INDONESIA ECONOMIC PROSPECTS IEP The Invisible Toll of COVID-19 on Learning JUNE 2023 © 2023 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions, and is supported by funding from the Australian Government under the Australia-World Bank Indonesia Partnership (ABIP) program. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent, or the Australian Government. The World Bank does not guarantee the accuracy, completeness, or currency of the data included in this work and does not assume responsibility for any errors, omissions, or discrepancies in the information, or liability with respect to the use of or failure to use the information, methods, processes, or conclusions set forth. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be construed or considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved. Rights and Permissions The material in this work is subject to copyright. Because The World Bank encourages dissemination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. Any queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@ worldbank.org. Cover photo: ©Odua Images/shutterstock.com and ©Agung Bayu/shutterstock.com. Part A photo: © World Bank. Further permission required for reuse. Cover design: Arsianti The report was designed and typeset by Arsianti Indonesia Economic Prospects June 2023 Ta bl e of C o n te n ts LIST OF FIGURES, TABLES AND BOXES IV PREFACE VI ABBREVIATION VII EXECUTIVE SUMMARY 1 I. Economic Update 1 II. Pathways to Learning Recovery and a More Productive Future for Indonesia’s 3 Children A. ECONOMIC UPDATE 5 1. Recent Economic Developments 5 2. The Policy Stance 13 3. The Outlook and Risks 20 4. Structural Growth Constraints and Reforms Priorities 23 B. PATHWAYS TO LEARNING RECOVERY AND A MORE 34 PRODUCTIVE FUTURE FOR INDONESIA’S CHILDREN 1. Preface 32 2. The COVID-19 pandemic aggravated the pre-existing global learning crisis 32 3. Remembering where we were – the Indonesian education system prior to 34 the COVID-19 pandemic 4. GoI’s efforts to sustain education despite the challenges during theCOVID-19 35 pandemic 5. Did learning losses occur, and if so, to whom, how, and how much? 37 6. Conclusion and Policy Recommendations 45 ANNEXES 49 REFERENCES 56 NOTE: CLICK THE SIDE BUTTONS TO GO TO THE SECTION YOU WANT TO READ OR GO TO THE TABLE OF CONTENTS (TOC). CLICK HOME BUTTON TO GO BACK TO TOC PAGE iii Indonesia Economic Prospects June 2023 LIST OF FIGURES, TABLES, BOXES FIGURES Figure A.1: Growth is mainly supported by private consumption and exports 6 Figure A.2: Leading indicators point to easing investment 6 Figure A.3: Potential GDP growth is declining due to weakening labor input and productivity growth 6 Figure A.4: Services contributing the most to growth 6 Figure A.5: Inflation tapered down earlier than expected 7 Figure A.6: … but became broader-based as more goods and services had higher price rises due to 7 second round effects from earlier commodity price shocks Figure A.7: Sector composition during the Asian financial crisis and COVID Crisis 8 Figure A.8: Goods trade growth continued to moderate 10 Figure A.9: …while fading commodity price windfalls dampened export growth 10 Figure A.10: Manufactures have been contributing little to recent export growth, supported mostly by 10 sustained raw minerals (coal) exports Figure A.11: The moderation of goods exports was accompanied by strengthening services trade 10 Figure A.12: The current account surplus was sustained, supported by high commodity prices 11 Figure A.13: External financing needs came mostly from investments 11 Figure A.14: Forex reserves stocks are adequate 12 Figure A.15: The Rupiah remained stable compared to peer countries 12 Figure A.16: External debt exposure is declining 13 Figure A.17: Credit risk premia declined though remained above pre-pandemic level 13 Figure A.18: Faster fiscal consolidation supported by strong revenue performance 14 Figure A.19: Commodity windfalls, domestic demand and reforms supported a strong revenue 14 performance so far Figure A.20: … while rising energy subsidies drove expenditure growth 15 Figure A.21: Indonesia’s public debt is gradually declining, in contrast with some of its peers 15 Figure A.22: Overall, policy rate differential with the US Federal Reserve has been narrowing despite 16 recent pickup Figure A.23: BI has used a mix of policy responses to navigate external shocks, which have eased 16 in early 2023 Figure A.24: Financial sector indicators remain sound 20 Figure A.25: Credit to the private sector is stable 20 Figure A.26: Capital injection to SOEs has increased 22 Figure A.27: … Contributing to higher investment in economic infrastructure by SOEs 22 Figure A.28: Indonesia’s investment growth has been larger than that of LMICs 24 Figure A.29: TFP, labor and human capital growth had slowed in recent years 24 Figure A.30: Within-sector productivity growth contribution to total labor productivity growth remained 25 dominant and stable Figure A.31: In addition to intersectoral reallocation, services productivity growth declined and led to 25 the overall drop in labor productivity Figure A.32: Poverty headcount rates using various $ per-day 2011 PPP as well as national poverty line 27 (NPL) iv Indonesia Economic Prospects June 2023 Figure A.33: Log GDP per capita (PPP) vs poverty rate for peers 27 Figure A.34: Poverty rates for Indonesia and its economic peers 27 Figure A.35: Share of population classified as structurally poor, economically insecure, and economically 27 secure Figure A.36: Determinants of competitiveness will vary according to a country’s stage of development 28 Figure A.37: Indonesia performs well on drivers of factor accumulation relative to its peers though lags 28 on efficiency drivers Figure A.38: Indonesia maintains one of the most restrictive policies on international services trade 29 Figure A.39: Indonesia could reach HIC by 2045 if it can sustain its performance of the last 10 years 29 Figure A.40: Closing competitiveness gaps with Korea across drivers of factor accumulation and 29 efficiency drivers in the next 10 years could help accelerate annual average growth to above 7 percent Figure B.1: Learning trajectories pre-and post-COVID-19 33 Figure B.2: Size of learning losses in months, by subject, public-private status of educational institutions, 38 and area Figure B.3: Relationship between months of school closure and learning loss. 39 Figure B.4: Size of learning losses in months, by subject, gender, and household poverty status 40 Figure B.5: Size of learning gaps between subgroups (in months) between 2019 and 2023, by subject 40 Figure B.6: Learning gaps among subgroups with different experiences in their environment during 41 school closures Figure B.7: Average number of structured learning hours by schools and madrasahs, 2018/19 – 2021/22 42 Figure B.8: Simulated age-earning profiles of workers with and without learning loss, by gender 44 Annex Figure B.1: Coverage of geographical areas under the 2023 Learning Loss survey 51 TABLES Table A.1: Infrastructure SOEs Liability-to-Equity Ratio 23 Table A.2: Selected Macroeconomic Indicators 30 Table B.1: Proportion of educational institutions that used different curricula during the school closure (%) 43 Annex Table B.1: List of surveyed province and districts 52 Annex Table B.2: Number of educational institutions surveyed in 2023 and number of SDI 2019 institutions 53 used for the Learning Loss analysis Annex Table B.3: Number of students surveyed in 2023 and SDI 2019 students used for the Learning Loss 53 analysis Annex Table B.4: Percentage of Grade 4 students answering specific math tasks correctly 53 Annex Table B.5: Percentage of Grade 4 students answering specific language tasks correctly 54 Annex Table B.6: Descriptive statistics on Learning Loss derived from the results of regression analyses 55 BOXES Box A.1: Financial Inclusion in Indonesia 17 Box A.2: Key elements of the financial sector omnibus law 19 Box A.3: Risks from infrastructure SOEs in Indonesia 22 Box A.4: Indonesia’s gains in terms of poverty reduction 26 Box B.1: Definition and Conceptual Model of Learning Loss 33 v Indonesia Economic Prospects June 2023 Preface The Indonesia Economic Prospects (IEP) is a bi-annual World Bank report that assesses recent macroeconomic developments, outlook, and risks, as well as specific development challenges for the Indonesian economy. In doing so, the IEP aims to inform the public policy debate and is geared towards a wide audience, including the general public, the government, the private sector, civil society organizations, and other domestic and international stakeholders. The IEP is a product of the World Bank Jakarta office and receives strategic guidance from an editorial board chaired by Satu Kahkonen, Country Director for Indonesia and Timor-Leste. The report is prepared by the Macroeconomics, Trade and Investment (MTI) Global Practice team, under the guidance of Lars Christian Moller (Practice Manager) and Habib Rab (Lead Economist). The report is co-led by Wael Mansour (Senior Economist), Indira Maulani Hapsari (Senior Economist) and Shinsaku Nomura (Senior Economist). Deviana Djalil provided administrative support and coordinated the organization of the report launch event. The dissemination is organized by Gb Surya Ningnagara and Maulyati N. Slamet under the guidance of Lestari Boediono Qureshi. The report was designed and typeset by Arsianti. Part A was prepared by Wael Mansour and Indira Maulani Hapsari (report leads), Ahya Ihsan, Angella Faith Montfaucon, Assyifa Szami Ilman, Csilla Lakatos, Dwi Endah Abriningrum, Jana Mirjam Silberring, Kathleen Victoria Tedi, Ratih Dwi Rahmadanti and Rong Qian. Inputs were provided by Anastasiya Denisova, Gracia Hadiwidjaja and Rachmat Reksa Samudra (social protection and labor markets), Francesco Strobbe, I Gede Putra Arsana, Salman Alibhai, Neni Lestari and Ou Nie (financial sector). Box A.1 was prepared by I Gede Putra Arsana. Box A.2 was prepared by Francesco Strobbe and Salman Alibhai. Box A.3 was prepared by Ratih Dwi Rahmadanti. Box A.4 was prepared by Utz Johann Pape and Samuel Nursamsu. Part A benefitted from the comments of Habib Rab, as well as Ergys Islamaj and Ibrahim Saeed Chowhdury as peer reviewers. Part B was prepared by Shinsaku Nomura (report lead), Delbert Lim, and Anna Hata. Part B benefitted from the comments from Cristian Aedo, Achim Daniel Schmillen, Harry Patrinos, Koen Martijn Geven, Tobias Pfutze, Ezequiel Molina, and Jack Philip Baldwin. Rythia Afkar and Seo Yeon Hong provided contributions to the survey design, and Elisabeth Yunita Ekasari and Sylvia Njotomihardjo provided administrative support to the Part B. This report is available for download in English and Indonesian via: www.worldbank.org/iep Previous report editions: This report is available for download in English and Indonesian via: www.worldbank.org/iep Previous report editions: • December 2022: Trade for Growth and Economic Transformation • June 2022: Financial Deepening for Stronger Growth and Sustainable Recovery • December 2021: A Green Horizon: Toward a High Growth and Low Carbon Economy To receive the IEP and related publications by email, please email ddjalil@worldbank.org. For questions and comments, please email wmansour@worldbank.org and ihapsari@worldbank.org.   For information about the World Bank and its activities in Indonesia, please visit:   www.worldbank.org/id instagram.com/worldbank @BankDunia #IEPBankDunia www.linkedin.com/company/the-world-bank   BankDunia vi Indonesia Economic Prospects June 2023 Abbreviations AEs Advanced Economies MoF Ministry of Finance AKMI Asesmen Kompetensi Madrasah MoH Ministry of Health Indonesia/ Indonesian Madrasah MoHA Ministry of Home Affairs Competency Assessment MoRA Ministry of Religious Affairs AN Asesmen Nasional/ National Assessment MSMEs Micro, Small and Medium Enterprises ARA Assessing Reserve Adequacy NEET Not in Education Employment or Training BI Bank Indonesia NER Net Enrolment Rate BOS Bantuan Operasional Sekolah NPL Non-Performing Loan BPS Badan Pusat Statistik OECD Organization for Economic Cooperation CDS Credit Default Swaps and Development CPI Consumer Price Index OJK Otoritas Jasa Keuangan/ Financial EAP East Asia Pacific Services Authority ECED Early childhood education and PISA Programme for International Student development Assessment EM Emerging Market PMT Proxy Means Test EMBI Market Bond Index PPDB Penerimaan Peserta Didik Baru/ EMDEs Market and Developing Economies New Student Acceptance EMIS Education Management Information PPP Purchasing Power Parity System REER Real effective exchange rate FDI Foreign Direct Investment ROA Return on Assets FDIC Deposit Insurance Corporation RPP Rancangan Rencana Pembelajaran/ FSOL Financial Sector Omnibus Law Lesson Plan GBV Gender Based Violence SAKERNAS Survei Angkatan Kerja Nasional GDP Gross Domestic Product SBN Surat Berharga Negara GNI Gross National Income Sd standard deviation GoI Government of Indonesia SDI Service Delivery Indicator HIC High-Income Country SOEs State-Owned Enterprises IDR Indonesian Rupiah SUSENAS Indonesia Socioeconomic Survey IFLS Indonesia Family Life Survey SVB Valley Bank IMF International Monetary Fund TFP Total Factor Productivity INOVASI Innovation for Indonesia’s School THL Tax Harmonization Law Children US$ United States Dollar JCOL Omnibus Law on Job Creation VAT Value Added Tax LAR Loan at Risk WDI World Development Indicators LAYS Learning-adjusted years of schooling WEO World Economic Outlook LFP Force Participation Labor Yoy Year-on-year LIC Low Income Country YTD Year-to-Date LMICs Lower Middle-Income Country MoECRT Ministry of Education, Culture, Research and Technology v ii Executive summary Indonesia Economic Prospects June 2023 E xe cut i ve Su m m a r y I. Economic Update Commodity windfalls and Growth strengthened to 5.3 percent in 2022, the highest in the last decade and private consumption have stronger than the region’s median. Growth came on the back of positive terms-of- sustained Indonesia’s growth trade led by commodity related exports and a recovery in private consumption. This despite a difficult global environment, but signs momentum continued in 2023 with private consumption and exports supporting 5 of normalizing domestic percent growth in the first quarter (Q1-23). Nevertheless, there are signs that domestic demand are emerging. demand is starting to moderate. This includes a softening in imports and investment growth, a deceleration in private sector credit growth, as well as a slowdown in core inflation since the beginning of the year. Inflation is easing at a faster Headline inflation declined, reaching 4 percent yoy in May 2023. This is the lowest pace than markets anticipated. inflation recorded since it peaked in September 2022 when global inflationary pressures mounted following Russia’s invasion of Ukraine. The slowing pace of inflation is attributed to a combination of external and domestic policy-related factors. This includes the decline in global oil prices, improved harvest, government intervention at sub-regional level to ease supply bottlenecks notably for food and rice, and the appreciation of the Rupiah which lowered the cost of imports. Nevertheless, inflation became more broad-based, partly reflecting a pick-up in demand for most goods and services as headline and core inflation are converging. Indonesia’s external The widening current account surplus in early 2023 is linked primarily to weakening vulnerabilities remain moderate. imports of goods instead of rising exports. The latter have decelerated as prices of major export commodities like coal, palm oil, and other metals dropped, while manufacturing exports’ contribution remains limited. External financing pressures have also eased. Foreign Direct Investment (FDI) has been a steady source of external financing in the past three years and has outperformed the more volatile and shorter- term portfolio and debt flows. External buffers remain strong and have supported the appreciation of the Rupiah since the start of 2023. Furthermore, Indonesia is becoming more resilient to external shocks. This is primarily due to declining debt held by non-residents, an improvement in investors perception of Indonesian assets, and a more stable exchange rate compared to peers. The fiscal stance has With a fiscal deficit of 2.4 percent of GDP in 2022, the GoI had returned to its fiscal rule normalized reflecting faster mandate one year earlier than targeted. This was possible due to a strong revenue fiscal consolidation, anchored performance that was buoyed by a mix of high commodity prices, rising domestic by a broad-based rise in revenues and prudent public demand, and tax reforms. Moreover, spending was contained through rolling back spending. COVID-19 programs, partial removal of energy subsidies, and under-execution of public investment. The fiscal outcome is persistent so far in 2023 with the surplus reaching 0.6 percent of GDP in Q1-23, up from 0.1 percent of GDP in Q1-22. In line with fiscal consolidation, public debt has gradually declined and now stands at 39.2 percent in March 2023. It remains though above its pre-pandemic level in 2019. With ample liquidity in domestic markets and BI halting budgetary financing, the public debt composition is changing. By Q1-23, domestic debt accounted for 72.1 percent of total public debt with commercial banks increasing their sovereign lending. 