well 1.0% GDP), but double coverage among highest advanced (17%), nearly on par with OECD. income quintile vs lowest. ALMP spending relatively low compared to high labor underutilization Frontier: Advanced skills on digital lacking OECD, rates notably in rural and peri-urban areas (youth and informally structured services and agriculture unemployment, women’s unemployment, low labor market widest gender gap (up to 50%) and lower force participation, high informality). wages than OECD average. Constraints: Financing to expand coverage, Constraints: Occupational perceptions, employer targeting, design (additional incentives), and bias, advanced skills levels (OJT). access to information and outreach. (v) Financial Inclusion: Women’s financial inclusion (vi) Entrepreneurship: Women Business and Law Index is (banking) doubled over 15 yrs to 63%. high on par with HIC and improving (score 83/100). Financial Capital Frontier: Still lower than men and women’s OECD Frontier: Women’s firm ownership still one-fourth avg. (98%). OECD avg (11 vs 40%, respectively). Constraints: Awareness, social perceptions, Constraints: Occupational perceptions, financial dedicated programs (financing and design). sector bias, networks, advanced skills levels (OJT). (vii) Role Perceptions: Highly favorable perceptions of (ix) Early Childhood Development Programs: ECD women’s work among certain regions and higher enrollment among younger than 5 years has education levels up to 90%. increased 4-fold over 15 yrs (10 to 40%). Govt. spending on ECD has modestly increased over Frontier: Little change over decade or age groups. decade (reaching 0.29% GDP). On avg. 1 out of 5 unfavorable. Lower average perceptions (70%) in central and southeastern Frontier: Enrollment and spending remains half regions) and among women vs men (78 vs 91%, of OECD. respectively), and less than secondary education. Constraints: Limited locally adaptable models, Capital Social Constraints: Information and social beliefs. financing, quality regulation. (viii) Time Use: Gender time use and roles on (x) Representation: Women’s senior leadership has household care (child, older care) vs employment increased modestly over 15 yrs (14 to 20%). shifting over decade modestly. Frontier: Wide regional variation (10 to 35%). Frontier: Household care by women remains up Constraints: Information and social beliefs. to 4 times time use of men, and higher than OECD gender gap. Constraints: Information, services, expectations. Source: World Bank staff authors in consultation with Government of Türkiye and stakeholders. 132 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Table 12.  Integrated human capital and jobs framework: ten measures for overall and gender equity Pillar Short-Term Long-Term (i) Develop Jobs Financing System at scale with (iii) Reform labor and social security policies to close gender equity targets, including: (a) jobs- inclusion and gender gaps for the most vulnerable, conditional MSME financing (credits/grants) specifically: (a) remove gender-based differences through MoLSS/İŞKUR- MOIT-KOSGEB and private in labor code policies such as hiring (ie. restrictions sector partnership (national development finance in construction, mining, other), (b) remove gender- institutions, Organizational Industrial Zones, based differences in social security policies Chambers of Commerce); (b) national labor (retirement age, duration of maternity and paternity market e-registry/geospatial tracking, targeting benefits); (c) introduce new independent workers and services platform, linking and adapting accounts with gradual subsidies for vulnerable MoLSS e-METIP (to broader profiles), İŞKUR informal workers, ensuring gender targeting and ALMPs (job matching, counseling, training), ISAS using existing e-Government system for payments; (MoFSS) and MOIT Enterprise Database as inter- (d) introduce greater coverage of flexible/part-time operable registry of firms and vulnerable workers; work including for the informal sector; (e) conduct (c) consolidation and targeting of existing in-depth labor and social security policy inclusion and Capital Labor multiple employment incentives/wage subsidies financial diagnostic with tri-partite social dialogue to (İŞKUR/SGK), expanding coverage to low- and inform these and other reforms. semi-skilled informal workers in low-employment, peri-urban and rural regions. (iv) Develop secondary schools’ school-to-work case management system targeting vulnerable girls and (ii) Develop performance-based financing and boys (low-income, rural and peri-urban) jointly with coverage at-scale for joint job training and private sector. Boost fiscal space and counseling employment services