PANAMA FROM GROWTH TO PROSPERITY POVERTY AND EQUITY ASSESSMENT 2024 PANAMA FROM GROWTH TO PROSPERITY POVERTY AND EQUITY ASSESSMENT 2024 © [2024] International Bank for Reconstruction and Development/World Bank 1818 H Street NW, Washington, D.C. 20433 Telephone: (202) 473-1000 Internet: www.worldbank.org This document is a product of World Bank staff, with external collaborations. The findings, interpretations, and conclusions expressed herein do not neces- sarily reflect the opinions of the World Bank, its Executive Directors, or the governments they represent. The World Bank does not warrant the accuracy, completeness, or validity of the information included in this work and does not assume responsibility for any errors, omissions, or discrepancies in the information herein, or any lia- bility with respect to the use of or failure to use the information, methods, processes, or conclusions set forth. 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Design and Layout Manthra Comunicación · info@manthra.ec Acknowledgments This report benefited from inputs and comments from public, private, academic, and civil institutions, and other multilateral agencies in Panama. We would like to especially thank all the representatives of the Ministry of Economy and Finance (MEF) and the National Institute of Statistics and Census (INEC), for the special attention given to this report, access to data, particularly to Hernán Arboleda, Director of Socio-Economic Analysis of the MEF, Julio Diéguez, Head of the Information and Statistical Analysis Department of the MEF, Samuel Moreno, Director of the INEC and Hilda Martínez, Deputy Director of Sociodemographics of the INEC, for responding to our repeated queries and the clarifications provided on statistical, social, economic, and public policy issues. We would also especially like to thank the participants of the two poverty mapping workshops, held in 2024 between January 22nd and January 26th and between April 22nd and April 24th. The poverty maps that were produced in these workshops have been a valuable input for this report. The report has benefited from a continuous consultation process with different organizations, specifically during the World Bank missions from July 23rd to 28th, 2023, from January 22nd to 26th, 2024 and from April 22nd to 24th, 2024. We are very grateful for the contributions and inputs that guided and contributed to this report made by MEF, INEC, and the following institutions: Ministry of Environment (MiAmbiente), Ministry of Social Development (MIDES), Ministry of Education (MEDUCA), Ministry of Government (MINGOB), Ministry of Women, Ministry of Labor (MITRADEL), Micro, Small and Medium Enterprise Authority (AMPYME), National Institute for Vocational Training and Capacity Building for Human Development (INADEH), Institute for the Training and Utilization of Human Resources (IFARHU), Specialized Technical Institute (ITSE), National Competitiveness Center (CNC), National Council of Private Enterprise (CONEP), University of Panama, Technological University of Panama, Inter-American Development Bank, and the United Nations System in Panama. The team was led by Javier Romero (Economist), under the direction and guidance of Carlos Felipe Jaramillo (Regional Vice President), Michel Kerf (Country Director), Joelle Dehasse (Country Manager), Óscar Calvo González (Regional Director), Carlos Rodríguez Castelán (Practice Manager), and Pedro Rodríguez (Program Leader). Core team members in alphabetical order include Kiyomi E. Cadena (Consultant), Sofía Collante Zárate (Consultant), Angela Rocío López Sánchez (Consultant), Ramiro Alberto Málaga (Consultant), and Catherine Rodríguez Orgales (Consultant). The team is grateful for the valuable contributions of Meilyn Gem (Operations Officer) and Janibeth Miranda (Senior External Relations Officer). i We would like to thank the members of the World Bank Group’s Global Practices. Sector-spe- cific knowledge, input, contributions, and guidance were provided by the following experts, in alphabetical order: Ana I. Aguilera (Senior Social Development Specialist), Gabriela Alonso Mendieta (Consultant), Mauricio Amaya (Consultant), Marina Bassi (Program Leader, HLCDR), Ricardo Benzecry (Consultant), Adriana Camacho (Consultant), Luis Aníbal Cano de Urquidi (Senior Operations Officer), Cornelia Mirela Catuneanu (Operations Analyst), Lelys Ileana Di- narte Díaz (Research Economist), Luis Rolando Durán (Senior Disaster Risk Management Spe- cialist), Karlene Collette Francis (Senior Operations Officer), María Elena García Mora (Senior Social Development Specialist), Leah Arabella Germer (Agriculture Specialist), Úrsula Martínez (Social Protection Specialist), Elena Mora López (Agriculture Analyst), Harry Edmund Moroz (Senior Social Protection and Employment Economist), Joel E. Reyes (Senior Education, Human Development, Specialist), Ignacio Rodríguez (Consultant), Federica Secci (Senior Health Spe- cialist), Katharina Siegmann (Senior Environment Specialist), Cornelia M. Tesliuc (Senior Social Protection Specialist), María Victoria Traverso (Agriculture Analyst), Hulya Ulku (Senior Econo- mist), David Vilar (Program Leader, Infrastructure), and Mariana Viollaz (Consultant). The team would like to thank the reviewers Javier Báez (Lead Economist, EAEPV), Gabriela Inchauste (Lead Economist, EAWPV), and Mónica Yánez (Senior Economist, HSAED) for their comments and suggestions. In addition, Gustavo Javier Canavire (Senior Economist, Poverty and Equity), María Dávalos (Senior Economist, Poverty and Equity), Jacobus Joost De Hoop (Senior Economist, Poverty and Equity), Samuel Freije-Rodriguez (Lead Economist, Poverty and Equity), Gabriel Lara Ibarra (Senior Economist, Poverty and Equity), Hugo Rolando Ñopo (Senior Economist, Poverty and Equity), and Eliana Carolina Rubiano (Senior Economist, Poverty and Equity) provided useful comments during the production of this report. The team is very grateful to Jonathan Alexander Bello Sangronis (Team Assistant, LCCPA), Fran- cisco David Gómez Sánchez (Team Assistant, LCCPA), Ana Carolina Leguizamo (Program As- sistant), and Sara Esther Paredes Ponce (Senior Executive Assistant) for their assistance in the production of the report. Finally, the team would like to thank the administrative support staff in the Panama Coun- try Office for making all the necessary arrangements for the extensive series of face-to-face mission meetings that informed this report and for providing critical administrative support throughout the process. ii Table of Contents Acknowledgments i Table of Contents iii Abbreviations and acronyms vii The report, in a nutshell viii EXECUTIVE SUMMARY 1 Panama: Rapid growth, Significant Poverty Reduction, and Widespread Inequality 1 What explains recent progress in poverty reduction in Panama? 2 What are the barriers to greater equity and poverty reduction? 3 1. Lagging populations lack adequate income-generating capacities 3 2. The labor market does not foster equity 4 3. Low and unequal human capital limits equity gains 5 4. Natural hazards threaten the progress achieved among the most disadvantaged 6 Policy Priorities: 7 Pillar I: Promoting the Closing of Territorial and Ethnic Gaps 7 Pillar II: Promoting the Accumulation of Human Capital and Productive Job Creation 8 Pillar III: Promoting Household Resilience to Natural Hazards 9 PANAMA: FROM GROWTH TO PROSPERITY 10 1. Gains and Challenges Related to Poverty and Equity 11 1.1 High Growth and Significant Poverty Reduction, but High and Persistent Inequality 11 Vertical Inequalities 16 Horizontal Inequalities: Territorial, Ethnic, and Gender 18 2.Factors Behind Recent Gains and Challenges 23 2.1 Drivers of Poverty Reduction 23 2.2 The poorest segment of the population lacks income-generating capacity 29 2.3 Despite improvements, the labor market remains unequal 31 Barriers to a More Equitable Labor Market 34 2.4 Gaps and inequalities in education and health persist despite progress 44 Barriers to Human Capital Accumulation 54 2.5 Progress Achieved Is at Risk: Vulnerability to Poverty and Natural Hazards 57 The poor and non-poor are equally exposed to natural hazards 57 iii 3. Tools to Reduce Poverty and Inequality 63 Pillar I: Promote the Closing of Territorial and Ethnic Gapss 63 Pillar II: Promote the Accumulation of Human Capital and Growth of Productive Jobs 66 Pillar III: Promote Household Resilience to Natural Hazards 71 REFERENCES 73 APPENDIX 78 Appendix 1: Additional Figures 79 Appendix 2: Additional Tables 86 Appendix 3: Additional Boxes 88 Appendix 4: Methodological Notes 95 FIGURES Figure ES1. While Panama’s poverty rates are low from international standards ... 1 Figure ES2 . … the country continues to face widespread inequality. 2 Figure 1. Per capita Income Convergence in Latin America and the United States. 13 Figure 2. Panama has experienced a significant reduction of poverty and expansion of the middle class. 13 Figure 3. Not everyone has benefited equally from growth, and the poverty gap between urban areas and comarcas has widened. 14 Figure 4. Gini Coefficient in Latin America, 2008 and 2019. 14 Figure 5. While growth in Panama has been pro-poor, it has been insufficient to significalty reduce inequality. 17 Figure 6. Panama exhibits considerable income variation between households within provinces. 17 Figure 7. Asset-Based Framework for the Top and Bottom 20% of the Distribution, 2023. 18 Figure 8. Map of Moderate Poverty by Corregimiento and Population Center, 2022. 19 Figure 9. Monetary Poverty and Non-Monetary Welfare Indicators. 21 Figure 10. Role of Rural-Urban Population Shifts in Poverty Reduction, 2008–2023. 24 Figure 11. Educational Level of Internal Migrants by Ethnicity (%), 2023. 25 Figure 12. Changes in Poverty According to Household Income Source by Area, 2008–2023. 27 Figure 13. Sectoral Effects on Rural Poverty Reduction, 2008–2023. 29 Figure 14. Labor Market Indicators, 2001–2023. 32 Figure 15. Inequality in Labor and Household Income per Capita, 2008—2023. 33 Figure 16. Labor Market Structure, 2023. 34 Figure 17. Job Quality Index, LAC, 2008–2021. 36 Figure 18. Job Quality Index by Population Group, 2023. 36 iv Figure 19. Employment by Subsector, 2023. 37 Figure 20. Employment by Company Size, 2023. 37 Figure 21. Relative Productivity and Employed Population Ratio by Subsector, 2021. 39 Figure 22. Labor Productivity by Company Size, 2011–2018. 40 Figure 23 Labor Market Rigidity Index vs. Informality, 2019. 41 Figure 24. Returns to Education. 44 Figure 25. HCI, Basic HCI, and Complete HCI. 45 Figure 26. HCI, 2010–2020. 46 Figure 27. Attendance at Any Educational Institution by Grade and Age. 47 Figure 28. Attendance at Any Educational Institution by Population Group (4-5 years and 18-24 years). 47 Figure 29. Share of Students Above Minimum Level by Subject. 49 Figure 30. Share of Students Above Minimum Level in Mathematics by Student Characteristic. 49 Figure 31. Main Activities of People Aged 18–24 by Socioeconomic Characteristic. 50 Figure 32. Share of People with Some Form of Tertiary Education by Age. 51 Figure 33. Stunting in Children Aged 0–4 by Population Groups and Health Region. 53 Figure 34. Teenage Pregnancy and Motherhood among Women Aged 15–24 by Socioeconomic Characteristic. 53 Figure 35. Women’s Activities By Adolescent Maternity (Aged 18–24). 57 Figure 36. Poverty- and Risk-Induced Vulnerability. 58 Figure 37. Pluvial Flooding with a 20-Year Return Period Under the SSP-3 7.0 Scenario (Panama City). 60 Figure 38. Pluvial Flooding with a 100-Year Return Period Under the SSP-3 7.0 Scenario (Panama City). 61 Figure 39. Percentage of Poor and Non-Poor Affected by River, Pluvial, and Coastal Flooding. 61 Figure 40. Share of People Living in Moderate Poverty and Coverage by Social Program. 62 TABLES Table 1. Lack of productive assets and unequal access to labor markets and basic services hamper poverty reduction efforts. 30 vi Abbreviations and acronyms AD Afro-descendant AG Ángel Guardián AMPYME Micro, Small and Medium Enterprise Authority CCKP Climate Change Knowledge Portal CSS Social Security Administration, Caja de Seguro Social HCI Human Capital Index HIC High-income country HOI Human Opportunity Index ICT Information and communication technologies National Institute for Vocational Training and Capacity Building for Human INADEH Development INEC National Institute of Statistics and Census IP Indigenous population ITSE Specialized Technical Institute LAC Latin America and the Caribbean LPG Liquefied petroleum gas MEF Ministry of Economy and Finance MIC Middle-income country MINGOB Ministry of Government MITRADEL Ministry of Women, Ministry of Labor MPI Multidimensional Poverty Index MSME Micro, small, and medium-sized enterprise NEET Not in employment, education, or training OECD Organisation for Economic Co-operation and Development OLS Ordinary least squares Social Assistance Program for Universal Education, Programa de Asistencia PASE-U Social Educativa Universal PISA Program for International Student Assessment PPP Purchasing Power Parity RdO Red de Oportunidades STEM Science, technology, engineering, and mathematics WAP Working-age population WDI World Development Indicators vii The report, in a nutshell Panama has achieved significant poverty reduction, but it remains one of the most unequal countries in the world. Economic inequality and poverty pockets in Panama stem from disparities across ethnic, territorial, employment, human capi- tal, and resilience dimensions. Panama must focus on the drivers of inequality and poverty, addres- sing urgent deprivations in the short term while promoting structu- ral changes in the medium and long term to address poverty and high inequality. viii Executive Summary Panama: Rapid growth, Significant Poverty Reduction, and Widespread Inequality Panama has been one of the fastest-growing countries in the region, with rapid economic expansion accompanied by significant poverty reduction. Driven by public and private investment as well as labor accumulation, the Panamanian economy grew by an annual average of 5.7 percent between 1990 and 2023, much higher than the regional average of 2.5 percent. This growth contributed to a significant reduction in poverty. Using the poverty line of US$6.85 per day per capita (2017 PPP), the share of Panamanians affected by poverty improved from one in two in 19891 to only one in ten in 2023 (Figure ES1). Figure ES1. Figure ES1. Panama's poverty rates are low in international comparison. While Panama’s poverty rates are low from international standards 100 80 Percentage of the population in poverty ($6.85/day 2017PPP) 60 40 LAC Panama 20 0 HIC MYS MDV RUS CHL BGR URY UKR SRB TUR BTN LCA KAZ ARG MNE THA PAN MUS ALB GRD JAM CRI MDA BOL TUN UZB SUR MKD VNM PRY PSE DOM TON MEX IRN MNG BRA CHN LAC SLV ECU GAB MHL PER XKX COL LKA HND CPV ARM FJI PHL GEO NAM IDN KGZ BWA MRT MMR EGY KIR LAO BGD SEN CMR VUT CIV AGO SWZ DJI GHA STP GMB LSO BEN IND ZWE MLI GIN TGO BFA TCD LBR GNB SLE NGA ETH UGA KEN RWA TZA ZMB SYR MOZ CAF NER SSD BDI MWI COD TJK PAK Source: WDI. Note: Figures include 95 countries. Latest available data range between 2015 and 2022. High-income countries are not included, except for those in LAC: Chile, Panama, and Uruguay. 1 Due to data availability and for purposes of international comparison, the report uses the international poverty line of US$6.85 per day per person (2017 PPP) and the SEDLAC harmonized income aggregate, unless otherwise specified. Aggregate trends are similar when national definitions are used. See the methodological appendix for more information. 1 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figure ES2. Figure ES2. the country continues …widespread But faces to face widespread inequality. inequality. 70 60 Panama LAC 50 40 Gini coefficient 30 20 10 0 NAM COL SWZ BRA ZMB AGO PAN MOZ ZWE LAC HND CRI ECU PRY LSO COD TUR SSD GRD RWA LCA GHA MEX CAF CHL UGA CPV CMR DJI BOL ARG MYS PHL STP URY TZA PER JAM SUR SLV GMB LAO KEN MWI GAB IDN TGO LKA BDI BFA TCD CHN DOM MUS SEN VNM RUS MLI SLE MHL CIV LBR NGA ETH THA IRN BEN GEO TUN PSE MKD BGD GNB NER IND VUT MRT EGY MNG UZB FJI MMR GIN KAZ XKX KGZ BTN ARM KIR TON SYR MDA UKR TJK PAK Source: WDI. Note: Figures include 95 countries. Latest available data range between 2015 and 2022. High-income countries are not included, except for those in LAC: Chile, Panama, and Uruguay. Nevertheless, Panama remains one of the most unequal countries in the world. While poverty in urban areas was 4.8 percent in 2023, poverty in indigenous regions (comarcas) reached 76 percent—15 times higher2. Limited progress in reducing inequality, as measured by the Gini coefficient, contrasts with Panama’s achievements in other areas. Globally, Panama ranked 11th in inequality in 2000, with a Gini coefficient of 53.83. Two decades later, it ranked 8th, with a Gini coefficient of 50.9 as of 2022 (Figure ES2). This report examines Panama’s achievements and challenges in reducing poverty and inequality to inform policy options. With a special focus on the 2008–2023 period4, the report documents progress in poverty and equity in recent decades, highlighting access to basic services, expansion of quality jobs, improvement of human capital, and promotion of household resilience as critical policy priorities. What explains recent progress in poverty reduction in Panama? Poverty reduction between 2008 and 2023 was largely driven by rural areas. Nationally, poverty decreased from 23.2 percent in 2008 to 12.9 percent in 2023. Urban poverty fell from 10.3 percent in 2008 to nearly 5 percent in 2015, primarily due to gains in labor income before the 2 This report uses the term comarcas for indigenous territories at the provincial level of Emberá-Wounaan, Guna Yala, and Ngäbe-Buglé. 3 The 2000 ranking includes 79 countries for which data are available between 2000 and 2005. 4 The 2008–2023 period covers the longest series of income poverty measurements with the income aggregate being strictly comparable. 2 economic slowdown of the mid-2010s. Since then, urban poverty has largely plateaued. In turn, rural poverty decreased from 46.5 percent to 32.3 percent between 2008 and 2023. However, within rural areas, indigenous comarcas5 lagged behind (with poverty rates around 85 percent until the mid-2010s), poverty reduction in these areas started to accelerate, remaining at very high level of 76 percent in 2023. Although the labor market played an important role, most of the reduction in rural poverty was due to social protection programs. New social protection programs, such as Red de Oportunidades (RdO), and non-contributory pensions were important for poverty reduction through the early 2010s. Given the lack of labor market dynamism in rural areas, migration to urban centers also contributed to poverty alleviation efforts, accounting for 22 percent of national poverty reduction. Subsequently, labor income in rural areas became the main driver of poverty reduction due increased agricultural income because of government support, a rise in coffee production, and public investment projects—mainly in the comarcas—which generated income and employment in other sectors. However, with the completion of these projects and the COVID-19 crisis, these labor improvements proved fragile, leaving rural poverty in 2023 at 2017 levels. Panama has also seen significant growth in its middle class, but persistent inequalities remain. The middle class (defined as the population with an income of between US$14 and US$81 per day per person in 2017 PPP) increased from 45.7 percent in 2008 to 59.9 percent in 2023. This surpasses regional progress, positioning Panama as the country with the third-largest middle class in Latin America and the Caribbean (LAC), behind only Uruguay and Chile. Yet, inequality has remained persistent, with the Gini index declining more slowly than in many other countries in the region during the same period. What are the barriers to greater equity and poverty reduction? 1. Lagging populations lack adequate income-generating capacities Poverty in Panama is highly concentrated in rural areas and comarcas. Nearly three out of four people in poverty live in rural areas, with comarcas—home to only 6.6 percent of the country’s population—accounting for 39 percent of the country’s poor. Despite comarcas having abundant natural resources (land and forests), their potential remains underdeveloped. These areas have lower levels of productive assets (e.g., human, physical, and financial capital), limited access to basic services, and poor market connectivity. The country’s poor population faces multiple barriers to generating quality income. Labor market conditions are especially unequal: workers in the poorest 20 percent earn US$1.2 per hour (2017 PPP), barely 11 percent of the earnings of workers in the richest 20 percent. 5 Rural areas include both comarcas and other rural areas. 3 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 This disparity is due to various factors. The poorest 20 percent have an average of seven years of schooling, half as many as the richest 20 percent. Access to basic services such as electricity, water, and sanitation is almost universal among the richest households, while around a quarter of the poorest households lack access to these services. Furthermore, households in the lowest income quintile do not have adequate access to roads and the Internet, hindering their connectivity to high-quality markets and jobs. Conditions are even more precarious in comarcas, with access to basic services lagging behind other rural areas by about a decade. Although educational achievement among heads of household in comarcas increased from 3.4 years of schooling in 2001 to 6.3 years in 2023, it is still only half of what it was in urban areas two decades ago. Significant socioeconomic gaps also exist in the broader population. Indigenous groups fare worse across well-being indicators, not only in comarcas but also in other urban and rural areas. Additionally, women face disadvantages, including high rates of teenage pregnancy, which limited educational attainment and labor market participation. The country has also seen a recent surge in migrants in transit, representing further challenges. 2. The labor market does not foster equity. While labor income has increased, informality remains high. Labor income increased by an average of 2.2 percent per year between 2001 and 2023, but the share of formal employment, measured by contributions to the Social Security Administration (Caja de Seguro Social, CSS) remained near the 2005 level at around 55 percent in 2023. Job quality has declined over the last decade, particularly among low-income households6. As of 2023, the poorest 40 percent of the population had high rates of informal employment (82 percent), self-employment (45.3 percent), and employment in the primary sector (36.6 percent), compared to the richest 60 percent (44.4 percent, 25.5 percent and 7 percent, respectively). Indigenous and unskilled workers are more likely to earn lower incomes and have informal employment, and women participate in the labor force at a rate one-third lower than that of men. Labor market conditions and challenges facing micro, small, and medium-sized enterprises (MSMEs) hinder progress on closing labor productivity gaps. Panama has considerable productivity disparities between sectors, along with low reallocation of workers between them, higher than those of countries with similar incomes and the regional average. Additionally, formal economic activity is heavily concentrated in the Trans-Isthmian region7. MSMEs, which employ 80 percent of workers in the poorest 40 percent the population, suffer from productivity levels that are low and have remained relatively unchanged in recent years. These businesses face barriers to growth, including precarious conditions for innovation and entrepreneurship, insufficient access to private financing, and insufficient credit access (World Bank 2023). Furthermore, distortions in the Panamanian labor market, one of the most rigid in the region, could constrain the efficient reallocation of labor. For example, strict dismissal procedures for 6 Job quality refers to the Job Quality Index, which incorporates the following dimensions: income, access to employment benefits, job security, and sat- isfaction of workers (Brummund et al., 2016). 7 The Trans-Isthmian region comprises the provinces of Panama, Colón, and Panama Oeste and accounts for 58 percent of the population, 85 percent of the GDP, and 78 percent of private jobs in formal companies. 4 workers (Barreto et al. 2024) and a complex system of up to 96 minimum wages not linked to productivity hinder flexibility (OECD 2018). Panama faces the added challenge of creating high-quality jobs amid demographic pressures and global trends. The working age population (WAP) is growing faster than the regional average and is expected to peak in 2069, 26 years later than the regional average. To meet labor demand, Panama’s economy will must grow at 5 percent annually (World Bank 2024a). In addition, the country will have to adapt its workforce to mitigate the potential impact of new technologies and green sector trends, which currently benefit more qualified workers, on inequality (Winkler et al. 2024). In the last decade, Panama has seen minimal growth in non- routine jobs, which are less susceptible to automation, and 76 percent of jobs are not classified as green, despite the country’s efforts to promote sustainability. 3. Low and unequal human capital limits equity gains. Panama’s systemic challenges in low human capital exacerbate existing labor productivity issues. The Human Capital Index (HCI), which measures the labor productivity of future generations, indicates significant challenges for Panama8. The country’s HCI has worsened over the past decade, remains low and uneven relative to its income level, and suggests that productivity will reach only half its potential, representing a 50 percent cost in future income (World Bank 2024). This is mainly due to low coverage for certain groups and insufficient education quality. Despite doubling the average years of school over the past five decades, Panama has lagged behind other countries, and the quality of education is inadequate, with only 16 percent of secondary students proficient in mathematics and fewer than half able to comprehend an age- appropriate text (PISA 2022). These issues are more pronounced among rural and indigenous populations, people with disabilities, and households with poorly educated heads of household. In addition, Panama faces challenges related to child and reproductive health, high rates of stunted growth among children aged five and younger, and high levels of adolescent fertility. There is ample room to improve the provision of basic health and education services. Despite recent increases in government spending, resources are used inefficiently. In education, the targeting of programs is ineffective, there is a shortage of secondary schools in rural areas and comarcas, and access to and use of information and communication technologies (ICT) is low nationwide (Lopez 2021; PISA 2022). The teaching profession attracts students with very low academic skills, and there is no competency framework or teacher performance assessments (Cruz-Aguayu et al. 2020). In the health sector, the country faces challenges in primary care, with non-universal, inequitable, and fragmented access, resource allocation based on historical budgets, and inefficient procurement and use of medications (Gutierrez et al. 2023; Secci et al. 2024). 