1 Indonesia Economic Prospects June 2023 Softening inflation and BI raised its policy rate by a cumulative of 225 basis points last year but has held it at resilient capital flows have led 5.75 percent since January 2023. Inflation is steadily easing, and inflation expectations Bank Indonesia (BI) to ease its pace of monetary tightening. are now anchored and expected to drop below BI target in the second half of 2023. Moreover, despite the narrowest interest rate spread recorded between US Fed rate and Bank Indonesia’s policy rate, portfolio flows have turned positive, giving a boost to the Rupiah. Decelerating inflation provides BI with more space for accommodative monetary policy to counter rising borrowing costs and support growth. BI has been actively using a series of policy measures to navigate external market pressures amidst synchronous global shocks. This includes using a combination of foreign currency interventions to stabilize the currency, policy interest rate, and exchange rate flexibility. The outlook remains stable GDP growth is projected to moderate to 4.9 percent in 2023 and stay broadly flat at as the economy normalizes 5 percent in the medium term. Growth will be supported by private consumption as following the post-pandemic inflationary pressures subside. The current account balance is projected to retain a recovery. small surplus (0.02 percent of GDP) in 2023 before turning into a deficit of 1.0 percent of GDP in 2025. This follows a deceleration in exports growth as prices of palm oil and coal soften and as global demand weakens further. Imports will also moderate in line with moderating domestic demand and investment in 2023. However, positive interest rate differentials with the US and a stable macro framework are projected to continue to support portfolio inflows. As a result, official reserves are expected to remain adequate to finance 6 months of imports. The fiscal deficit is also projected to remain below 3 percent of GDP in line with the reinstated fiscal rule. This will be achieved through commodity windfalls, continuous reforms to boost domestic revenues, and prudent public spending policies. While this is a robust outcome Potential growth is declining due to reduced labor input, weak human capital given levels of global formation and slowing productivity growth. Investment and to a lesser extent labor uncertainty, Indonesia still input have been key growth drivers prior to the pandemic, but all growth drivers have faces declining productivity growth like other Emerging now moderated, particularly total factor productivity (TFP). Investment contributed Market economies. to about 60 percent growth in 2003-2019 with private contributions far outweighing public. This is far higher than the contribution of capital to growth in other Lower Middle-Income Countries (LMICs). However, TFP growth slowed by nearly half in the 2010’s period relative to the 2000’s. Declining TFP and human capital are in line with lower labor productivity growth, as gains from reallocation of resources across sectors seem to be fading. The slowdown in sectoral reallocation of labor partly reflects lower absorption of labor by the services and industry sectors and decrease in productivity growth in services. Policy makers are encouraged Indonesia has combined macroeconomic stability with reforms to promote to build on recent reforms and competitiveness over the past three years. This includes flagship reforms like the adopt further market-friendly Financial Sector and Job Creation Omnibus Laws. Building on these, the next stage policies and reduce constraints to competition to accelerate is to identify specific constraints within policy areas (e.g., finance, procurement, land, productivity growth. business regulations, trade) or within sectors that prohibit market contestability. Indonesia could achieve its goal of becoming a High-Income Country by 2045 if it can sustain its performance in growth of GNI per capita from the last 10 years. Growth over the last decade, however, has been driven by commodity cycles as well as improved governance, infrastructure, and macro stability accumulation. Going forward, the drivers of growth will need to turn to market friendly policies and institutions that allocate resources to the most productive firms and industries. 2 Indonesia Economic Prospects June 2023 II. Pathways to Learning Recovery and a more Productive Future for Indonesia’s Children COVID-19 was an enormous shock The pandemic led to the collapse of the human capital accumulation process, to people’s life trajectories all over affecting the human capital development of children and youth, particularly in the world, especially disrupting human capital accumulation terms of learning. Learning crises already existed around the world prior to the among children and young people. onslaught of COVID-19, and the crisis deepened during the pandemic. Learning losses caused by COVID-19 often exacerbated existing inequalities within countries which could negatively affect students’ future earnings and the country’s future productivity. The Government of Indonesia The pandemic resulted in the mandatory closure of educational institutions (either (GoI) has put tremendous efforts fully or partially) from March 2020, for a total of approximately 644 days, or about into mitigating the learning disruption caused by COVID-19. 21 months, a relatively long period among Lower Middle-Income Countries and in Southeast Asia. The GoI introduced an Emergency Curriculum and implemented remote-based learning, however service delivery was a challenge. Since the nationwide re-opening of educational institutions in January 2022, the GoI has emphasized learning recovery, reinforced through a series of medium-term educational reforms. This study provides new evidence At the national level, the Grade 4 students in Indonesia in 2023 lost 11.2 months of learning loss in math and equivalent of math skills and 10.8 months equivalent of language skills in comparison language, comparing data on Grade 4 student learning before with Grade 4 students in 2019. Students from poor households were hit harder (in 2019) and after the COVID-19- with losing 18.1 and 27.2 months of learning in math and language, which led to pandemic-induced school closures widened inequity in learning outcomes. School opening hours, household access across Indonesia (in 2023). to the internet, and experience of sickness or the death of somebody close also seem to be correlated with lower performance and/or larger learning losses. In line with international literature Using the Indonesia Family Life Survey (IFLS) 2014, which showed lower earnings on COVID-19 – induced learning among workers with lower competencies in math, the estimated lifetime loss of losses, students’ future earnings and Indonesia’s future productivity earnings will be 30.9 percent among men and 39.2 percent among women of will be negatively affected if no what it would have been without the pandemic. Government remedy actions can action is taken. mitigate those losses going forward. This study highlights the urgency Deliberate commitment and actions are needed because learning losses are of addressing learning loss by somewhat ‘invisible’ to many stakeholders, and many are tempted to go back to stimulating political commitment for learning recovery and business-as-usual rather than confront the challenges. Specifically, actions should prompting deliberate actions, with entail increasing learning time, teaching at the right level for students, and tracking adequate resources to complete students’ performance, as well as addressing inequality in learning by offering them. targeted support to disadvantaged or underperforming students. 3 A. Economic Update Indonesia Economic Prospects June 2023 A. Economic Update 1. Recent Economic Developments Commodity windfalls and private consumption have sustained Indonesia’s growth despite a difficult global environment, but signs of normalizing domestic demand are emerging. The global economy has Aggressive monetary policy tightening in many economies to curb inflation, as well been grappling with political as banking failures in the US and Europe, are expected to constrain lending activities uncertainty, high inflation, in the short-term (World Bank, 2023a). Furthermore, the ongoing war in Ukraine and high cost of finance, and increased geopolitical fragmentation have exacerbated global uncertainty and which have weighed on global present major risks to international trade and investment flows. While the risks of demand. global stagflation have now abated,¹ global demand continues to be soft. The East Asia Pacific (EAP) The EAP region is set to grow at a much faster pace than the global economy in 2023. region has so far been more This is in large part driven by China’s full reopening and departure from pandemic-era resilient than other regions. restrictions, along with robust recovery of private consumption and export demand from major EAP countries. Commodity prices, while still elevated, have eased since January, relieving pressure on food and energy importers in the region. However, recent high-frequency indicators such as retail sales and goods exports point to a slowing growth momentum (World Bank, 2023d). Amidst this global uncertainty, Growth strengthened in 2022, the highest in the last decade. GDP grew by 5.3 percent Indonesia’s growth remains yoy, stronger than the region’s median growth rate, thanks to a positive terms-of-trade robust, but there are signs shock led by commodity related exports and a recovery in private consumption. This that domestic demand is momentum continued in 2023 with private consumption and exports supporting a moderating. 5 percent growth in the first quarter of 2023 (Q1-23) (Figure A.1). Nevertheless, there are signs that domestic demand is starting to moderate (Figure A.2). These include a notable weakening in both import and investment growth, a deceleration in private sector credit growth, as well as a slowdown in core inflation since the beginning of the year. Investment, a key growth driver The economy has been growing at 5 percent yoy for five consecutive quarters. While in past commodity booms, has this is a robust outcome given levels of global uncertainty, it remains below the growth been weak. Investment will be levels of 6-8 percent needed to reach high-income status as outlined in Indonesia central to reversing the decline Vision 2045.² Periods of high growth in the country have been accompanied by a in potential GDP growth. significant contribution from investment both domestic and foreign. This was the case during the 2000s commodity boom periods³ when investments soared, peaking at 17 percent growth in 2004, which helped raise potential growth. Investment growth has lately decelerated and reached a two-year low of only 2.1 percent in Q1-23 yoy. In conjunction, potential GDP growth has also been trending downwards, (Figure A.3). 1 Stagflation was highlighted as a major risk in global projections a year ago in the World Bank’s global economic prospects June 2022 (World Bank, 2022a). ² Indonesia 2045: Berdaulat, Maju, Adil dan Makmur, an Executive Summary (2019). 3 Indonesia has undergone five periods of commodity boom since 2000: (i) Q4 2003 – Q1 2004, (ii) Q3 2006 – Q1 2008, (iii) Q1 2015 – Q4 2016, (iv) Q3 2019 – Q1 2020, and most recently (v) Q2 2021 – Q1 2022. An episode of commodity boom corresponds to a quarter when prices of commodities (coal and CPO as Indonesia’s major export commodities) exceeding one standard deviation from the average price changes. 5 Indonesia Economic Prospects June 2023 From the supply side, services Over the last decade, trade, hospitality, and manufacturing sectors have been the continue to drive growth, biggest drivers of real GDP growth (Figure A.4). In 2022, transport and communication aligned with recovering private contributed the most at 1.2 percentage point (pp) of the 5.0 percent growth rate. This consumption. was followed by trade and hospitality at 1.1 pp, and manufacturing at 1.0 pp. Both trade and hospitality, as well as manufacturing employ a larger number of lower- skilled labor compared to other sectors. These trends followed into Q1-23. They are aligned with the consumption boom that is largely attributed to improving mobility and tourism activities in 2023. Indonesia has hosted several international events in 2022 and 2023. It also welcomed a larger number of tourists following the end of COVID-19 travel restrictions, especially from China. Figure A.1: Growth is mainly supported by private Figure A.2: Leading indicators point to easing investment consumption and exports (3mma index, Jan 2022=100) (percent yoy; percentage points contribution to growth) Private cons. Public cons. Investment Car Sales: Commercial Investment Change in stocks Cement Sales Cap Goods Imports 10 Stat. discrepancy Net exports 125 GDP 120 115 5 110 105 100 0 95 90 85 -5 80 Q1-2023 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Mar-22 Nov-22 May-22 Mar-23 Jan-22 Sep-22 Jan-23 Jul-22 Source: BPS; World Bank staff calculations Source: CEIC; World Bank staff calculations. Figure A.3: Potential GDP growth is declining due to Figure A.4: Services contributing the most to growth weakening labor input and productivity growth (percent yoy, percentage points contribution to growth) (growth, percent yoy) Tax-subsidy Actual GDP YoY Potential GDP YoY Services with high skilled labor concentration 15 Services with low skilled labor concentration Non-mining 10 Mining & quarrying 10 Agriculture 5 Total GDP 0 5 -5 0 -10 -5 -15 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Q1 2023 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 Source: CEIC; World Bank staff calculations. Source: BPS; World Bank staff calculations Note: Non-mining industry comprises Manufacturing, Utilities, and Construction. Services with high skilled labor concentration comprises Information and Communication, Financial, Real Estate, Business, Public Administration, Education, Other services, Human Health and Social Work. Services with low skilled labor concentration comprises Trade, Transportation and Hospitality sector. 6 Indonesia Economic Prospects June 2023 Inflation is easing at a faster In line with peers, headline inflation edged down, reaching 4 percent yoy in May pace than markets anticipated. 2023. This is the lowest inflation recorded since it peaked in September 2022 when global inflationary pressures mounted following Russia’s invasion of Ukraine (Figure A.5). This brings inflation back down to Bank Indonesia’s inflation target range (2-4 percent) for the first time since June 2022 and sooner than anticipated by most observers. Nevertheless, inflation became There has been a significant change in the distribution of price increases across the CPI more broad-based, partly components (Figure A.6). In January 2022, prices across 60 percent of the CPI basket reflecting a pick-up in demand rose between 0-2 percent while the rest increased between 2-4 percent. However, in for most goods and services as May 2023, prices across 88 percent of the basket rose between 0-4 percent, and 12 headline and core inflation are percent of it rose 12-14 percent. This is reflective of second round effects from rising converging. commodity prices in 2022. The slowing pace of inflation These can be grouped in four areas: i) the decline in global oil prices that have is attributed to a combination impacted energy as well as transport prices, ii) improved harvest and decline in of external and policy-related cooking oil prices, iii) government intervention at sub-regional level to ease supply factors. bottlenecks notably for food and rice, and iv) the appreciation of the Rupiah which lowered the cost of imports. Those factors have outweighed the seasonal effects from Ramadan, which puts pressure on prices given heightened demand for food and consumer goods. Meanwhile, core inflation continued to edge down since the start of the year and has recorded 2.8 percent yoy. Such trend reflects a potential softening of domestic demand. Figure A.5: Inflation tapered down earlier than expected Figure A.6: … but became broader-based as more (contribution to inflation, percentage points) goods and services had higher price rises due to second round effects from earlier commodity price shocks (percent yoy) Personal Care and Other Services 0-2% 2-4% 4-6% 6-8% Food and Beverage Provision/Restaurant Education 8-10% 10-12% 12-14% 14-16% Recreation, Sports, & Culture 100 Information, Communication & Financial Services Transportation Health 8 Household Equipment & Routine Maintenance 80 Housing, Water, Electricity & Other Fuel Clothing and Footwear 6 Food, Beverage and Tobacco 60 CPI CPI BENCHMARK 4 40 2 20 0 -2 0 Jul-20 Jul-21 Jul-22 Apr-20 Apr-21 Apr-22 Jan-20 Jan-21 Jan-22 Jan-23 Oct-20 Oct-21 Oct-22 Jan-22 May-22 Jan-23 May-23 Jan-20 May-20 Jan-21 May-21 Nov-20 Nov-21 Nov-22 Mar-22 Mar-23 Mar-20 Mar-21 Sep-20 Sep-21 Sep-22 Jul-21 Jul-22 Jul-20 Source: CEIC, World Bank staff calculations. Source: BPS, CEIC, World Bank staff calculations. Notes: The average selected peers consist of 6 countries comprising Note: Price distribution is calculated as the changes of CPI Brazil, China, Malaysia, Philippines, India and Thailand. components across sectors using its weight. 7 Indonesia Economic Prospects June 2023 Labor markets have recovered from COVID-19 but not equally across different groups, with new trends emerging, including a rising gig economy and older age workers. More people are getting Female LFP rose substantially. While more jobs have been added due to solid growth, back into the workforce, but the rise in female LFP could partly be driven by falling household income that pushed employment is not recovering women to enter the labor force. The latest data on real wages indicates that while equally across different groups they had not returned on average to pre-pandemic norms, they have increased and many workers are still on nevertheless for all sectors except agriculture, finance, electricity, gas and water reduced hours. supply. Moreover, the share of unpaid workers rose by 1.6 pp compared to before the pandemic. Workers are still facing difficulties in finding jobs with unemployment remaining above pre-pandemic levels. It continues to deteriorate also for some groups. Among youth and elder workers, unemployment rates rose from 18.6 percent (0.7 for elder) to 20.6 percent (2.9 for elder) between 2019 and 2022. Furthermore, even after three years since the pandemic hit, two-thirds of workers are having to work less hours than before.⁵ Unlike other crises, the This is potentially due to the significant reduction in the share of employment in pandemic did not change the agriculture already underway prior to the pandemic. Indeed, the size of the workforce structure of the labor market. in the agriculture sector had shrunk from 40.7% in 1997 to 28.6% in 2022. As a result, less workers were able to turn to agriculture to cushion the impact of the COVID-19 crisis. Three years after the Asian Financial Crisis started in 1997, shares of workers in the agriculture sector increased by 4.6 pp to 45.3% in 2000, while shares of workers in both manufacturing and services declined (Figure A.7). On the other hand, the distribution of workers across sectors remained unchanged three years after the COVID-19 crisis began. Unlike previous episodes of economic shocks, which led to firm closures and worker dismissals, COVID-19 was perceived as temporary health induced shock that led firms to pursue reduced hours instead of closures as a main coping mechanism. Figure A.7: Sector composition during the Asian financial crisis and COVID Crisis Sectoral composition of workers during Asian Financial Crisis and Covid-19 (%) 100 80 40.2 37.3 49.2 49.2 60 19.1 17.4 40 23.3 22.2 20 40.7 45.3 27.5 28.6 0 1997 2000 2019 2022 Agriculture Industry Services Source: Sakernas (1997 and 2000 data are using the yearly, 2019 and 2022 are using August round) 4 Source: Sakernas, February 2023 based on BPS Press Release in May 2023. For the remaining of labor section, labor market comparisons were made using August rounds of Sakernas to avoid any effects from seasonality. 5 3.48 out of 4.15 million workers experienced reduced hours. Source: Sakernas, August 2022. 