system with gender equity training to expand coverage of full-time school job targets: comprising private sector vocational counselors particularly for youth NEET and informal training (MoNE) and on-the-job training (MoLSS/ households. İŞKUR, linking MoNE Vocational Training-İŞKUR On the Job Programs. Expand eligibility to continuing/retraining for NEET and informal workers targeting high demand occupations and peri-urban and rural regions. (v) Develop targeted outreach and subsidies for (vi) Expand at-scale pre-entrepreneurship and self- expanding e-bank accounts and e-financial employment support system for the most vulnerable services equitably to vulnerable women and (low-income, youth, peri-urban and rural regions) men: Strengthen investments in financial literacy, with gender equity targets, including: MoLSS/ Financial accounts and nominal in-kind subsidies, digital İŞKUR-KOSGEB partnership to target high-value Capital payment accounts, and savings outreach through added private enterprises and social cooperatives, inter-Governmental partnerships (notably İŞKUR linked to e-registry platform above (i), including local bureaus and MoFSS social worker outreach, nascent İŞKUR entrepreneurship support scheme, joint with KOSGEB, Central Bank, other agencies). early creditworthiness counseling through mentor firms and entrepreneurship OJT, seed financing, and e-commerce platform for market access. (vii) Develop locally-adapted, early childhood (ix) Develop early childhood education accreditation/ education public-private delivery models with quality assurance system with performance- targeted financial household support: with based contracting. Ensure high quality assurance private sector and social cooperatives, unified systems and financing arrangements (public, private, quality assurance, performance-based subsidies cooperatives, or PPP providers) for expansion, to providers, and conditional cash transfers for introducing performance-based grants/subsidies. Capital Social vulnerable informal women working linked to ECE enrolment, with MoNE, MoFSS, municipalities. (x) Develop outreach on gender-inclusive civic representation and participation at local and (viii) Scale up outreach on occupational gender national levels: with MoFSS, MoNE, regional inclusion among households and youth: authorities, local community groups. with MoFSS, MoNE, regional authorities, local community groups. Source: World Bank staff authors in consultation with Government of Türkiye and stakeholders. Outlook: Holistic Systems for Equitable Utilization 133 Overall, Türkiye can push the frontiers of human capital utilization, jobs and inclusion through new systems-based approaches, which would equally support gender equity. The youthfulness of its populace and its well-established institutional foundations are among its most vital assets towards realizing this call. Institutions and policies, particularly a holistic jobs system buttressed by financial and social measures, can further expand gender-inclusive, quality jobs. Türkiye is ready to usher in a new era of broad-based growth that support vulnerable households and gender equity; how far it will go depends on how far and fast its policies can be adapted to simultaneously address holistic needs in the future. 134 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Annex Trends in World Bank Portfolio on Gender-Tagged Investment Projects Figure 82.  World Bank-financed project approvals tagged as gender-inclusive in Türkiye and global regions over time, 2017–2023. 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% FY18 FY19 FY20 FY21 FY22 FY23 East Asia and Pacific (EAP) Eastern and Southern Africa (AFE) Europe and Central Asia (ECA) Latin America and Caribbean (LCR) Middle East and North Africa (MNA) South Asia (SAR) Western and Central Africa (AFW) Türkiye Source: World Bank staff authors calculations using publicly-available data S. FY = fiscal year covering second half of preceding and first half of designated calendar year. Figure 83.  World Bank-financed project approvals tagged as gender-inclusive in Türkiye by theme, 2017–2023 Number of projects appoved Share with gender tag (%) 8 100% 7 6 75% 5 4 50% 3 2 25% 1 0 0% od n es . .. n ... bs rt nd er l.. d. io tio po d at ra iv jo la Fo an an at la W ct s tu & d uc an pu d tra ss de na an n an Ed Tr io po ne ex tra t, e ct re en nc ve & & e s, tu nm ilie ot iti n ic gy ul io t pr om pe es ric er ro rit al En om vi ,r on Ag ut ci En an ,n ec So ,c rb lth ro ce U ea ac an M H n Fi No. proj. w/o gender tag No. proj. w/ gender tag % of proj. w/ gender tag Source: World Bank staff authors calculations/Ruscuklu S. FY = fiscal year covering second half of preceding and first half of designated calendar year. Annex 135 Mapping of Selected Projects Supported by International Partners Table 13.  