8 The index measures the amount of human capital that children born today could attain by the age of 18, considering the risks and opportunities to education and health in the country in which they reside. The index, therefore, reflects productivity potential compared to a scenario in which all edu- cational and health opportunities are provided. 5 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Higher education also offers limited prospects as a pathway to quality jobs. First, attendance levels are low. According to the Censo de Población y Vivienda 2023, only 35 percent of 18–24-year-olds attend tertiary education institutions, lower than an average of 52 percent in LAC and over 80 percent in Europe and the U.S., and only about 20 percent of Panamanians earn a higher education degree. Second, careers have adapted little over time, a potential indication of a mismatch between labor demand and educational offerings. Only 4 percent of adult graduates hold technical degrees, and the share of individuals with science, technology, engineering, and mathematics (STEM) careers has remained low and constant since 1960, at around 7 percent for women and 20 percent for men. Finally, men tend to join the labor force early, limiting their educational achievements, while women stay longer in school. However, one-third of women aged 24 and under are neither studying nor working (not in employment, education, or training [NEETs]), and this rate is higher for women in rural areas, indigenous women, and teenage mothers. Limited data on the coverage and quality of tertiary education is another challenge facing the sector (Reisberg 2021). 4. Natural hazards threaten the progress achieved among the most disadvantaged. While Panamanian households have seen improvements in their well-being, their conditions remain fragile. In 2022, nearly one in three Panamanians were vulnerable to poverty, an indication that these households either live in or could fall into poverty in the short term9. Vulnerability to poverty varies significantly across the country, with rates as high as 96.9 percent in indigenous comarcas, and is concentrated in the provinces of Panama and Panama Oeste (representing one-third of the vulnerable population) due to population size, underscoring the fragility of urban areas. Panama’s high exposure to natural hazards and climate change adds to household fragility. The country ranks 14th 10 globally in terms of exposure to multiple natural hazards, with 15 percent of its territory and 12.5 percent of its population exposed to two or more hazards11. Floods are the most common threat, and climate change is expected to double their frequency by mid- century. Other hydrometeorological risks include droughts, strong winds, and indirect impacts of tropical cyclones. Households vulnerable to poverty are particularly susceptible to natural hazards given their limited resilience. Both poor and non-poor households face similar exposure to flooding, but poor households, which rely more on climate-dependent sectors like agriculture, have less capacity to recover. For example, in 2022, 8.8 percent of poor households with agricultural income reported being affected by natural hazards, mainly floods, compared to only 4.9 percent of non-poor households with agricultural income. Poor households often lack the assets to effectively respond to shocks, and the limited coverage of adaptive social protection programs (main programs do not reach 27.6 percent of the poor population) remains a major challenge. 9 Defined as a probability greater than 50 percent in the next two years, using the definition of national poverty. 10 EM-DAT: International Disaster Database (www.emdat.be). 11 World Bank’s Climate Change Knowledge Portal: https://climateknowledgeportal.worldbank.org/country/panama/vulnerability: 6 Policy Priorities: Based on Panama’s sustainable growth and its macroeconomic fundamentals, it would be necessary to outline policy priorities to reduce poverty and inequality. The country has established the necessary conditions for continued economic growth, such as a stable and reliable macroeconomic policy framework and low levels of debt and inflation (World Bank 2023). However, the country’s challenge is not only to sustain its economic growth but also to ensure growth benefits the populations most in need. Inclusive growth is key to combating poverty, reducing inequality, and promoting social stability, which, in turn, creates a more favorable environment for investment and development that benefits the entire country. Pillar I: Promoting the Closing of Territorial and Ethnic Gaps A territorial development strategy could be implemented based on local plans to expand access to basic services and infrastructure. This strategy should promote efforts to increase access to resilient basic infrastructure, such as water, sanitation, electricity, and rural roads, while strengthening the capacity of subnational governments to plan and manage infrastructure and the provision of key services, including in indigenous comarcas. This territorial strategy should also promote economic activities to boost productivity and income in rural areas and comarcas. Generating economic opportunities by attracting investment could increase agricultural productivity and foster new activities based on the sustainable exploitation of natural capital, such as ecotourism and cultural tourism. This would require meeting various sector needs such as improving the country’s infrastructure, ensuring access to appropriate technology, fostering sustainable practices, and implementing training and technical support programs. It is essential to strengthen and expand social assistance programs and improve the data available for decision-making in social sectors to protect high-risk groups in the short term. The authorities need to improve the coverage, targeting, and adequacy of social assistance programs. A significant share of social benefits goes to households in the middle- and high- income quintiles. Innovations in this report, such as the Poverty Map 2022, can facilitate the targeting of programs and investments in underserved areas. Additionally, it is necessary to ensure that stakeholders have a systematic understanding of the redistributive effects of subsidies, programs, and taxes in Panama, along with potential reforms. An important step toward this goal is to increase the transparency of official data and methodologies for measuring poverty and other well-being indicators. 7 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Pillar II: Promoting the Accumulation of Human Capital and Productive Job Creation The level and trend of Panama’s HCI highlights the need to strengthen human capital in the country. The authorities need to improve the coverage and quality of education and health services nationwide, with a special emphasis on rural and indigenous populations as well as households with low levels of educational achievement. In the education sector, short-term priorities include optimizing programs that encourage school attendance and reduce dropout rates, designing remedial programs, and promoting the effective use of ICT, while long-term priorities include continuing to invest in infrastructure in rural areas and comarcas as well as improving the entire teaching profession. In tertiary education, priorities include conducting a study of the country’s labor demands, which would be used to strengthen technical and technological programs that aim to increase labor productivity; implementing programs designed for NEET youth; and certifying existing programs to ensure the quality of the future labor force. In the health sector, the authorities need to reduce inequalities in access to basic services in rural areas and comarcas, and they need to strengthen primary care. The use of telemedicine may reduce some of these gaps in access. Finally, to promote the productive participation of women and young mothers, Panama needs to create early childcare programs and ensure the implementation of the recently approved guidelines on Education in Sexuality and Affectivity. There is a need to promote continuing education and improve skills. Short-term priorities include conducting an impact assessment of implemented active labor policies, while medium-term priorities include strengthening continuing education programs nationwide and promoting training in sector-specific skills (e.g., agriculture). It is also important to identify economic sectors where technology adoption can help people upgrade their skills, increasing economic inclusion and ensuring the economy can adapt to new market demands. Panama also needs to strengthen MSMEs and address knowledge gaps. There is limited recent information on the characteristics of labor demand and the barriers faced by MSMEs. It is important to acquire the relevant data and identify reforms to fill these gaps12. Available data suggest that promoting innovation, entrepreneurship, access to credit and private financing, formalization, and access to physical and digital infrastructure could strengthen the MSME sector, which employs most of the country’s low-income workers (World Bank 2023). Short- term priorities include evaluating and improving programs such as those offered by AMPYME and strengthening the institutional framework of the national innovation system (World Bank 2023). Finally, regulatory changes in the labor market could benefit both workers and businesses. The country could benefit from a systematic review of labor policies, especially those that impose a high administrative cost on dismissal and hiring processes for formal workers. Reviewing and simplifying the minimum wage matrix in short-to-medium term could reduce disincentives to formalization. A review of policies on the retirement age and parental leave could also encourage women’s labor market participation. 12 The Economic Census 2025 and business surveys that will be conducted based on the new sampling frame represent an opportunity to inform sec- tor-specific policies. 8 Pillar III: Promoting Household Resilience to Natural Hazards Given the increase in the frequency of natural hazards, it is vital for Panama to promote household resilience. Exposure depends on the type of hazard: Panama and Panama Oeste are vulnerable to pluvial flooding; Bocas del Toro, Darién, and Chiriquí are especially affected by fluvial flooding; and people living comarcas and Bocas del Toro are vulnerable to coastal flooding. Short-term policy priorities include identifying vulnerable people and communities by geographic location, socioeconomic status, intersectionality (e.g., gender, ethnicity, and disability), and resilience and adaptation capacity, while a medium-term priority is to create an adaptive social protection policy to ensure an effective response to disasters. Potential medium-to-long-term policy priorities include relocating populations to safe areas and investing in resilient critical infrastructure, especially in rural areas, where households are especially vulnerable to the impact of disasters. 9 Panama: From Growth to Prosperity 1.1 High Growth and Significant Poverty Reduction, but High and Persistent Inequality 1. Over the past three decades, Panama has accelerated economic growth, which has driven a significant increase Gains and in job creation and poverty reduction. The country’s GDP per capita increased from 25.7 percent of the level of the United States in 1990 to 48.6 percent in Challenges 2023, resulting in Panama leading the convergence of per capita income in Latin America and the Caribbean (LAC) (Figure 1). Panama’s GDP growth, which Related to Poverty averaged 5.7 percent between 1990 and 2023, has led to significant job creation, and Equity with the labor force participation rate rising from 48 percent to 62 percent over the past three decades. In turn, the poverty rate13 fell from 50.2 percent in 1989 to 12.9 percent in 2023, while the share of vulnerable households declined as the middle class expanded (Figure 2). Currently, almost 60 percent of the Panamanian population is considered middle class, one of the largest proportions in the region, only below that of Uruguay and Chile. The country’s economic model is based on expanding capital- and labor- intensive sectors. The model has been based on sectors that require a high level of investment and job creation, but technology and skills development has been limited. Panama has solidified its 13 The analysis uses international definitions of poverty (poverty line and income aggregate), unless otherwise stated. A person is considered poor if household per capita income is less than US$6.85 per day (2017 PPP). The appendix includes more de- tails on the poverty methodology. 11 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 position as a logistics and commercial hub, and it has emerged as an important financial center thanks to its geographical position around the Panama Canal and continuous investments in infrastructure (World Bank 2023). High rates of private and public investment have driven both existing and emerging sectors14. In recent decades, construction and services have been the main growth drivers, transforming the structure of the labor market15. Between 1989 and 2019, the construction sector’s contribution to GDP increased from 1 percent to 18 percent, and the share of construction jobs increased from 3.1 percent to 8.9 percent of total employment. Commerce and services16 have accounted for most employment growth, increasing from 14.4 percent to 23.4 percent of total employment in the same period. Rapid growth in construction and services has benefited low-income households, with the share of agriculture declining from 29.6 percent in 1989 to 15.7 percent in 201917. Economic growth started to decelerate in the mid-2010s, before collapsing with the COVID-19 crisis. Panama’s economy began to slow down prior to 2019, in part due to the completion of mega infrastructure projects and lower investment flows18. The economy was severely affected by the pandemic (with GDP contracting by 17.8 percent, year-on-year, in 2020), with the labor market and labor conditions reaching their lowest levels during the COVID-19 crisis. Informality and unemployment rates reached their highest levels in 2020 (52.8 percent and 18.5 percent, respectively)19, and labor markets have not yet recovered to their pre-pandemic levels. The economic slowdown was concentrated in regions and sectors that had previously driven growth. For example, employment growth in the construction sector declined from an average of 7 percent in 2008–2012 to 0.6 percent between 2013 and 2019 (World Bank 2023). While poverty has reached low levels in urban areas, it remains extremely high in comarcas20, with poverty and basic service access rates comparable to those of low-income economies. Poverty reduction has been rapid in urban areas, falling from 32.0 percent in 1989 to 4.8 percent in 2023 (Figure 2). Poverty reduction in the comarcas began to accelerate in the years preceding the pandemic, but poverty levels in these areas remain extremely high, at 76 percent in 2023. Despite recent progress, the gap between comarcas and urban areas has increased. Comarcas were 3.6 times poorer than urban areas in 2001, but this had increased to 15 times by 2023. Moreover, the level of access to basic services in comarcas are well below the national average, as only 50.6 percent have access to electricity, 51.0 percent have access to drinking water, and 52.9 percent have access to sanitation—similar to levels observed in low-income economies. 14 In the 2014–2019 period, private investment totaled 41.1 percent of GDP, with foreign direct investment flows at 8.3 percent of GDP. High rates of private investment drove the growth of commerce, finance, real estate, and port and logistics activities. Public investment averaged 7.4 percent in 2008–2019, driven by megaprojects such as the expansion of the Panama Canal and Tocumen Airport (World Bank 2023). 15 To avoid distortions caused by the COVID-19 crisis, some sections of this report excludes 2020 from the long-term trend and instead focus on 1990 to 2019. 16 The commerce sector includes retail and wholesale commerce, while the service sector includes consumer services related to restaurants, hotels, and repairs. 17 The transition from agriculture to other sectors was not reflected in the comarcas, where the population is still almost exclusively dedicated to agricul- ture. 18 Foreign direct investment flows fell from 10 percent of GDP in 2014 to 6 percent in 2019, and foreign investment in the transport and financial sectors also declined (World Bank 2023). 19 Encuesta de Mercado Laboral Telefónica 2020. 20 Since 1972, the Panamanian government has established comarcas, delimited regions in which indigenous peoples hold exclusive land rights and have considerable administrative autonomy. For the purposes of this report and based on the availability of data from Panama household surveys, this report uses the term comarcas to refer to the provincial-level territories of Emberá-Wounaan, Guna Yala, and Ngäbe-Buglé. 12 Figure 1 Figure 1. Per capita income convergence in Latin American countries compared to the United States. Per capita Income Convergence in Latin America and the United States. 50 PIB per capita/US PIB per capita)*100 40 30 20 10 PAN URY CHL ARG CRI DOM MEX COL BRA PER ECU GTM SLV BOL 1990 2023 Source: WDI. Figure 2.2 Figure Panama has experienced a significant reduction of poverty and expansion of the middle class. 100% 90% 80% Percentage of the population 70% 60% 50% 40% 30% 20% 10% 0% 1989 2000 2010 2017 2018 2019 2021 2023 LAC 2021 Poor US$6.85 Vulnerable US$6.85-$14 Middle Class US$14-$81 Rich + US$81 Source: CEDLAS and World Bank. Note: Since 2008, imputed rents have been included in the household income aggregate, which makes it not strictly comparable with the previous series. 13 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figure 3 Figure 3. Not everyone has Not everyone has benefited benefited equally equally from the from growth, growth. and the poverty gap between urban areas and The difference in poverty comarcas has widened. between urban areas and comarcas has increased. 100 90 80 Percentage of the population in poverty 70 ($6.85/day 2017PPP) 60 50 40 30 20 10 0 1989 1991 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008* 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2021 2023 Years National Rural Urban Comarca Source: CEDLAS and the World Bank. Note: Since 2008, imputed rents are included in the household income aggregate for Panama. Figure 4 Gini coefficient in Latin American countries, 2008 and 2019. Figure 4. Gini Coefficient in Latin America, 2008 and 2019. 60 50 40 Gini index 30 20 10 0 BRA COL LAC PAN HND CRI CHL ECU PRY MEX DOM BOL PER URY SLV circa 2019 circa 2008 Source: LAC Equity Lab. Note: Data are presented up to 2019 to avoid the distortion caused by the COVID-19 crisis in 2020. 14 Over the past 15 years, Panama has continued to reduce poverty. The poverty rate almost halved from 23.2 percent in 2008 to 12.9 percent in 2023 (Figure 3). Poverty reduction in urban areas accelerated in the early 2010s, with urban poverty reaching its lowest point of around 5 percent in 2016, where it has remained since. In rural areas, poverty steadily decreased from 46.5 percent in 2008 to 28.2 percent in 2019. In comarcas, poverty reduction began to accelerate in 2015, falling from 76.5 percent in 2008 to 64.9 percent in 2019. Progress has also been made in non-monetary terms: Panama has reduced multidimensional poverty, as measured by the Multidimensional Poverty Index (MPI-5)21, from 26.1 percent in 2010 to 14.1 percent in 2023, largely due to rural electrification and improved school attendance. However, recent progress in rural areas and comarcas has been threatened by the pandemic. While urban poverty has returned to pre-pandemic levels, rural areas have not recovered as well, with rural poverty increasing from 28.2 percent in 2019 to 32.3 percent in 2023. In comarcas, poverty increased by 6 percentage points over the same period. The COVID-19 pandemic exposed existing vulnerabilities, which had already been evident in the years leading up to the pandemic. Although the living conditions of people in poverty improved between 2008 and 2023, they still lag far behind those of the non-poor population (Table A1). In particular, labor market conditions remain highly unequal. Despite pro-poor growth, Panama remains one of the most unequal countries in the world. Between 2008 and 2019, inequality in Panama decreased by 2.9 Gini points (from 52.7 to 49.8), a rate slightly higher than the regional average decrease of 2.4 Gini points but below that observed in some other countries (Figure 4)22. This reduction in inequality was driven by pro-poor growth: per capita income growth among households in the poorest 40 percent of the income distribution was 4.7 percent per year between 2008 and 2019, while it was 3.9 percent for the richest 60 percent during the same period. However, the income of the poorest deciles would need to grow further to see a considerable reduction in inequality23. One reason for the limited reduction in inequality, despite pro-poor growth, is the large initial disparity in total household per capita income (Figure 5). In 2008, income in the richest decile was 13 times higher than in the poorest. Another contributing factor is that while labor income grew across all income groups (at 3.9 percent annually), the richest households derive a large share of their income from work (51 percent of the income in the poorest decile comes from work, compared to 70 percent in the richest decile). Reducing inequality is essential to achieving sustainable economic growth. A more inclusive society where people have equal opportunities fosters economic development and social stability. In Panama, there are large disparities within groups (vertical inequalities) as well 21 For this report, a Multidimensional Poverty Index (MPI-5) has been calculated using the Censo de Población y Vivienda 2010 and 2023, following the Alkire-Foster methodology (2011). The MPI-5 follows the same non-monetary indicators proposed by the World Bank for the construction of a non-mon- etary poverty measure and comprises five deprivations: (i) educational attainment, (ii) school attendance, (iii) electricity, (iv) sanitation, and (v) drinking water. The MPI-5 is not intended to replace the official MPI; rather, it provides an alternative measure to track progress over time. Several indicators of the official MPI, such as access to drinking water, cannot be measured prior to 2015 using EPM data, making it challenging to analyze them over time. 22 The trend is shown up to 2019 to avoid the distortion caused by the COVID-19 crisis. While inequality decreased further after the pandemic (reaching 48.9 Gini points in 2023), this was the result of a worsening situation of households in the highest deciles. 23 Despite pro-poor growth, income growth rates in the poorest and richest deciles are relatively similar. For example, between 2008 and 2019, in Bolivia, income growth among the poorest 40 percent was 5.5 percent per year, compared to 2.8 percent for the richest 60 percent, which was reflected in a remarkable decline in the Gini coefficient from 50.8 in 2008 to 41.6 in 2019. 15 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 as between groups (horizontal inequalities). Differentiating between these two types of inequalities is valuable for policy design, as each type requires different tools and approaches. Vertical Inequalities Lncome inequality in Panama is largely driven by disparities within provinces, although inequalities between provinces are also significant. The dispersion of household income per capita in Panama is among the highest in LAC. Income at the 90th percentile is almost 11 times higher than at the 10th percentile, highlighting deep territorial and ethnic disparities. The province of Panama has the highest income dispersion in the country (Figure 6). However, differences between provinces and regions are also considerable. For example, the level of household income per capita in the 90th percentile in comarcas (about US$400 in 2017 PPP) is much lower than the national average (US$917 in 2017 PPP). Large disparities in productive assets, unequal access to labor markets and basic services, greater exposure to risk, and limited social support constrain the ability of poor households to generate income. This report uses the asset-based approach24 to identify key constraints and opportunities for reducing poverty and inequality in Panama. Workers in the poorest 20 percent of the income distribution have an average of 7 years of completed schooling, while the richest 20 percent have twice that amount (Figure 7). Access to basic services, such as electricity, water, and sanitation, is almost universal among the richest households, but among the poorest households, 27 percent lack access to drinking water, 17 percent lack access to sanitation, and 15 percent lack access to electricity. Furthermore, households in the lowest income quintile have lower access to quality roads25 and the Internet, limiting their connectivity to markets and quality jobs. Consequently, the poorest 20 percent face higher rates of labor informality, and their labor income is almost seven times lower than that of the richest quintile. Although social protection programs have played an important role in reducing poverty in Panama, their coverage and adequacy remain low. The poorest households are also more vulnerable to climatic events. In 2022, 10 percent of households in the poorest quintile reported being affected by some climatic event, much higher than only 4 percent of the richest households. 24 zThis section follows an asset-based framework, which provides evidence on the different elements that boost or deter households’ income-generating capacity and ultimately their economic development. The main factors are the ability of households to generate income based on the assets they own (including human capital, financial and physical assets, and social capital) and how much they can earn from the assets they own. Transfers can provide a cushion, although they are less sustainable. High prices can erode the value of households’ income or increase the value of their assets. Further- more, external shocks can affect any or all components of a household’s income-generating capacity. Appendix 3 includes more information on the asset-based framework. 