8 Indonesia Economic Prospects June 2023 Post-pandemic labor trends Although workers remained in their sectors, reduced hours led to underemployment show rising numbers of gig and workers turning to informal jobs to make up for income loss. Between August workers, mostly informal, as 2019 and 2022, the share of self-employed workers rose by 1.8 pp while the share of the digital economy expanded, permanent workers fell by 3.0 pp. The recovery from the pandemic was also paralleled and more older age workers by the development of the digital economy and a significant growth in both internet entered the labor force. connectivity and use of smartphones including in rural areas. This has accelerated an already growing gig economy. Six to seven percent of informal workers in Indonesia are full-time gig workers. Around 63 percent are providing location-based services, mainly in urban areas. Furthermore, the age composition of the labor market also slightly changed with more older age workers entering the labor market between 2019 and 2022. The share of elder workers in the labor force increased by 2.5 pp to 13.5 percent while shares of workers in other age groups dropped. The ageing of the labor Informal or gig workers tend not to be covered by existing social protection systems. market and increasing reliance The rising number of gig or informal jobs calls for a rethink of worker protection on gig employment call for particularly if digital labor platforms provoke a race to the bottom regarding working expanded social protection conditions. The increased entry of elder workers into the labor force could already and rethinking of programs to be an indicator of both the falling incomes of this population and their inability to increase worker productivity. access social protection schemes. Moreover, elder workers are less likely to find a job and once unemployed are more likely to leave the labor force discouraged. Thus, an inclusive system where informal and older workers can be protected through access to social insurance schemes and other relevant worker protection is important. Indonesia’s trade growth is moderating and remains dominated by raw minerals, namely coal, while manufacturing exports’ contribution remains limited. Indonesia’s international trade Although global supply chain disruptions have abated and global shipping conditions flows continued to slow in the have returned to pre-pandemic levels, subdued global demand and the decline first half of 2023, dampened in commodity prices have been weighing significantly on Indonesia’s exports. The by global growth, persistent growth of goods exports has been persistently slowing since Q3-21. Export of goods inflation, and moderating reached US$19.3 billion in April 2023, a contraction of 29 percent yoy, and a significant commodity prices. drop from the all-time high of US$28 billion in August 2022 (Figure A.8). Global commodity prices have edged down over the past six months after record-high levels for many commodities last year. As a result, the contribution of commodity prices to export growth narrowed (Figure A.9). Meanwhile, imports have also dropped amidst moderating domestic demand to reach US$15.4 billion in April 2023, a contraction of 22 percent yoy. Raw minerals, namely coal, Exports of coal were boosted by an all-time high global coal consumption in 2022 remain the primary driver explained by strong demand in Europe (seeking alternatives to Russian natural of recent growth in exports gas), India (to meet its increasing power needs), and China (to fill shortfalls from but have started trending hydropower caused by record breaking droughts). As a result, Indonesia’s coal downwards in Q1-23. exports increased from US$33 billion in 2021 to a staggering US$55 billion in 2022. China, the largest importer of Indonesian coal, followed by India and Japan, have been driving the increase of coal and overall Indonesian exports. At the beginning of 2023, Indonesia’s minerals exports growth started to soften as global commodity prices dropped (Figure A.10) although remain significant, boosted by China’s post- pandemic recovery. 9 Indonesia Economic Prospects June 2023 The contribution of While manufacturing of base metals such as iron and steel accounted for approximately manufactures to export growth one-third of export growth, exports of non-commodity-based manufactures such has been limited. as clothing or plastics had a negative contribution to export growth. This reflects weakening global demand for non-energy related goods as global inflationary pressures persist. Such impact can be partially mitigated through reforms to boost the competitiveness of non-commodity industries (World Bank, 2022b). Unlike goods exports, services Services trade has traditionally accounted for a relatively small share of Indonesia’s exports continue to strengthen total trade flows, adding up to only 7.3 percent of total exports and 15.9 percent of following the recovery of total imports in 2022. Growth rates of services trade have been on the rise, serving as tourism and sea transport a counterbalance to moderating goods trade growth since Q2-21 (Figure A.11). In Q1- services from pandemic- 23, services exports grew by a stark 91.5 percent yoy, compared to only 0.8 percent induced restrictions. for goods exports. A widening services trade deficit underscores the need for policies to improve Indonesia’s services trade competitiveness. Figure A.8: Goods trade growth continued to Figure A.9: …while fading commodity price windfalls moderate dampened export growth (percent yoy growth (values)) (contribution to percent yoy growth) 80 Exports Imports 120 Price Volume 100 60 80 40 60 20 40 20 0 0 -20 -20 -40 -40 -60 -60 Mar-20 Mar-21 Mar-22 Jun-20 Mar-23 Jun-21 Jun-22 Sep-20 Dec-20 Sep-21 Dec-21 Sep-22 Dec-22 Mar-20 Mar-21 Mar-22 Jun-20 Mar-23 Jun-21 Jun-22 Sep-20 Dec-20 Sep-21 Dec-21 Sep-22 Dec-22 Figure A.10: Manufactures have been contributing Figure A.11: The moderation of goods exports was little to recent export growth, supported mostly by accompanied by strengthening services trade sustained raw minerals (coal) exports (USD billion (LHS) and percent yoy growth (RHS)) (contribution to percent yoy growth) Agriculture (incl. palm oil) Raw minerals and fuels Services exports (LHS) Base metals and products Other manufactures Goods exports (LHS) 80 Goods exports growth (RHS) 100 Services exports growth (RHS) 100 60 80 40 50 Growth Rate (%) USD (Billion) 60 20 0 40 0 -50 20 -20 0 -100 -40 Mar-20 Mar-21 Mar-22 Jun-20 Mar-23 Jun-21 Jun-22 Sep-20 Dec-20 Sep-21 Dec-21 Sep-22 Dec-22 Mar-20 Mar-21 Mar-22 Jun-20 Mar-23 Jun-21 Jun-22 Sep-20 Dec-20 Sep-21 Dec-21 Sep-22 Dec-22 Source: BPS and Bank Indonesia; World Bank staff calculations. 10 Indonesia Economic Prospects June 2023 Global financing pressures are offset by Indonesia’s declining financing needs and more stable financing sources. Indonesia’s external position While the current account surplus has widened on a yoy basis, from 0.2 percent of GDP remains in surplus despite in Q1-22 to 0.9 percent in Q1-23, the quarterly trend seems to be moderating since the easing commodity prices, and start of the year (Figure A.12). The widening surplus is linked primarily to weakening thanks to moderating domestic imports of goods instead of rising exports. The latter have been decelerating as prices demand. of major export commodities like coal, palm oil, and other metals dropped. This has also been accompanied by a widening of the primary account deficit, compared to Q1 last year, as repatriation of company dividends increased notably in the mining sector. External financing pressures External financing remains adequate at US$ 3.6 billion in Q1-23 (1.1 percent of GDP) have eased since the beginning thanks to the current account surplus. Moreover, investor confidence in Indonesian of the year given declining assets remained strong, resulting in portfolio inflows of 1.3 percent of GDP over the financing needs and stable same period. This reversed the 2022 trend and was realized despite tightening global financing sources. financial conditions and outflows in many EMDEs. The bulk of external financing came from FDI and other private investments including currency, loans, trade credits, and advances (Figure A.13). FDI has been a steady source of external financing in the past 3 years and has outperformed the more volatile and shorter-term portfolio and debt flows. Figure A.12: The current account surplus was Figure A.13: External financing needs came mostly sustained, supported by high commodity prices from investments (percent of GDP) (financing sources, USD billion) Income FDI Portfolio Inv. Services Trade Capital Acc. Other Inv.:Public Goods Trade Other Inv.: Private Change in Reserves Current account balance Financing Needs 5 80 4 3 60 2 40 1 0 20 -1 -2 0 -3 -4 -20 Mar-20 Sep-20 Mar-21 Sep-21 Mar-22 Sep-22 Mar-23 2016 2017 2018 2019 2020 2021 2022 Source: Bank Indonesia, CEIC, World Bank staff calculations. Source: Bank Indonesia, World Bank staff calculations. Indonesia is more resilient to external shocks as foreign exchange reserves have increased, external debt has been falling, and investor perceptions of risk and the currency have been stable External buffers remain strong BI’s foreign currency reserves went from US$ 137.2 billion in 2022 to US$ 139.3 billion with rising Net Foreign Assets in May, covering 6 months of imports and short-term debt. Using the Assessment of Bank Indonesia (BI). of Reserve Adequacy methodology of the IMF, BI reserves remain adequate. They are sufficient to absorb near-term external shocks with enough cover for short-term debts and other liabilities (Figure A.14). Reserves to ARA metrics ratio were slightly below that of peer countries. 11 Indonesia Economic Prospects June 2023 Strong external buffers have The Rupiah appreciated by 4.6 percent ytd against the USD, while long-term bond enabled BI to stabilize the yields declined by 61 bps over the same period. The currency has become less Rupiah in 2022. sensitive to capital flows movement. Rupiah’s volatility is relatively low compared to peer countries (Figure A.15). Indonesia’s real effective exchange rate (REER) also appreciated 6.4 percent for the ytd. External debt vulnerabilities Indonesia’s external debt stock continues to drop, reaching 28.4 percent of GDP by have declined. March 2023 (Figure A.16). Both public and private sector external debt have fallen, an indication of ample liquidity in domestic markets following the commodity boom. Indonesian private companies are now turning more to domestic markets to finance their operational needs, reducing as such currency risk. The GoI has also shifted its borrowing away from external to domestic sovereign bonds (SBN). It reduced the risks from exchange rate and global financial market volatility. Furthermore, external borrowing maturities have been extended. Short-term external borrowing (both private and public) is at its lowest levels, reducing as such the impact from capital flows volatility. Indonesia’s sovereign debt Global uncertainty from Russia’s war on Ukraine, advanced economy monetary credit premium has been tightening cycle, and prospects of China’s outlook have all escalated EMDEs’ credit edging downward but it risk premiums in the second half of 2022, though it moderated since the beginning remains slightly higher than of this year (Figure A.17). This is also the case for Indonesia where the medium-term peers. (5-years) credit default swaps (CDS) have declined but remain above pre-pandemic levels and higher than peers in the region. Figure A.14: Forex reserves stocks are adequate Figure A.15: The Rupiah remained stable compared to (ARA metric decomposition, in billion USD) peer countries (currency volatility, daily movement, annualized, index) Export revenues (BXGS) Broad money (FMB_USD) interquartile range Indonesia Short-term Debt (D_SRM) Other Liabilities (OL) 0.35 160 Reserves 140 0.3 120 0.25 100 0.2 80 0.15 60 0.1 40 0.05 20 0 0 May-19 May-20 May-21 May-22 May-23 Jan-19 Sep-19 Jan-20 Sep-20 Jan-21 Sep-21 Jan-22 Sep-22 Jan-23 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Source: Haver Analytics, World Bank staff calculations. Source: Bank Indonesia, IMF, World Bank staff calculations. Note: ARA (Assessing Reserve Adequacy) Metric is defined as all Note: Peers are Argentina, Brazil, Russia, Turkey, South Africa, Malaysia, the country ‘liabilities’ that is held under foreign currency (IMF India, and Mexico. formula includes exports + broad money + short term debt + other liabilities) 6 ARA metric is a methodology developed by the IMF to measure a country’s potential foreign exchange liquidity in adverse circumstances against which reserves could be held as a precautionary buffer (IMF, 2016). 12 Indonesia Economic Prospects June 2023 Figure A.16: External debt exposure is declining Figure A.17: Credit risk premia declined though (percent of GDP) remained above pre-pandemic level (CDS spread 5-year, basis points) 40% 36.5% 39.4% China Malaysia Indonesia 34.9% Brazil Philippines South Africa 30.2% 1,000 14.8% 28.4% Russia’s Invasion of Ukraine Capital Outflows from EMDEs 30% US Inflation Reached 40-year high Early Spread of COVID-19 13.3% 13.3% 800 11.4% 10.4% 20% 600 10% 400 4.7% 4.8% 3.9% 3.9% 3.7% 200 0% 2019 2020 2021 2022 2023 Short-term public debt Short-term private debt 0 Sep-19 Sep-20 Sep-21 Sep-22 May-19 May-20 May-21 May-22 May-23 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23 Long-term public debt Long-term private debt Debt stock (% of GDP) Source: Bank Indonesia, World Bank staff calculations. Source: JP Morgan, World Bank staff calculations Note: For 2023, data only limited to March 2023 2. The Policy Stance The fiscal stance has normalized reflecting faster fiscal consolidation, anchored by a broad-based rise in revenues and prudent public spending both recurrent and capital. Indonesia’s fiscal policy stance The fiscal deficit, which peaked at 6.1 percent of GDP in 2020, declined to 2.4 percent has normalized reflecting faster of GDP in 2022, below the 4.5 percent of GDP target in the revised Budget (Figure fiscal consolidation in 2022. A.18). This implies that the government had returned to its fiscal rule mandate, of having a fiscal deficit below 3 percent of GDP, one year earlier than targeted. This was driven by higher-than-expected revenue realization (116 percent of the target in the revised Budget law) spending discipline (99 percent of the revised Budget target). Strong revenue was buoyed by Revenues rose by 31 percent in 2022. This was largely led by i) higher commodity a mix of high commodity prices, prices with related revenues⁷ up by 63 percent; ii) a recovery in domestic demand rising domestic demand, and boosting income tax, VAT, and excises; and iii) reforms from the Tax Harmonization reforms; whilst spending was Law (THL) including a voluntary disclosure program, a tax on the digital economy, contained through the rolling and a VAT rate hike that was effective in April 2022⁸ (Figure A.19). On the other hand, back of COVID-19 programs. expenditure growth moderated to 10 percent as the GoI rolled back pandemic- related stimulus measures. Expenditures were largely driven by energy subsidies, which reached 2.8 percent of GDP in 2022 (Figure A.20). This forced GoI to hike subsidized fuel prices by an average of 30 percent in September 2022 and use part of the savings to compensate the most vulnerable.⁹ Interest payments also rose to 2 percent of GDP following the expanding public debt stock during COVID-19 as well as the rising borrowing costs given monetary policy tightening. Meanwhile capital expenditure under executed and declined by 0.3 percent in 2022. 7 In particular, natural resources non-tax revenue including oil and gas and mining grew at 80 percent in 2022. ⁸ The Ministry of Finance estimated the impact of tax reform implementation in 2022 around 0.6 percent of GDP. ⁹ See the World Bank (2022b) for more details on the energy subsidies. 13 Indonesia Economic Prospects June 2023 In 2023, fiscal outcomes in The GoI recorded a fiscal surplus of 0.6 percent of GDP in Q1-23, up significantly from the first quarter recorded a 0.1 percent of GDP in Q1-22. Revenues maintained a strong performance so far (up sizeable surplus driven also 27 percent yoy), supported by rising domestic VAT and progress in tax returns filing/ by commodity windfalls and reporting. On the other hand, expenditure grew by a moderate 6 percent due to contained expenditure growth. interest payment, reflecting a continued rise in borrowing costs, as well as a pickup in spending on goods and services in various programs.10 Capital expenditure also recovered and was up 25 percent. However, its contribution to total expenditure growth remains modest. Meanwhile, social expenditure and subnational transfers contracted due to delays in determining the terms of earmarked general allocation funds. Public debt gradually declined, Public debt dropped from its peak of 40.7 percent of GDP in 2021 to 39.5 percent in in line with fiscal consolidation, 2022, and now stands at 39.1 percent in March 2023. It remains though above its pre- and its composition changed. pandemic level in 2019 (Figure A.21). With ample liquidity in the domestic markets and BI halting budgetary financing in 2023, the public debt composition is changing. By the end of Q1-23, domestic debt accounted for 72.1 percent of total public debt (up from 70.8 percent in 2022) with commercial banks increasing their sovereign lending. Banks now hold 29.9 percent of domestic government debt while the public holds 35.2 percent. Such composition change reduces public debt risks associated to exchange rate volatility. However, the implications of rising borrowing from domestic banks on crowding-out private sector credit will need to be monitored. Budget financing conditions Indonesia’s sovereign bonds remain attractive to investors. This is evidenced by the remain favorable for Indonesia relatively high bid-to-cover ratios of government bonds, which suggests that demand despite uncertainty and for GoI bonds remains strong. Additionally, the interest rate on Indonesia’s 10-year external volatility, but financing Rupiah bond has trended downwards and is below the Emerging Market Bond costs are expected to climb. Index (EMBI) average. However, the EMBI has recently increased due to rising global uncertainty and volatility. Taking advantage of the 2022 burden-sharing policy with BI and anticipating market volatility and uncertainty in 2023, the GoI accumulated a financing surplus of nearly IDR 120 trillion (0.6 percent of GDP). This surplus coupled with favorable fiscal performance resulted in ample budgetary liquidity in 2023. Figure A.18: Faster fiscal consolidation supported Figure A.19: Commodity windfalls, domestic demand and by strong revenue performance reforms supported a strong revenue performance so far (revenue, expenditure, fiscal balance, % of GDP) (contribution to annual nominal growth, percent) Income Tax (non-oil&gas) Sales Tax (VAT) 18 40 Excises International Trade Tax Other taxes NTR - others 15 Grants Income Tax (oil&gas) 30 NTR - natural resources Revenues 12 9 Fiscal balance (Budget) 20 6 Fiscal balance Total revenue 10 3 Total expenditure 0 0 -3 -10 -6 -9 -20 2015 2016 2017 2018 2019 2020 2021 2022 2023* 2016 2017 2018 2019 2020 2021 2022 Mar-23 Note: * 2023 are projections Source: Ministry of Finance and WB staff calculations Source: Ministry of Finance and WB staff calculations 10 This includes higher disbursement for programs in education (BOS program for MoRA), defense (maintenance for defense equipment), health (health equipment and services including for police), and infrastructure (housing assistance and road maintenance). 