Summary of internationally financed jobs projects by target and type Classification By target group # % of No. Projects Budget US$ millions % of Budget Women-only 12 35% 469.5 3 37% 7% Quota 4 12% 658.9 52% Both Women/Men 18 53% 139.0 11% TOTAL 34 100% 1267.4 100% By type # % of No. Projects Budget US$ millions % of Budget Firms' Support 4 12% 861.2 68% Job Seeker Services 15 44% 263.3 21% Mixed (Firms+Job Seekers) 3 9% 81.8 6% Institutional Support 11 32% 61.2 5% TOTAL 34 100% 1267.4 100% Source: World Bank staff authors calculations based on published program documentation and Ministry of Labor and Social Security Directorate of European Union and Financial Assistance https://www.ikg.gov.tr/?lang=en 136 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Table 14.  Detailed description of internationally financed jobs projects Annex Type: Firms (F) Target: Budget (US$ or Job Seekers’ Women- equivalent, Employability only (W), Est. no. end- M; 1 euro = Ongoing Services (S), Quota (Q) beneficiaries/ $1.09, 25– Donor Partner Closing or Mixed (M), or or Both m/f National expected (if No. Project Name Jun–23) Institution Institution Date Closed Institutional (I) neutral (B) Agency PIU applicable) Türkiye Tarım Kredi Formal Employment European Kooperatifleri / 1 Support in Agricultural $51.2 Union&World Agricultural Credit 2024 O M Q ACC 7,600 Sector Project (FESAS) Bank Cooperative of Turkiye (ACC) Social Entrepreneurship EU&World Coalition 2 Community of Practice $3.3 Coalition (MoTrade) 2023 O M W 500 Bank (MoTrade) and Pilot (est. out of $5 M) Improving Job and Ministry of Labor European 3 Vocational Counselling $5.5 and Social Security 2023 O I B ISKUR Union Services Project (MoLSS) Labour Market Support European 4 $21.3 MoLSS 2024 O I B ISKUR Programme for NEETs Union İŞKUR–UNHCR Ministry of National 5 $10.9 UNHCR 2024 O I B ISKUR Cooperation Protocol Education (MoNE) Yes You Can: Socio- Emotional Skills for 6 $0.6 World Bank 2018 C I B ISKUR Higher Employability in Turkey Evaluation German German Federal Strengthening the International Ministry for Economic 7 Institutional Capacity $1.1 Cooperation Cooperation and 2019 C I B ISKUR of İŞKUR Project Organization Development (BMZ) (GIZ) Fund German United Nations Employment and Skills 8 $4.0 Development Development 2021 C I B ISKUR 9,000 Development Project Bank (KfW) Program (UNDP) Promoting Youth Employment in European 9 $19.1 2017 C S B ISKUR 36,300 Sectoral Investment Union Areas 137 138 Type: Firms (F) Target: Budget (US$ or Job Seekers’ Women- equivalent, Employability only (W), Est. no. end- M; 1 euro = Ongoing Services (S), Quota (Q) beneficiaries/ $1.09, 25– Donor Partner Closing or Mixed (M), or or Both m/f National expected (if No. Project Name Jun–23) Institution Institution Date Closed Institutional (I) neutral (B) Agency PIU applicable) German Education and International Employment Support Ankara Chamber of 10 $3.3 Cooperation 2018 C S B ISKUR 1,000 Project for Social Commerce Organization Adaptation (GiZ) Supporting Employment and Vice Presidency 11 Vocational Training for $0 I bu tama 2019 C S B ISKUR 3,300 Office Syrian Refugees and Host Communities Governments There is Hope in the UN World Food 12 $0.7 of South Korea 2021 C S B ISKUR 117 Kitchen Project Program and Norway Employment Support Project (İSDEP) (just European 13 closed but kept as O $49.5 Union&World MoLSS 2022 O S Q ISKUR 37,000 since ongoing with Bank phase II) Support for Transition European MoLSS and Turkish 14 to Labor Market $87.2 Union&World 2024 O S Q ISKUR 25,000 Red Crescent (TRC) Project (ISDEP II) Bank EU&European Finance and Advice Bank for 15 to Women in Business $41.4 Reconstruction 2017 C F W ISKUR 800 Programme and Development Supporting Women’s International Access to More Labour 16 $0.6 2022 O I W ISKUR 800 and Better Job Organization Opportunities Project (ILO) More and Better Jobs International Swedish International for Women: Women’s Labor Development 17 $3.4 2018 C S W ISKUR 1,200 Empowerment through Organization Cooperation Agency Decent Work in Turkey (ILO) (SIDA) Provision of Career Services through 18 Multi-Stakeholder $3.7 EU MoLSS 2017 C S B Local 1,500 Partnership Model (CAREER) Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Type: Firms (F) Target: Annex Budget (US$ or Job Seekers’ Women- equivalent, Employability only (W), Est. no. end- M; 1 euro = Ongoing Services (S), Quota (Q) beneficiaries/ $1.09, 25– Donor Partner Closing or Mixed (M), or or Both m/f National expected (if No. Project Name Jun–23) Institution Institution Date Closed