25 According to the household survey (EPM), a road can be rated as good, regular, or bad depending on the rainy or dry season. 16 Figure 5 Figure 5. Growth in Panama has been pro-poor, but not sufficient. While growth in Panama has been pro-poor, it has been insufficient Growth Incidence Curve, 2008-2019. to significalty reduce inequality. Total household income per capita (2017 PPP) 6 3.000 5 2.500 Annualized growth (%) 4 2.000 3 1.500 2 1.000 1 500 0 0 1 2 3 4 5 6 7 8 9 10 Household income per capita decile Total household income per capital in 2008 Labor income growth Total household income per capita growth Source: CEDLAS and the World Bank. Figure 6 Figure 6. Panama exhibits considerable variation in the income between households within the provinces. Panama exhibits considerable income variation between households within provinces. 2,500 2,199 Total household income per capita (2017 PPP) 2,000 1,876 1,810 1,673 1,673 1,576 1,538 1,435 1,500 1,320 1,284 1,093 1,000 993 917 885 830 749 782 760 756 685 566 608 650 622 600 550 500 527 518 492 367 384 267 337 282 272 290 287 220 203 160 173 173 173 162 170 133 143 128 129 90 88 56 0 National Panama Los Santos Herrera Chiriquí Coclé Colón Veraguas Bocas del Toro Darién C. Emberá C. Guna Yala C. Ngäbe Buglé 10th Percentile Mean 90th Percentile Median Source: CEDLAS and the World Bank. 17 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figure 7 a Figure Asset-based 7. framework for the top and bottom 20% of the distribution, 2023. Asset-Based Accumulation Framework of productive for the Top and Bottom 20% of the Income Distribution, 2023 assets 16 100 14 90 12 80 70 10 Years 60 % 8 50 6 40 30 4 20 2 10 0 0 Years of Water Sanitation Internet Electricity Quality roads education Bottom 20% Top20% Source: EML 2023 and EPM 2022. Note: Coverage of public transfers includes the Red de Oportunidades, 120 a las 65, Ángel Guardián and Bono Familiar para Alimentos (SENAPAN) programs. Horizontal Inequalities: Territorial, Ethnic, and Gender Panama exhibits significant territorial disparities in poverty levels26. To estimate poverty with high of geographic precision, the World Bank, in collaboration with the National Institute of Statistics and Censuses (INEC) and the Ministry of Economy and Finance (MEF), has developed the 2022 Poverty Map at the corregimiento level, based on the official poverty definition and national poverty lines (Box 1)27. Poverty rates vary widely across Panama. The least poor corregimiento is San Francisco in Panama City (0.05 percent), while the poorest is Krüa in the Ngäbe Buglé comarca (98 percent). The provinces of Panama and Colón have corregimientos with the lowest rates of moderate poverty, while the Emberá, Guna Yala, and Ngäbe Buglé comarcas have corregimientos with the highest rates (Figure 8a). Aside from the high concentration of poverty in comarcas, there is significant variation within provinces. For example, the province of Colón has districts with high poverty, such as Donoso (63 percent), and low poverty, such as Colón (17 percent). Despite the high concentration of poverty in rural areas and comarcas, one in four people living in poverty resides in urban areas. Due to its population size, the province of Panama has the second-largest number of people living in poverty (about 70,000), following the Ngäbe- Buglé comarca (about 189,000) (Figure 8b). Furthermore, while urban areas generally have lower poverty levels, significant disparities exist within them. For example, within Panama City, districts such as Curundú and El Chorrillo are notable poverty pockets compared to surrounding corregimientos (Figure 8c). 26 Panama is made up of 13 provinces, which are comprised of 82 districts (2023) that in turn are divided into 699 corregimientos. 27 The 2022 Poverty Map estimates poverty at the level of the corregimiento using moderate poverty lines (B/.112.54 in rural areas and B/.148.01 in urban areas) and extreme poverty lines (B/.62.40 in rural areas and B/.73.22 in urban areas). In 2022, at the national level, moderate and extreme poverty was 22.17 percent and 9.36 percent, respectively. 18 Box 1. Poverty Maps 2022 and Small Area Estimation Method Panama’s household surveys, such as Encuesta de Propósitos Múltiples 2022 (EPM 2022), provide representative estimates of provincial areas, urban areas, rural areas, and the urban parts of the city of Colón and Panama City. However, these surveys do not allow for poverty estimates of corregimientos or districts, which represents an obstacle to properly designing poverty reduction programs, improving the provision of public services in lagging areas, and improving resource allocation. In a joint effort between the World Bank, the National Institute of Statistics and Censuses (INEC), and the Ministry of Economy and Finance (MEF), moderate and extreme poverty levels were estimated using official poverty lines at the corregimiento and district levels, drawing on data from the Censo de Población y Vivienda 2023 and the Encuesta de Propósitos Múltiples 2022. The small area estimation method combines survey and census data to estimate poverty rates in areas where the survey sample size is insufficient. Regression models are used to relate a welfare variable (income or consumption) to auxiliary covariates available in both the survey and the census. Figure 8. Map of Moderate Poverty by Corregimiento and Population Center, 2022. a. Map of Moderate Poverty by Corregimiento, 2022 19 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 b. Number of Poor People and Poverty Rate by Corregimiento c. Panama City: Poverty at the Population Center Level in the Districts of Panama and San Miguelito Source: Censo de Población y Vivienda 2023; Encuesta de Propósitos Múltiples 2022. The IP in Panama face significant disadvantages, not only in comarcas but also in urban and other rural areas. According to the Censo de Población y Vivienda 2023, 17.2 percent of the Panamanian population (697,139 people) identify as indigenous, of whom 36 percent reside in comarcas, 31 percent in other rural areas, and 33 percent in urban areas. Indigenous people’s situation in comarcas is worse than in other areas. Poverty in comarcas increased from 69.4 percent in 2019 to an alarming 76.0 percent in 2023. Additionally, comarcas have 20 the worst average indicators in education and basic services, such as access to drinking water, sanitation, and electricity (Figure 9a). Market connectivity is also limited, with 78.8 percent and 34.6 percent of households lacking access to roads and the Internet, respectively. Indigenous peoples living in urban areas also face significant privations compared to Afro- descendant (AD), non-indigenous, and non-Afro-descendant (Non-IP-AD) populations. For example, the poverty rate for indigenous people living in urban areas is 14.8 percent, almost 4 times the aggregate urban poverty rate. Moreover, 29 percent of indigenous people in urban areas lack access to sanitation services at home, and one in four does not have access to drinking water (Figure 9b). By contrast, ADs have poverty rates and access to services levels comparable to Non-IP-ADs (Box A1 in the appendix). Figure 9. Monetary 9 and Non-Monetary Welfare Indicators Poverty Figure Monetary poverty and non-monetary welfare indicators. a. Rural areas b. Urban areas Poor Poor US $6.85* US $6.85* 76,0 100 40 80 No access No No access No 30 to roads water 60 to roads water 54,6 78,8 20 40 10 20 0 0 House hold No head with No House hold sanitation no education sanitation head with 44,0 50,8 no education No No No No electricity 51,9 34,6 internet electricity internet Rural IP Rural No-AD-IP Urban IP Urban No-IP-AD Urban AD Rural AD Comarca Source: EPM 2022 and EML 2023. Note: IP = indigenous population; AD = Afro-descendant population; Non-IP-AD = non-indigenous and non-Afro population. According to the Human Opportunity Index (HOI), access to basic services in Panama remains unequal, with ethnicity, area of residence, and parents’ education being the main determinants. The HOI, a measure that adjusts services access based individual circumstances, reveals improvements in access to basic services (i.e., electricity, sanitation, and secondary school enrollment) in Panama between 2015 and 2022, yet access varies significantly28. The Dissimilarity Index (D-Index) shows that the ethnicity of the household head and the place where a child lives (rural or urban) are the primary factors explaining unequal access to basic services such as 28 The HOI is an equity-adjusted access measure that captures the extent to which access would need to be reallocated among different groups for each to have equal access. For more details on the concepts and methodology of the HOI, see Paes de Barros et al. (2009). 21 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 electricity, water, and sanitation29. Limited access to opportunities during childhood is closely linked to outcomes in previous generations, perpetuating low intergenerational mobility. These findings underscore the unique challenges faced by Panama’s IP, whose poverty rate is almost 6 times higher than the rest of the population, with almost half of this gap unexplained by observable characteristics30. Women in Panama, particularly indigenous women, face disparities in access to resources, economic opportunities, and agency, exacerbating their exclusion. In comarcas, women have, on average, fewer years of education (5.1 years compared to 6.7 years for men) and less health insurance coverage (5.1 percent compared to 6.2 percent for men) than men. This contrasts with women nationally, who have better access to resources than men. Indigenous women also earn the lowest hourly wages, a mere 30 percent of the average wage for men, and nearly three in ten indigenous women are unpaid workers. Additionally, Panama has one of the highest teenage pregnancy rates in the region, with 69.9 births per 1,000 women aged 15–19, much higher than the average of 43.7 in LAC and 15.4 in high-income countries. Early motherhood can negatively affect education and economic opportunities, with 59 percent of teenage mothers neither studying nor working, perpetuating the cycle of poverty across generations (Figure A1). Panama is also grappling with an unprecedented increase in migrants in transit, posing challenges for both migrants and the IP along migration routes. In 2023, 525,085 migrants crossed the Darién region, and flows are expected to increase, as 109,069 people crossed in the first quarter of 2024 alone31. Conditions at crossing points are extremely precarious and dangerous, with migrants lacking shelter, information, food, medical care, and basic services. Many migrants, particularly women, face physical and sexual violence—41 percent of migrant women report having suffered gender violence while on transit routes (World Bank 2023a). Indigenous comarcas, already burdened by high poverty rates, are among the communities receiving migratory flows32. The lack of an effective state response to the challenges posed by migration has resulted in environmental degradation (e.g., river and soil contamination), the spread of preventable tropical diseases, increased violence, and displacement of children from schools. 29 The D-Index measures whether opportunities (e.g., access to services) are allocated equitably by comparing the probability of access under different circumstances. 30 When comparing an indigenous person with a non-indigenous person in Panama -with the same demographic and geographic characteristics, and with similar level of education and employment-, the indigenous person is more likely to be poor, suggesting the existence of structural barriers facing the indigenous population. 31 Ministry of Public Security of Panama. 32 For example, the poverty rate in the corregimientos of Lajas Blancas, Carreto, and Bajo Chiquito (where the main migratory flow points are located) are 79.8 percent, 84.8 percent, and 72.1 percent, respectively. 22 2.1 Drivers of Poverty Reduction Over the past three decades, Panama’s 2. remarkable economic growth and job creation have resulted in significant poverty reduction, although progress varies between urban and rural areas. Almost half of the reduction in poverty between 1989 and 2023 can be attributed Factors to increases in the employed population (19 percent of the reduction)33 and labor income (28 percent of the reduction). Before 2008, the rising share of employed Behind Recent adults was the primary driver of poverty reduction, reflecting consistent growth in Gains and Challenges the employment rate. However, after 2008, labor income and social transfers played a greater role, with variations depending on the urban or rural area. This section examines poverty reduction dynamics between 2008 and 2023 by analyzing: (i) poverty reduction in rural and urban areas and the role of internal migration; (ii) sources of income contributing to poverty reduction; and (iii) factors driving recent growth in rural areas. Between 2008 and 2023, both rural and urban areas experienced significant reductions in poverty, with rural areas playing a more prominent role. At the national level, poverty decreased from 23.2 percent to 12.9 percent during this period34. Urban poverty fell from 10.3 percent in 2008 to nearly 5 percent in 33 Based on the analysis of changes in poverty by income source, following the Shapley methodology proposed by Azevedo et al. (2012), according to Paes de Barros et al. (2006). 34 The analysis of changes in poverty resulting from growth and redistribution (based on the methodology proposed by Datt and Ravallion [1992]) finds that economic growth has been the main driver of poverty reduction, accounting for 69 percent of total poverty reduction. 23 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 2015, primarily driven by gains in labor income prior to the economic slowdown in the mid-2010s. Since then, urban poverty has remained at this level. Meanwhile, rural poverty decreased from 46.5 percent to 32.3 percent over the same period, contributing nearly half of the total poverty reduction in the last 15 years. By comparison, one-third of poverty reduction at the national level is attributable to decreases in urban poverty (Figure 10). Internal migration from rural to urban areas has contributed to poverty reduction, although its impact has diminished over time. Between 2008 and 2023, internal migration accounted for around 22 percent of poverty reduction at the national level35. The share of the population residing in urban areas increased from 62.4 percent in 2001 to 70.5 percent in 2023. According to the 2023 Census, 33 percent of the Panamanian population (1.3 million) lived in a town different from their place of birth, with many moving to the province of Panama or Panama Oeste. Within this group, 14.8 percent migrated from rural areas (198,839 people) and 9.4 percent were indigenous (126,414 people)36. Figure 10 Figure 10. The role of rural-urban population shifts in poverty reduction, 2008-2023. Role of Rural-Urban Population Shifts in Poverty Reduction, 2008–2023 2 0 -2 Changes in poverty -4 -6 -8 -10 -12 2008-2015 2015-2019 2019-2023 2008-2023 Migration effect Interaction effect Rural Urban Source: Own calculations based on the EML. Note: The interaction effect captures the joint effect of population shifts and differences in the speed of poverty reduction between urban and rural areas (for further methodological description, see Ravallion and Huppi (1991). 35 The change in poverty decomposition follows the methodology proposed by Ravallion and Huppi (1991). This technique provides insights into what extent changes in poverty are due to economic growth in urban and rural areas, as well as to changes in the population (migration). This decomposition captures only the direct effect of the transfer of people from rural to urban areas, and not the potential role of migration through remittances from migrants to their places of origin, for which other types of decompositions are used. 36 Migration of the indigenous population has repercussions on the loss of language and traditions. 24 11.11 Figure Figure Educational level Educational Level of internal of Internal migrants Migrants by ethnicity, by Ethnicity (%), 2023 percentage, 2023. 50 40 30 20 10 0 No edu No edu No edu Ter Ter Ter Pri Pri Pri Sec Sec Sec Indigenous population Afro-descendant No Indigenous Non Afro-descendant Non migrant Migrant Source: Censo de Población y Vivienda 2023. Note: Only includes the population over age 15. Urban migration has affected the concentration of poverty. While migration has had a positive effect on poverty reduction at the national level, it has also influenced the concentration of poverty, primarily due to the self-selection of migrants. For example, the share of migrants with no education is lower than the share of non-migrants with no education, and this is especially true among the IP (23.5 percent vs. 29.5 percent, respectively) (Figure 11). By contrast, internal migrants have higher levels of secondary and tertiary education than non- migrants, with 23.5 percent of the indigenous non-migrant population having a secondary or superior education, lower than 33.6 percent of the indigenous migrant population. Labor income played a critical role in poverty reduction in urban areas, but the COVID-19 pandemic had a significant impact on urban labor markets (Figure 12). An analysis of changes in poverty by income source reveals that, at the national level, labor income accounted for around 25 percent of poverty reduction prior to 2019. In urban areas, labor income contributed to more than half of the reduction, bringing poverty levels down to nearly 5 percent in 2015. However, the pandemic severely disrupted urban labor markets, exerting upward pressure on poverty, which were mitigated to some extent by the implementation of emergency programs. In rural areas, public transfers have been the main source of poverty reduction, although labor income, partly driven by government interventions, also played an important role in the pre- pandemic period. (Figure 13). While the implementation of new social protection programs 25 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 resulted in substantial poverty reduction in the early 2010s37, labor income emerged as the main driver of poverty reduction between 2015 and 2019. Support for the agriculture sector, particularly through market price protections, grew significantly from a total of US$208 million in the 2010–2014 to US$738 million in 2015–2019 (Chacón A. et al. 2023). Additionally, large public investment projects in education, roads, and housing improvements in comarcas further supported these gains38. In the Ngäbe Buglé comarca, public investment amounted to US$300 million during this period, contributing to a 17 percent increase in job creation between 2015 and 2019, higher than the national increase of 11 percent. Poverty reduction in rural areas has been hampered by falling investment in comarcas and the COVID-19 crisis. Between 2020 and 2022, investment in Ngäbe Buglé declined by more than 40 percent to US$173 million, and private sector jobs contracted by 18 percent. The pandemic affected both urban and rural areas, though urban areas experienced a faster recovery. Urban employment, heavily concentrated in severely affected sectors such as commerce and services, was initially hit harder but rebounded more quickly due to effective mitigation measures39. By contrast, rural areas and comarcas have yet to recover fully from the economic impact of the pandemic. During the pandemic, agricultural producers benefited from the Panama Solidario program that prioritized purchasing domestic products for food aid distribution, benefiting 81 percent of local producers40. However, support for the agriculture sector was reduced following the closing of the program (ARAP 2021). 37 Created in 2006, RdO is the country’s main conditional cash transfer program and has a special component for rural areas. Other programs such as Beca Universal and 120 a los 65 were created in 2010. The impact of public transfers on poverty reduction between 2008 and 2015 was mainly in rural areas outside comarcas, within which public transfers have had a limited role. 38 The investment projects included improvements in school infrastructure, construction of new school buildings, and new roads, as well as housing im- provements through the Techos de Esperanza program. 39 Without mitigation measures, urban poverty is expected to have almost doubled from 4.8 percent in 2019 to 8.6 percent in 2020. In rural areas, poverty would have increased by one-third, from 28.2 percent in 2019 to 37.9 percent in 2020. However, Panama Solidario (PS), the emergency cash transfer pro- gram established to mitigate the effects of the crisis, is estimated to have reduced the poverty rate in urban areas to 4.5 percent in 2020. In rural areas, PS had a more limited effect, contributing to lowering the poverty rate to 35.6 percent in the same year. 40 https://arap.gob.pa/informe-de-dos-anos-de-gestion/ 26 Figure 12. Changes in Poverty According to Household Income Source by Area, 2008–2023 National 6.0 4.0 2.0 Percentage points 0.0 -2.0 -4.0 -6.0 -8.0 -10.0 -12.0 -14.0 -16.0 2008-2015 2015-2019 2019-2023 2008-2023 Urban 6.0 4.0 2.0 Percentage points 0.0 -2.0 -4.0 -6.0 -8.0 -10.0 -12.0 -14.0 -16.0 2008-2015 2015-2019 2019-2023 2008-2023 Rural 6.0 4.0 2.0 Percentage points 0.0 -2.0 -4.0 -6.0 -8.0 -10.0 -12.0 -14.0 -16.0 2008-2015 2015-2019 2019-2023 2008-2023 Employed population Public transfers Employment income Pensions and retirement Dependency ratio Other non-employment income Remittances Source: CEDLAS and the World Bank. Note: The poverty decomposition follows the Shaley methodology proposed by Azevedo, Sanfelice, and Nguyen, 2012, in which the per capita income as a well-being aggregate is calculated according to the components. 27 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Increases in agricultural income, along with a transition of workers to better-paying sectors such as construction, contributed to rural poverty reduction in the years leading up to the pandemic. While agricultural employment has decreased nationally, it remains a cornerstone of the economy in the comarcas (98.7 percent) and for the poorest 40 percent of the population (36.6 percent). Between 2008 and 2023, more than half of the reduction in rural poverty was due to agricultural and primary activities (Figure 13). This is explained, in part, by a substantial increase in support for the agricultural sector, mainly since 201541. Approximately 70 percent of this support was provided through market price protection mechanisms, such as tariffs, import fees, and price-fixing mechanisms (Chacon et al. 2023). Furthermore, Panama has established a coffee industry, which has increased production by 12 percent over the last five years and has expanded in some comarcas (MIDA 2022). For the rural populations not employed in the primary sector, the share of employment in the construction and banking services sectors has increased. For example, the share of poorer workers in construction has increased from 8.3 percent to 14.0 percent. This transition of workers to relatively better- paying sectors accounted for 14 percent of rural poverty reduction between 2008 and 2023 (Figure 13). However, neither the gains from agricultural support nor the sectoral transition effects were sustained after the pandemic, increasing rural poverty. While transfers have played a significant role in reducing poverty, the coverage, targeting, and adequacy of the main social assistance programs require improvement. The main conditional cash-transfer program, Red de Oportunidades (RdO), covers 20 percent of the population in the poorest quintile, while other programs such as 120 a los 65 and Ángel Guardián (AG) only cover 11.8 percent and 2.3 percent, respectively. Most of RdO benefits reach the poorest quintile (76 percent); but 120 a los 65 and AG, despite targeting the poorest population, show leakage to the richest quintiles. Pase-U, although not specifically designed to target the poor population42, covers 76.9 percent percent of the poorest quantile. Across the various social assistance programs, benefits contribute between 38 and 12 percent of household income in the poorest quintile. However, the program with the best targeting—RdO—has the lowest adequacy43. 41 While support to the agricultural sector represented, on average, 0.5 percent of GDP between 2010 and 2014 (US$208 million), support increased to 1.2 percent of GDP between 2015 and 2019 (US$738 million). The products included in this analysis are: chicken, beef, pork, rice, milk, eggs, sugar cane, pineapple, plantain, and corn, which make up 78 percent of the gross value of agricultural production (Chacon et al. 2023). 42 Pase-U targets low-cost public and private schools attended primarily by children in the poorest quintiles. 43 The adequacy of social assistance programs refers to the total amount of the transfer received by the population participating in the program in relation to their total income. 28 Figure 13 Figure 13. effects on rural poverty reduction, 2008-2023 Sectoral Huppi-Ravallion Decomposition. Sectoral Effects on Rural Poverty Reduction, 2008–2023. (Huppi-Ravallion Decomposition) 10.0 Poverty changes (percentage points) 5.0 0.0 -5.0 -10.0 -15.0 -20.0 2008-2015 2015-2019 2019-2023 2008-2023 Population-shifts effect Interaction effect Agriculture and primary activities Not specified Commerce and services Construction Education and health Domestic services Utilities, transportation and communications Public administration Manufacturing Professional services Source: CEDLAS and the World Bank. Note: Based on the methodology proposed by Ravallion and Huppi (1991). The decomposition estimates changes in poverty strictly due to changes in labor income. This approach excludes effects due to non-labor income, such as public transfers or pensions. The ‘population change effect’ captures the impact of changes in the distribution of the population when moving from one sector to another. The ‘intra-sector effect’ measures the impact of changes within a specific employment sector on poverty reduction based on main labor income. The ‘interaction effect’ captures the combined impact of population shifts and differences in the rate of poverty reduction across sectors (for a detailed methodological description, see Ravallion and Huppi [1991]). The ‘unspecified’ sector refers to people employed in the labor market who did not report the sector in which they work. Additionally, the mining sector is classified within the ‘agriculture and primary activities’ sector. 