14 Indonesia Economic Prospects June 2023 Figure A.20: … while rising energy subsidies drove Figure A.21: Indonesia’s public debt is gradually expenditure growth declining, in contrast with some of its peers (contribution to annual nominal growth, percent) (public Sector Debt, percent of GDP) Personnel Material Brazil China Capital Energy subsidy 120 Indonesia Malaysia Social Others Philippines Thailand Interest payments Non-energy subsidy 100 Vietnam 20 Total 80 60 10 40 0 20 0 -10 2016 2017 2018 2019 2020 2021 2022 Mar-23 Source: Ministry of Finance and WB staff calculations Source: IMF-Fiscal Monitor April 2023 Note: For Indonesia, 2022 and 2023 data are derived MoF; For Malaysia, Thailand, and Vietnam, 2022 data are estimates; 2023 data for all countries are estimates Easing inflation and resilient capital flows have led Bank Indonesia to ease its pace of monetary tightening After six consecutive hikes in BI raised its policy rate by a cumulative 225 basis points last year. Since January 2023, 2022, BI maintained its policy however, BI has held its policy rate at 5.75 percent. Inflationary pressures are steadily rate unchanged so far in 2023 easing, and inflation expectations are now anchored and expected to drop below as inflationary and external market pressures eased. BI target in the second half of 2023. Moreover, despite the narrowest interest rate spread recorded between US Fed rate and Indonesia, portfolio flows have stabilized and turned positive, giving a boost to the Rupiah. Decelerating inflation provides With inflation trending downwards and BI maintaining its policy rate unchanged, BI with more space for the real interest rate is gradually picking up. By April 2023, it reached an estimated accommodative monetary 1.72 percent (Figure A.22). The real interest rate is expected to gradually edge up policy to counter rising though by the end of the year if inflation remains within BI’s desirable target range borrowing costs and support of 3±1 percent. As a result, this would raise borrowing costs further and impact growth. economic activity especially through private sector credit. This could be an important consideration for BI to help calibrate its monetary policy stance going forward. BI has used a series of policy In 2022, BI used foreign currency reserves more prominently to stabilize the Rupiah measures to navigate external when it came under pressure from tightening external markets. This policy protected market pressures amidst households’ purchasing power amidst rising cost-push inflation. Such intervention synchronous global shocks. seemed more prominent compared to other EMDEs, although the reserve drainage was also less acute (Figure A.23). BI has also used interest rate prominently as a policy instrument to maintain the attractiveness of Indonesian assets to foreign investors and attract portfolio flows. However, in the beginning of 2023, it allowed for more exchange rate movement in response to external market pressures and built buffers through foreign exchange reserves. 15 Indonesia Economic Prospects June 2023 BI also utilizes non-monetary BI recently implemented macroprudential policies to encourage banks to disburse instruments to boost domestic credits to priority and green sectors. It has also introduced new regulations related consumption and manage to credit card usage aimed at improving transactions efficiency and boosting credit. liquidity. Meanwhile, BI performed twist operations11 to stabilize the currency, and raised the reserve requirement ratio in June and September last year. As a result, M2 growth further decelerated to 5.5 percent yoy in April from 8.4 percent yoy in end-2022. Net claims on the central government also declined by 25.3 percent yoy in April as BI stopped its monetary financing scheme from 2022. Furthermore, the central bank – through the Central and Regional Inflation Control Team (Tim Pengendalian Inflasi Pusat dan Daerah) – has worked closely with regional governments to strengthen food supply and distribution systems within the regions to help manage inflation. Figure A.22: Overall, policy rate differential with Figure A.23: BI has used a mix of policy responses to the US Federal Reserve has been narrowing despite navigate external shocks, which have eased in early recent pickup 2023 (real interest rate differential with the US, percent) (standardized monthly change, percent) Indonesia Malaysia Policy Intervention to External Market Pressure Philippines India South Africa China 100% 8 PEERS AVERAGE ALL 50% 6 0% -50% 4 -100% 2 South Africa Brazil South Africa Brazil India Indonesia India Indonesia Argentina Argentina 0 -2 March - Dec 2022 Jan - March 2023 May-19 May-20 May-21 May-22 May-23 Jan-19 Sep-19 Jan-20 Sep-20 Jan-21 Sep-21 Jan-22 Sep-22 Jan-23 Exchange rate Interest rate Foreign reserves Source: CEIC, Consensus Forecast, World Bank staff calculations. Source: Haver Analytics, World Bank staff calculations. Note: Real interest rate is defined as nominal interest rate minus Note: Interest policy is calculated through spread of Indonesia expected inflation. Peers comprises of 19 comparator countries. – US interest rate. A negative denotes narrowing spread of the interest rate. The policy response is calculated through monthly changes minus average changes since 2010, divided by its St. Dev. With banking sector vulnerabilities remaining low and demand for private sector credit growing, structural reforms to deepen the financial sector are underway and remain key for growth Bank asset quality remains The system-wide non-performing loan (NPL) ratio has not changed much since mid- generally high, and bank 2020 and stands at 2.5 percent as of March 2023 (Figure A.24). The average loan at capital and provisioning risk (LAR) ratio12 for the top banks has been on a downward trend for some time and levels adequate to withstand stood at 14.4 percent as of December 2022. The capital adequacy ratio remains stable potential adverse shocks. at 24.6 percent as of March 2023, well above the regulatory minimum of 8 percent. Provisioning levels relative to NPLs stood at 214 percent in January 2023 compared to 198 percent a year ago. 11 Twist operation is where BI selling short-term SBN and purchasing long-term SBN in the secondary market to increase the attractiveness of SBN yields. 12 Based on BI definition, LAR calculation includes restructured loans in collectability (performing loans), restructured & non restructured special mention loans, and NPL. 16 Indonesia Economic Prospects June 2023 However, close monitoring of This is because NPL data could reflect the deterioration in asset quality only with a banking sector stability risks is lag. In anticipation of potential deterioration of credit quality due to the end of credit still warranted. restructuring on March 31, 2023, banks were encouraged to increase the coverage of the allowance for impairment losses for restructured loans. This is especially the case for current quality loans and special mention loans, which could become NPLs. Banking sector profitability As of February 2023, return on assets (ROA) and interest margin to gross income remains stable after a decline were at 2.8 percent and 4.7 percent respectively. This is higher than the 2.3 percent from pre-pandemic levels. ROA and 4.5 percent interest margin to gross income a year ago and edging closer to pre-pandemic levels. Meanwhile, return on equity (ROE) recorded 13.3 percent as of December 2022, lower than pre-pandemic levels of 14.6 percent. Profitability of Indonesian banks has traditionally been higher than EAP regional peers, due to market structure, weaker competition, and the dominance of state-owned banks. Credit to the private sector has Support from the banking system to the real economy continues to show strength been on the rise amidst ample despite monetary tightening. Credit growth has been positive for almost two years liquidity in the market, though and grew by 9.9 percent yoy as of March 2023, broadly at par with pre-pandemic it recently decelerated. average. Survey data also points to stable household demand for credit (Figure A.25). As of January 2023, lending to Micro, Small and Medium Enterprises (MSMEs) stood at IDR 1,358 trillion (6.4 percent of GDP), accounting for 21 percent of all bank lending. This is an increase from the low baseline of 18 percent seen during the pandemic period. Such improvement is supported by BI’s regulatory requirement on credit allocation to MSMEs. At 37 percent of GDP, overall private sector credit in Indonesia remains below EAP average (171 percent of GDP).13 This signals room for financial sector deepening through structural reforms. Financial inclusion is one area of reform (see Box A.1), the implementation of the recently approved Financial Sector Omnibus Law is another. BOX A.1 Financial Inclusion in Indonesia With over 98 million adults (almost 50 percent) without access to a transaction account, Indonesia has one of the largest unbanked populations in the world. This means limited scope for households and firms to invest in their future and to protect themselves from unexpected shocks. The access to and usage of transaction accounts has remained stagnant since 2017. Transaction accounts play a critical role in enabling the use of other financial services, such as credit, insurance, and investment. As per the Global Findex 2021, only 52 percent of Indonesian adults have access to a transaction account, which is a 3 percent increase from 2017. However, this significantly lags EAP and lower-middle- income country averages, which are 81 percent and 62 percent, respectively. The use of digital payments, at 37 percent, is only half of the regional average of 76 percent. Credit to the private sector, particularly to MSMEs, stands out as a related and critical financial inclusion constraint. As of January 2023, lending to MSMEs stands at IDR 1,329 trillion and accounts for only 21 percent of all bank lending, even though 98 percent of all firms in Indonesia are MSMEs. In the latest round of the World Bank Business Pulse Surveys (October 2022) 54 percent of MSMEs reported difficulty in accessing finance when they needed it. Credit constraints are amplified for female borrowers, who are more likely to lack collateral to secure loans, and for populations outside of Java. 13 World Bank’s World Development Indicators (WDI). 17 Indonesia Economic Prospects June 2023 Fintech, the application of digital technology to financial services, provides new opportunities to advance financial inclusion, both for households and firms. Most notably, it serves as a medium for democratizing access to financial services and reaching underserved clients, who may lack formal credit histories, high-value assets, or access to bank branches. At the same time, if not closely regulated, digital financial services (DFS) can pose new risks for both households and firms, including over-indebtedness, predatory lending, and cyber-security. Establishing a regulatory environment that promotes the responsible expansion of DFS is therefore a key priority in increasing access and usage of financial services in Indonesia. The number of fintech players in Indonesia increased six-fold over the last decade, rising from 51 active players in 2011 to 334 in 2022. While the first wave of fintech growth was dominated by the payment segment, the ecosystem is now a more diverse landscape driven by lending (30 million active borrower accounts), payments (60 million active users), and wealth management (9 million retail investors).14 The expansion of fintech is introducing new dynamics in the financial sector, with emerging players such as P2P lenders and digital banks both competing and collaborating with incumbent players such as commercial banks. Opportunities lie on the horizon to increase adoption of DFS and advance financial inclusion in Indonesia. For instance, digitalizing large-volume recurrent payments streams such as social assistance transfers, can both transition the unbanked toward accounts and reduce costs. Instilling public trust can also play a meaningful role. A new Bank Indonesia initiative on central bank digital currency (Digital Rupiah), for example, can help enhance consumer confidence in new financial technologies. Finally, scaling digital financial literacy, to help households understand both the benefits and pitfalls of new technologies, can drive demand, and increase safe usage. Indonesia has recently passed After almost two years of preparation, the FSOL was approved by the Parliament the Financial Sector Omnibus on December 15, 2022, and ratified by the President on January 12, 2023. The law Law (FSOL), a major reform integrates 17 institutional and sectoral laws for the financial sector, paving the way step. for financial deepening, while strengthening financial efficiency and resilience. By doing so, the law has paved the way for some of the key structural reforms in the financial sector15 (See Box A.2). Going forward, it is crucial to focus on the timely implementation of the FSOL. This will require the issuance of several implementing regulations at both GOI and institution-specific levels. Additionally, it is important to move forward with the ongoing amendment process of the Bankruptcy Law, which was not part of the FSOL, to ensure that creditors’ interests are adequately protected. Recent turbulences in global Instability in advanced economies’ (AEs) banking system have caused widespread banking markets appear to concerns of broader contagion and spillover across the global financial system and have had a very limited and more incidences of bank runs.16 EMDEs were primarily affected by the change in risk only indirect impact on the sentiment manifesting itself in exchange rate depreciation and capital outflows, which Indonesian financial sector. could aggravate if new adverse developments were to occur. 14 Kumar et al (2023) 15 Those structural reforms were outlined in detail in World Bank (2022a) 16 Those turbulences started with the failure of Silicon Valley Bank (SVB) in the United States in March 2023 and subsequent takeover by the US Fed- eral Deposit Insurance Corporation (FDIC) and Credit Suisse’s acquisition by UBS orchestrated by the Swiss central bank and financial regulators. 18 Indonesia Economic Prospects June 2023 BOX A.2 Key elements of the financial sector omnibus law The FSOL has achieved significant milestones in critical areas such as institutional architecture and financial stability, long-term finance, sustainable finance, financial innovation and consumer protection, and access to MSME finance. Institutional architecture and financial stability. Greater effectiveness of supervision and regulation by expanding the role of the Deposit Insurance Agency (Lembaga Penjamin Simpanan LPS) in the resolution of banks and insurance companies; strengthening the Financial Services Authority’s (Otoritas Jasa Keuangan OJK) powers on early interventions and inspections, as well as on undertaking consolidated and conglomerate supervision of financial conglomerates; establishing BI as the authority in charge of macroprudential policy; leveling the playing field for legal protection of all supervisors. Long-term finance. Legal foundations for collective investment products, trust-like structures, close-out netting in financial hedging/derivatives transactions and crypto assets. Improved governance, fit and proper requirements consumer protection and liquidation processes for the insurance sector. Establishment of the Policyholder Protection Scheme with mandatory participation requirement. Comprehensive revision of the voluntary pension law, with improved governance, actuarial focus/function, pension age or early retirement issues and introduction of cut-loss provisions. Sustainable Finance. Legal foundation to incorporate sustainable finance, in particular green finance, into financial regulation and supervision and for the development of carbon market and carbon trading activities. This can support financial flows toward climate mitigation and adaptation. Financial Innovation and Consumer Protection. Strengthened BI and OJK coordination in overseeing and regulating fintech development bringing flexibility to the regulation and favoring the expansion of innovation. Mandate on consumer protection clearly assigned to financial sector authorities and inclusion of dispute resolution for all consumers of financial services. Access to Finance for MSMEs. Regulation to allow state-owned-banks (SOBs) to write-off NPLs on their MSME loan portfolios, which will help clean up SOB balance sheets and ensure consistency in reporting of NPLs in the banking sector. The government intention is for this to lower NPLs on MSME portfolios and encourage banks to extend credit to MSMEs. For the Indonesian financial First, strong capital adequacy, balance-sheet and liquidity indicators provide a sector, the effect is likely to be cushion against interest rate and liquidity risk shocks. Second, there are limited direct contained. linkages with the affected entities or financial institutions holding a significant share of AT1 bonds written off by the Swiss authorities.17 Third, Indonesian banks, as with most EMDEs, are less reliant on short-term funding and nonstable deposits. Furthermore, Indonesia has not seen large portfolio equity and debt outflows in March, and the currency remains relatively stable. However, there are reasons for This could expose them to interest rate risks, and deposit insurance coverage in caution, as Indonesian banks Indonesia is lower than that in AEs. Close monitoring of these developments is still increased their holdings of merited, as recent developments regarding the closure of First Republic bank in the government securities. United States, the second largest bank closure in the country’s history, indicate that the stress felt by the global banking sector is not over yet. 17 In the case of the Credit Suisse acquisition deal. 19 Indonesia Economic Prospects June 2023 Figure A.24: Financial sector indicators remain sound Figure A.25: Credit to the private sector is stable NPL (LHS) CAR (LHS) Working Capital Investment Tier-1 Capital (LHS) Provision to NPL (RHS) 18% Consumption Total Loan 30% 230% 220% 13% 25% 210% 20% 8% 200% 15% 190% 3% 180% 10% 170% -2% 5% 160% 0% 150% -7% Mar-20 Nov-20 Nov-21 May-20 Mar-21 Nov-22 May-21 Mar-22 May-22 Jan-20 Sep-20 Jan-21 Sep-21 Jan-22 Jul-20 Sep-22 Jan-23 Jul-21 Jul-22 Jan-21 Apr-21 Jan-22 Apr-22 Jan-23 Jan-20 Apr-20 Oct-21 Oct-22 Oct-20 Jul-21 Jul-22 Jul-20 Source: The Financial Services Authority (OJK) Source: The Financial Services Authority (OJK) 3. The Outlook and Risks The global economic outlook Global growth is projected to slow to 2.1 percent in 2023 before recovering softly remains soft amidst economic to 2.4 percent in 2024. Most of the slowdown comes from AEs where inflation is uncertainty. elevated, monetary policy is tighter and demand thus softer. After peaking in 2022, commodity prices are expected to moderate. In 2022, a warmer-than-expected winter in the Northern Hemisphere reduced electricity consumption and thus demand for oil and gas (World Bank,2023a). This trend may continue in 2023. Global inflation has also abated and provides space for central banks to ease the pace for monetary tightening. The EAP region is expected to buck the global trend with growth projected to strengthen to 5 percent in 2023. The recovery in China will balance the moderating activity of other economies in the region. Downside risks are high as Several recent bank collapses in both the US and Europe have raised global risk premia. wider-than-expected banking Regulatory failures, poor risk management, combined with high and rising interest stress and potentially persistent rates could trigger other banking crises. This could therefore prompt higher financial inflationary pressures could vulnerabilities, and further tightening in credit conditions, skewing the economic risks further harm growth. further to the downside. Moreover, inflation could be more persistent than expected, particularly if there is a shock coming from commodity or food prices given uncertain geopolitical conditions and increased risks on food crops from climate change. If this materializes, further monetary tightening could take place, exacerbating the already subdued economic activity. Indonesia’s growth is expected GDP growth is projected to moderate from 5.3 percent in 2022 to 4.9 percent in to remain robust, though the 2023 and stay broadly flat at 5 percent in the medium term (Table A.2). Growth will pace is moderating. continue to be supported by private consumption as inflationary pressures subside. Exports are also expected to remain stable despite softening commodity prices. Global uncertainties are projected to impact foreign investment, which would put a drag on growth and suppress growth potential. Imports are also projected to weaken. The upcoming elections, however, are expected to increase both private and public consumption and provide a temporary boost to domestic demand. 