Institutional (I) neutral (B) Agency PIU applicable) Technical Assistance for Garment Training 19 $3.2 EU MoLSS 2017 C S W Local 1,500 and Entrepreneurship Initiative (GATE) Empowering Women Ministry of Family 20 through Cooperatives $3.3 EU 2024 O S W MoFSS DGSW 12,000 and Social Services (WOMENCOOP) Increasing the Policy Making Capacity of Directorate General of 21 $1.8 EU MoLSS 2023 O I B MoLSS DGILF International Labour Force in the Field of Labour Migration An Integrated Model for the Elimination of the Worst Forms 22 of Child Labour in $27.3 ILO& MoLSS 2023 O S B MoLSS DGL 2,400 Seasonal Agriculture in Hazelnut Harvesting in Türkiye Promoting Decent Future of Work 23 Approach with a Focus $1.7 EU MoLSS 2023 O I W MoLSS DGL of Gender Equality (FoW) Improving Occupational Health MoLSS 24 and Safety Especially $19.2 EU MoLSS 2023 O F B 23,000 DGOHS in Mining Sector (OHSMS) Improving Occupational Health and Safety in Turkey MoLSS 25 $0 MoLSS 2017 C I B through compliance DGOHS with International Labour Standards Women in Business Programme (WiB), 26 $327.0 EBRD MoLSS 2017 C F W PFIs 17,571 linked to above EBRD EU-Govt Grant 139 140 Type: Firms (F) Target: Budget (US$ or Job Seekers’ Women- equivalent, Employability only (W), Est. no. end- M; 1 euro = Ongoing Services (S), Quota (Q) beneficiaries/ $1.09, 25– Donor Partner Closing or Mixed (M), or or Both m/f National expected (if No. Project Name Jun–23) Institution Institution Date Closed Institutional (I) neutral (B) Agency PIU applicable) Operation on Supporting Registered 27 $27.3 EU SGK 2024 O M W SGK 8,000 Women Employment (Women-Up) Promoting Registered Employment through 28 $13.8 EU MoLSS 2017 C I B SGK 14,600 Better Guidance and Inspection II Operation Supporting Registered Employment of Women 29 Through Home-Based EU MoLSS 2017 C S W SGK 26,532 Child Care Services (NANNY) Supporting Registered Employment of Women 30 through Promoting $26.2 EU SGK 2022 O S W SGK 12,972 Educated Child- Caregivers (EDU-CARE) Supporting Registered Employment of Women 31 through Institutional $32.6 EU SGK 2022 O S W SGK 17,959 Childcare Services (INST-CARE) Growing and Prospering the Entrepreneurship Ecosystem in Ankara 32 $2.7 EU MoLSS 2017 C F B tbc 530 to Increase Young Employment Operation (ECOSYSTEM) Promoting Youth Tigris Regional 33 Employment in TRC3 $4.1 EU MoLSS 2023 O S B Development 6,000 Region (PYETRC3) Agency (DiKA) Formal Employment World 34 $470.9 TKYB/MoTF F Q TKYB 3,000 Creation Project Bank&EU TOTAL $1,267.4 267,181 Source: World Bank staff authors compilation/Anil A. based on published program documentation and Ministry of Labor and Social Security Directorate of European Union and Financial Assistance https://www.ikg.gov.tr/?lang=en Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity E-Systems for Addressing Labor Market Vulnerability To strengthen Türkiye’s E-METIP system and expand its use for monitoring and addressing labor market vulnerabilities including those impacting gender equity, the following recommended steps can be taken, with accompanying detailed global examples: Step 1. Upgrading Real-Time Community-Data Collection and Monitoring Capacity Integration of the in-field data collection tool in combination with satellite imagery for real- time data collection, rapid, real-time needs and skills assessment of households in vulnerable areas, and risk management in challenging settings (World Bank GEMS / KoboToolbox). Geo-Enabling Initiative for Monitoring and Supervision (GEMS / KoboToolbox) The Geo-Enabling Initiative for Monitoring and Supervision (GEMS) is an initiative that aims to improve the Monitoring and Evaluation (M&E) of field activities while also increasing operation effectiveness on the ground via the use of digital data collection and analysis. This initiative has been implemented in over 100 countries and over 100 WBG projectsIt utilizes technology that is simple and ready-to-implement, which links low-tech approaches on the front end, such as digital questionnaires on mobile phones, with high-tech processes on the back end, such as automated data analytics and geospatial mapping. GEMS is based on the use of low-cost open-source technology, KoBoToolbox, smartphones, and the integration of geo-tagged field data. This data automatically feeds into a centralized M&E system to gain real-time insights on local dynamics. GEMS also provides support with advanced technology solutions, such as remote sensing through satellite imagery analysis for the development monitoring of environmental and social risks and safeguards. The system can support various types of surveying, such as household panel surveying for the Vulnerability Assessment, needs and eligibility