2.2 The poorest segment of the population lacks income-generating capacity. The poor population is highly concentrated in indigenous comarcas, where low levels of productive assets44 (human and financial capital) and limited access to services and markets constrain their ability to generate income. In 2023, indigenous comarcas accounted for 39 percent of people living in poverty, despite accounting for only 6.6 percent of the total population. Rural and indigenous territories face persistent challenges, including insufficient coverage of basic services, low accumulation of human capital, limited income generation, and exposure to climate risks. While there were long-term poverty improvements in rural areas between 2001 and 2023, progress has not been sufficient to reach urban standards or even the national average. According to the 2023 census, only 51 percent of the population in comarcas has access to water, 53 percent to sanitation, and 51 percent to electricity— 44 Productive assets include human, financial, natural, and social capital. 29 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 levels far below access rates in rural areas 13 years ago, which were 78 percent for water, 59 percent for electricity, and 80 percent for sanitation (Table 1). Additionally, the average years of schooling and labor income in urban areas were double those of rural areas in 2023. Table 1. Lack of productive assets and unequal access to labor markets and basic services hamper poverty reduction efforts. 2001 2023 Indicators Comarca Rural Urban Comarca Rural Urban Poor US$6.85 per day (2017 PPP) 94.1 63.5 25.7 76.0 32.3 4.8 Average years of education (aged 18+) 3.4 6.2 11.0 6.3 8.4 12.4 Head of household with no education 72.2 43.9 11.6 50.8 27.4 6.1 School enrollment (6-12 years) 82.5 91.8 98.0 94.8 97.7 99.3 Medical insurance 4.4 27.6 59.4 5.6 30.7 57.7 Labor force participation 60.5 56.4 58.2 68.0 63.8 61.4 Unemployment rate 0.3 5.1 12.0 1.5 4.0 7.9 Share of unpaid workers 27.2 11.1 0.9 37.8 14.5 1.0 Share of workers in micro-enterprises 91.9 59.5 23.9 63.3 66.8 41.5 (1-4 employees) Informal employment rate 94.6 76.8 46.7 91.9 73.5 40.6 Mean hourly labor income 2.2 4.1 8.2 5.1 6.7 10.9 Climate change impacts 12.8 6.2 6.9 2010 2023 Access to water 46.3 78.3 96.6 51.0 79.4 96.4 Access to electricity 10.8 58.9 96.9 50.6 82.0 98.5 Access to sanitation 34.1 80.5 97.1 52.9 84.9 98.2 Source: EML (2001, 2023), EPM (2022), and Censo de Población y Vivienda (2010). Indigenous comarcas possess abundant and diverse natural capital, including lands and forests, but this potential remains largely untapped. With 31.8 percent of its territory covered by forests45, Panama is among the countries with the greatest biological diversity46, and two- thirds of its forests are in indigenous territories47. Natural capital represents an important source of income, particularly for comarcas, where agriculture employs 98 percent of workers. Natural and cultural wealth offers tourism opportunities. However, lack of basic services and infrastructure, including roads (only 21 percent of comarcas and 62 percent of rural areas 45 Including 120 protected areas, 12 wildlife zones, and a variety of ecosystems (Sistema Nacional de Áreas Protegidas (SINAP). 46 https://www.ibat-alliance.org/country_profiles. 47 World Bank 2021. 30 can be accessed by roads), limits access to these areas. Development in these areas must be sustainable, as deforestation remains a serious concern; between 2012 and 2019, a total of 56,369.49 hectares (equivalent to 8,052.78 ha per year) were deforested48. Extreme weather events and climate change pose a threat to biodiversity and rural agriculture. 2.3 Despite improvements, the labor market remains unequal. Labor income has increased significantly in Panama, contributing to poverty reduction. From 2001 to 2023, mean real hourly income increased by 46 percent, at an average annual rate of 2.2 percent. Increased labor income accounted for 25 percent of the country’s poverty reduction in 2008–2015 and 38 percent of poverty reduction in rural areas in 2015–2019. However, following a period of significant job creation, the labor market has weakened over the last decade. The country’s rapid economic growth in previous decades drove increases in labor force participation and employment (Figure 14a). In 2023, the labor force participation rate was 62.4 percent and the employment rate was 57.8 percent49, higher than that of comparable countries such as Costa Rica (53.9 percent and 49.5 percent, respectively) and Uruguay (62.2 percent and 57.1 percent, respectively). Yet, following the construction boom, employment growth slowed significantly—from an average of 4.1 percent between 2001 and 2012 to 2.5 percent between 2013 and 2019—and it was further disrupted by the pandemic. Informality also increased during the 2013–2019 period, but it had by 2023 returned to levels recorded in 2005 (Figure 14b). The increase in labor force participation reflects a significant increase in women’s participation, which helped narrow the gap between women and men. Women’s labor force participation increased from 38.4 percent in 2001 to 55.5 percent in 2019. However, the pandemic severely impacted both labor force participation and employment, reversing progress to levels recorded during the previous decade. Despite the narrowing of gender gaps over time, inequalities persist, with women’s labor force participation being 33 percent lower than that of men in 2023. 48 Panama has 5,945,470 hectares of forest, covering 68 percent of the national territory (MiAmbiente). Between 2012 and 2019, the country lost 56,369.49 hectares of forest (equivalent to 8,052.78 ha per year). While this rate of deforestation is less than that of other countries in the region, such as Brazil (1,100,000 ha per year), Colombia (59,142 ha per year), and Bolivia (50,834 ha per year)—where extensive agricultural practices (particularly soy and livestock) have destroyed large forest areas—the relative impact in Panama is more pronounced. Panama’s deforestation rate represents 2 percent loss of its forests per year, higher than that of Brazil (0.5 percent), Colombia (0.3 percent), and Bolivia (0.43 percent). (World Population Review 2024). 49 Own calculations based on data from Encuesta de Mercado Laboral 2023. 31 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figure 14. 14 a Indicators, 2001–2023. Labor Market Figure Labor market indicators, 2001-2023. a. Employment and Participation 70 25 65 60 20 Employment and Participation Rate 55 Unemployment rate 50 15 45 40 10 35 30 5 25 20 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2021 2023 Employment Participation Unemployment (right axis) Source: EML 2001–2023. Figure 14 b Labor informality b. Labor Informality 60 55.5 55 55 50 Percentage 45 40 35 30 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2021 2023 Contribution to the CSS Source: EML 2001–2023. 32 The wage and formal employment gap has narrowed for most population groups, but labor participation and employment gaps have widened for others, particularly affecting the poorest households and vulnerable groups. The labor participation and employment gap for the poorest 40 percent of the population, the indigenous, the unskilled, and the young has increased, although the school enrollment rate among young people has increased. Moreover, the wage gap has narrowed for all groups, and the gap in formal employment has also decreased among all groups, except for workers with a secondary education (Figure A2). Despite these improvements, significant disparities in access to formal employment and income persist, especially for low-skilled workers and indigenous groups. Gaps in access to formal employment and income are significant and much wider than those in employment for almost all groups (Figure A3). In 2023, low-skilled workers earned a mean hourly wage up to 74 percent lower than workers with a tertiary education, and their formal employment rate was 74 percentage points lower. The IP earned incomes 36 percent lower than the non-IP. While women have achieved equal income and formality levels compared to men, there is still a participation and employment gap of 24 percentage points between men and women. Household income inequality mirrors labor market inequalities. In Panama, as in most countries, labor income is the largest source of household income (70 percent in 2019). Changes in labor income inequality (as measured by the Gini index) is generally accompanied by changes in household income per capita inequality. However, in the post-pandemic years, labor income inequality worsened, while social assistance programs significantly mitigated household income inequality (Figure 15). In 2023, labor income inequality, with a Gini index of 57.6, remained similar to the level recorded in 2008. Figure 15. 15 Figure Inequality in and in Labor Inequality the Household Income per Capita, labor and households income 2008—2023 per capita, 2008 - 2023. 63 61 59 57.3 56.2 57 57.6 55 Gini 52.7 53 49.8 51 49 48.9 47 45 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2021 2023 Labor income Household income Source: EML 2008–2023. 33 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Barriers to a More Equitable Labor Market Labor Market Structure and Employment Quality The lack of equity in labor income is closely tied to the unequal labor structure faced by workers. In 2023, most jobs were concentrated in service-related activities, especially commerce, with most workers in wage-earning employment. However, three out of five workers were employed in the informal sector (Figure 16.a). Workers in the poorest 40 percent of the income distribution had a higher share of young dependents (under 15 years old), had greater rates of inactivity (45 percent, compared to the national average of 38 percent), and were more likely to hold agricultural jobs or be engaged in unpaid work (14.8 percent). The quality of employment among workers in the poorest households was also lower, with nearly nine out of ten jobs being informal. Figure 16. Labor Market Structure, 2023 Figure 16 a. National total Figure 16 Percentage (%) 0 10 20 30 40 (%) Percentage 50 60 70 80 Working-Age Population 0 10 20 30 77.340 50 60 70 80 WAP by type Working-Age of activity Population Employed P 57.8 77.3 Inactive P 37.6 Employed population (EP)of WAP by type by sector activity AGR 15.2 SRV 59.8 P 57.8 Employed IND 25 Inactive P 37.6 Unemployed P 4.6 Unpaid 5.1 EP by Employed population occupation (EP) by sector Self15.2 employed 31 AGR SRV 59.8 Wage worker 61.1 IND 25 Employer 2.9 Unemployed P 4.6 Unpaid 5.1 EP by EPformality status by occupation 3144.4 Formal Self employed Informal Wage worker 61.155.6 Employer 2.9 EP by formality status Formal 44.4 Informal 55.6 Percentage (%) b. Poorest 40%0 10 20 30 40 50 60 70 Percentage (%) Working-Age Population 0 10 20 61.4 30 40 50 60 70 WAP by type Working-Age of activity Population Employed P 48.8 61.4 Inactive P 27.6 Employed population by (EP)of WAP by type sector activity AGR 36.6 SRV Employed P 40.7 48.8 IND 22.7 Inactive P 27.6 Unemployed P 3.9 Unpaid 14.8 EP by Employed population occupation (EP) by sector Self AGRemployed 36.6 45.3 Wage SRV worker 38.5 IND 22.7 40.7 Employer 1.4 Unemployed P 3.9 Unpaid 14.8 EP by EPformality status Formal by occupation 18 Self employed 45.3 Informal 82 Wage worker 38.5 Employer 1.4 EP by formality status Formal 18 Informal 82 Source: Own calculations based on EML 2023. The employment structure of the poorest population has not changed significantly in recent decades, although unemployment has decreased. Between 2001 and 2023, the working-age population and the share of employed people in the poorest 40 percent of the income distribution grew at a slower rate than the national average (3.7 and 4.3 percentage points compared to 5.0 and 5.8 percentage points, respectively). While labor inactivity decreased by 1.9 percentage points, mainly due to greater female labor participation, it 34 remained constant for the poorest population, albeit with a higher proportion of students. The share of unemployed people within the working-age population (WAP) decreased by 4.4 percentage points for the poorest labor force and by 3.8 percentage points for the national total. On the other hand, the occupational structure of the poorest workers has changed, with reduced participation in agricultural activities, though informality remains high. Compared to 2001, workers in poorer households were 15.6 percentage points less likely to hold agricultural occupations, transitioning mainly to service activities, which increased by 10 percentage points. Wage-earning employment decreased slightly (by 2.1 percentage points nationally and 3.2 percentage points among the poorest population). Informality decreased by 2.3 percentage points compared to 2005 among the poorest households, but it remained high at 82 percent in 2023. In Panama, low job quality has become an increasing concern in recent years, disproportionately affecting vulnerable populations. The Job Quality Index50 has decreased since 2015 at a faster rate than in any other country in the region (Figure 17), driven mainly by a reduction in social security benefits (labor informality). In addition to earning lower incomes, the poorest population often faces more precarious working conditions. Low job quality is also correlated with sociodemographic characteristics, with the indigenous, low-skilled, and young population experiencing the greatest challenges (Figure 18). Vulnerable populations are disproportionally concentrated in economic sectors such as agriculture or commerce and are more likely to be self-employed. More than 70 percent of the IP and more than 65 percent of unskilled and young workers are employed in sectors such as agriculture and commerce, while 60 percent of workers in the richest households are employed outside these sectors (Figure 19). Similarly, 80 percent of the population in poorer households are either self-employed or wage earners in companies with fewer than 10 workers. This share is 70 percent for the IP and unskilled workers and 64 percent for young workers (Figure 20). Self-employment or employment in a small business are correlated with higher levels of informal employment, lower levels of labor productivity, less access to financing, and fewer incentives for business registration (Aberra et al. 2022). 50 The Job Quality Index incorporates: (i) income security: wage above the upper-middle class poverty line of US$6.85 per day in PPP; (ii) access to em- ployment benefits: employment provides health insurance or retirement benefits; (iii) contract-based security: the worker has a contract, employment is permanent, or the worker has held the job for a period greater than three years; and (iv) job satisfaction: the worker is satisfied with his or her job (assumes that the worker does not have a second job). 35 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figure 17 Figure 17. Job Quality Index, LAC 2008-2021. Job Quality Index, LAC, 2008–2021. 0.85 0.80 0.75 0.70 Index 0.65 0.60 0.55 0.50 CRI URY BRA ECU PAN DOM ARG COL BOL PRY SLV PER Circa 2008 2015 2019 2021 Source: World Bank Equity Lab. 18. 18 Figure Figure Job IndexIndex Quality Job Quality different amongGroup, by Population 2023 groups, 2023. 0.90 0.80 0.70 0.60 0.50 Index 0.40 0.30 0.20 0.10 0.00 Richest Poorest Indigenous Unskilled Youth 60% 40% (15-24) Source: Own calculations based on the EML 2023. 36 Figure 19. Figure 19 Employment by Subsector, 2023 Employment by subsectors, groups, 2023. 100 90 80 70 % of workers 60 50 40 30 20 10 0 Richest Poorest Indigenous Unskilled Youth 60% 40% (15-24) Agriculture Manufacturing Commerce Domestic service Construction Electricity, gas and water Financial and professional services Public administration Education and health Source: Own calculations based on the EML 2023. Figure 20 Figure 20. Employment by company size, groups, 2023. Employment by Company Size, 2023. 100 90 80 70 % of workers 60 50 40 30 20 10 0 Richest Poorest Indigenous Unskilled Youth 60% 40% (15-24) 50+ 11 - 50 2-10 Self-employed Source: Own calculations based on the EML2023. Note: Note: Theself-employed * The self-employedcategory includes category unpaid includes workers unpaid and employers. workers and employers. 37 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Productivity Gaps and Businesses Barriers Labor productivity has increased in Panama, but wide gaps exist between economic sectors, posing a barrier to equity. Labor productivity is a key driver of economic growth and higher income levels (OECD, 2023). Differences in productivity across countries and sectors often translate into differences in income. In Panama, the increase in labor productivity, understood as value added per worker, explains most of annual value-added growth in recent decades, above demographic changes, employment, and labor force participation (Figure A4). However, the significant economic growth experienced by the country is due to increased productivity in specific subsectors within services and industry (tradable services and construction), generating aggregate productivity gains (Figure A5), but also productivity gaps between sectors, which are wider than in comparable economies and the regional average (Figure A6). Panama exhibits limited reallocation of labor to more productive sectors, potentially contributing to productivity differences. The country’s recent labor productivity growth is due primarily to increases in productivity within sectors rather than the displacement of workers to more productive sectors (Figure A7). As a result, sectors such as agriculture and non-tradable services—including retail commerce—continue to lag behind, even though they account for the largest share of employment (Figure 21). Job creation over the last decade has been driven by low-productivity sectors. Between 2011 and 2019, employment growth was disproportionately concentrated in the least productive sectors, including other service activities, retail commerce, and health. By contrast, employment participation in high-productivity sectors, such as free-trade and wholesale commerce, electricity, gas, and water, and financial activities, declined during this period. Labor participation in agriculture—the country’s least productive sector—also fell significantly. There are also wide productivity gaps at the territorial level. An analysis of the formal private sector based on the Directorio de Empresas y Locales - DEL (2023)51 shows that 86 percent of the country’s workers in formal private companies are concentrated in the provinces of Panama (65 percent), Chiriquí (8.3 percent), Panama Oeste (7.4 percent), and Colón (6 percent). This concentration in the province of Panama is disproportionate to its share of the working-age population (37 percent, compared to 11.5 percent, 16.6 percent, and 6.9 percent in Chiriquí, Panama Oeste, and Colón, respectively). The relative productivity of Panama Oeste, Colón, and Panama surpasses the national average by 20 percent, 89 percent, and 120 percent, respectively, while in the rest of the provinces, including Chiriquí (home to 15 percent of the country’s companies), productivity levels fall below 40 percent of the national average. 51 The Directorio de Empresas y Locales (DEL) is the main source of information for the National Economic Census. The National Institute of Statistics and Census (INEC) collects a form with specific information directly from companies identified through administrative records of the Social Security Admin- istration (CSS), the Ministry of Commerce and Industry, Panamá Emprende, the Ministry of Economy and Finance, the General Directorate of Revenue, and economic surveys. DEL covers the national territory, excluding comarcas and areas difficult to reach—locations that will be updated using adminis- trative records, which are currently not found in the database. 38 Figure 21 Relative productivity Figure 21. and employed population proportion, subsectors, 2021. Relative Productivity and Employed Population Ratio by Subsector, 2021 450 20 400 18 Employed population % Relative productivity 350 16 300 14 12 250 10 200 8 150 6 100 4 50 2 0 0 Agriculture Other service activities* Hotels and restaurants Administrative activities Teaching Health and social assistance Retail commerce Public administration Manufacturing Transportation communication Wholesale commerce Construction insurance activities and water supply Free zone trade Real estate activities Mines Information and Financial and Electricity, gas, Employed population % (right axis) Relative productivity. Economy Total=100 Source: Own calculations based on the EML 2021; value-added information provided by INEC. Small businesses, which employ 80 percent of workers from households in the poorest 40 percent, have not experienced gains in labor productivity. While workers in large companies saw an increase in their labor income at an annual rate of 4.3 percent between 2015 and 2019, labor income of self-employed workers and workers in small companies increased by only 0.2 percent. According to the available information from the Encuesta a Empresas No Financieras (2012–2019)52, the labor productivity of small formal companies, measured as their income minus costs per worker, has stagnated in recent years (Figure 22). Labor dynamics in the formal private sector are dominated by older and large companies. Data from Directorio Nacional de Empresas (2023) show that 55 percent of formal private sector jobs are in companies that are at least 10 years old and employ at least 50 workers, despite these companies representing only 2 percent of all formal private companies. By contrast, only about 6 percent and 15 percent of jobs are in formal companies that are younger than 5 years old and employ 5–19 employees, respectively. The concentration of formal employment in older, larger companies in Panama is higher than in countries such as the Dominican Republic (48 percent) and Vietnam and Turkey (20 percent) (Winkler and Montenegro 2021). 52 Encuesta Entre Empresas No Financieras (EEENF) is an annual survey based on a sample taken from an economic census of the country’s provinces (excluding indigenous comarcas or areas that are difficult to access). The EEENF measures the economic activity of all companies to gather information on the main economic characteristics as well as the structure and behavior of the country’s different sectors. The survey does not collect information on agricultural, financial, or construction companies, and it features limited information on the characteristics of companies. Information for 2019-2020 was limited due to the COVID-19 pandemic and displays comparability problems. 39 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 The level of entrepreneurship and innovation is relatively low in Panama, potentially hampering the productivity growth of micro, small, and medium-sized enterprises (MSMEs). Entrepreneurship and innovation are important for increasing business productivity. According to the Systematic Country Diagnosis Update (World Bank, 2023), Panama ranked 76th out of 137 countries in the Global Entrepreneurship and Development Institute’s Global Entrepreneurship Index (GEI) (2020) in 2019, behind countries like Chile (19th) and Uruguay (60th). Key sub-indicators in which Panama scored poorly include technological absorption (10.5/100), entrepreneurial opportunities (17.8), process innovation (17.9), and capital risk (18.5). The country’s poor performance on entrepreneurial and innovative capacity are due to: (i) inadequate educational quality; (ii) limited access to private financing; and (iii) insufficient financial support for aspiring entrepreneurs and MSMEs. In a survey conducted by the Micro, Small and Medium Enterprise Authority (AMPYME) targeting informal MSMEs, 61 percent of participating companies reported having limited access to credit due to lack of collateral, complex application processes, and limited banking services tailored to small businesses. By contrast, large companies reported minimal credit restrictions (World Bank, 2023). Figure 22. Figure 22 Labor Productivity by Company Size, 2011–2018 Labor productivity by company size, 2011-2018. 30 25 Thousand of B/. 2017 PPP 20 15 10 5 0 Total Micro-small Medium-sized large (1 - 10) (11 - 50) (51 + ) 2011 2018 Source: EENF – INEC. 40 Figura 23. Ingles Figure 23. Labor Market Rigidity Index vs. Informality, 2019 2.50 Panama Honduras 2.00 Rigidity Index of the labor market Mexico Peru 1.50 1.00 0.50 Chile Ecuador 0.0 Costa Rica Brazil Dominican -0.50 Argentina Republic El Salvador -1.0 Colombia Uruguay -1.5 0.0 20 40 60 80 100 Informality Source: EML 2023; Doing business 2019. Labor Market Regulation Labor market rigidity also poses a challenge to the reallocation of workers to more productive sectors and promoting labor formality. Rules defining minimum wage levels and job security are important labor market regulations (OECD, 2020). However, Panama has a high degree of labor market rigidity53 compared to other countries in the region (Figure 23). This rigidity can distort labor dynamics, constraining the movement of workers from traditional sectors with low levels of productivity to more dynamic sectors with higher levels of productivity, and hindering efforts to close productivity gaps between sectors. In Panama, the procedures for dismissing workers are significantly stricter than in countries in the region. Panama is ranked among the countries with the highest rigidity in worker dismissal processes in the region (Barreto et al. 2024). While strong hiring and dismissal procedures aim to help increase workers’ labor protection, they can also have unintended consequences that vary by worker demographics. Prime working-age men (aged 25–54) and better educated workers are more likely to benefit from these protections. Conversely, workers without coverage—such as young people and less-skilled workers—may be disadvantaged if employers hesitate to hire formal workers under rigid labor security regulations (Betcherman, 2019). 53 The labor market Rigidity Index covers four harmonized sub-indexes derived from the World Bank’s database on labor market regulation in the Doing Business Report: (i) limitations on hiring, (ii) restrictions on working hours, (iii) dismissal procedures, and (iv) dismissal costs. 