20 Indonesia Economic Prospects June 2023 But unfavorable global Sustained global monetary tightening could keep financing costs high and tighten conditions could weigh on credit conditions. Banking sector shocks in the US have increased global financial Indonesia’s growth and tighten uncertainty and may prompt capital outflows from EMDEs, including Indonesia, policy space. which could incite further policy tightening. Moreover, deteriorating global economic activities can lead to adverse impact on exports and further weaken investment. Domestically, despite moderating, inflation could be stubborn and put a strain on consumer purchasing power. Inflation is projected to Headline inflation is projected to continue its gradual decline and is projected to moderate and remain within reach 3.6 percent by December 2023. With signs of moderating demand, inflation BI’s target this year. is expected to taper further down in 2024-2025 at an average of 3.5 percent. The authorities have also announced that there will be no increase in the VAT or electricity tariffs this year, which would put less pressure on prices. Easing inflation could provide greater space for monetary policy to remain accommodative in supporting the recovery. The external balance is The current account surplus is projected to record a small surplus of 0.02 percent projected to deteriorate as of GDP in 2023 before turning into deficit of 1.0 percent in 2025. Export growth is commodity exports soften, expected to decelerate as prices of palm oil and coal soften and as global demand though moderating imports decelerates further. Imports will moderate in line with moderating domestic demand partially offset the decline. and investment in 2023. Indonesia is expected to comfortably meet its external financing requirements. FDI is projected to gradually pick-up as the Omnibus Law on Job Creation (JCOL) and the GoI agenda to develop the downstream mining and mineral industries are implemented, reaching 1.4 percent of GDP in 2025. Positive interest rate differentials with the US and a stable macro framework are projected to continue to support portfolio inflows. As a result, official reserves are expected to remain ample to finance 6.0 months of next year’s imports over the medium-term. The fiscal deficit is expected to In 2023, the fiscal deficit is projected to be around 2.5 percent of GDP, lower than remain below 3 percent of GDP the 2013 Budget target of 2.8 percent of GDP. This is attributed to strong revenue in 2023-2025 in line with the performance from commodity windfalls, though revenue growth is expected to reinstated fiscal rule. moderate compared to 2022. Faster disbursements ahead of the 2024 elections will keep expenditures close to the Budget’s target. In the medium-term, revenues are projected to improve gradually as the Tax Harmonization Law reforms begin to hold. Public spending is projected to remain stable at around 15 percent of GDP with a compositional shift towards medium-term priorities such as health, social assistance, and infrastructure investment. The subsidies bill is expected to drop with declining global energy prices. With fiscal consolidation achieved, a sizeable surplus in 2022, and favorable financing conditions, the GoI is expected to comfortably meet its fiscal financing needs (averaging 5.9 percent of GDP in 2023-2025). It will do so while navigating emerging external risks as well as domestic risks particularly those coming from infrastructure SOEs’ (Box A.3). 21 Indonesia Economic Prospects June 2023 BOX A.3 Risks from infrastructure SOEs in Indonesia Globally and in Indonesia, SOEs have played a vital role for public investment but remained under- funded. The World Bank (2017) finds that 66 percent of public investment worldwide is implemented by SOEs, which often rely on government capital injections to keep them afloat. Relative to comparable private firms in terms of asset size and sector, global infrastructure SOEs have larger liabilities by almost 1 pp of GDP. Its fiscal implications are sizable. Global estimates suggest that infrastructure SOEs required annual fiscal injections of 0.3 percent of GDP on average to remain afloat during 2008-2019 (World Bank, 2023c). This is a comparable figure to Indonesia where capital injections to SOEs witnessed a significant increase in 2015 and 2016 but declined afterwards (Figure A.26). Investment in economic infrastructure by SOEs in Indonesia expanded from 0.9 percent of GDP (average 2011-2016) to 1.6 percent of GDP (average 2017-2019). Currently, SOEs in Indonesia account for more than one-third of infrastructure investment (Figure A.27). Indonesia’s highly leveraged infrastructure SOEs may pose fiscal risks, especially in the wake of insolvency in one of these entities. As infrastructure SOEs have increasingly taken on debts to fund large projects, their liability-to-equity ratios have risen. Indonesia’s infrastructure SOEs leverage ratios are comparable to those of global SOEs in the same industry, but they are significantly higher than peer private firms listed on the Indonesia Stock Exchange and in emerging market (EM) countries (Table A.1). Waskita Karya, one such SOEs, has been unable to pay the coupon and principal on its bonds since February 2023. The company is now preparing a comprehensive debt restructuring agreement, scheduled to conclude in June. Although its main creditors are 5 state-owned banks (SOBs), contagion risk to the banking sector is expected to be limited, as Waskita’s borrowing represents only 0.4 to 1.4 percent of overall SOB’s lending portfolio (around 0.15 percent of GDP). Capital injections for SOEs are likely to increase with the Ministry of State-Owned Enterprises (MSOE) requesting an additional IDR 25 trillion (0.1 percent of GDP) on top of the IDR 40.4 trillion (0.2 percent of GDP) initially allocated in the 2023 Budget. The MSOE has consolidated several SOEs so far to enhance their performance and competitiveness. Between 2019 and 2022, the total number of SOEs has been reduced from 114 to 41 through consolidation. Furthermore, the MSOE is planning to reduce the number of infrastructure SOEs from 9 to 4. This consolidation is expected to streamline the firms’ business focus and enable better performing entities to take over the assets of poorly performing ones. Figure A.26: Capital injection to SOEs has Figure A.27: … Contributing to higher investment in increased economic infrastructure by SOEs (LHS-IDR trillion; RHS percent of GDP) (infrastructure investment by sources, percent of GDP) Capital injection SOEs Private 80 Capital injection (% GDP) 0.8 6 Subnational Government Central Government Total 60 0.6 4 40 0.4 2 20 0.2 0 0.0 0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022E 2023F 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Source: MoF and WB staff calculations See footnote 28 for a definition of economic infrastructure. Source: MoF, Prospera’s INFRA-Dashboard, and WB staff calculations 22 Indonesia Economic Prospects June 2023 Table A.1: Infrastructure SOEs Liability-to-Equity Ratio Construction SOEs 2016 2017 2018 2019 2020 2021 Q3-2022 Adhi Karya 2.7 3.8 3.8 4.3 5.8 6.1 5.5 Waskita Karya 2.7 3.3 3.3 3.2 5.4 4.4 3.9 Wijaya Karya 1.5 2.1 2.4 2.2 3.1 3.0 3.1 Hutama Karya 2.2 4.7 5.1 3.0 2.5 1.4 0.8 Jasa Marga 2.3 3.3 3.1 3.3 3.2 3.0 2.9 IDX – industry average 1.9 1.3 1.4 EM – industry average 0.8 0.8 1.2 1.3 1.5 1.2 1.6 Global SOEs – road construction firms’ average 2.2 3.2 4.0 Source: IDX Statistics, Government Financial Audited Reports (LKPP), Aswath Damodaran data page based on company filings https://pages.stern.nyu.edu/~adamodar/ where we used D/E ratio for EM (emerging market) countries, and World Bank Database of Infrastructure SOEs. Note: Currently, the available data on IDX website can provide the average of industry ratio in 2019-2022 only. Hutama Karya’s ratio in 2022 was from its full-year (not Q3) financial statements. 4. Structural Growth Constraints and Reforms Priorities Potential growth is declining due to reduced labor input, human capital challenges and slowing productivity growth. Investment and to a lesser Investment contributed on average 5.6 pp to growth between 2003-2019 with extent labor input have been private investment far exceeding public. This is equivalent to about 60 percent of key growth drivers prior to growth,18 which is higher than the contribution of capital to growth in other Lower the pandemic, but all growth Middle-Income Countries (LMICs) (Figure A.28). At the same time, however, growth drivers have now moderated, in TFP slowed by nearly half in the 2010s (contributing on average 0.6 pp annually) particularly total factor relative to the 2000s (1 pp annually). The contribution of TFP growth in Indonesia’s productivity (TFP). has been lower compared to other LMIC’s. This may reflect the relative importance of capital deepening in Indonesia and human capital challenges, both of which are key to TFP growth in the long run.19 Labor input contributed 14 percent to growth, and human capital 8 percent. Like TFP, both labor and human capital growth have slowed in recent years (Figure A.29) and have been growing at slower rates than other LMICs in the last 20 years.20 Productivity gains from the Between the early 2000s and 2019 (prior to COVID-19), labor productivity growth reallocation of resources across slowed by about 0.7 pp. While there have been significant gains from labor moving sectors seem to be fading. from lower productivity sectors to higher productivity ones, these gains have been gradually fading (e.g. from agriculture to industry). Within-sector productivity21 growth accounted for over 70 percent of total labor productivity growth (Figure A.30), like other EMDE’s and advanced economies. 18 Capital accumulation has been primarily driven by private investments, which averaged 29.0 percent of GDP, while public investment averaged only 2.9 percent of GDP in the past decade (Worldbank MPO Database, 2023). 19 Dieppe (2021). 20 On average, TFP growth was 0.9 21 Within sector productivity captures that part of overall labor productivity growth that is due to productivity improvements within the same sector. This may reflect the effects of improvements in human capital, investments in physical capital, technological advances, and the reallocation of resources from the least to the most productive firms within each sector. Between-sector productivity growth captures the part of overall labor pro- ductivity growth that is driven by the reallocation of resources between two different sectors. This includes both static sectoral effect, and dynamic sectoral effect. Static reallocation: shows that workers are moving to sectors with different productivity levels regardless of whether productivity in those destination sectors is rising or falling. Dynamic reallocation: shows that workers are moving to sectors with different productivity growth rates. 23 Indonesia Economic Prospects June 2023 The slowdown in sectoral There have been large labor movements from agriculture (1.3 pp decrease) to reallocation of labor partly industry (0.2 pp) and services (0.7 pp).22 While services have higher productivity in reflects lower absorption of absolute terms, its productivity growth declined and led to the overall drop in labor labor by the services and productivity (Figure A.31). Productivity growth in services fell by 14 percent while industry sectors and decrease in productivity increased by 50 percent in industry and 50 percent in agriculture. This is productivity growth in services. consistent with the shift of lower-skilled labor from agriculture to services, particularly in trade, hotel, and restaurants. Moreover, a substantial share of employment and financial resources in Indonesia has also shifted to business in these relatively low productive service sectors.23 The pandemic exacerbated COVID-19 further exacerbated the decline in human capital and severely affected the declining potential growth capital accumulation. Between 2020 and 2022, the contribution of capital stock to trend. growth dropped to just 4.5 pp annually (Figure A.29), owing to a slowdown in public investments as the GoI reallocated fiscal spending to addressing the pandemic. However, private investment, particularly FDI, recovered slightly in 2022. Meanwhile, human capital growth slowed down. Adjusted years of schooling decreased to 7.8 years from around 8.2 prior to COVID-19. Figure A.28: Indonesia’s investment growth has been Figure A.29: TFP, labor and human capital growth larger than that of LMICs had slowed in recent years 12 5.7 6.06 6 Compound Annual Growth rates Percentage Points (Contributions to 10 5.46 1.0 5.0 1.98 5 4.5 (Percentage Points) 0.88 0.6 8 1.05 1.17 0.6 4 0.3 1.0 1.95 1.66 0.9 0.6 0.0 Growth) 6 3.5 3 0.8 3.2 4 2 2.7 5.63 5.95 2 1 0 0 Indonesia 2003-2019 Lower Middle Income, 2003- 2003-2012 2013-2019 2020-2022 2017 Capital Stock gK Labor gL* Capital Stock Labor Human Capital per Labor gh Total Factor Productivity gA Human Capital per Labor Total Factor Productivity Real GDP gY Real GDP Source: World Development Indicators; World Bank staff calculations using Growth Decomposition Tool 22 Employment rate growth had a negative contribution to value added growth in the period, as not all the decrease in agriculture if fully reflected in the increases in industry and services 23 Ikhsan et al. (2022). 24 Indonesia Economic Prospects June 2023 Figure A.30: Within-sector productivity growth Figure A.31: In addition to intersectoral reallocation, contribution to total labor productivity growth services productivity growth declined and led to the remained dominant and stable overall drop in labor productivity Percentage points Productivity 4 Within sector Between sector 3 change, 1.3 Intersectoral 2 reallocation 0.8 3 Productivity 1 change, Services sector 1.2 0 2 1.4 -1 Productivity change, 0.6 1990s 1990s 1990s 2003-08 2013-17 2003-08 2013-17 2001-2010 2011-2017 0.4 Industry sector 1 0.88 0.93 Productivity change, 0 Advanced economies EMDEs Indonesia Agriculture 2003-2012 2013-2019 sector y=4.35% y=3.66% Source: World Development Indicators; Dieppe (2021), World Bank staff calculations using Growth Decomposition Tool Policy makers are encouraged to build on recent competitiveness reforms to embed further market friendly policies that can accelerate productivity growth. Indonesia has combined Prudent and targeted fiscal and monetary policy responses to COVID-19 and macroeconomic stability commodity price shocks have helped maintain macroeconomic policy space. In with reforms to promote parallel, GoI has pursued reforms to address critical bottlenecks to competitiveness. competitiveness over the past 3 These include measures to liberalize the investment regime through the JCOL, and turbulent years. policies to strengthen the financial sector through the FSOL. Implementation of these recent Ensuring the predictability, credibility, and transparency of investment and financial investment and financial sector sector reforms will be central to investor sentiment. Combining these with Indonesia’s reforms could help reverse the stable macroeconomic conditions and low levels of private and public debt could drop in productivity growth and help contain the costs and risks of private investment. This could promote efficient potential output in Indonesia. allocation of resources, which is necessary to help raise productivity growth and potential output growth. Beyond implementation of Competitiveness is the set of institutions, policies and factors that determine the level recent reforms, additional of productivity in a country.24 Determinants of competitiveness evolve at different efforts to remove constraints stages of development (Figure A.36):25 to competition could raise Indonesia’s competitiveness. a. At early stages of development, foundational policies and institutions that promote strong governance, human capital, infrastructure, and macroeconomic stability are critical for structural transformation and growth. They allow labor and investments to shift from low growth agriculture to high growth industry and services. b. For Indonesia, which has already experienced significant structural transformation across sectors, the focus should be on improving productivity within sectors. This 24 Sala-I-Martin and Artadi (2004). 25 Adapted from Sala-I-Martin, X (2004) and Porter, M (1990), “The Competitive Advantage of Nations” New York: Macmillan, Inc. 25 Indonesia Economic Prospects June 2023 requires policies and institutions that promote competition through business regulations that level the playing field; flexible labor markets; an efficient financial system; and contestable markets. These reforms aim to shift resources away from the least productive and towards the most productive firms and industries. c. For higher income countries that tend to be innovation-driven, determinants of competitiveness include research and development and business sophistication. Indonesia has performed Indonesia has experienced steady improvements in its public sector governance well on basic governance, framework and infrastructure regulations and outcomes, whilst also implementing basic infrastructure, and a solid macro policy framework. These have led to structural transformation and macro stability, which have important gains in poverty reduction with more inclusive growth and declines in been important for structural inequality since 2014 (see Box A.4). But Indonesia has fallen behind on human capital transformation and growth.26 (Figure A.37). Despite progress in recent years, Indonesia remains challenged by stunting, education quality, and health services gaps. Some of these challenges have been aggravated by learning losses caused by the pandemic, which are discussed in further detail in Part B of the report. BOX A.4 Indonesia’s gains in terms of poverty reduction Indonesia has virtually achieved the goal of eradicating extreme poverty. Indonesia’s extreme poverty rate dropped from 18.8 percent in 2002 to 2.7 percent in 2019 (Figure A.32), using the US$ 1.90 2011 PPP per day. Amidst these promising developments, the Government of Indonesia (GoI) committed in 2020 to fully eradicating extreme poverty by 2024. Indeed, extreme poverty continued to drop further to 1.5 percent in 2022 A small amount of frictional poverty is likely to remain, with further progress being difficult to monitor based on surveys given measurement error and statistical inaccuracies. The decline in poverty was broader than just for the extreme poor. In addition to the international extreme poverty line at US$ 1.90 2011 PPP, for the purposes of international comparisons, the World Bank defines international poverty lines at US$ 3.20 2011 PPP for lower middle-income. In Indonesia, the share of the poor, defined as living below a poverty line at US$ 3.20 2011 PPP, dropped from 61 percent in 2002 to 20 percent in 2019 and further to 15.7 percent in 2022. While the pace of poverty reduction is comparable to peers. While millions have moved out of poverty, not all are economically secure.27 The concept of economic insecurity measures vulnerability of households to shocks that can affect their consumption level and bring them down into poverty. In 2019, 40 percent of Indonesians were economically insecure (Figure A.35). Most of these households are non-poor but can fall into poverty when exposed to a shock. The share of economically insecure households has hardly changed since 2011, reflecting that while a significant share of households managed to reach economic security, a similar share escaped poverty but are still insecure. Economic insecurity can undermine improvements in productivity. Short spells of lowered consumption can reduce productivity in the long run due to adverse effects on human capital investment at the household level. Reliance on adverse strategies when coping with income shocks —such as the sale of productive assets— can further reduce productivity. Even before shocks, economically insecure households may anticipate them and adopt conservative or risk-averse production and investment strategies that lower consumption and/or investment. Thus, regardless of whether poor households adopt adverse coping strategies after or before shocks, they reduce long-term productivity. This in turn lowers their chances of securely escaping poverty. 