assessment, and pre-enrollment for services in education, job employment, social protection, infrastructure, transport, and more. • The GEMS-trained PEQPESU project in the Democratic Republic of Congo (DRC) was able to create a detailed database and interactive map of over 25,000 secondary schools within just three months. This helped to geo-locate all secondary education facilities in the country and record detailed indicators of the individual schools. The database is now used to identify service delivery gaps, plan interventions, and coordinate across agencies. • Programs supported by the World Bank have adopted GEMS during the planning phase to leverage the tool for structured baseline data collection and ongoing M&E. The platform was used to record information from local enumerators on the state of infrastructure for displaced populations, determine the needs for host communities and plan sub-projects to support them. The baseline database contains detailed information on all proposed investments, including an evaluation of existing infrastructure, gap assessments, and cost estimates that allow for a structured follow-up in one integrated project platform. https://thedocs.worldbank.org/en/doc/4e1fb3d2785e13359d205ec6dd8dd194-0090082021/original/GEMS-Sector-Case​ -Studies-interactive-PDF.pdf Annex 141 Step 2. Detailing Information Collected on Labor Market Vulnerabilities and Profiling for Decision- and Policy-Making Processes Development of the comprehensive Vulnerability Welfare Assessment Index methodology (including Employment Resilience Assessment) and dataset (World Bank WelTrAC). World Bank Welfare Tracking in the Aftermath of Crisis (WelTrAC) Tool—Indonesia The World Bank has developed the Welfare Tracking in the Aftermath of Crisis (WelTrAC) tool to address the gaps in real-time, reliable data on the dynamics of welfare and living conditions of the population affected by the 2018 Central Sulawesi earthquake. The tool supports the government’s relief, recovery, and resilience-building efforts. The WelTrAC tool employs an interactive, detailed web-based monitoring dashboard to track impacts, household characteristics, coping mechanisms, and labor mobility, and to target responses. The tool uses a combination of panel household survey data and high-resolution remote-sensed satellite imagery data to measure the pace of physical reconstruction and the extent to which this may drive welfare recovery. The satellite data are used in sampling strategies to obtain a representative sample of households. The two-year household panel datasets of WelTrAC provide rich information, making it possible to analyze a wide range of short- and medium-term impacts of the disaster on the welfare and livelihoods of the affected populations. The datasets enable an assessment of the households’ welfare and employment resilience dynamics over time and enable targeted interventions on an individual level. Integrating an AI-powered tool into the M&E and case management system will help predict the risk of long-term unemployment or vulnerability at the micro and micro level and serve as a decision-support tool for administration and case workers (eg. EUIF OTT). AI-powered decision support tool (OTT) of the Estonian Unemployment Insurance Fund (EUIF) The Estonian Unemployment Insurance Fund (EUIF) has partnered with Nortal, a technology company, the Center of IT Impact Studies (CITIS), a strategic consulting company, and data analysis firm Resta to develop an AI-powered decision support tool (OTT) that predicts the risk of long- term unemployment. The tool utilizes over 100,000 client records to estimate the probabilities of different employment pathways, systematizes clients to provide support where it is most needed, and distributes the workload between civil servants. It calculates the probability of someone getting a new job and their level of risk of becoming unemployed again. The risk score is accompanied by information regarding the jobseeker’s strengths and weaknesses. The tool collects data from connected public registries and analyzes information from the last five years, including salaries from the Tax Office, education from the Board of Education, and subsidies from the Social Welfare Office. With the help of the tool, counselors can distinguish between low-risk and high-risk applicants, enabling them to focus on job seekers with the highest risk of prolonged unemployment. They 142 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity can use the data provided by the tool, along with their experience, to decide the frequency and channels of counseling and what kind of active labor market policy measures could be offered to the population. The