41 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 The country’s complex minimum wage matrix complicates the labor market. In Panama, the government establishes the minimum wage matrix by executive decree every two years based on recommendations from the Minimum Wage Commission. The matrix details the wage adjustment according to region, economic activity, and company size. As of 2024, there were up to 96 different hourly minimum wages, ranging from B/.1.64 to B/.4.88. Most minimum wages have increased at similar rates since the late 1990s, prioritizing aggregate considerations over sectoral or company-level productivity considerations (OECD, 2018). However, studies on best practices on allocation indicate that a system with multiple minimum wage levels (by region, sector, and/or occupation) can be difficult to implement and enforce, and may induce additional labor market distortions. Thus, minimum wage increases that do not follow corresponding adjustments in the economy´s labor productivity can generate distortions (World Bank 2014). Future Labor Market Challenges In addition to high informality, low productivity, and labor market rigidity, Panama’s still expanding WAP presents challenges for the labor market in the future. The country’s overall job creation rate has been positive and higher than that of the WAP—even amid the economic slowdown in the mid-2010s. However, Panama’s WAP growth rate has been increasing and is expected to be double the average of LAC by 2030 (ECLAC 2022). Panama’s population under age 15 is expected to peak by 2025, a decade later than the LAC average, which creates a narrow window of opportunity to adapt the Panamanian labor market. (Figure A8). Meeting these demographic challenges will require to maintain a sustainable and equitable employment growth in the coming decades. To maintain an employment growth rate close to pre-pandemic levels (1.8 percent in 2019) and reach full employment (80 percent by 2040), Panama must maintain an annual GDP growth rate of at least 5 percent, considering the growth-employment elasticity of recent years. Although the WAP is in an expansion phase since 2018, the country faces additional demographic pressures, as its population over age 65 reached 7 percent, marking the onset of population aging. To ensure the stainability of the pension system and maintain the current growth trajectory, Panama needs to improve job quality and address the rising prevalence of non-communicable diseases (Gutierrez et al. 2023). To fully leverage its demographic dividend, Panama will have to ensure its workforce can adapt to global labor market trends and increase the use of technologies, which will require improved cognitive skills. Panama’s workforce must align with global trends in job creation driven by new technologies (World Bank, 2021). These include jobs in analytical and interpersonal- intensive tasks, such as managers, teachers, and engineers (Appendix 3) that generally tend to have greater access to digital technologies (Gmyrek et al. 2024). By contrast, jobs that are at high risk of automation and displacement include those that rely on routine tasks such as machine operators and cashiers. 42 Most Panamanian jobs, especially low-skilled, continue to involve routine and manual tasks, which are risk of automation. While non-routine cognitive analytical jobs have grown modestly (1.5 percent from 2011 to 2023) and jobs in other tasks have remained constant, jobs requiring intensive interpersonal skill have an increase of 4 percent in 2016 and then declined in subsequent years (Figure A9). Technology-intensive jobs tend to be filled by workers who are already better off, exacerbating inequalities. In Panama, workers with jobs requiring intensive analytical skills are often highly educated people who work in large and formal companies, while low-skilled and informal workers tend to have less formal education (Figure A10). For example, 74 percent of workers in highly analytical-intensive jobs have a tertiary education, and mere 1.5 percent of them have no formal education. Gaps in education are closely linked to gaps in access to technology-intensive occupations, highlighting the importance of increasing the country’s human capital to ensure a more equitable labor market. Green growth54 in Panama is hampered by the prevalence of ‘non-green’55 jobs, low human capital, and a rigid labor market. Only 24 percent of Panamanian jobs are classified as green, with agriculture accounting for 94 percent of employment in non-green occupations. Workers in non-green jobs and sectors are more likely to be poor, informal, and rural (Winkler et al. 2024). While the country has adopted clear objectives to ensure a green transition, their successful implementation depends on factors such as human capital, labor market flexibility, and the business environment. Panama ranks 86th out of 190 countries in overall ease of doing business (World Bank 2023), and inadequate human capital and a rigid labor market hinder its green transition. The country’s human capital challenges include low educational quality, misalignment between educational offerings and business needs, and the expansion of low-skilled sectors (Lavado and Yamada 2022). 54 For example, policies and prior actions to policy loans between the World Bank and Panama on climate change resilience and green growth. 55 Within the classification of green economies, there are both (non) green jobs and (non) green sectors (Winkler, Di Maro, Montoya, Olivieri, and Vazquez 2024). Green jobs are measured following the definition adopted by the Green Economy program developed by the Occupational Information Network (O*NET) and include occupations necessary to obtain/sustain a green economy, including jobs related to reducing the use of fossil fuels, decreasing pollution and GHG emissions, improving energy efficiency, increasing recycling, and adopting renewable energy. Green sectors, on the other hand, refer to those sectors of the economy whose CO2 emissions are lower than those of the country average. 43 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figure 24. 24. Figure Returns to Education Returns to education 2.00 1.80 1.60 1.40 1.33 1.40 1.17 1.13 1.10 1.20 1.05 1.07 1.03 1.00 0.80 0.64 0.63 0.54 0.60 0.44 0.47 0.43 0.41 0.34 0.40 0.20 0.00 2001 2005 2010 2015 2019 2021 2023 LAC 2021 Secondary Tertiary Note: The figure shows coefficients obtained from linear least squares (LLS) regressions where the dependent Note: The figure shows coefficients obtained from ordinary least squares (OLS) regressions, where the dependent variable is the variable is the natural logarithm of the after-tax hourly wage in the main occupation for wage-earners and natural logarithm of the self-employed after-tax workers hourly for each wage year. in the main Following occupation Fernandez for wage et al. (2024), earners controls and self-employed include a categoricalworkers variablefor each year. Following Fernandez et for educational al. (2024), controls attainment, include where the a categorical reference category variable is havingfor the less educational than level, where upper secondary, the upper reference category is secondary, lesstertiary havingand than upper secondary education; and tertiaryvariable a dichotomous fora education; dichotomous women; for women; Source: variableexperience. and potential and potential experience. EML (2021-2023) Source: EML and (2021-2023) Fernandez et and Fernandez al. (2024), al. (2024), et20, Figure for the Figure 20, for the Latin American Latin American average in 2021. average in 2021. Despite the challenges facing the labor market, Panama shows relatively high returns to education, suggesting possible incentives for human capital accumulation. EML data show that returns to secondary and tertiary education in the country are high, surpassing the LAC average (Figure 24). However, significant challenges in the health and education sectors hinder human capital accumulation and diminish labor productivity. 2.4 Gaps and inequalities in education and health persist despite progress. In addition to income generation and labor market challenges, Panama faces systemic problems in the accumulation of human capital. Low educational quality at all levels and for all students, high school dropout rates, and concerning child health and adolescent fertility indicators for certain population groups create significant barriers to successful labor market transitions. These factors prevent future generations from reaching their full labor potential and limit the country’s prospects for economic growth and poverty reduction. This section details these gaps and examines barriers within Panama’s education and health systems, including inefficiencies in government expenditure and deficiencies in the supply and demand for essential public services. 44 Panama has a low Human Capital Index (HCI) relative to its income level. According to the latest HCI estimate from 2020, if deficiencies in the provision of education and health services continue, future generations will only be able to achieve 50 percent of their potential labor productivity by age 18 (Figure 25). When factoring in the probability of securing a job that fully utilizes skills, the country’s average productive potential drops to less than 35 percent. Compared to LAC countries, middle-income countries (MICs), and high-income countries (HICs), Panama’s performance is below average across all measures of the HCI. Gaps are particularly stark in access to quality education at the national level. Both expected years of schooling and learning outcomes have worsened over the last decade. Combined with slow progress in health indicators, this has resulted in a negative trend in the country’s HCI over the last ten years (Figure 26) (World Bank 2024). Figure 25. Figure Basic HCU 25. and complete HCI. HCI, Basic HCI, and Complete HCI 0.80 0.68 0.70 Human Capial Index, 2020 0.60 0.55 0.52 0.50 0.49 0.48 0.50 0.40 0.34 0.35 0.32 0.34 0.28 0.29 0.30 0.20 HCI Adjusted HCI (basic) Adjusted HCI (complete) Panama LAC HIC MIC Source: WDI 2024; World Bank 2024. Note: Includes all countries with a Human Capital Index in 2020. The adjusted basic HCI considers the fraction of the working-age population that is employed. The adjusted (complete) HCI includes ‘better employment,’ defined as non-agricultural employees, plus employers. 45 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figure Figure26. 26. HCI, 2010–2020 Evolution of the HCI 2010-2020 and its subcomponents. Health Child survival Education HCI -0.030 -0.020 -0.010 0.000 0.010 0.020 0.030 0.040 MIC LAC HIC Panama Source: WDI 2024; World Bank 2024. Note: Includes all countries with Human Capital Index in 2020. LAC: Latin American and the Caribbean; HIC: high-income countries; MIC: middle-income countries. Gaps and Inequalities in Education Although there have been improvements in education coverage, progress in Panama has been slower than in other countries in the region. Average years of schooling increased from 6.9 for people born before 1950 to 12.1 for those born in the 1990s, with remarkable advances for women, rural residents, and indigenous people. However, significant inequalities persist: the IP born in the 1990s has fewer average years of schooling than the urban population born in the 1950s, and the rural population has achieved only the level of schooling attained by those born in the 1960s (Figure A11). Furthermore, the increase in average years of schooling in Panama is lower than that of economies such as Singapore and even regional peers such as Colombia, Chile, and Bolivia during the same period (Figure A12). Educational coverage for new generations in Panama varies according to age and population group. Among children aged 4-5, 46 percent of children in urban areas attend an educational institution, higher than 34 percent in rural areas, 24 percent among the IP, and 29 percent of children in households with low levels of education. Similarly, 7 percent of children aged 6–12 with a disability do not attend school, higher than 3.5 percent of children without disabilities. 46 Figure Figure27. 27 Attendance Attendance at Educational at Any Institution any educational by Grade and institution andAge grade/level by age. 100% 19% 90% 19% 80% 12% 70% 60% 74% 84% 92% 24% 82% 99% 98% 98% 50% 97% 84% 39% 75% 40% 80% 67% 42% 30% 41% 39% 38% 35% 20% 29% 24% 20% 19% 19% 10% 14% 8% 7% 0% 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Preschool Primary Junior High Secondary Tertiary Preschool Primary Junior High Secondary Tertiary Figure 28. Figure 28. Attendance at any educational institution by population groups yearsat Attendance (4-5 Educational Any 18-24 and Institution by Population Group (4-5 years and 18-24 years) years). 60% 50% 40% 13% 30% 11% 43% 10% 20% 9% 22% 15% 21% 33% 10% 23% 19% 14% 8% 5% 6% 7% 0% Urban Rural IP Head Prim. Urban Rural IP Head Prim. Edu. or Edu. or less less 4-5 years 18-24 years Preschool Primary Junior High Secondary Tertiary Source: Censo de Población y Vivienda (2023), calculation by the authors. Note: Left Figure: Two questions from the 2023 Census were used to calculate the grade level for everyone: (i) whether the individual is attending at the time of the Census; and (ii) the last grade completed by the individual. To determine the grade that the individual was in in 2023, one year is added to the answer given to the question about the last grade completed if the individual answers that he or she was attending an educational institution. The horizontal axis details the educational level that everyone by a certain age must complete by law. In Panama, education is compulsory until the completion of secondary education. Right Figure: Details the inequalities in coverage for preschool and tertiary education. IP = indigenous population. 47 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Although preschool education is legally compulsory, only 19 percent of 4-year-olds and 62 percent of 5-year-olds attend an educational institution (Figure 27)56. School dropout rates and educational lag increase significantly after age 15, with only 87 percent of 15- to 17-year-olds enrolled in an educational institution, and nearly 10 percent attend levels not appropriate for their age. Furthermore, tertiary education coverage is low, with only 36 percent of 18- to 24-year-olds enrolled, lower than the LAC and European average of 52 percent and more than 80 percent, respectively (Figure 28). These averages hide inequalities between groups, which have negative long-term implications, as gaps in human capital at an early age are difficult to close later on (Heckman 2011). Inequalities in tertiary education are especially notable, with coverage reaching 43 percent in urban areas and falling below 22 percent for other groups. The decline in total educational coverage as children and young people age is closely linked to high repetition and dropout rates. These issues are particularly pronounced at the junior high and high school level, particularly in rural, indigenous, and public schools (INEC 2024). Among rural and indigenous populations, as well as in households where the head of family has only completed primary school, about 30 percent of students who drop out do so at the end of sixth grade, and another 20 percent do so at the end of ninth grade, indicating a higher risk of dropping out at the end of primary school. By contrast, urban students are less likely to drop out, with only about 18 percent leaving school between the end of primary and junior high school. School dropout rates are the highest in rural areas and among students in the final grades of primary and junior high school, just before many leave the education system. Learning levels in Panama are alarmingly low and unequal (World Bank 2023, 2024). According to the most recent PISA (2022) data, only 16 percent of 15-year-olds meet the minimum proficiency levels in mathematics, considerably lower than in other countries in the region or with similar incomes (Figure 29)57. In reading and science, only 49 percent and 42 percent of students, respectively, exceed the minimum proficiency level, below the average of comparable countries. Moreover, disparities in learning quality within Panama are significant and more pronounced than in other countries. Students from rural and indigenous areas, as well as those from households where mothers have lower levels of schooling, score considerably lower in all measured subjects (Figure 30). 56 Under the Organic Law of Education, with amendments incorporated in Decree No. 305 of 2004, compulsory education in Panama includes preschool (4 to 5 years old), primary (6 to 11 years old) and junior high school (12 to 14 years old). In addition, there is the secondary level (15 to 17 years old) in ac- ademic or technical professional mode and superior or tertiary education, aimed at all those who completed high school and includes post-secondary, non-university and university education. 57 According to OECD technical reports (2023), the response rate of Panamanian students dropped to 77 percent in 2022, possibly due to the widespread protests during that year. The reports suggest that students in lower grades and those with special needs did not participate on the test, which means that the country’s results could be biased upward, indicating that learning levels could be even lower. 48 Figure 29. Percentage of students above the minimum level by area of knowledge Figure (PISA 29. 2022). Share of Students Above Minimum Level by Subject 90% 80% 80% 80% 77% 77% 71% 70% 66% 60% 54% 49% 49% 50% 47% 47% 42% 40% 29% 29% 30% 20% 16% 10% 0% Mathematics Reading Science Panama LAC OECD HIC MIC Source: PISA 2022, calculation by the authors. LAC = Latin American and the Caribbean; OECD = OECD member countries; HIC = high-income countries; MIC = middle-income countries. Figure 30. Figure 30. of students above the minimum level in mathematics by Percentage Students Above Minimum Share ofcharacteristics student Level in Mathematics by Student Characteristic (PISA 2022). 80% 70% 60% 50% 40% 30% 20% 10% 0% Urban Rural Public Private Primary Secondary Tertiary Location Nature Mother’s education Panama LAC OECD Source: PISA 2022, calculation by the authors. Note: LAC countries are all Latin American and the Caribbean countries, OECD member countries, HIC countries are all high-income countries, and MIC countries are all middle-income countries that participated in the test in 2022. Extended school closures in Panama due to COVID-19 could have serious consequences for human capital (World Bank, 2024). The country experienced one of the longest lockdowns in the world during the pandemic, with 55 weeks of complete closure between March 2020 and March 2022, compared to the LAC and global average of 33 and 20 weeks, respectively 49 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 (UNESCO). Recent INEC data show that repetition and dropout rates for primary and junior high school education between 2021 and 2022 were similar to pre-pandemic averages (2015–2019). However, these rates increased from 5 percent to 6 percent for repetition and from 3 percent to 5 percent for dropouts, indicating a concerning trend. PISA (2022) data, the only standardized international knowledge test available for the country post-lockdowns, reveal that performance in mathematics decreased after the pandemic, while performance in reading and science increased marginally. Estimates suggest that the extended school lockdowns reduced adjusted learning years for affected Panamanian generations from 6.5 years before the pandemic to 5.58 years in an optimistic scenario and to 4.39 years in a pessimistic scenario. If these learning losses are not reversed, an 8 percent decrease in average labor income for this generation is projected in the optimistic scenario and 16 percent in the pessimistic scenario (World Bank 2024). Gaps and Inequalities in the Transition to the Labor Market Early life choices of young Panamanians vary depending on sex, ethnicity, geographic location, and household type, negatively affecting their transition to the labor market. The primary activities of men and women aged 15–24 in Panama begin to diverge significantly from age 16. While men tend to transition from studying to working at an early age, women, although they remain in the education system longer, are more likely to neither study nor work in later life. In urban areas, only 39 percent of women and 27 percent of men aged 18–24 attend tertiary education, considerably lower than the LAC average of 52 percent (Vieira do Nascimento 2020). These rates are even lower for men and women from rural and indigenous populations (21 percent) and from households with low levels of education (12 percent) (Figure 31). Among these groups, about half of rural, indigenous, or low-educated men work exclusively, while almost half of women neither study nor work. Figure 31. Figure Main31. activities of men and women aged 18 to 24 according to socioeconomic Main characteristics. Activities of People Aged 18–24 by Socioeconomic Characteristic 100% 8% 6% 10% 14% 12% 11% 13% 90% 16% 80% 18% 21% 19% 18% 70% 27% 47% 54% 42% 60% 50% 16% 34% 53% 51% 47% 40% 17% 17% 30% 19% 39% 20% 26% 27% 23% 14% 12% 9% 14% 10% 4% 5% 6% 5% 5% 6% 8% 6% 0% Urban Rural IP Sec. or Urban Rural IP Sec. or less less Women Men Primary or Secondary Tertiary Only works NEET Others Source: Census 2023, calculation by the authors. Note: Other activities include working and studying, just looking for work, and studying and looking for work. NEET are those individuals who report that they neither study nor work. 50 Figure 32. Figure 32. Percentage of individuals with some form of tertiary education degree according to age. Share of People with Some Form of Tertiary Education by Age 30% 5% 5% 4% 5% 25% 3% 4% 1% 3% 2% 1% 20% 15% 20% 20% 20% 20% 19% 19% 19% 19% 18% 16% 10% 14% 10% 1% 5% 5% 2% 1% 4% 3% 3% 4% 4% 3% 3% 3% 3% 3% 3% 2% 2% 0% 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 No University or Technical Career Degree Bachelor's Degree Postgraduate Source: Census 2023, calculation by the authors. Attendance and graduation rates in tertiary education programs in Panama are low. Approximately 36 percent of young people aged 18–24 attend tertiary education, but only 20 percent of 25-year-olds attain a tertiary qualification, suggesting significant dropout rates. Human capital accumulation normalizes around age 30 (Figure 32). A bachelor’s degree is the most common tertiary education qualification, with about 20 percent of individuals completing this level, followed by postgraduate education (5 percent) and technical or non- university education (4 percent), despite the country’s efforts to promote technical programs. There are significant inequities in educational attainment. Only 7 percent of indigenous peoples (IP) and 12 percent of the rural population attain a bachelor’s degree in Panama. There are also differences by gender (17 percent of men vs. 28 percent of women) and between the AD population and those who do not identify as either AD or IP (21 percent vs. 27 percent), although these disparities are not observed at other educational levels. The knowledge areas of tertiary education graduates vary by cohort and population group. There has been a decline in the share of graduates in commerce, teaching, and law, with an increase in those studying services and health. Nevertheless, the share of graduates in science, technology, engineering, and mathematics (STEM) has remained consistently low at around 11 percent across all population groups. Among younger generations, 20 percent of men graduate in STEM compared to only 7 percent of women, which may help explain the limited increase in non-routine jobs and labor productivity growth. Traditional knowledge areas also exhibit disparities: 10 percent of men graduate in health or teaching programs, lower than 24 percent of women. For the non-IP, commerce is the most common field of study, while teaching predominates among IP. Although most IP reside in rural areas, only about 1 percent of them study programs in agriculture or veterinary medicine. 51 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 The number of years of schooling completed by young people strongly influence wages, perpetuating intergenerational inequalities. On average, employed women aged 18–24 have more years of schooling and earn higher wages than men. However, wage disparities are more noticeable than differences in education levels, indicating the influence of other factors in determining labor income (Figure A13). For example, most young people with education up to junior high school or less work in agriculture, mining, or unskilled services (over 93 percent). For those with secondary education, this probability decreases to 77 percent, while likelihood of employment as technicians or mid-level professionals increases to 14 percent. Finally, among individuals with tertiary education, the probability of employment as technicians reaches 34 percent and as professionals to 18 percent. Even among professionals, there are wage disparities across population groups due to differences in degree areas and the quality of education. Limited access to and completion of tertiary education programs may reflect poor alignment with private sector needs and the rapid global changes driven by technology adoption and climate change. Gaps and Inequalities in Health Although education is the primary factor contributing to the lag in human capital accumulation, Panama also faces significant challenges and inequalities in health, particularly in child health and adolescent fertility58. Stunting among children under five years old reveals stark disparities: while 12-13 percent of these children in urban and rural areas experience stunting, this rises to nearly 40 percent among indigenous children (Figure 33). Similarly, in 2022, although the neonatal infant mortality rate per thousand live births was lower in comarcas, the trend in postnatal mortality was reversed. Inequalities in fertility are also significant. Eleven percent of women aged 15–24 in urban areas are teenage mothers, compared to 20 percent in rural areas, 27 percent among indigenous youth, and 19 percent in households whose family heads have low education levels (Figure 34). Teenage pregnancy is strongly correlated with the poverty level of the corregimiento. The frequency of teenage pregnancies may also be related to the fact that 60 percent of young people aged 15–19 report never having received a single talk on family planning, a share that increases to 70 percent for the indigenous and rural population (ENSPA 2019). Studies in the region suggest that lack of opportunities, limited agency of women in labor markets, and society and interpersonal relationships are key determinants of teenage pregnancy (Azevedo et al. 2012). 58 A detailed analysis of the operation, strengths, and weaknesses of the health sector is beyond the scope of this report. However, recent reports by Secci et al. (2024) and Gutiérrez et al. (2024) address these areas. Panama’s health sector would benefit from a comprehensive systematization of its oper- ations. Establishing a unified system would enable the consolidation of complete information on infrastructure, human resources, supplies, and vital statistics, among others critical areas. Such a system would enhance the ability to monitor and assess sector-specific policies and programs. 