26 The competitiveness assessments are based on composite indices 4 drivers of factor accumulation (basic governance, human capital, basic infra- structure, and macro stability) and 5 efficiency drivers (business regulations, labor markets, financial sector, competition, and trade openness). The composite indices are z scores, which assess Indonesia’s performance relative to 9 comparator countries (Brazil, China, Egypt, India, Indonesia, Republic of Korea, Nigeria, Mexico, Philippines, Türkiye). The z scores were calculated by: (i) subtracting the average from the series for each country’s value; and (ii) dividing by the standard deviation. 27 Economic insecurity is defined as either: (i) being poor with a likelihood of less than 10 percent to be poor next year, or (ii) being non-poor with a likelihood of more than 10 percent to be poor next year. Thus, economically secure households are non-poor with a likelihood of less than 10 percent to be poor next year. Source: World Bank (2023b). 26 Indonesia Economic Prospects June 2023 Figure A.32: Poverty headcount rates using various Figure A.33: Log GDP per capita (PPP) vs poverty rate $ per-day 2011 PPP as well as national poverty line for peers (NPL) NPL $1.9 $3.2 $5.5 9.9 Thailand 100% 9.7 China Log GDP per capita (PPP) 90% 80% 9.5 70% Indonesia 9.3 60% Vietnam 50% 9.1 40% 8.9 Philippines 30% 20% Lao PDR 8.7 10% 0% 8.5 0 10 20 30 40 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 US$ 3.20 PPP Poverty rate (2018) Figure A.34: Poverty rates for Indonesia and its Figure A.35: Share of population classified as economic peers structurally poor, economically insecure, and economically secure 20% 100% 90% 80% 15% 70% 60% 10% 50% 40% 5% 30% 20% 10% 0% 0% Thailand Thailand Vietnam Malaysia Vietnam Malaysia Philippines Philippines Indonesia China Indonesia China 2011 2019 2011 2019 $3.20 $1.90 $1.90 $3.20 Structural Poor Insecure Secure Source: World Bank (2023b) Relative to peers, however, Indonesia has historically restricted market competition through regulation, which Indonesia lags on policies prevent more productive firms and industries to grow. GoI efforts under the JCOL and institutions designed to help tackle some of these, including through the removal of ‘sectors open with open markets and promote conditions’ from the Investment Law; removal of requirements to establish business competition. sectors ‘reserved for MSMEs and cooperatives’ and those that are ‘open to large businesses on condition that they cooperate with MSMEs and cooperatives’; and removal of sector discrimination towards foreign investments from five sectoral laws.28 Building on these, the next stage is to identify specific constraints within policy areas (e.g., finance, procurement, land, business regulations, trade) or within sectors that prohibit market contestability. For example, in the last Indonesia Economic Prospects (December 2022), several barriers to international trade were highlighted. Additionally, restrictions on international trade in services are among the most restrictive in Indonesia (Figure A.38). 28 (i) Law no. 13/2010 on Horticulture; (ii) Law no. 39/2014 on Estate Crops; (iii) Law no. 38/2009 on Postal; (iv) Law no. 1/2009 on Aviation; and (v) Law no. 17/2008 on Shipping. 27 Indonesia Economic Prospects June 2023 Removing constraints to Countries such as the Republic of Korea that have sustained strong growth have competition is shown globally sustained performers on foundational drivers of growth and opened markets to to promote economic growth. competition. Other emerging market economies that have opened markets but fallen behind on basic foundations have suffered rapidly declining potential and actual growth. The focus on market friendly reforms is consistent with Indonesia’s progress in implementing recommendations of the Growth Commission report (World Bank, 2008) for sustained long-term growth (See figures in Annex 1). Relative to peers Indonesia has a committed, credible, and capable public sector; maintained macroeconomic stability; and achieved high rates of savings and investment. But it has scope to improve market competition, and openness to trade and technology transfer. Indonesia could achieve its goal If Indonesia can sustain its performance in growth of GNI per capita from the last of becoming a High-Income 10 years, it could potentially reach HIC status by 2045. Growth over the last 20 Country by 2045, but this will years, however, has been driven by commodity cycles and foundational policies require a new generation of reforms that further open and and institutions. A combination of these have helped accelerate investment and job sustain its markets to domestic creation. Going forward, the drivers of competitiveness will need to turn to market and foreign competition. friendly policies and institutions that are able to allocate resources to productive firms and industries. This also includes improving efficiency gains in natural resource to bring benefits for human capital and natural capital (World Bank 2023e). Strengthening competitiveness Competitiveness reforms can boost GDP growth through their impacts on capital drivers in Indonesia so they can accumulation, labor utilization, and total factor productivity (or efficiency). Based on converge to levels achieved in a methodology to assess the structural drivers of growth using Stochastic Frontier the Republic of Korea in the next 10 years could potentially Analysis,29 preliminary analysis shows that closing gaps in human capital, the quality accelerate growth to above 7 of business regulations, and government effectiveness (which cover market-based percent. institutions), could have the biggest impact on growth. Figure A.36: Determinants of competitiveness Figure A.37: Indonesia performs well on drivers of will vary according to a country’s stage of factor accumulation relative to its peers though lags on development efficiency drivers (z score) Indonesia performance in structural reform areas relative to peers (z scores based on multiple competitiveness indices) Macroeconomics Basic Governance Infrastructure Labor markets Structural reform areas International trade Basic human capital Business regulations Financial sector Competition -0.2 0.3 0.8 Z score (higher score = stronger performance relative to peers; lower score = weaker performance relative to peers) Sources: Adapted from Sala-I-Martin and Artadi (2004), Porter Notes: Z scores derived for sub-indicators under each of the above (1990), and World Economic Forum’s Global Competitiveness indices, then grouped according to 9 categories. Results are averages Index. of Z scores of sub-indicators under each category. Sources: latest data points from Global Competitiveness Index, Economic Freedom Index, OECD Product Market Regulations, Bertelsmann Transformation Index, Economist Intelligence Unit. 29 Rovo (2020). 28 Indonesia Economic Prospects June 2023 Figure A.38: Indonesia maintains one of the most Figure A.39: Indonesia could reach HIC by 2045 if it can restrictive policies on international services trade sustain its performance of the last 10 years (y axis = OECD STRI; x axis = log of per capita GDP) (y axis = number of years to reach HIC based on growth in GNI pc between 2009 and 2019) Services Trade Restrictions Index (2022) vs. log of per Number of years to reach HIC (based on historical capita GDP (2021) vs. services trade (% of GDP, 2015- average growth 2009-2019) 70 2021 average) STRI score (higher score = greater restrictions) 60 0.4 Indonesia 50 India 0.35 40 30 0.3 China 20 Turkiye 10 Mexico Korea 0.25 0 Brazil 0.2 7 8 9 10 11 Log of per capita GDP (2021) Sources: OECD Trade Restrictions Index, World Development Sources: World Development Indicators, compiled by WB Staff. Indicators, compiled by WB Staff. Figure A.40: Closing competitiveness gaps with Korea across drivers of factor accumulation and efficiency drivers in the next 10 years could help accelerate annual average growth to above 7 percent Sources: World Bank staff calculation 29 Indonesia Economic Prospects June 2023 Table A.2: Selected Macroeconomic Indicators 2019 2020 2021 2022 2023 2024 2025 Actual WB projection Real GDP growth and inflation, percent change Real GDP 5.0 -2.1 3.7 5.3 4.9 5.0 5.0 Consumer Price Inflation (CPI) (average, %) 2.8 2.0 1.6 4.2 4.1 3.6 3.4 Consumer Price Inflation (CPI) (end of period, %) 2.6 1.7 1.9 5.5 3.6 3.4 3.3 Private Consumption 5.2 -2.7 2.0 4.9 4.6 4.7 5.0 Government Consumption 3.3 2.1 4.2 -4.5 4.1 1.4 -0.7 Gross Fixed Investment 4.5 -5.0 3.8 3.9 5.0 5.9 6.1 Exports -0.5 -8.4 18.0 16.3 15.8 9.0 9.0 Imports -7.1 -17.6 24.9 14.7 6.8 9.4 9.5 Fiscal accounts, central government, percent of GDP Revenues 12.4 10.7 11.8 13.4 12.7 12.8 13.0 of which Tax Revenue 9.8 8.3 9.1 10.4 10.1 10.2 10.4 Expenditures 14.6 16.8 16.4 15.8 15.1 15.2 15.5 Primary Balance -0.5 -4.1 -2.6 -0.4 -0.4 -0.5 -0.4 Fiscal Balance -2.2 -6.1 -4.6 -2.4 -2.5 -2.5 -2.5 Central Government Debt(a) 30.2 39.3 40.7 39.5 39.2 38.8 38.6 Balance of Payments, percent of GDP unless indicated otherwise Current Account Balance -2.7 -0.4 0.3 1.0 0.0 -0.4 -1.0 Exports, Goods and Services 17.9 16.8 20.8 23.9 22.4 22.2 22.0 Imports, Goods and Services -18.2 -15.1 -18.3 -20.7 -20.3 -20.6 -20.9 Net Foreign Direct Investment 1.8 1.3 1.5 1.1 1.3 1.3 1.4 Gross Reserves (months of imports of goods and 9.7 7.5 6.4 5.8 6.1 5.9 5.8 services) Terms of Trade (2019=100) 100.0 111.5 190.0 Memorandum items Nominal GDP (IDR trillion) 15,833 15,443 16,977 19,588 20,987 22,686 24,493 Per Capita GDP (US$) 3,877 3,757 3,856 4,021 … … … Nominal GDP (US$ billion) 1,119 1,059 1,187 1,319 … … … 30 B. Pathways to Learning Recovery and a More Productive Future for Indonesia’s Children Indonesia Economic Prospects June 2023 B. Pathways to Learning Recovery and a More Productive Future for Indonesia’s Children 1. Preface In June 2023, most students The situation was different in many educational institutions in the preceding three in Indonesia celebrated the academic years, when many were closed to physical attendance or students could end of academic year 2022- not see each other’s faces behind their masks. Educational institutions today may 23 together at schools and madrasahs (Islamic schools) seem to have reverted to pre-pandemic conditions; however, the experience has [hereafter, this report refers left invisible tolls in human capital development among the children and the youth to them jointly as educational of this generation. As learning is cumulative by nature, current learning loss, if left institutions] across the unremedied, will exacerbate and prevent future learning– especially if losses occur archipelago nation. in linked foundational skills.30 Learning loss can derail not only student learning trajectories but also their overall human capital that contribute towards their potential economic prospects and lifetime earnings. In order to assess the magnitude The 2019 SDI survey collected data on the language and math competencies of of learning loss during the Grade 4 students, and the same instruments were used to test the language and COVID-19 pandemic, a sample- based school survey was math competency of Grade 4 students in 2023.31 By using these two years of learning conducted nationwide in data, this report aims to provide new evidence of learning loss before and after the Indonesia in March 2023, visiting COVID-19-induced school closures in Indonesia (2019 and 2023). educational institutions that had been included in the World Bank’s Service Delivery Indicator (SDI) survey in 2019. 2. The COVID-19 pandemic aggravated the pre- existing global learning crisis COVID-19 was an enormous Human capital is the knowledge, skills, health, emotional and mental wellbeing shock to people’s life that people accumulate over their lifetime. COVID-19 impacted all age groups, but trajectories, especially especially children and youth, since it affected the vital stages of the human capital disrupting human capital accumulation among children accumulation process through disruption of learning processes and opportunities. and young people.32 30 Schady et al. (2023) 31 More details about the survey are discussed in Section 5 and Annex 1. 32 Schady et al. (2023) 32 Indonesia Economic Prospects June 2023 The COVID-19 pandemic caused 1.3 billion children in Lower Middle Income Countries (LMICs)34 missed at least half a a significant disruption to year of school, 960 million missed a year, and 711 million missed a year and a half or education systems around the more.35 In Southeast Asia, there was a considerable variation in the length of school world, with school closures affecting 1.6 billion children closures, for example, 115 days in Singapore, 321 days in Vietnam, and 532 days in the with learning losses and Philippines.36 Meanwhile in Indonesia, the number of days of fully or partially closed dropouts.33 was 644 days (see more from the survey in Section 6).37 Learning crises already existed Even before the COVID-19 pandemic, there was a global learning crisis. 258 million around the world prior to the children in primary and secondary school age were out of school, and even if they COVID-19 pandemic, and the went to school, many children were learning very little.38 Global evidence in LMICs crisis exacerbated existing inequalities within countries. shows various dimensions of inequality in learning losses based on geography, gender, age/grade, public/private, socioeconomic status and disability.39 The compound challenges of school closure, the loss of family livelihoods, health problems and so on varied from country to country- and household- contexts. These seem to have caused more severe impacts on those who had less means to mitigate such negative shocks, including the poor, people in rural areas, those with disabilities, and other marginalized groups. BOX B.1 Definition and Conceptual Model of Learning Loss Learning loss: Learning loss consists of (i) Figure B.1: Learning trajectories pre-and post- “foregone learning” which refers to learning COVID-19 that will not occur due to school closure, and (ii) “forgetting” which refers to already acquired learning that students forgot or lost during school closures caused by disengagement with the education system.40 Learning loss can also capture dropping out triggered by income shock. With no mitigation, the length of school closure will reduce the amount of time students have available for learning opportunities from the education system. Without adequate measures, learning losses may continue to accumulate even after students are back in Source: World Bank et al. (2022) school, and students risk learning less every year compared to pre-COVID-19 student cohorts.41 See the conceptual model in Figure B.1. 33 World Bank et al. (2021) 34 The classifications are updated annually and are based on the GNI per capita (Atlas method) of the previous year. According to the latest classi- fication published on July 1, 2022, Indonesia’s GNI per capita was $4,180 was in 2021 and included in the LMIC category [GNI per capita range of $1,086 - $4,255]. 35 Schady et al. (2023) 36 UNESCO Institute for Statistics (https://covid19.uis.unesco.org/global-monitoring-school-closures-covid19/). This includes closed and partially open days between March 1, 2020 to March 31, 2022. 37 This is based on the aforementioned data from UNESCO Institute for Statistics, including fully closed and partially open days between March 1, 2020 to March 31, 2022. According to the government regulations, educational institutions in Indonesia were closed for 650 calendar days between March 24, 2020, as declared by MoECRT and MoRA decree, and January 3, 2022 as declared in the joint Ministerial Decree on December 22, 2021. 38 UNESCO (2019) 39 World Bank et al. (2021); UNICEF (2021b) 40 World Bank et al. (2021) 41 UNICEF et al.(2022) 33 Indonesia Economic Prospects June 2023 3. Remembering where we were – the Indonesian education system prior to the COVID-19 pandemic? Indonesia has the worlds’ fourth The formal education system, governed and regulated by the Ministry of Education, largest education system, with Culture, Research and Technology (MoECRT) and the Ministry of Religious Affairs approximately four percent of (MoRA), educates approximately 53 million children from Grade 1 to 12 and employs the world’s student population.42 about 3.3 million teachers. In addition, nearly 230,000 early childhood education services support 7.4 million children at pre-school age, and over 4,000 higher education institutions support nearly eight million students at tertiary education level. The last two decades saw a The enrollment of students at primary and secondary levels has increased by more remarkable improvement in than ten million (31 percent increase) in the past two decades since 2002, driven in access to education, reaching large part by advances in secondary education.47 The net enrolment rate (NER44) for close to universal primary primary education has increased from 89 percent to 93 percent between 2005 and education. 