calculations resulting from the OTT can also be applied to analyze how benefits, subsidies, and inclusion programs can affect movement to work or to analyze the mid-term and long- term effectiveness of the support provided. Step 3. Developing Robust Case Management Systems and Service Delivery for Holistically Addressing Labor Market and Social Vulnerabilities Implementation of the Case Management Information Systems (CMIS) software that supports all phases of case management services, simplifying case management for field and case workers for better delivery and monitoring of services and benefiting vulnerable population (World Bank Case Compass or CORE-MIS application). World Bank’s Social Protection & Jobs “Case Compass” Toolkit The Case Compass Toolkit enables the design of in-country Case Management Information Systems (CMIS), which is a digital platform that facilitates personalized interactions between social workers and beneficiaries of job and social protection programs, better serving vulnerable populations. A CMIS is a software that supports all phases of case management interventions, including processes that require repeated interactions between social workers and beneficiaries of social services. The World Bank Case Compass team provides advice to in-country decision-makers and software development teams on system design and implementation. The CMIS guide, prototyping tool, and learning materials are also available online. • In Colombia, the CMIS supports the case management program "Mi Familia" ("My Family"), which provides tailored psychological support to promote children’s and teenagers’ development and mitigate the risks of growing up in a violent, abusive, or negligent family environment. • In Italy, the GePI platform supports social workers in the case management of families enrolled in Italy’s guaranteed minimum income scheme, Reddito di Cittadinanza (RdC), or "Citizenship Income." • In Romania, Aurora, a CMIS for child protection, enables community workers to identify vulnerable children, assess the vulnerabilities of children and their families, manage cases and services provided, and monitor and integrate social workers’ and other community workers’ activities at the local level. • In Germany, VerBIS (Vermittlungs-, Beratungs- und Informationssystem), or "Placement, consultation, and information system," was developed as a CMIS for case management and in- depth case management of persons capable of work eligible for the Basic Income Support for Jobseekers benefit. Annex 143 CORE-MIS application to support cash transfer and economic inclusion programs The World Bank Core Management Information System (CORE-MIS) is a user-friendly, web-based application developed with free and open-source tools that support cash transfer and economic inclusion programs. The tool can be quickly adapted and deployed to deliver social protection programs and is currently being piloted in low-income African countries affected by COVID-19. CORE- MIS is easily modifiable and has 15 operational modules, including integration with KoboToolbox. It is interoperable with other systems and social registries and can be used in supporting conditional and unconditional cash transfers and economic inclusion programs such as public works programs, training programs, saving groups, communication campaigns, and grievance redressal mechanisms. The system supports targeting, registration, assessment and enrollment as well as the provision of services, payment management and program monitoring and management. • In Zambia, CORE-MIS was customized for the COVID-19 Emergency Cash Transfer program, introducing an app for the registration of potential beneficiaries, a data cleaning module, a payment management module, integration with the Zambian Integrated Social Protection Information System Payment System, modifications to the GRM module, integration of CORE- MIS with the PayPoint Manager App, and a direct link to the GEWEL payment gateway for digital payments. • In Nepal the Social Security Fund launched an accident and disability insurance scheme for formal sector workers, using the OpenMIS software for claims management, review, and reporting. The system was customized to ensure interoperability with the in-house beneficiary and payment management system. • Recently, the World Bank, the Federal Ministry for Economic Cooperation and Development (BMZ), and the Swiss Agency for Development and Cooperation (SDC) announced an integrated new open-source software package to manage social protection and health financing schemes in low- and middle-income countries. The new software combines the OpenMIS initiative with the World Bank’s digital platform CORE-MIS and is available at no cost to governments. Step 4: Consolidating Service Delivery Into a Single Point of User Contact (One-Stop Shop) for Efficiency of Organizational Processes, Resources and Beneficiary Engagement Introduction of the Digital Family-Job Card as a single point of interaction between government agencies to support the vulnerable population in areas such as education, jobs and social protection, finance, justice, and medical and social support (eg. Kazakhstan or India). 