52 Figure 33 Figure 33. in children aged 0 to 4 by population groups and health region. Stunting Stunting in Children Aged 0–4 by Population Groups and Health Region 49% 21.9 12% 6.3 7.9 7.2 5.5 4.2 Neonatal Postneonatal Maternal Stunting % mortality mortality mortality (0 to 4 years) (under one year) (1 - 11 months) Source: Encuesta Nacional de Salud de Panamá (ENSPA) (2019); INEC (2022). Comarcas Other provinces Note: Infant mortality is calculated per thousand live births. Maternal mortality is calculated per hundred thousand inhabitants, based on the estimated population of women aged 15–49, as of July 1 of each year. Stunting is the percentage of children aged 0–4 years with the indicator Height/Age <-2SD. Figure 34. Figure 34Pregnancy and Motherhood among Women Aged 15–24 Teenage Teenage pregnancy by Socioeconomic and motherhood in Panama according to Characteristic socioeconomic characteristics (women between 15 and 24 years). 50% 45% 43% 40% 35% 33% 30% 30% 27% 27% 25% 20% 21% 19% 19% 19% 20% 16% 15% 12% 11% 11% 11% 10% 6% 5% 0% Urban Rural NI-NA Afro- descendant Indigenous or less Junior high Secondary Superior Prim. Location Race Edu, head Source: Censo de Población y Vivienda 2023, calculation by the authors. Note: NI-NA refers to women who neither belong to the indigenous population nor are Afro-descendants. Mothers Teenage mothers 53 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Panama must address critical inequities in adult health to improve outcomes and reduce disparities. Reducing disparities in prenatal care for pregnant women in comarcas is important, as these inequities are strongly correlated with higher maternal mortality rates (Figure 33). In 2020, indigenous women in comarcas receive, on average, half of the recommended prenatal check-ups, and only 6 out of 10 women receive professional care at birth. The country also faces challenges in primary care, with non-universal, inequitable, and fragmented access, which will be further strained by population aging and rising prevalence of non-communicable diseases (Secci et al. 2024). Furthermore, monthly household health expenditure is notably high and shows a regressive pattern: the poorest quintile allocates 6.6 percent of its total consumption expenditure to health, compared to 4.9 percent for the richest quintile. The poorest households are also more likely to face catastrophic health expenses–defined as expenses greater than 10 percent of consumption (Gutiérrez et al. 2024). Barriers to Human Capital Accumulation Level of Expenditure and Efficiency in the Use of Resources Allocated to Health and Education Historically low levels of government expenditure in the education sector, which have recently increased, combined with inefficiencies in the use of education and health resources, contribute to low levels of human capital in Panama (Figure A14 and Figure A15). In the health sector, Gutiérrez et al. (2023) note disparities in spending between regions, excessive investment in hospital services with low occupancy, an oversized hospital infrastructure relative to primary care, and deficiencies in the procurement and use of medications. In the education sector, there is insufficient data to assess expenditure disparities across regions or evaluate educational inputs, which is key for improving efficiency in the sector. Available data indicate a need to better target educational programs. For example, approximately 61 percent of students whose head of household has a tertiary education receive the Pase-U program, although they likely do not need it (Figure A15). Similarly, according to López (2023), exclusion errors in the Red de Oportunidades program reach 88 percent and inclusion errors reach 35 percent. Available Health and Education Infrastructure Panama faces a shortage of junior high and secondary schools, which may exacerbate dropout rates. Out of the country’s 683 corregimientos, 92 percent have at least one primary school and 84 percent one preschool, while only 66 percent and 34 percent have at least one junior high and secondary school, respectively. This infrastructure gap affects the distance students must travel to the nearest school, especially in rural areas, influencing dropout rates, particularly for secondary education (Figure A16). Other factors, such as irregular topography, bodies of water, poor road quality, and travel costs and time also contribute to these challenges, especially for indigenous and rural populations. For example, although the comarca Ngäbe-Buglé has one of the shortest average distances to a secondary school, it has one of the highest secondary dropout rate. 54 Data on the quality of school infrastructure and teaching materials are limited, but existing information from the Ministry of Education’s Data Integration System (SIDE) (2022) shows significant inequities based on location. In comarcas, only 70 percent of schools have access to electricity, 55 percent to drinking water, and 32 percent to the Internet, much lower than the national averages of 88 percent, 84 percent, and 55 percent, respectively. According to PISA 2022, Panama’s secondary schools have only 0.41 computers per student, of which only 57 percent are connected to the Internet, lower than OECD and LAC averages (0.79 and 0.46 computers per student, respectively, and 83 percent and 59 percent with Internet access, respectively). This ratio drops to 0.27 computers per student in public schools, of which 45 percent are connected to the Internet. Additionally, only 48 percent of students report having access to educational software, with significant disparities between urban (60 percent) and rural (41 percent) areas, suggesting suboptimal use of technology. Health infrastructure and the number of health care professionals are below LAC averages and unevenly distributed. In Panama, there are 1.6 doctors and 3.2 nurses per one hundred thousand inhabitants, lower than the LAC average of 2.3 and 3.8, respectively (WDI 2024). Rural areas experience even lower rates, with the availability of doctors and nurses being 50 percent and 40 percent, respectively, lower in rural than urban areas (INEC 2022). While Panama exceeds the LAC average for the number of hospital beds per 1,000 inhabitants (2.5 vs. 1.9), it falls short of high-income (5.2) and middle-income (3.5) countries. Panama has at least one hospital in each province, and health centers, subcenters, and health posts are distributed throughout the territory. The provinces with the highest rate of health centers and subcenters per ten thousand inhabitants are Los Santos, the Emberá comarca, and Darién, while those with the lowest rates are the province of Panama and the Guna Yala and Ngäbe Bugle comarcas. However, there is no information about the quality of these health centers and the services they provide, suggesting that inequalities in care may be more complex than the data indicate. Quantity and Quality of Teaching Staff High student-teacher ratios in Panama contribute to poor learning outcomes, especially in early education. Before the pandemic, student-teacher ratios in preschool and primary education exceeded those of HICs by 8 and 6 more students per teacher, respectively. Post-pandemic, the number of teachers has increased in junior high school and preschool (decreasing their student-teacher ratios) but decreased in primary and secondary schools (increasing their student-teacher ratios). Evidence suggests that reducing class sizes to no more than eight students, particularly in early grades, improve the quality of learning, emphasizing the need for more teachers in preschool and primary education. Teacher qualifications and training also impact education quality. Only 39 percent of teachers in Panama have a postgraduate degree, lower than an average of 54 percent in the OECD and 28 percent in LAC (PISA 2022). Many lack specialized university training in pedagogy, affecting both their instructional and subject-level knowledge. While teacher training levels are similar across the country, there is no information on their quality. It is important to strengthen teacher assessments in Panama, including defining a detailed framework for 55 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 teacher competencies to identify weaknesses and promote continuous improvement (Cruz- Aguayu et al. 2020), as Panama’s teaching profession attracts students with low academic skills, despite offering competitive wages and high job satisfaction (PISA 2022) (Figure A18). Low Education Quality, Lack of Motivation, and Professional Guidance Neither school dropout rates nor limited access to tertiary education can be attributed to low educational aspirations or inadequate financial returns to education. More than 60 percent of young people express a desire to pursue a postgraduate education, a higher proportion than in OECD countries (PISA 2022), consistent with high economic returns to higher education (Fernández et al. 2024). However, dropout rates, across population groups, are driven by lack of interest, lack of resources, or pregnancy in the case of 14-year-olds. Lack of interest is due to low quality of education and limited opportunities for educational advancement. For example, only 10 percent of principals report that their students receive additional math classes, much lower than average of 29 percent in Latin America and 44 percent in OECD countries. Furthermore, only 20 percent of young Panamanians receive professional guidance from experts, compared to 17 percent in Latin America and 36 percent in the OECD. Lack of guidance influence decisions to dropout or pursue unsuitable careers, which increase dropout rates in tertiary education. Finally, the tertiary education system does not have an adequate information system, accreditation mechanisms, and links to the productive sector, limiting the ability to respond to changing business demands (Reisberg 2021). Teenage Pregnancy Teenage pregnancy has serious repercussions on human capital accumulation and women’s integration into the labor market, worsening poverty, inequality, and social mobility. Only 9 percent of women aged 18–24 who are teenage mothers attend a tertiary education institution, much lower than 39 percent of women who are not (Figure 35). The probability of not being in education, employment, or training (NEET) is close to 60 percent for teenage mothers, compared to 28 percent for their peers. These differences are amplified when comparing rural or indigenous women, where the rate of NEET is high even for those who are not teenage mothers. 56 Figure 35. Figure 35. Women’s Activities By Adolescent Maternity (Aged 18–24) Women's activities according to adolescent maternity (18 to 24 years). 100% 3% 4% 4% 1% 4% 4% 2% 1% 90% 22% 25% 80% 41% 48% 70% 11% 53% 55% 65% 10% 65% 60% 15% 6% 15% 50% 5% 16% 40% 6% 6% 19% 3% 3% 30% 44% 21% 42% 20% 20% 29% 20% 20% 19% 10% 11% 11% 7% 6% 4% 5% 5% 5% 7% 5% 0% 4% 4% Not teenager Teenage Not teenager Teenage Not teenager Teenage Not teenager Teenage mother mother mother mother mother mother mother mother Urban Rural No PI IP Attending secondary Attending tertiary Only works Studies and works NEET Others Nota: Other activities include working and studying, only looking for work, studying and looking for work. NiNi Source: Censo deare those individuals Población who y Vivienda report (2023). that they by Calculation neither study or work. Source: Census (2023). the authors. Calculation Note: Other by the authors. activities include working and studying, only looking for work, studying and looking for work. NEET = Not in education, employment, or training. 2.5 Progress Achieved Is at Risk: Vulnerability to Poverty and Natural Hazards In 2022, 31.6 percent of the Panamanian population was vulnerable to poverty59. Vulnerability to poverty is commonly defined as the risk that households will fall into or remain in poverty due to idiosyncratic (household-specific) risks, external risks (e.g., flooding), or aggregate risks (e.g., a recession). The vulnerable population includes those who are currently poor or face a probability greater than 50 percent of being poor in the next two years. Following Barriga-Cabanillas et al. (2023), this section assumes that the probability of being poor, obtained using the small area estimation method, would remain for the next two years, and it estimates poverty vulnerability at the level of the corregimiento. Almost 9 percent of the country’s inhabitants experience risk-induced vulnerability (those who were not poor in 2022 would be poor at some point in the next two years). The risk is almost universal in comarcas (Figure 36). However, due to their larger population size, a significant proportion of people at risk of poverty are concentrated in the provinces of Panama, Chiriquí, and Panama Oeste. In addition to being vulnerable to poverty, Panama’s population is exposed to various natural hazards. Exposure varies by hazard type, with flooding, extreme heat waves, and wildfires 59 This section defines national poverty using the 2022 moderate and extreme poverty lines. 57 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 being the most prominent hazards. The country faces high risk associated with river, pluvial, and coastal flooding, as well as earthquakes, landslides, tsunamis, volcanic activity, and wildfires. (ThinkHazard! 2020). Panama is one of the countries most exposed to natural hazards, with substantial mortality associated with these risks. Data from the World Bank’s Climate Change Knowledge Portal (CCKP) show that between 1982 and 200860, Panama experienced 32 disasters, resulting in economic damages estimated at US$86 million and 249 lives lost. Panama ranked 14th globally in terms of exposure to multiple hazards relative to its land area, with 15 percent of its territory and 12.5 percent of its population exposed to two or more risks61. The country also ranks 35th worldwide in terms of mortality caused by natural disasters. Figure 36 Figure 36. Poverty- and Risk-Induced Vulnerability 1.0 0.9 0.8 0.7 Vulnerability 0.6 0.5 0.4 0.3 0.2 0.1 0.0 . Pa n í n lé l a l á qu as ra rá os na ro é n te ló rié er a m c gl ba gu Ru l be Co Co iri To nt es Ya r tio na Da r Bu He Ur Ch ra Pa s Sa aO Em el na Na Ve e sd Gu äb m C. Lo ca na Ng C. Bo C. Induced by poverty Induced by risk Source: Censo de Población y Vivienda 2023, Encuesta de Propósitos Múltiples 2022. Flooding represents the most frequent natural hazard in Panama and has the greatest impact in terms of affected population. According to CCKP data, between 1980 and 2020, flooding occurred 32 times, followed by storms, droughts, and earthquakes, each with seven occurrences. During this period, flooding affected a total of 172,278 people, making it the most significant natural disaster, drought affected 81,000 people in a single event in 1983, storms affected 45,282 people, and earthquakes affected 21,511 people. Given the frequency, impact, and risks associated with flooding (as well as the availability of data on this type of natural hazard)62, this report focuses primarily on flooding. 60 The information consolidated by the CCKP only includes up to 2008. 61 Extracted from the OFDA/CRED International Disaster Database – www.emdat.be – Université Catholique de Louvain – Brussels – Belgium. 62 The flooding scenarios were prepared by Fathom, and this section uses Fathom V3. 58 Climate change will significantly increase the likelihood of extreme flooding in Panama. By mid-century, under the Shared Socioeconomic Pathways-3 7.0 (SSP-3 7.0) scenario63, the probability of flooding will almost double, particularly in the provinces of Darién, Los Santos, and Herrera. Projections for 2035–2064 show that the country’s central and eastern Pacific coastal provinces will experience nearly a twofold increase in the probability of extreme precipitation events compared to historical 100-year return periods. Droughts in Panama have a significant economic impact. According to the recent study by Barnes et al. (2024), the most severe droughts have been the result of the El Niño Southern Oscillation (ENSO) events, while abundant rainfall was recorded in the watershed that feeds the Panama Canal during La Niña years. According to Barnes et al., water in the watershed is not only stored in Gatun and Alajuela lakes for operating the Panama Canal but is also used to supply fresh water to 55 percent of the Panamanian population. For example, water from the watershed provides 95 percent of the water needs of both Panama City and Colón, consuming 30 percent of the water in the watershed. In 2023-2024, the intensification of El Niño caused water shortages and restricted the transit of ships through the Panama Canal, resulting in considerable economic losses. Addressing drought-related challenges involves better water management, particularly as 42 percent of drinking water is currently lost due to leaks, and infrastructure investments, such as the proposed Rio Indio dam, which would take approximately five years to complete. The most severe flooding events, although also the least common, can affect up to 18 percent of the population. The probability of a climate event occurring is measured by the return period; for example, an event with a 100-year return period is one in which there is a 1 in 100 chance of occurring in any given year. Over a 30-year time horizon, there is a 26 percent chance of an event with a 100-year return period occurring, since it can be approximated as the sum of probabilities of the event occurring in each of the 30 years64. Flooding can be categorized as river, pluvial, or coastal. River flooding is caused by the overflow of rivers or streams; pluvial flooding is the result of the rapid accumulation of rainwater; and coastal flooding is caused by rising sea levels in coastal areas. Considering all types of flooding with a 100-year return period, an estimated 18 percent of Panama’s population would be at risk of flooding. Pluvial flooding, which is a less severe flooding event, can affect large areas of the country. Over a 30-year horizon, there is a 79 percent and 26 percent probability of a pluvial flooding event with a 20-year return and 100-year return period, respectively (Figure 37) (Figure 38). In both scenarios, the maximum water depth would be less than one meter but would affect large parts of the country. Pluvial flooding with a 100-year return period could affect up to 647,00065 people nationwide, with 460,000 in urban areas and 187,000 in rural areas. The province of Panama is at the greatest risk, with a potentially affected population of 253,000 people, followed by Panama Oeste and Chiriquí. 63 The CCKP’s projections uses the SSP3-7.0, which is a climate scenario characterized by high population growth, slow and uneven economic development, and limited international cooperation. This climate scenario would lead to a significant increase in greenhouse gas emissions. 64 For example, assuming independence, it can be approximated with 1-(1-(1/return period)) ^(horizon) = 1-(1-0.01) ^30=1-0.99^30=0.2603. 65 Since there is no georeferencing information available for all homes, the geographic extent of populated areas with the depth of flooding in each of the scenarios was compared to estimate the number of people affected. The number of people currently living in the affected areas was then calculated by proportionally distributing the population based on the size and population density of the populated area. 59 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 River flooding would impact fewer people than pluvial flooding but would have more severe effects. River flooding with a 100-year return period could affect up to 46,500 people across Panama, of which 16,400 in urban areas and 30,000 in rural areas. The province of Bocas del Toro faces the greatest risk, with 19,400 people potentially affected, followed by Darién, with 6,900 people exposed to flooding several meters deep. In some areas, such as Darién, floodwaters could reach depths of more than six meters. Finally, coastal fooding mainly affects people living in Guna Yala and Bocas del Toro. Coastal flooding with a 100-year return period is expected to affect fewer people than pluvial and fluvial flooding, with an estimated 37,300 people at risk throughout the country. Of these, 17,800 people would be in urban areas and 19,500 in rural areas. The comarca Guna Yala, with 15,500 people, and the province of Bocas del Toro, with 12,700 people, are the most exposed regions to this type of flooding. Figure 37. Pluvial Flooding with a 20-Year Return Period Under the SSP-3 7.0 Scenario (Panama City) Figure 37 Pluvial ooding 1 in 20 SSP-3 7.0 Band 1 (Gray) 100 cm 0 cm OpenStreetMap Source: Fathom V3. 60 Figure 38. Figura 38 Flooding with a 100-Year Return Period Under the SSP-3 7.0 Scenario (Panama City) Pluvial ooding 1 in 100 SSP-3 7.0 Band 1 (Gray) 100 cm 0 cm OpenStreetMap Source: Fathom V3. The poor and non-poor are equally exposed to natural hazards. Eighteen percent of the population, including 19 percent of the poor, face flood risks. Flooding affects poor households, those vulnerable to poverty, and the rest of the population alike. A comparison of the proportions of the poor and non-poor population exposed to river, pluvial, and coastal flooding with 100-year return periods revealed no relevant discrepancies, either in terms of proportions or severity, as measured by flood depth. The only exceptions were the provinces of Bocas del Toro, Guna Yala, and Emberá-Wounaan, where the poor experience slightly higher flood risks than the non-poor. (Figure 39)66. Figure 39 Figure 39. Percentage of Poor and Non-Poor Affected by River, Pluvial, and Coastal Flooding Population (in %) in risk of flooding (all kinds) 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0     a not poor poor te not poor poor ro not poor poor í not poor poor n not poor poor é not poor poor as not poor poor é not poor poor la not poor poor ra not poor poor n not poor poor not poor poor an not poor poor l not poor poor not poor poor al not poor poor   qu na os an rié ló cl gl m re r Ya To gu es Ru na nt iri Co Co io Bu na rb Da er O ra Sa Ch at na el ou U Pa H be a Ve N sd Gu -W s m Lo gä ca na rá N Bo Pa be Em ]0 cm, 10 cm] ]10 cm, 30 cm] ]30 cm, 50 cm] ]50 cm, 100 cm] ]100 cm, 150 cm] ]150 cm, 200 cm] ]200 cm, 300 cm] ]300 cm, 600 cm] ]600 cm, 1000 cm] Source: Fathom V3, Censo de Población y Vivienda 2023, Encuesta de Propósitos Múltiples 2022. 66 To analyze differences in flood severity between the poor and non-poor, poverty levels were estimated at the populated center level using income vec- tors from poverty maps and small samples. The proportions of poor and non-poor households affected were then calculated. Averages and totals were subsequently aggregated at the provincial, urban, national area, and national total level. 61 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Lower-income households are disproportionately affected by flooding due to their limited resources to cope with its effects. These households tend to reside in dwellings made of precarious materials, reducing their resilience to disasters. Furthermore, their ability to adapt and recover from flooding damage is often constrained by lack of savings, insurance, and other financial resources to cover repair and reconstruction costs. One-third of the poor population lives in households that do not receive social protection benefits. Specifically, 31 percent of poor individuals live in households where no member is a beneficiary of the student scholarship, 120 a los 65 transfer, Ángel Guardian, or Red de Oportunidades programs. Nationally, 7.7 percent of the population in poverty does not have access to any of these programs, ranging from 4.9 percent in the province of Panama Oeste to 18.8 percent in the comarca Ngäbe Buglé (Figure 40). The coverage of the country’s social protection programs is not uniform across the country. The four major social protection programs have service rates that vary between districts and corregimientos. For example, the percentage of poor people over age 65 who report receiving benefits from the 120 a los 65 program varies from 22 percent in San Miguelito to 80 percent in Taboga. Similarly, the percentage of poor school-age children who report Figurebenefits receiving 40 from the Pase-U program varies from 26 percent in the district of Remedios to 87 percent INGLES in Balboa. Figure 40. Share of People Living in Moderate Poverty and Coverage by Social Program 1.0 0.05 0.03 0.06 0.9 0.07 0.09 0.18 0.19 0.23 0.24 0.30 0.32 0.8 0.38 0.42 0.22 0.20 0.10 0.43 0.44 0.47 0.43 0.08 0.10 0.55 0.52 0.7 0.12 Population percentage 0.07 0.09 0.6 0.07 0.30 0.05 0.06 0.09 0.08 0.5 0.38 0.05 0.30 0.4 0.42 0.37 0.07 0.66 0.71 0.42 0.33 0.66 0.41 0.34 0.3 0.41 0.40 0.29 0.34 0.2 0.43 0.30 0.34 0.1 0.21 0.21 0.17 0.14 0.10 0.10 0.14 0.10 0.08 0.08 0.0 la n é o n s lé ón ra os te uí á . l o al na ua aa gl or ié m an Ya oc ur es riq re nt ol Bu lT ar io na ag n rb R er C C Sa O hi ac a ou D de Pa U H r C un be á Ve N -W s m s G Lo gä ca na rá N Bo Pa be Em Poor being served Not poor being served Poor unserved Not poor unserved Source: Censo de Población y Vivienda 2023, Encuesta de Propósitos Múltiples 2022. 