2018, and the NER for secondary education has also risen from 53 percent to 79 percent in the same period.45 These substantive improvements in access to education have been supported by the Government of Indonesia’s (GoI) commitment and allocation of resources. However, the quality of In Indonesia, students attend schools for 12.4 years by age 18 on average, but actual education has been Indonesia’s learning was estimated to be only at the level of 7.8 years of schooling.46 At a primary most significant challenge, school level, 53 percent of children lived with learning poverty.47 Student learning at and the issue of low levels of the secondary level has also been a challenge, and over the past 20 years, average learning outcomes was present performance has not improved. Indonesia has participated in the Programme for even prior to the COVID-19 International Student Assessment (PISA)48 since 2001. Indonesia’s latest PISA scores pandemic. (2018) showed low mean scores in all subjects, with an average reading performance of 371 (ranked 71 out of 76 PISA participating countries/economies), an average math score 379 (ranked 70 out of 77) and an average science score of 396 (ranked 69 out of 77 countries).49 Since Indonesia’s first participation PISA in 2001, performance in reading has been hump-shaped, that is, it increased till 2009 but declined since then. Math and science performance fluctuated but remained relatively flat during the past 20 years. However, these results must be seen in the context of the vast strides that Indonesia has made in increasing enrollment. Typically, increasing enrollment leads to the inclusion of more disadvantaged or relatively academically weaker students.50 Inequity of learning opportunities and outcomes, however, especially among the poor, those living in remote areas, and living with disabilities, was another major concern. The gap in literacy between advantaged and disadvantaged socio-economic groups increased from 44 score points in 2009 to 52 score points in 2018.51 42 World Bank et al. (2021) . 43 World Bank (2020d) 44 Net Enrollment Rate (NER) is the ratio of children of official school age who are enrolled in school to the population of the corresponding school age group of children. 45 The World Bank Data 46 Ibid 47 Learning poverty refers to being unable to read and understand an age-appropriate text by age ten. More information can be found from (World Bank, 2021) The learning poverty of 53 percent in Indonesia is approximately 19 percentage points higher than the average for the East Asia and Pacific region. Learning poverty is higher for boys than girls in Indonesia; the percentage of boys with learning poverty is 55.4 percent compared to 51.3 percent for girls. 48 PISA is led by the Organisation for Economic Co-operation and Development (OECD), and it assesses the literacy, mathematics and science com- petencies of 15-year-olds. 49 OECD https://gpseducation.oecd.org/CountryProfile?primaryCountry=IDN&treshold=10&topic=PI 50 Beatty et al. (2021) 51 OECD (2019) 34 Indonesia Economic Prospects June 2023 GOI effort 4. GoI’s efforts to sustain education despite the challenges during the COVID-19 pandemic Since the decision to close GoI reacted first by ceasing regular activities, closing educational institutions and educational institutions on introducing new learning approaches primarily through home-based learning.53 The March 24, 2020, GoI has put central government (MoECRT and MoRA, together with Ministry of Health (MoH) tremendous effort into mitigate and Ministry of Home Affairs (MoHA)) developed distance learning guidance and learning disruption caused by a special curriculum in response to the change, and reformed some education COVID-19.52 financing schemes to support students and teachers during the distance learning period. The Emergency Curriculum was introduced as an option for schools, offering a simplification of the 2013 Curriculum, the prevalent curriculum prior to the pandemic. The role of subnational governments also emphasized education service delivery, including the use of curriculum, and decisions on re-opening educational institutions based on their own assessments of health risks and feasibility. Remote- and home-based In May-June 2020, during nationwide closures of educational institutions, only around learning came with a service 40 percent students reportedly used mobile learning apps and/or accessed online delivery challenge due to the schooling via the internet.54 MoECRT then started the first internet data subsidy lack of preparation of both program for students from September to December 2020,55 but the survey showed educational institutions and the proportion of students using mobile apps and/or accessing online schooling households. did not improve by November 2020.56,57 In areas outside Jakarta, particularly the population at the bottom 40 percent by income, were less likely to receive the internet quota subsidy and were hence less likely to use mobile learning apps and/ or online schooling at home.58,59 Students’ main obstacles were not only no/limited interest access but also lack of supporting devices and lack of adequate learning environment and support at home.60 Twenty-nine percent of parents reported that they had insufficient time and 25 percent reported a lack of capacity to support their children’s learning at home.61 COVID-19 pandemic negatively A study reported that student dropouts were already observed by December 2020 affected children’s learning (first year of COVID-19), due to economic reasons such as the decline in household opportunities and wellbeing. income and unpaid work.62 By September 2021, a study reported that total of 25,430 Indonesian children had lost one or both parents to COVID-19 and 20 percent of 15-24 year-olds stated that they were depressed or had low interest in doing any activities.63,64 Severe disruptions in daily life, social isolation from peers, and pressure to learn from home with limited guidance have impacted children’s mental health.65 52 Ministerial Circular Letter No. 4/2020 by MoECRT; Circular letter No B-686.1/DJ.I/ Dt.I.I/PP.00/03/2020 and Circular letter No B-699/Dt.i.i/ PP.03/03/2020 by MoRA.. 53 There were many learning activities to support home-based learning, such as educational TV and radio programs, online teacher training and platform for peer-to-peer communications, and so on. More information on GoI’s response to COVID-19 in the education sector can be found in Butcher et al. (2021). 54 Based on the HiFy survey Round 2. HiFy survey is a high-frequency phone-monitoring survey of households to collect data on the socio-economic impact of the COVID-19 in Indonesia, conducted by the World Bank. Participants were randomly selected across the country, and around between 3,000- 4,000 panel households participated in a 7-round panel survey between May 2020 and April 2022. More information can be obtained from World Bank (2023). 55 See more information on Butcher et al. (2021) 56 World Bank (2020a); World Bank (2020a) hn et al. 2019. 57 The MoECRT resumed the provision of the internet quota for students from March 2021 (Butcher et al.,2021), and its effect on student learning needs further investigation. 58 Ibid 59 Issues with the arguably limited effectiveness of online learning at home and insufficiency of the internet quota during the COVID-19 were also raised by the Indonesian Child Protection Commission (KPAI) in the Ministry of Women’s Empowerment and Child Protection which has been monitoring online education in 34 provinces of Indonesia (Pradana & Syarifuddin, 2021; Satryo, 2020). 60 HiFy survey Round 2 and Round 4, and Pradana & Syarifuddin (2021) 61 Schady et al. (2023) 62 UNICEF (2021b) 63 UNICEF (2021a) 64 UNICEF (2021) 65 UNICEF (2021b) 35 Indonesia Economic Prospects June 2023 Forty-five percent of children have been experiencing difficulties in concentrating, 13 percent have become angrier and 6.5 percent have experienced sleep difficulties.66 COVID-19 also affected children’s growth and development and led to behavioral change and sleep disorders in Indonesia, and cases of malnutrition, obesity, vitamin D deficit, lack of physical activities and more screen time are also reported.67 The incidence of cyber gender-based violence (GBV)68 has also seen a rise since the beginning of the pandemic, both globally69 and in Indonesia70 as children spent more time online as a result of school closures and lockdown measures.71 With the nationwide school A joint regulation on school reopening guidelines, issued by MoECRT, MoRA, MoH, re-opening from January 3, and MoHA on December 22, 2021, shifted the default school operation from remote- 2022, the educational challenges based or partial opening to full opening. This point marks the shift of the GoI’s effort shifted from how to mitigate the from mitigating the potential negative educational impact and health risks to learning negative impact of school closure to how to recover student recovery and acceleration. The main measures to support such initiatives shifted to learning. ensure that the planned medium-term reforms could get back on track. Post-COVID-19, MoECRT’s The MoECRT embarked on a series of reforms through the Merdeka Belajar (Freedom medium-term reforms through to Learn) policy starting in 2019, aiming to overcome the problem of quality of learning the Merdeka Belajar policy have evident from the PISA results in 2018.72 As concerns on acute education disruptions spearheaded the GoI’s learning due to COVID-19 faded over time, Merdeka Belajar became the mainstream recovery and acceleration efforts. campaign to accelerate student learning. The Merdeka curriculum was launched in February 2022 by MoECRT and adapted by MoRA in April 2022, aiming to improve learning outcomes by focusing on foundational skills including literacy, numeracy and character education.73 The implementation of the new curriculum is still in progress, and remains to be seen if and how the new curriculum and reform answers the problem of learning losses caused by COVID-19. One of key obstacles is the lack of evidence on students’ learning in post-pandemic to rethink education strategic planning in COVID-19 recovery. To plan for a post-pandemic world, the education sector must understand what students’ learning loss look like after the pandemic. This report aims to support GoI by contributing to filling in this knowledge gap. 66 According to a nationally representative household survey conducted between October – November 2020 with 12,216 households. For more information, see UNICEF et al.( 2021). 67 Sekartini (2021) 68 Cyber GBV refers to actions that harm others based on their gender identity or enforcing gender norms using the internet or mobile phone tech- nology, according to Hinson et al. (2018, p. 1). Cyber GBV is increasing globally over time especially among young people. More information can be found in Flynn et al. (2021). 69 UNICEF (2020b) 70 NCVAW (2020) 71 World Bank (forthcoming). 72 Made Hery Santosa, ‘Freedom to Learn (Merdeka Belajar)’, (Open Science Framework, 30 January 2022), https://doi.org/10.31219/osf.io/jkq7a. 73 INOVASI (2022) 36 Indonesia Economic Prospects June 2023 5. Did learning losses occur, and if so, to whom, how, and how much? 5.1. Literature on learning loss in Indonesia Earlier studies and anecdotal Using the globally standardized tool for estimating learning loss, the World Bank evidence have shown that estimated in 2021 that school closures for the first year and half due to COVID-19 student learning was negatively would result in a total learning loss of between 0.9 and 1.2 years of adjusted schooling affected by COVID-19 in Indonesia, like many other and the reduction of student’s PISA reading scores of between 25 and 35 points.74 countries, but a rigorous The extent of learning loss was affected by the effectiveness of distance learning assessment was needed to rather than by the duration of school closure during the time period used for the identify evidence-based actions analysis.75 A study conducted by the Innovation for Indonesia’s School Children for learning recovery. (INOVASI) project in partnership with the MoECRT in August 2021, found a loss of 5-6 months of progress of Grades 1 and 2 students in literacy and numeracy after 12 months of learning from home.76 These previous studies and available evidence related to learning loss was mainly from rapid assessments or early evaluation of the pandemic-induced school closures. Most of the studies were also geographically limited or based on estimations, lacking national-level empirical evidence. There was a need to identify student learning levels after school reopening, to formulate evidence-based actions for learning recovery. 5.2. Objective of the study and research design The objective of this study is The study compares performance of Grade 4 students in 2019 and 2023. While these to provide new evidence of are two different groups of individuals, this report employs the assessment result learning loss by comparing data of Grade 4 students in 2019 as a counterfactual for student performance of 2023 on Grade 4 student learning before (in 2019) and after the and considers that students in 2023 would have performed at the same level of COVID-19-pandemic-induced 2019 Grade 4 students, in the absence of the disruption caused by COVID-19. This school closure across Indonesia study also aims to examine how the changes differ by educational institution and (in 2023).77 individual characteristics, to better understand the complexity and diverse effects of the pandemic on students’ learning at a national level. The Learning Loss Survey 202378 To ensure comparability, the 2023 survey was designed to closely replicate the survey was designed with a key features of the 2019 survey. First, the survey visited the same educational sample-based and school-based institutions80 to allow direct comparison of performance between Grade 4 students student learning assessment survey in 2023 as a follow-up from different years.81 Second, the survey used identical test instruments in literacy the learning assessment survey and mathematics82 and followed the same test administration guidelines. Third, collected in 2019 as part of the the timing of data collection was also aligned to ensure the time elapsed since World Bank’s Service Delivery the beginning of academic year was equal between 2019 and 2023. The follow-up Indicator (SDI).79 survey was conducted from February to March 2023, in alignment with the survey timeline of 2019 survey, also conducted from February to March 2019. The 2023 74 Afkar & Yarrow (2021) 75 Afkar & Yarrow (2021) 76 INOVASI (2021) 77 See Annex 1 for the technical description of the survey, including the design, instruments, sampling, matching, and weighting. 78 This report refers to the 2023 survey as “the Learning Loss Survey of 2023” and the 2019 Survey as the SDI survey for the ease of referencing. It also avoids any confusions with GoI’s national assessments including AN and AKMI by using general terms such as a learning assessment survey or learning assessment. 79 SDI is a global tool developed by the World Bank to measure the quality of service delivery in the key areas of health and education, last performed in Indonesia in early 2019. Further information on the 2019 SDI survey can be found on the following link: https://openknowledge.worldbank.org/ entities/publication/f8d78c37-968a-55e2-96b4-9fc6067fce65. Indonesia’s 2019 SDI collected various school-related data, such as school management, school leadership, teacher performance, and student learning outcomes in language and math were also assessed. This learning assessment data was considered as a unique source of learning data prior to the pandemic, and the follow-up learning survey of 2023 was designed using 2019 SDI survey as the baseline. 80 There was an adjustment to the list of visited schools to make the survey nationally representative. See the following sections on sampling. 81 Methodologically, this is an approach whereby student performance data is collected from the same grade across different cohorts. In the interna- tional literature, some studies trace the same individual and compare before and after the pandemic. 82 It consists of 15 literacy questions and 17 math questions. Test questions are designed to capture the foundational skills of language and math. 37 Indonesia Economic Prospects June 2023 survey instruments also comprised a school principal module, teacher modules, and student modules to capture multidimensional information related to learning during the COVID-19 pandemic.83 5.3. Who suffered from learning losses, and how did they contribute to inequity? At the national level, the An analysis of learning assessment results revealed that the national average of Grade academic performance of Grade 4 children’s performance in math was 0.281 standard deviation (s.d.) lower than the 4 students in 2023, measured in average score of Grade 4 students in 2019, and their performance in language in basic language and mathematical 2023 was also 0.271 s.d. lower. Standard deviations are used in a large amount of skills, is substantially lower than literature documenting the heterogeneity of schooling productivity.85 Following the that of Grade 4 students in internationally used rule of thumb that average student learning in a calendar year 2019.84 (12 months) is equal to about 0.300 of a s.d.,86 the result is converted to the number of months lost in this section. Grade 4 students in Indonesia in 2023 have lost 11.2 months equivalent of math skills and 10.8 months equivalent of language skills in comparison with Grade 4 students Figure B.2: Size of learning losses in months, by subject, in 2019 (Figure B.2). public-private status of educational institutions, and Standardized scores and area the detailed analysis based on regression modeling All Urban Rural Public Private 0 and statistical testing of the means are presented in -2 Annex B.2. Learning Loss (months) -4 -6 -4.6 Urban students experienced Both urban and rural -8 larger learning losses in students experienced math while rural students learning losses, but the size -10 experienced larger learning -12 -10.4 -10.5 losses in language. of impact was different on -10.8 -11.2 -10.8 -11.8 math and language. Urban -14 -12.8 -13.4 -13.4 students lost 12.8 months -16 of learning in math but lost Math Language only 10.4 months of learning in language. On the other Source: Authors’ analysis using SDI Survey 2019 and Learning Loss hand, rural students lost Survey 2023 10.5 months of learning in Note: Detailed numbers are presented in Annex B.2. math and 13.4 months of learning in language (see Annex B.2 for standard scores and the result of statistical testing). 83 The school principal module collects information related to school characteristics, availability of internet access and school grants, use of different curricula, schooling time and use of remote or hybrid learning, and principals’ management practices during the pandemic. The teacher module includes two parts. First is an interview which asks teachers’ backgrounds, teaching practices during the pandemic, and their assessments and opinions of student academic performance. The second part is actual monitoring of teachers’ current teaching practices through video recordings of an entire class. An instrument called TEACH (a set of tools developed by the World Bank to enhance education quality (https://www.worldbank.org/en/topic/ education/brief/teach-helping-countries-track-and-improve-teaching-quality) was used to codify the teaching practices to systematically assess the ca- pacity and practice of teachers. Student modules consist of two parts. The first is the literacy and math tests. The second part is a student questionnaire to collect data on students’ background information, learning practices during school closures, access and availability of technology including internet or digital tools, and time use during school closures. 84 This study analyzes learning losses in math and language for Grade 4 students only. It is important to note that students in different grades are likely to have different learning losses. Grade 4 students studied by this survey experienced school closures during their first, second and third grades (aca- demic year 2019/20 – 2021/22) when they should have been learning the foundational skills. Students who are in secondary education in 2023 are likely to have different experiences. 