144 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Digital Family Card in Kazakhstan The Digital Family Card pilot was launched in 2022 and is implemented by the United Nations Development Programme (UNDP) in partnership with the Ministry of Labour and Social Protection of the Population of the Republic of Kazakhstan, the Ministry of Digital Development, Innovation and Aerospace Industry of the Republic of Kazakhstan and with financial support from the UN COVID-19 Response and Recovery Multi-Partner Trust Fund. It covers the entire territory of Kazakhstan, including 17 regions and 3 metropolises, namely Almaty, Astana, and Shymkent. The Digital Family Card is a platform for interaction between government agencies to support the population in areas such as education and social protection, finance, justice, and medical and social support. It helps identify families from vulnerable groups and assesses their needs comprehensively to provide them with socioeconomic support. In the first phase of the Digital Family Card implementation, all 5.9 million families in Kazakhstan were digitized to assess the well-being of each family. An in-depth analysis of the areas of health, education, social protection, employment, finance, justice, and agriculture was carried out based on government data sources for each family. The assessment is based on five criteria: economic conditions, healthcare, housing conditions, educational attainment, and social conditions. A total of 80 socioeconomic indicators are included in the family vulnerability assessment, including employment for each family member, real estate and commercial property, persons with disabilities in the family, bank loans and debts, and other indicators. The findings enabled the development and automation of the Family Well-being Assessment Methodology, which helps calculate scores for each family in Kazakhstan cities, regions, districts, and villages to identify the risk zone for each family. The data on the well-being of all families in the country is updated daily with the Digital Family Card. After receiving the data from the family vulnerability assessment, the Digital Family Card automatically initiates state support measures, identifies the responsible public authority, and provides the service in a proactive mode through e-gov. The Digital Family Card also provides a mobile app for social workers, which reduces the time needed to organize cases and process information and allows for greater efficiency, transparency, and monitoring of services to the population. The app is available in Kazakh and Russian in online and offline modes and has been piloted in Astana city to replace the use of paper documentation, increase transparency and reduce the time it takes to organize files and process information. https://www.undp.org/kazakhstan/stories/digitalisation-sustainable-development-and-social-well​-being-society Annex 145 India: registration in the national rural Employment Guarantee Scheme TThe Employment Guarantee Scheme is available to all rural households in areas designated by the central government. All adult members of the household who register are eligible to apply for work. Registrants must be local residents, willing to do unskilled manual work and apply as a household at the local program office. An individual may appear personally and make an oral request for registration. A door-to-door survey may also be conducted to identify persons willing to register. To provide maximum opportunities for families that may migrate, registration is open throughout the year. After verification, each registered household receives a job card that contains relevant information about the household, including its registration number, the age and gender of each member, employment details, and a photo. An annual updating exercise is conducted in the same manner as registration, taking into account the work and migration season of the local workforce. https://documents1.worldbank.org/curated/en/752071490779842532/pdf/113832-WP-HowtoComplete​-PUBLIC-Pdfs.pdf 146 Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity Türkiye at the Frontier: Human Capital Utilization, Jobs and Equity TECHNICAL DIAGNOSTIC