62 Pillar I: Promote the Closing of Territorial and Ethnic Gaps To foster inclusive growth and reverse 3. territorial and social exclusion in Panama, the country needs to promote opportunities for the IP, rural communities, and other vulnerable groups. This can be achieved with a long-term, inclusive regional development strategy that Tools complements Panama’s main growth poles while promoting: (a) access to productive assets through adequate to Reduce Poverty decentralization of basic services and improved connectivity with urban and Inequality centers; (b) the creation of economic poles to expand economic opportunities in lagging areas, including through sustainable agriculture, green economy initiatives, and sustainable tourism; and (c) strengthened local governance and citizen participation. In the short term, it is important to expand social assistance programs to protect vulnerable groups (in both rural and urban areas) and mobilize resources for inclusion and growth. The authorities should consider: • Improving basic infrastructure to close the country’s productive gaps. Currently, access to services in comarcas is much worse than it was in urban areas 20 years ago, and only 21 percent of the population has access to quality roads. It is necessary to prioritize medium-term investments in water, electricity, health, and education, as well as in infrastructure to connect rural areas, especially tourist areas and migrant-receiving 63 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 communities, with urban centers. Panama has already incorporated the closing of territorial disparities as a central element in its national agenda. In 2022, the government launched Plan Colmena to strengthen local capacity and coordinate the provision of public services for community development. • Generating long-term economic opportunities in comarcas by leveraging their productive and market capacities. Economic development in comarcas can be accelerated through investments and by strengthening public-private partnerships aimed at improving agricultural productivity (e.g., cocoa and coffee), promoting sustainable tourism (ecotourism and cultural tourism), and sustainably managing natural resources. Specifically, Panama should implement initiatives to: • Improve productivity. Long-term investments in agricultural infrastructure, roads, and highways, appropriate technology, sustainable practices, training programs, and technical support for farmers are critical to increase productivity. In line with World Bank Country Partnership Framework recommendations, the country’s agricultural production systems are diverse, and there are significant untapped opportunities to add value for both domestic consumption and exports through further development and diversification of agribusiness. Progress has already been made to improve family farming, including the development of the National Family Farming Plan in 2020. • Promote new economic activities in rural areas. The country’s natural resources and cultural heritage can be leveraged for sustainable tourism through institutional agreements and medium-term sector-specific instruments. These initiatives should align with sustainable resource management, such as strengthening forest management as outlined in the development of the Emberá-Wounaan Comarca Development Plan. • Strengthening the capacity of subnational governments to plan, design, and manage key infrastructure and services and reduce disparities. Lack of coordination and dialogue between indigenous authorities and government agencies has hindered investment in indigenous comarcas (World Bank 2018). Despite progress, such as the adoption of the National Plan for Indigenous Peoples and the creation of the National Council for the Integral Development of Indigenous Peoples, both indigenous and government authorities require capacity building. Strengthening government management through improved subnational governance and effective decentralization (e.g., by improving regulatory frameworks and strategic planning) is essential to integrate ethnic, gender, and territorial inclusion into key public policies. • Improving and expanding social assistance programs and information systems to protect vulnerable groups in the short term. Current social assistance programs often benefit middle- and high-income households67. For instance, subsidies such as those for liquefied petroleum 67 For example, while some eligible people in comarcas are excluded from the 120 a los 65 Program, some of these benefits reach households in the high- est quintiles (World Bank 2023). 64 gas (LPG) mainly benefit rich and urban areas68. To address this imbalance, the 2022 Poverty Map provides an innovative tool for better targeting of programs and investments in lagging areas. There is also a need to systematically understand the redistributive capacity of subsidies, programs, and taxes in Panama and their potential for reform. While a comprehensive regional development strategy is essential for increasing inclusion in the long term, short-term measures must focus on supporting vulnerable groups. In line with the recommendations of the 2023 Systematic Country Diagnostic Update (World Bank 2023), one key recommendation is to expand the coverage of programs, such as RdO, to include more poor households, especially in indigenous territories. In the past, these programs have played a significant role in poverty reduction. • Improving resource mobilization to increase investments in lagging areas in the short term. The high geographic and sectoral concentration of investments in the Trans-isthmian region adversely affects other territories and reinforces territorial and social exclusion. Remote rural areas, mainly comarcas, face limited access to basic services, restricting income-generating opportunities and budget allocation for decentralized services. Addressing these disparities requires prioritizing investments in key infrastructure and services. • Creating fiscal space for initiatives aimed at increasing inclusion and growth. Panama’s tax revenues are among the lowest in LAC. Its tax revenue as a percentage of GDP is 13.1 percent, lower than the regional average of 21.5 percent (OECD et al. 2024). Nevertheless, Panama has taken important steps to strengthen and modernize its public financial management system through initiatives such as the Panama Compras and the Integration and Technological Solutions of the Operational Management Model (ISTMO). To increase resource mobilization, Panama needs to implement a strategy that: (i) prioritizes key public investments; (ii) improves the targeting of subsidies; and (iii) develops a comprehensive tax reform that increases revenue mobilization while minimizing its impact on poverty. This will require a thorough understanding of the redistributive capacity of subsidies, programs, and taxes in Panama, as well as their potential reforms. A critical first step will involve improving the availability of relevant information, including the disclosure of official data and methodologies for the measurement of poverty, income, and other well- being indicators. 68 World Bank estimates suggest that 15 percent of the current LPG subsidy is absorbed by the richest decile, while only 5 percent is absorbed by the poorest. 65 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Pillar II: Promote the Accumulation of Human Capital and Growth of Productive Jobs The Panamanian authorities need to adopt human capital and labor market reforms to increase labor productivity and quality jobs. From the perspective of the labor supply, interventions must address multiple challenges in human capital accumulation, targeting stages from early childhood development to tertiary education, and provide opportunities for people who have exited formal education69. Additionally, reforms need to address challenges related to labor demand by modifying labor regulations and strengthening institutions. To improve the labor supply, the authorities should consider: • Reducing infant mortality, malnutrition, and adolescent fertility by implementing multisectoral strategies. In the medium term, this would involve reducing disparities in access to basic services such as sewage and drinking water in rural areas and comarcas through investments in infrastructure (e.g., investments proposed in the Colmena Plan). At the national level, expanding and improving the coverage of the Red de Oportunidades program could promote regular medical check-ups for children. The recently approved Public Policy on Early Childhood in Panama should be implemented to improve children’s health and cognitive skills (Attanasio et al. 2022) while encouraging maternal labor participation. To reduce adolescent fertility, the authorities need to ensure the short-term implementation of the recently approved Education in Sexuality and Affectivity guidelines nationwide and carry out awareness campaigns on the cycle of poverty associated with early pregnancy (Miller and Babiarz 2016; Dupas et al. 2024). Finally, to reduce inequality in access to health services and improve resilience to climate disasters, Panama should assess and continue efforts to expand and consolidate the Telemedicine program (Secci et al. 2024), which is supported by existing laws (Law 203 of 2021). • Achieving high-quality universal preschool education. In the short term, this would involve implementing national campaigns that highlight the importance of a solid educational foundation in early childhood for future academic success (Heckman 2011). It would also involve studying barriers to preschool, particularly in rural areas and among the IP long- term initiatives include evaluating and ensuring standards of excellence in service quality, including infrastructure, academic programs, curricula, and teacher training (Bendini et al. 2022); increasing the coverage of preschool education; and improving the capacity, quality, and number of teachers. • Reducing early dropout through differentiated strategies. While lack of interest is a common reason for dropping out of school, resource scarcity and limited educational opportunities are particularly prevalent challenges in rural areas. While constructing new schools is needed in rural areas and comarcas, improving the quality of education is 69 Given the budgetary constraints faced by all countries, the authorities should prioritize the implementation of strategies that ensure the largest possi- ble increases in learning-adjusted years of schooling (Angrist et al. 2020). Many of the policies recommended in this report, such as increasing access to date, improving teacher capacity, and improving infrastructure in comarcas, are among the most cost-effective. 66 essential across the country. Short-term initiatives include launching national information campaigns highlighting disparities in labor returns (Jensen 2010) and implementing an early warning system for students at risk of dropping out based on administrative data. The authorities also need to strengthen existing programs, such as PASE-U and the Estudiar sin Hambre program, through impact evaluations that provide guidance for better targeting and design (Barrera et al. 2011; Collante et al. 2022). Flexible remedial programs that include vocational or technical training, in collaboration with INADEH, can be beneficial for those that have already dropped out, particularly for people living in rural areas and comarcas. • Improving the quality of education nationwide. Improving learning outcomes at all educational levels in Panama is a priority, as only 16 percent of young people reach a minimum level of competence in mathematics. Multiple strategies are required to address this issue. Short-term measures include using data from national and international tests to identify areas for improvement and design remedial class programs to close skill gaps. The authorities also need to resume census assessments in 3rd and 6th grade through SIMCE and introduce junior high and secondary school assessments. Medium and long- term initiatives include improving the capacity of teachers by attracting qualified candidates, providing solid initial training in disciplinary and pedagogic knowledge, and incorporating a teacher assessment system with classroom observation and continuing education programs with classroom support (Bruns et al. 2014; Cruz-Aguayu et al. 2020). Advances in artificial intelligence also underscore the importance of efficiently integrating ICT into education, ensuring proper infrastructure, teacher training, and adequate teaching materials. World Bank resources such as the ETRI, Teach, and Coach can guide the implementation of these policies. Finally, Panama should strengthen government initiatives to modernize the national curriculum, with a special focus on the needs and characteristics of the IP (World Bank 2023). • Strengthening tertiary education to increase worker productivity and improve the transition to the labor market. Low levels of coverage and graduation at the tertiary level necessitate continued strengthening of technical and technological programs. Short-term initiatives include incorporating professional guidance programs for young people and establishing tertiary education financing programs based on meritocracy, need, and program quality (Londoño-Velez et al. 2020, 2023; Melguizo et al. 2016). Medium-term initiatives include studying the relevance of tertiary education programs in terms of demand, improving access to technologies, and advancing the country’s development objectives. Long-term initiatives include analyzing investment needs in infrastructure and equipment for existing tertiary education institutions, implementing an accreditation system, and creating a centralized information system that includes student records and information on program quality. Programs that update and improve the knowledge and skills of people in the labor market should also be prioritized to increase their productivity. 67 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 • Increasing the efficient use of public resources and ensuring program success by strengthening the Ministries of Education and Health70. Medium-term initiatives include modernizing these ministries’ information systems, increasing coordination between them, and establishing accountability mechanisms (World Bank 2023). In line with recommendations of Pillar I, consolidating the public financial management system—a collaboration between Panama and the World Bank since 2010—should continue in the short term. In comarcas, the authorities should implement results-based budgeting using a per capita approach and allocated by economic unit while establishing health, education, and comprehensive early childhood care centers. Panama needs supply-side interventions to support the population that has exited the formal education system. Medium-term priorities include implementing ongoing national education and skills training programs for different economic sectors and updating and improving work skills to meet new market demands. Requalification and continuing education programs can help workers remain competitive and productive. To support this segment of the population, the authorities should consider: • Continuing education programs tailored to the location and skills profile of vulnerable groups. Institutions such as INADEH and Public Employment Service could, in the medium term, adapt their services to address the specific needs of the poor, migrant, indigenous, and low-skilled population. They could do this by better understanding the skill profiles of these groups, launching campaigns to promote the use of institutional services among minority groups, developing programs focused on the cultivation of productive skills, and strengthening their institutional presence in regions with large minority populations such as indigenous comarcas. For the NEET population, especially dropouts who have not completed secondary education, the authorities could create flexible remedial programs that include vocational or technical training. This could be done in collaboration with INADEH, an institution actively exploring economic opportunities to train young people aged 15–17 in areas that in demand. • Addressing the unique needs of groups facing challenges in securing quality jobs. In recent years, the government has launched several active labor market programs in both rural and urban areas. These include Aprender Haciendo (2019), which promotes labor integration for young people aged 17–24; Empleabilidad Comunitaria (2021), which targets young people and adults in communities where state infrastructure projects are being developed; and Bolsa Electrónica de Empleo (2018), among others. Short-term initiatives include conducting an impact evaluation of these programs and a review of international best practices. This would help determine the feasibility of increasing investment in active labor market programs, ensuring their cost-effectiveness, and minimizing distortions or displacement effects on non-participants. 70 Coverage increases and improvements in educational quality have been central axes of the policies proposed by successive governments in Panama. Recent programs and initiatives include expansions in coverage through the construction of infrastructure in comarcas (Colmena Plan and the imple- mentation of the National Plan for the Integral Development of Indigenous Peoples, which includes a model for the management of education centers); incentives for school attendance (PASE-U and Estudiar sin Hambre); the introduction of information technologies as a key tool in the sector (Law of Dig- ital Equity); the promotion of tertiary education, especially technical and technological careers (the creation of ITSE and the strengthening of INADEH); the institutional strengthening of bilingual intercultural education and traditional medicine; and the establishment of the Comprehensive System for the Improvement of the Quality of Education (SIMECE). In the health sector, in addition to the Colmena Plan, efforts include the implementation of the National Plan for the Comprehensive Development of Indigenous Peoples (which involves the design and execution of plans for the comprehensive opening of health facilities); the implementation of the Telemedicine Master Plan and the National Plan for Sexual and Reproductive Health 2021– 2025; and advances in information systems, such as those for health care professionals. 68 On the labor demand side, policies to foster innovation, entrepreneurship, productivity, formalization, and sustainability of MSMEs are necessary to improve employment income and the quality of work for lower-income households. Panama has taken steps to increase its innovation capacity and promote entrepreneurship. In 2007, the country established the National Secretariat of Science, Technology and Innovation (SENACYT) and developed national strategic plans for science, technology, and innovation (PENCYT), the most recent covering 2019–2024. Additionally, initiatives such as Panama Emprende71 in 2017 and the 2020 legal framework for entrepreneurs have streamlined processes and reduced the time required to register a company by providing entrepreneurs with a virtual one-stop shop and temporary tax benefits. To continue to foster innovation, promote formal employment, and accelerate business growth, the authorities should consider: • Enhancing the information system and periodic collection of labor demand data in the medium term. Comprehensive data on MSMEs, both formal and informal, and job vacancies are essential for designing policies that foster the growth of small and medium-sized enterprises and optimize workforce allocation. While Panama currently gathers valuable periodic data on formal companies with more than five workers in specific sectors and has initiated a new national business census, significant information gaps remain on small companies (mostly informal), which employ most poor workers. This lack of information hinders the design of targeted policies to promote the growth of small companies. Additionally, policies supporting the development of a robust vacancy system could provide additional information on labor market trends and the country’s educational needs. • Improving the institutional framework of the national innovation system to promote productivity growth and entrepreneurship in the medium term. Policies to enhance scientific funding, particularly from the private sector, and promote better coordination between institutions involved in science and technology policy could improve efficiency by balancing strategic objectives, activities, resources, and responsibilities. Results-based funding programs and political support for training in public and private universities could also improve the quality of education, produce more technical professionals, and promote research. • Conducting rigorous impact assessments of strategic innovation and formalization plans and credit access programs in the short term and developing alternative strategies to reduce MSMEs’ operational costs in the medium term. Panama would benefit from a comprehensive analysis of the efficiency of innovation plans and the costs and procedures faced by small and medium-sized enterprises in different economic sectors and regions. Additionally, registration programs should incorporate a component that reduces costs and administrative burdens while making the process of employee affiliation to social security more flexible. • Promoting the use of technologies within sectors and jobs. This would require public and private efforts from both the supply and demand side of the labor market to increase workers’ cognitive skills and job opportunities. Short-term initiatives include promoting collaboration between the public sector, productive industries, and academia to increase innovation and 71 National Competitiveness Center (2024). Annual Competitiveness Report 2023. CNC: Panamá. 69 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 entrepreneurial capacity among entrepreneurs and companies. Simultaneously, industries must take steps to increase the supply of qualified workers, ensuring that inequalities in access to these jobs do not widen. Educational and job training institutions such as INADEH and ITSE must focus on teaching foundational and generic skills, leaving room for the productive sector to provide training on specific technologies. The promotion of short and modular career paths, complemented by carefully designed and fiscally sustainable subsidies to support company productivity (World Bank 2024b), can serve as a first step. • Identifying and supporting economic sectors where the adoption of technologies results in inclusion benefits. The integration of technologies in sectors such as agriculture can drive productivity and increase resilience to climate events (Edmund and Viollaz 2024). Creating an industry identification process in the short term and adopting digital technologies and automation in agriculture, facilitated through extension services, in the medium term could help drive agricultural productivity and close skills gaps. Finally, Panama needs to improve regulatory frameworks and implement other cross-cutting reforms to increase inclusive growth. To improve the labor market, the authorities should consider: • Encouraging formalization and job reallocation in high-productivity sectors to address distortions created by labor policies. The country’s productivity gains in recent decades have largely occurred within sectors, rather than through the reallocation of workers to more productive sectors. Medium-term initiatives include conducting a systematic review of labor policies, particularly those that impose high administrative costs on hiring and dismissing formal workers, and areas where Panama exhibits the greatest rigidity. Additionally, reviewing and simplifying the minimum wage matrix by incorporating productivity indexations for specific sectors could help improve labor formalization. • Removing barriers to women’s inclusion in the labor market. In Panama, women’s labor participation remains lower than that of men. High fertility and teenage pregnancy rates, the disproportionate burden of caregiving tasks on women, poor access to child care centers, and wide disparities in parental leave policies (i.e., three months for women versus three days for men) hinder women’s participation in the labor market, especially among the poorest households. Although policies such as the Policy for the Employability and Labor Insertion of Women with Vulnerable Conditions (2021) have been adopted, more targeted efforts are needed that address the needs of vulnerable women. Medium-term initiatives include designing programs that reduce time spent on caregiving tasks and provide incentives for hiring women, especially among the vulnerable population. Increasing access to childcare, establishing and enforcing quality and safety standards, and raising awareness of the benefits of childcare services can help boost demand for these services and increase women’s labor participation. Also, in urban areas, aligning retirement ages for men and women would encourage the hiring of women and promote gender equality, ensuring that men and women receive equal retirement benefits. 70 Pillar III: Promote Household Resilience to Natural Hazards To improve household resilience through the social protection system, the authorities should consider: • Identifying households in or at risk of poverty that currently do not receive social protection benefits. Currently, one-third of poor households are not covered by the social protection system. Identifying these households is important to understand the gaps in coverage and address the barriers preventing access to existing programs. The authorities also need to collect socioeconomic, demographic, and geographic data to build a complete profile of households living in or are at risk of extreme poverty. • Maintaining a registry of beneficiaries with georeferenced information linked to administrative records. A registry with detailed data on beneficiaries, including geographic location and links to relevant administrative records, will enable better targeting of poor households without coverage and households affected by disasters. Such a registry would provide a comprehensive view of the needs and conditions of each household, allowing for tailored programs. It would also support monitoring and evaluation efforts, allowing the authorities to measure program impacts, identify inefficiencies, and make evidence-based adjustments. Prioritizing resources for the most vulnerable households will maximize the social return on investment in social protection, enhance poverty reduction efforts, and promote equity. • Conducting impact assessments of social programs to improve the quality of social expenditure and investment. The four main social protection programs lack homogeneous territorial coverage, leaving one-third of the poor without coverage. Rigorous assessments of these programs’ coverage and impact are needed to determine whether these programs meet their objectives and achieve the expected outcomes. These evaluations should identify areas for improvement, inefficiencies, and unintended effects, providing insights for refining program design, targeting, and implementation. • Developing an adaptive social protection system. With climate change increasing the likelihood of extreme weather events, Panama’s social protection system must be able to adapt and respond to disasters, economic crises, and public health emergencies. Targeting must be dynamic, as households enter and exit poverty for various reasons. Integration with sectors such as health, education, and employment will ensure a comprehensive response to the needs of the population. Community participation is also essential to align programs with local priorities. To sustain poverty reduction over time, the country’s social protection system must balance efforts to reduce poverty with efforts to ensure long-term growth. To improve integrated disaster risk management (IDRM), the authorities should consider: • Increasing resilience by identifying areas and households at risk, prioritizing care for those with the greatest needs, and keeping communities informed. Identifying areas, homes, infrastructure, and economic activities at risk of flooding and other disasters, such as droughts, is important to improve resilience to disasters and climate change. A flooding analysis reveals that there are areas across Panama at high risk of flooding several meters 71 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 deep. Mapping risk exposure will enable the authorities to assess the magnitude and distribution of vulnerabilities and allocate resources effectively. Additionally, disseminating risk information to businesses, investors, and citizens will promote informed decision- making and encourage the adoption of prevention and mitigation measures. Effective risk communication will foster a culture of prevention, reducing exposure and optimizing available resources to protect the most affected populations. • Adopting resilient building codes and investing in critical infrastructure to minimize the impacts of disasters and guarantee sustainable and safe development. Large areas of Panama are exposed to low-depth pluvial flooding. Given the higher likelihood of low-intensity events, it is important to ensure resilient housing and infrastructure. To foster sustainable and resilient development, the authorities need to adopt building codes that promote risk- adapted infrastructure and housing, avoiding areas with greater exposure, and ensuring the use of a cost-benefit approach. These measures must be implemented in coordination with government entities and the private sector, ensuring their compliance. Furthermore, investing in resilient infrastructure, especially in critical sectors such as communication routes and water systems, is vital to minimize the adverse impacts of disasters and facilitate recovery. Strengthening and adapting existing infrastructure will also improve its resilience to extreme events, protect communities, and generate long-term savings by reducing costly post-disaster repairs and reconstruction. • Preparing and updating contingency plans, implementing risk reduction strategies, and investing in early warning systems for effective disaster risk management. Government agencies need to prepare and regularly update their contingency plans, set clear responsibilities, and create effective coordination mechanisms. 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Most teenage mothers neither study nor work. Most teenage mothers neither study nor work. 100% 90% 80% 28% 70% 59% 10% 60% 50% 15% 40% 5% 30% 20% 20% 43% 10% 14% 0% Teenage mother Not teenage mother Only studies Only works Studies and works NEET Other Formality (rich 60%) Source: Censo de Población y Vivienda, 2023. poor 40% Income: Income Occupation Figure A 2-3. Participation Figure A 2. Figure A 3. Formality Change in Labor Market Gap by Group, 2001–2023 Labor Market Gaps by Group, 2023 (25-64) Income 15-24 Age: Occupation Participation Formality Women (rich 60%) poor 40% Income: Formality Income (Men) Occupation Figure A 2-3. Secondary (tertiary) Income 10 Edu: Participation 0 Formality Occupation Income: -10 Indigenous poor 40% (25-64) Income -20 15-24 (Non-Indigenous) Age: Participation (rich 60%) Occupation -30 Formality Participation -40 Women (Men) -50 (tertiary) Formality Income Primary -60 Edu: Secondary (tertiary) Income 10 -70 Edu: 0 Occupation Income: Occupation -10 -80 Indigenous poor 40% -20 (Non-Indigenous) Participation Participation (rich 60%) Age: -30 Edu: Formality 15-24 -40 None Formality (25-64) -50 (tertiary) (tertiary) Income Primary -60 (tertiary) Edu: Income None -70 Edu: Occupation -80 Occupation Participation Age: Edu: 15-24 None Formality (25-64) (tertiary) Participation Edu: Edu: (tertiary) Income None Edu: Formality Secondary Primary (Non-Indigenous) Occupation (tertiary) (tertiary) Indigenous Participation Income Edu: Edu: Formality Secondary Primary (Non-Indigenous) (tertiary) (tertiary) Occupation Indigenous Income Participation Occupation Participation Occupation Participation Formality Participation Occupation Formality Formality Income Formality Income Income Women (Men) Income Women (Men) Occupation Occupation Participation Participation -50 -30 -10 10 Source: Own calculations based on the EML 2023. -50 -30 -10 Percentage points 10 Note: Comparison groups for each category are shown Percentage points in parentheses. Source: Own calculations based on the EML 2001 and 2023. Note: Each bar shows absolute changes in gaps from 2001 to 2023 (2005– 2023, in the case of labor informality due to information availability), with negative (positive) numbers indicating a reduction (increase) in the gap between comparison groups. Comparison groups are shown in parentheses. The gap is calculated by subtracting the first group minus the comparison group. 79 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figure A4. Growth decomposition in value added per capita, y, Panama Figure A 4. Growth Decomposition in Value Added per Capita. Growth decomposition in value added per capita, y, Panama 2015-2021 y=0.3% 2010-2015 y=5.9% 2005-2010 y=5.5% 2000-2005 y=2.3% 1995-2000 y=2.8% -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Annual contribution to growth (pp) Productivity (w) Employment rate (e) Participation rate (p) Demographic shift (a) Figure A6. Productivity relative to the U.S., change 2000-2021 Figure A 5. Productivity relative to the U.S., 2000–2021 80 70 60 Relative Productivity, U.S. = 100 50 . 40 30 20 10 0 HIC URY CHL PAN CRI UMI LAC 2000 2021 Source:: WB Jobs Structure tool. Figure A 6 Productivity relative to the U.S., sectors 2021 Figure A 6. Productivity relative to the U.S. by Sector, 2021. 80 70 Relative Productivity 2021, U.S. = 100 60 50 40 30 20 10 0 HIC URY CHL CRI LAC UMI PAN Services Industry Agriculture 80 Source:: WB Jobs Structure tool. Figure A7. Productivity growth decomposition, w, Panama Figure A 7. Productivity Growth Decomposition . Productivity growth decomposition, w, Panama 2015-2021 w=1% 2010-2015 w=5.1% 2005-2010 w=5.2% 2000-2005 w=1.3% 1995-2000 w=2.2% -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Annual contribution to growth (pp) Productivity within the sector Static reallocation Dynamic reallocation Source: WB Jobs Structure tool. Figure A 8. A 8 Figure Population Projections by Age Group. 7 6 2086 maximum population: 6.3 millions 5 Millions of people 4 2069 maximum population: 3 15 - 65 years 3.8 millions 2025 maximum population: 2 0-14 years 1.2 millions 1 0 1950 1954 1958 1962 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 2014 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 2058 2062 2066 2070 2074 2078 2082 2086 2090 2094 2098 0 to 14 15 to 64 65 and more Total LAC Source: ECLAC 2022. Figure A 9 Tasks included in the works, 2011-2023 Figure A 9. Tasks Included in Jobs, 2011–2023 5 4 3 Index, 2011 = 0 2 1 0 -1 2011 2012 2013 2014 2016 2017 2018 2019 2021 2023 Non-routine - cognitive analytical Routine - cognitive Non-routine - cognitive interpersonal Manual Source: EML 2023. 81 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figura A 10 Figure A 10. Gaps in the Ratio of Workers in Future-Oriented, Cognitive-Intensive Jobs. 20 10 0 -10 -20 -30 -40 -50 -60 -70 -80 Women (men) Indigenous Edu: None Edu: Primary Edu: Secondary Age: 15-24 Income: Poorest Informal Small business (Non-Indigenous) (tertiary) (tertiary) (tertiary) (25-64) 40% (richest 60%) (formal) (1-10) (large 11+) NR - cognitive analytical NR - cognitive interpersonal Source: EML based on Edmund and Viollaz 2024. Note: Each bar shows gaps in the share of workers in occupations located in the top quartile of task intensity. For example, the percentage of male workers that participate in occupations in the top 25 percent of non-routine analytical tasks is 20.3 for the population overall and 29.4 in the case of women, resulting in a gender gap of 9.4 percentage points. Comparison groups are described in parentheses. Figure A11. Growth of average years of schooling by generations and population Figure A 11. groups in Panama. Growth of Average Years of Schooling by Generation and Population Group, Panama. 14 12 10 8 6 4 2 0 Before 1950 1950-1959 1960-1969 1970-1979 1980-1989 1990-1999 Cohorts Urban Rural Women Men Non-IP-AD Afro-desc. Indigenous Source: Censo de Población y Vivienda (2023). Calculation by the authors. 82 Figure A12. Growth of average years of schooling by generations and population A 12. in Latin America. groups Figure Growth of Average Years of Schooling by Generation and Population Group, Latin America. 90 SGP 80 KOR 70 Employed Population % 60 50 HNK 40 COL BOL 30 PER CHL CRI 20 PAN ARG DOM 10 SLV 0 55-64 25-35 Source: ILOSTAT 2021. Figure A13. 13. Figure A wages Average earned and years of schooling for young people Average Wages Earned and Years of Schooling for Participants in the Labor Market Aged 18–24. between 18 and 24 years old who participate in the labor market. 4,000 14 3,500 13 Self-reported monthly salary (Balboas) 12 3,000 11 Years of schooling 2,500 10 2,000 9 1,500 8 1,000 7 500 6 0 5 Total Women Men Urban Rural No IP-AP AP IP Head Tert. Head Sec. oe less Average wage Average years of education Source: Censo de Población y Vivienda (2023). Calculation by the authors. 83 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figure A14. Efficiency of government expenditure on education in Panama. Figure A 14. Efficiency of Government Education Expenditure. 1.00 0.90 0.80 HCI - Education Subcomponent 0.70 0.60 0.50 0.40 0.30 0.20 0 1000 2000 3000 4000 5000 6000 Expenditure on education per capita ($ 2020 PPP) All countries LAC Panama Note: Based on World Bank (2024). Source: WDI 2024, calculation by the authors. All countries with Human Capital Index in 2020 are included Figure A15. Efficiency of government expenditure on health in Panama. Figure A 15. Efficiency of Government Health Expenditure. 1.00 0.98 0.96 HCI - Health Subcomponent 0.94 0.92 0.90 0.88 0.86 0.84 0.82 0.80 0 1000 2000 3000 4000 5000 6000 Expenditure on health per capita ($ 2020 PPP) All countries LAC Panama Note: Based on World Bank (2024). Source: WDI 2024, calculation by the authors. All countries with Human Capital Index in 2020 are included. 84 Figure A16. Population covered by young people receiving scholarships according to Figure A 16. population group. Population receiving scholarships by Population Group. 85% 79% 80% 78% 78% 75% 75% 73% 74% 73% 71% 71% 69% 70% 67% 68% 66% 66% 65% 61% 61% 60% 55% 50% 45% 40% Urban Rural No IP-AP AP IP Prim. or Some Superior less Secondary Location Ethnicity / Race Head Education Population total Attending population Figure Source: Censo A17. y Vivienda (2023). Calculation by the authors. de Población Average distance to the nearest school by area, according to age and educational level that should be attended. Figure A 17. Average Distance to the Nearest School by Area, Age, and Educational level that Should be Attended. 7.0 6.0 5.0 4.0 Kms 3.0 2.0 1.0 0.0 Preschool Primary Junior High Secondary Preschool Primary Junior High Secondary Urban Rural Distance of attendants Distance of Dropouts / Non attendants Source: Censo de Población y Vivienda (2023) and INEC (2023). Calculation by the authors. Figure A18. Percentage of students above the minimum level in mathematics attracted A 18. Figureto teaching and engineering careers in Panama. Share of Students with Above Minimum Skills in Mathematics Interested in Teaching and Engineering Careers. 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% City Town Public Private City Town Public Privado City Town Public Private Panama LAC OECD Engineering Teaching Source: Censo de Población y Vivienda (2023). Calculation by the authors. 85 Appendix 2: Additional Tables PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Tabla A1. Population Characteristics by Income Level, 2008, 2015, and 2023. 2008 2015 2023 Indicator Middle Middle Middle Poor Vulnerable Poor Vulnerable Poor Vulnerable Class Class Class Daily per capita income 4 10 29 4 10 31 4 10 32 Urban 28% 63% 81% 23% 59% 79% 26% 62% 81% Rural 72% 37% 19% 77% 41% 21% 74% 38% 19% Comarca 19% 2% 0% 35% 3% 0% 39% 6% 0% Rest Rural 53% 35% 19% 42% 38% 20% 35% 33% 19% General Characteristics Households with female head 30% 30% 31% 37% 34% 33% 42% 39% 39% Members 0-12 years old 40% 30% 18% 43% 31% 19% 42% 31% 17% Members 13-18 years old 14% 13% 9% 15% 14% 10% 14% 12% 9% Members 19-70 years old 42% 53% 67% 40% 49% 65% 41% 50% 65% Members +70 years old 3% 4% 6% 2% 6% 7% 2% 7% 8% Average age of household 47 48 50 46 51 51 50 54 55 head Household receives public 10% 5% 4% 70% 47% 20% 70% 53% 29% transfers Average years of schooling 6 8 10 5 7 10 7 8 11 of household head Education School enrollment 97% 99% 100% 97% 99% 100% 96% 99% 100% (6-12 years old) School enrollment 72% 81% 89% 80% 85% 89% 84% 92% 94% (12-18 years old) Unemployment rate 7% 8% 4% 7% 8% 4% 9% 11% 6% Informal employment rate 87% 55% 33% 92% 63% 33% 95% 76% 42% Labor Market Wage-earners ratio 32% 65% 75% 23% 56% 74% 20% 43% 67% Self-employed ratio 49% 30% 20% 50% 39% 22% 49% 47% 28% Unpaid workers ratio 19% 4% 1% 27% 5% 1% 30% 8% 2% Median hourly labor income 1 4 6 1 3 7 1 3 7 Sanitation ND ND ND 65% 76% 87% 81% 89% 91% Access to Basic Services* Internet ND ND ND 65% 79% 91% 82% 92% 97% Electricity ND ND ND 71% 93% 98% 83% 95% 99% Precarious dwelling ND ND ND 33% 13% 4% 22% 7% 3% Source: EML 2008, 2015 and 2023, EPM 2015 and 2022. Note: * = Access to basic services was calculated using the EPM. The definition of access to services is based on the official definition of multidimensional poverty. ND = No available data. Access to basic services is excluded since it is not included in EPM 2008. Public transfers include: scholarships from public institutions, benefits from Pase-U, RdO and Bono Familia para Alimentos, food supplements, and Angel Guardián and housing assistance. Income is in 2017 PPP. 86 Appendix 3: Additional Boxes Box A1. Well-Being of Afro-Descendants in Panama According to statistical information from household surveys and the Censo de Población y Vivienda 2023, the monetary well-being of Afro-descendants (ADs) is comparable to that of the non-Afro-descendant and non-indigenous population (Non-AD-IP). In Panama, 31.6 percent of the population self-identifies as AD (1,285,881 people), the vast majority of whom live in urban areas (75.1 percent). Given their concentration in urban areas, ADs’ coverage of water, sanitation, and electricity services is above 93 percent, similar to that of the Non-AD-IP and well above the indigenous population. In monetary terms, the per capita income of ADs (US$32 per day, 2017 PPP) is similar to that of the Non-AD-IP and almost 3 times higher than that of IPs (US$12 per day, 2017 PPP). While 45 percent of IPs live in poverty, only 5.8 percent of ADs do. However, studies show that ADs (particularly women) have not fully benefited from the country’s economic growth, have limited access to labor markets and health services, and have been excluded from political participation (UNDP and INAMU 2020). AD women face compounded discrimination due to their gender and ethnicity, which is further exacerbated by poverty is, limiting their access to economic, educational, and social opportunities. Furthermore, they face lack of representation and recognition in public policies and must navigate stereotypes and entrenched social structures that perpetuate their marginalization Figura Recuadro A1 Figure Box A1. Poverty and Access to Services by Ethnicity, 2023 100 95 97 98 94 94 94 80 73 70 60 52 45 40 34 32 20 12 6 8 0 Poor Daily household Water Electricity Sanitation ($6.85 per day) per capita income (2017 USD PPP) AD Non-IP-AD IP Source: EML 2023 for information on poverty and Censo de Población y Vivienda 2023 for information on access. 87 Appendix 4: Methodological Notes PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 1. Measuring Poverty in Panama Official Methodology for Measuring Poverty Since 2007, Panama has adopted the United Nations Economic Commission for Latin America and the Caribbean (ECLAC) methodology for measuring poverty based on people’s income and minimum welfare thresholds. The 2007-2008 Income and Expenditure Survey was used to establish poverty lines. The extreme poverty line corresponds to the per capita value of a basic food basket, while the general poverty line incorporates expenditures on essential non-food goods. Furthermore, poverty lines are calculated for urban and rural areas. The rural poverty line assumes a cost per kilocalorie equal to 80 percent of the urban poverty line (as observed in the 2003 Living Standards Survey)72. The poverty lines are updated with the Consumer Price Index (CPI). The CPI of Panama and San Miguelito is used for urban poverty lines, while the CPI for the rest of urban areas is used for rural poverty lines. According to the 2008 Living Standards Survey, there are no major differences in the cost of a basket of goods and services between rural and urban areas. The income aggregate is calculated from the Encuesta de Mercado Laboral (August) and the Encuesta de Propósitos Múltiples (March) and collected by the National Institute of Statistics and Census (INEC). Income includes monetary and non-monetary income reported by all people in the household, and it is divided into two categories: labor income (monetary and non-monetary), and non-labor income (pensions, transfers, and others) (Figure AM1). The income aggregate does not include imputed rent to maintain the comparability of the series, as its collection began in 2008. The official methodology for constructing the household income aggregate includes: • Income of domestic workers living in the home. • Imputations for non-response (labor income, thirteenth month pay, retirement income, and other income). • Imputations for extreme values (maximum and minimum). Specifically, minimum values are corrected for private employees in the formal sector. 72For more details on official poverty lines, see https://www.cepal.org/es/publicaciones/3845-propuesta-nueva-linea-pobreza-panama 88 Figure AM 1. Components of Official Aggregate Income in Panama. Household per capita income (total household income/members) Number of Household income members + + + Labor income Non-labor income + + + + + Monetary Non-monetary Pensions Transfers Others • Salary in cash • Salary in-kind • Retirement • Rents, income, interest, or • Self- employment • Self- employment • Pension (accident or + + profits income income illness) • Lottery or in-kind Private Public gambling • Self- prizes consumption • Alimony • Scholarships income from public • Cash institutions • Thirteenth assistance month pay • Beca • Food Universal • Second job assistance salary/income • RdO • Scholarships from private • SENAPAN institutions family voucher • School supplies • Food supplements • School feeding • Agricultural inputs • Other assistance • Agricultural income • 120 a los 65 • Angel Guardián • PARVIS Mejorado • Housing assistance • Bono Solidario Source: Own preparation. 89 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Figure AM2. Poverty trend in Panama, official measurement. Figure AM 2. Official Poverty Rate, 2008–2022. Moderate poverty 40 35 30 25 20 15 10 2008 2009 2010 2011 2012 2013 2014 2015 2016* 2017* 2018* 2019 2021 2022* Official WB replica Figure AM3. 3. Figure AMExtreme poverty trend in Panama, official measurement. Official Extreme Poverty Rate, 2008–2022. Extreme poverty 40 35 30 25 20 15 10 5 0 2008 2009 2010 2011 2012 2013 2014 2015 2016* 2017* 2018* 2019 2021 2022* Official WB replica Source: EML and EPM. Note: * = EPM is used as a source. For the replication exercise, the official methodology was followed, except for non-response imputations and extreme values imputations. As a supplement to the monetary poverty measure, Panama calculates the Multidimensional Poverty Index (MPI), which evaluates poverty based on 5 dimensions: (1) education; (2) housing, basic services, and Internet access; (3) environment, surroundings, and sanitation; (4) work; and (5) health. The MPI was published by the MEF in 2017 and 2018 using the Encuesta de Propósitos Múltiples (EPM) methodology and the Alkire-Foster (2011) methodology for extreme values. 90 Comparison with the SEDLAC Aggregate The Socioeconomic Database for Latin America and the Caribbean (SEDLAC) is produced by the Center for Distributive, Labor and Social Studies (CEDLAS) of the University of La Plata and the World Bank. SEDLAC aims to ensure comparability of social and economic data from countries in the region, thereby harmonizing variables from household surveys such as income, demographics, education, employment, infrastructure, and durable goods and services. For Panama, the income aggregate is calculated from the Encuesta de Mercado Laboral and includes labor income, non-labor income, and imputed rent (the latter as of 2008) (Figure AM4). SEDLAC makes a downward adjustment to rural income (by a factor of 15 percent) to capture price differences between rural and urban areas. As opposed to the official aggregate, the SEDLAC harmonized aggregate excludes domestic workers and tenants residing in the household. Figure AM 4. Components of the SEDLAC Harmonized Aggregate Income for Panama. Household per capita income = (total household income/members) Household income Number of members x + + + - Spatial deflation Labor income Non-labor income Domestic Imputed rent workers or tenants + + + + + Monetary Non-monetary Pensions Transfers Others • Salary in • Salary in- • Retirement • Rents, cash kind income, • Pension + + interest, or • Self- • Self- (accident or profits employment employment illness) Private Public income income • Lottery or in-kind • Alimony • Scholarships gambling • Self- from public prizes consumption • Cash institutions income assistance • Beca • Thirteenth • Food Universal month pay assistance • RdO • Second • Scholarships job salary/ from private • SENAPAN income institutions family voucher • School supplies • Food supplements • School feeding • Agricultural inputs • Other assistance • Agricultural income • 120 a los 65 • Angel Guardián • PARVIS Mejorado • Housing Source: Own preparation. assistance • Bono Solidario 91 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 The World Bank estimates poverty in Latin American and Caribbean countries using the SEDLAC harmonized income and international lines. In high-income countries, such as Panama, the most relevant poverty line is the US$6.85 per day line (in 2017 PPP). Trends in poverty reduction in Panama, as measured by both the SEDLAC aggregate with the international line and by official measures, are similar, although the levels are not the same. Panama’s official poverty rate is higher than the international poverty rate. In 2022, the overall poverty line was 148.01 balboas per month per person in urban areas and 111.5 balboas per month per person in rural areas. While the international poverty line of US$6.85 per day is equivalent to 110.44 balboas per person per month. Figure AM 5. Official and International Poverty Rates, 2008–2023. 40 33.8 35 30 25 23.2 21.8 Poverty rate (%) 21.5 20 15 12.9 12.9 12.1 10 5 0 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2021 2023 Official poverty International poverty $6.85 Source: Own preparation. To facilitate international comparisons and extend the series up to 2023, the report uses the SEDLAC harmonized income aggregate and the international poverty line of US$6.85 per day for its analysis. 2. Asset-Based Approach This report uses the asset-based approach to identify key constraints and opportunities for poverty reduction in Panama. The asset-based framework guides the analysis by focusing on the ability of households to generate income and how risk may constrain their ability. This approach has been developed by Lopez-Calva and Rodriguez-Castelan (2016), which in turn is an extension of a model presented by Attanasio and Székely (2001) and Bussolo and Lopez- Calva (2014). 92 The asset-based approach recognizes that the ability of households to generate income depends on different factors that foster or weaken their economic position, and all of these are also exposed to external risks (Figure AM 6). The main factors are the ability of households to generate income based on the assets they own (including human capital, financial and physical assets, and social capital) and how much they can earn from the assets they own. Transfers can provide a cushion, although they are less sustainable. (High) prices can erode the value of households’ income or increase the value of their assets. Furthermore, external shocks can affect any or all components of a household’s income-generating capacity. Figure AM 6. Asset-Based Framework for Understanding Household Income and the Role of Risk. Return on assets Transfers Household income - Accumulation of assets x Intensity of use of assets x + x External shocks Prices Prices Source: Lopez-Calva and Rodriguez-Castelan (2016). 3. Calculating the Type of Tasks in Panamanian Jobs The analysis of the intensity of routine and non-routine tasks in Panama starts with information collected by Edmund and Viollaz (2024), which is based on the analysis of Lo Bello et al. (2019). The approach matches employment data from Central American countries and the Dominican Republic, with task data from similar countries collected by the OECD’s Programme for the International Assessment of Adult Competencies (PIAAC). For Panama, information is used from Mexico, the closest country covered by PIAAC in four dimensions: technology, globalization, skills, and structural change. Technology is measured by the percentage of the population that uses the Internet; globalization by net foreign direct investment inflows as a percentage of gross domestic product; skills by the percentage of the population aged 25 and older that has completed at least secondary education; and structural change by the share of employment in agriculture, industry, and services. Task measures were constructed following the methodology and definitions in Lewandowski et al. (2022). Questions available in PIAAC that are similar in content to the questions used by Acemoglu and Restrepo (2017) are identified to construct the O*NET-based routine and non- routine task measures. The analysis then searched for combinations of survey questions and response groupings, for which the U.S. PIAAC-based occupation measures (averaged for each occupation) are most highly correlated with the O*NET-based occupation measures. The set of PIAAC variables and response groupings that maximize correlation with the O*NET measures are listed in Table 2. The same variables and response groupings were considered and averaged at the two-digit ISCO-08 International Standard Occupational Classification level using the 93 PANAMA: From Growth to Prosperity Poverty and Equity Assessment - 2024 Mexican PIAAC data and their weights. These averages were then assigned to Panama’s household and labor force surveys from 2011 to the most recent year available, where they are applied to the occupations defined in the two-digit ISCO-08 occupational classification. Table AM 1. Task Variables that Maximize Correlation between United States PIAAC and O*NET Task Measures Non-routine cognitive interper- Non-routine cognitive analytical Routine cognitive Manual sonal Variable tasks Metric Variable tasks Metric Variable tasks Metric Variable tasks Metric At least once a Change the At least once a Problem solving Supervise others Yes Never Physical tasks month order of tasks month Give speeches/ Read newspa- At least once a At least once a make presenta- Some frequency Fill out forms pers month month tions Read Give speeches/ At least once a professional make presenta- Never month magazines tions Programming Some frequency 94