85 See for example, Azevedo et al. (2020) 86 See for example, Hanushek & Wößmann (2020). In OECD countries, learning gains on most national and international tests during one school year are between 0.25-0.33 standard deviation (Woessmann, 2016). In developing countries, the standard deviation equivalent to one year of schooling are 0.45 in Vietnam and 0.2 in Peru (Singh, 2020), in a range of 0.2 to 0.3 standard deviations in Tanzania, Uganda, and Kenya (Jones, 2017), and a range of 0.04 to 0.56 depending on municipalities with its average of 0.3 in Brazil (Azevedo and Goldemberg, 2020). Based on the literature and to the best of our knowledge, authors assess that a 0.3 standard deviation is the fairest assumption to equate with one year of learning for Indonesia on this instru- ment. More discussion can be found in: Woessmann (2016); Singh (2020); Jones (2017); Azevedo & Goldemberg (2020). 38 Indonesia Economic Prospects June 2023 Overall, public educational Students in public educational institutions experienced 11.8 months and 13.4 months institutions experienced greater equivalent of learning losses in math and language whereas students in private learning losses than private institutions lost 10.8 and 4.6 months of learning respectively. educational institutions. Despite having one of the Indonesia’s 21 months of Figure B.3: Relationship between months of school world’s longest periods of regulatory school closure closure and learning loss. school closure, Indonesia’s (including instructed learning loss may not appear as 26 BGD large as the global trend after school closure, period of 24 14 months of school reopening remote-learning and partial 22 since January 2022. school opening) is one of 20 MAL Learning Loss (months) 18 the longest in the world. 16 However, the approximately 14 IDN 11 months of learning loss 12 ETH POL ARG MEX in math and language may 10 BRA 8 ZAF CAN not appear as large as 6 GER BEL ESP USAUGA UK ITA CZE international trends indicate. 4 CHE RUS NLD Evidence from a recent study 2 AUS DNK 0 by the World Bank using 0 2 4 6 8 10 12 14 16 18 20 22 data from 22 countries, shows each month of school School Closure (months) closure tends to lead to one Source: Indonesia’s learning loss is based on this study. Other month of lost learning on countries are plotted based on Schady et al.(2023, p.6). See Schady average. Figure B.3 presents et al (2023) for a detailed description of country comparison. the relationship between Notes: The dashed 45-degree line indicates where learning losses in months are equal to length of school closures in months. months of school closure Learning losses in months are benchmarked against “typical” and months of learning.87 learning gains within each country before the pandemic. The estimates thus should not be compared across countries because, Overall, there is a tendency for example, three months of learning losses in the Netherlands for one-month of school does not compare one-to-one with three months of learning losses closure to relate to one in South Africa, where pre-pandemic learning was lower to begin with. See International Organization for Standardization (ISO) for month of learning loss. This country abbreviations, https://www.iso.org/obp/ui/#search. may be partly explained by the learning recovery that took place since school reopening. This may also be related to how the education was delivered during the school closure or measurement related aspects such as the grade assessed and test instruments used for assessments. Boys experienced greater Both boys and girls experienced learning losses, but the size of impact was different learning loss in language on math and language. Boys lost 9.2 months of learning in math and 12.0 months of while girls experienced greater learning in language whereas girls lost 13.2 months of learning in math, but only 9.6 learning loss in math. months of learning in language. Students from poor families A proxy poverty index88 was created based on the Indonesia Socioeconomic Survey experienced significantly more (SUSENAS) from March 2022, and applied to the household asset information reported learning loss in both math and by students through the Learning Loss Survey of 2023. Students were separated into language. five groups based on the poverty score calculated from the poverty (or asset) index. Students from the bottom 20 percentile of household wealth experienced significantly 87 Schady et al (2023) selected studies to plot learning losses from difference countries based on four criteria: (1) they had credible estimates of learning progress before school closures, which made it possible to construct a reliable counterfactual (what learning would have been in the absence of COVID-19); (2) they measured learning carefully using comparable reading, language, or math tests across years; (3) they reported learning losses in months or allowed for this conversion; and (4) they did not use a sample with special characteristics (such as students receiving some special interventions). (p.68) 88 An econometric model was used to describe a situation where information on household or individual characteristics correlated with welfare levels is used in a formal algorithm to proxy household income, welfare or need. 39 Indonesia Economic Prospects June 2023 larger learning loss. They lost 18.1 months and 27.2 months of learning in math and language.89 On the other hand, students from the top 20 percentile of household wealth only lost 3.5 and 5.6 months of learning in math and language. Based on this number only, poor students suffered more significantly and relatively wealthy students effectively managed to mitigate the loss of learning opportunities. As a result of learning losses The learning inequalities existed across subgroups prior to the pandemic. For caused during the pandemic, example, students in public educational institutions were on average 3.9 months inequalities across subgroups behind students in private schools in language. This gap widened to 12.8 months due widened. to greater learning loss among students in public schools. The learning gap widened the most between the wealthy and poor students. The learning gap which existed prior to the pandemic of 13.9 months in math and 18.7 months in language widened to 28.5 and 40.2 months in respective subjects. On the other hand, there were some reductions in math learning gaps in rural-urban and male-female subgroups because of urban and female students, who performed better prior to the pandemic, experienced greater learning losses (Figure B.5). Figure B.4: Size of learning losses in months, by Figure B.5: Size of learning gaps between subgroups (in subject, gender, and household poverty status months) between 2019 and 2023, by subject Household Household Asset Asset Top Bottom Male Female 20% 20% 0 Learning Loss (months) -5 -10 -15 -20 -25 -30 Math Language Source: Authors’ analysis using SDI Survey 2019 and Learning Loss Source: Authors’ analysis using SDI Survey 2019 and Learning Loss Survey 2023 Survey 2023 Note: The pseudo-poverty quintile was developed by using an Note: School status compares public – private; regional status asset index derived from the March 2022 Indonesia Socioeconomic compares rural – urban; gender compares male – female, poverty Survey (SUSENAS), a nationally representative household survey in compares bottom 20% and top 20% of household wealth. Indonesia. Eleven household asset variables, which are present in both surveys, were used in a regression model against household expenditure per capita, and the coefficients generated from the model were incorporated in the learning assessment (reported by students) to create a simulated household expenditure per capita, and subsequently its quintile. Note: Detailed numbers are presented in Annex B.2. This survey was conducted in March 2023, nine months through the academic year after the students became grade 4. By subtracting 27 89 months, it means their performance level is equivalent to the beginning of Grade 2 average. 40 Indonesia Economic Prospects June 2023 5.4. What factors affected learning loss? Experiencing sickness or death The survey asked if the student experienced any sickness or death of their own of family members or someone family or somebody close during the time of school closures. A significant number of close during the period of school students reported Yes to these cases – respectively 25.6 percent and 16.4 percent. The closure had negative impacts on student learning. question did not exclude death or sickness caused by other reasons than COVID-19, but the statistics show such incidents were common. Students who did not experience the death of someone close had average learning gaps of 8.9 months equivalent in comparison with 2019 average in math and language.90 On the other hand, the students who experienced death of family members or someone close performed 17.0 and 15.1 months behind the 2019 average in math and language, creating average 8.1- and 6.2-months equivalent gaps in math and language between these groups (Figure B.6). Use of the internet created While the pandemic accelerated digital transformation in the education sector,91 it wide diversity in learning also revealed a digital divide, limited capacities of the supply side to meet diverse outcomes at an individual level. needs, and created challenges among students, teachers, educational institutions and parents to access remote learning. While the average scores of students who reported using the internet ‘often’ were 7.4 (math) and 4.1 months (language) behind the national average of 2019, those who reported ‘never’ had 35.0 (math) and 57.3 (language) months equivalent learning gaps from the national average of 2019 (Figure B.6). While this use of the internet indicator is correlated with poverty or remoteness,92 this shows the use of the internet during COVID-19 pandemic was correlated with student learning outcomes, for better or for worse. Figure B.6: Learning gaps among subgroups with different experiences in their environment during school closures Sickness Death Internet use Yes No Yes No Often Sometimes Rarely Never 0 Learning Gap from 2019 average (months) -10 -4.1 -7.4 -11.3-10 -8.9 -8.9 -9.6 -8.2 -11.9 -11.9 -20 -17-15.1 -16.1 -16.2 -30 -40 -35 -50 -60 -57.7 -70 Math Language Source: Authors’ analysis using SDI Survey 2019 and Learning Loss Survey 2023 Note: This figure uses an average score of students in 2023 in comparison to 2019 national average (learning gap). Since these group do not have pre-COVID-19 score average, this is not called a learning loss. 90 This is not called a learning loss because individual level scores for this group in 2019 do not exist. 91 World Bank (2022) 92 In November 2020, a HiFY survey showed that around 51 percent of students reported receiving the internet quota subsidy, but only 82 percent of them were using it for daily learning. The percentage of population outside Java receiving the internet quota was only 37 percent, highlighting a challenge of equitable and effective distribution of internet quota (Butcher et al. 2021). 41 Indonesia Economic Prospects June 2023 Structured learning hours93 From the early stage of the COVID-19 pandemic, there was a major concern about seem to be one of the critical learning loss caused by the closure of schools, which could lead to significant factors affecting learning loss in disruptions in learning process and learning hours. The Learning Loss Survey 2023 Indonesia. asked principals how many hours they officially offered schooling to Grade 4 students (in Grades 2 and 3 in the previous years). Figure B.7 shows the numbers of officially recorded schooling hours including remote-learning, partial school opening, and full school openings by MoECRT schools and madrasahs. Before the pandemic, average operating hours were 1,086 hours in 2018/19 (1,061 hours for schools, 1,149 hours for madrasahs). In the academic year 2019/20, educational institutions were fully open until the announcement of school closures in March 2020. The academic year 2020/21 was the year with the severest school closures due to the pandemic in most places in Indonesia. Educational institutions gradually opened after school reopening was officially announced in December 2021, and more educational institutions fully opened during the year 2021/22. One important finding is that during these three years, average total schooling hours were 2,599 hours (866 hours per year) among madrasahs and 2,271 hours (757 hours per year) among schools.94 Annual structured learning hours during this period (on average) was reduced 29 percent among schools and 25 percent among madrasahs on average. There has been a complex The distribution of the curriculum is summarized in Table B.1.. Following the instruction landscape of curriculum of the central government, the most commonly used curriculum during the period implementation during the past of school closure was the Emergency Curriculum – which 43.7 percent of educational three years. institutions followed. On the other hand, emergency curricula designed or provided by the district (36.2 percent), foundations (i.e., NGO, private) (4.4 percent), or educational institutions themselves (25.8 percent) were also in use. Almost none of educational institutions used the standard curriculum from pre-pandemic times, and very few educational institutions (mostly schools) adopted the new Merdeka curriculum. It is also noteworthy that 9.2 percent of schools and 16.1 percent of madrasahs reported that they used multiple curricula, which could be in different years of school closure.95 Figure B.7: Average number of structured learning hours by schools and madrasahs, 2018/19 – 2021/22 1400 1200 1000 Average hours 800 596 597 658 600 1,149 1,086 1,061 775 685 668 220 400 160 148 200 345 247 248 362 264 329 129 123 86 137 0 2018/19 2019/20 2020/21 2021/22 2018/19 2019/20 2020/21 2021/22 2018/19 2019/20 2020/21 2021/22 All Schools Madrasahs Remote Learning Hours Partial Opening Full Opening Source: Authors’ analysis using SDI Survey 2019 and Learning Loss Survey 2023 93 These are learning hours that educational institutions reported that operating (either remotely, partially open, or fully open) and students were supposed to be actively engaged in learning. 94 These self-reported statistics may contain principals’ over- or under-reporting, and these statistics of learning hours may not indicate the quality or effectiveness of each mode of learning. Therefore, a detailed analysis of how these learning hours correlate with student performance and learning loss will be conducted in the next study. 95 Assessing the correlation between the use of curriculum and learning loss would require a close assessment of curriculum implementation by teachers. This report does not cover detailed analysis of teacher performance and practices, so the analysis of curriculum and learning loss will be discussed in subsequent analytical work. 42 Indonesia Economic Prospects June 2023 Table B.1: Proportion of educational institutions that used different curricula during the school closure (%) District Foundation School 2006 2013 Emergency Merdeka Curriculum Emergency Emergency Emergency Curriculum Curriculum Curriculum Curriculum Curriculum Curriculum Curriculum Schools 0.1 0.0 43.1 37.0 3.3 25.2 0.5 Madrasahs 0.5 0.0 45.9 33.6 8.0 28.0 0.0 Total 0.2 0.0 43.7 36.2 4.4 25.8 0.4 Source: Authors’ analysis using SDI Survey 2019 and Learning Loss Survey 2023 Note: 9.2 percent of schools and 16.1 percent of madrasahs reported that they used multiple curricula during this period. A majority of teachers The survey asked two questions related to teachers’ perceptions or opinions about overestimate Grade 4 student’s the competencies of Grade 4 students. Among the teachers who taught Grade 4 both competencies for both language during pre-pandemic time and today, 27 percent said the performance of Grade 4 and math and do not realize learning losses.96 students is better today than in pre-COVID-19 times. 36 percent said the performance is about the same, and 37 percent said the performance today is worse than the pre- COVID-19 period. However, teachers underestimate the seriousness of the issue. 73.4 percent of language teachers and 48.6 percent of math teachers97 responded that more than 60 percent of their students have the right level of competencies for Grade 4.98 5.5. How could learning losses affect future economic productivity If learning losses caused by the COVID-19 led to a large loss of human capital in three life stages from young children, COVID-19 pandemic are left school-age children to youth. Global literature has estimated that a child who has unaddressed, they have the discontinued schooling experiences a decline in their cognitive and social-emotional potential to significantly impact students’ future earnings and the development trajectory, which could translate into a 25 percent reduction in earnings country’s productivity.99 when the child becomes an adult.100 In aggregate, learning losses experienced by today’s students could reduce future global earnings by US$21 trillion if unaddressed.101 Just in the past three years, the pandemic has led to significant reductions in employment opportunities, and consequently led to an increase in the number of youth who are not in education, employment, or training (NEET). The unemployment rate rose by 1.8 percent to 7.1 percent in 2020 compared to the year before.102 Underemployment (i.e., underuse of a worker’s potential because a job does not use the worker’s skills, is part-time, or leaves the worker idle) also causes a long-term impact, affecting the career development for youth and their lifetime earning trajectory.103 In line with the international According to the Indonesia Family Life Survey (IFLS) 2014 data,104 which had simple literature, learning loss carries cognitive and math test modules, one standard deviation increase in the math is significant implications for correlated with 36 percent higher earnings.105 Using this statistic and adjusting for individual future earnings. inflation, the lost earnings or lost productivity of a future worker due to learning 96 The survey collected more teacher related variables including classroom observation of teaching practices; however, this study reports only on this variable due to its relevance to the recommendations. 97 Teachers were asked to estimate the percentage of students in their class that can perform at right competency for Grade 4 in language and math 98 The question related to the percentage of students that are at the right level of competencies for Grade 4. Teachers were given categorical answers as: 0-20%, 21-40%, 40-60% ,60-80%, or 80-100%. 99 Azevedo et al. (2020) 100 Schady et al. (2023) 101 Ibid. 102 World Bank (2020d) 103 Ibid. 104 IFLS 2014 is a nationwide household survey conducted the GoI. It had a module for an IQ-test, pattern recognition, and a simple math test. Test items are available online at https://www.rand.org/pubs/working_papers/WR1143z3.html. This study created a standardized score by using math items only. 105 This is based on a regression analysis, controlling for age [which proxies the work experience] and gender. 43 Indonesia Economic Prospects June 2023 loss would be on average IDR 9.9 million or US$ 691106 per year (in 2021 prices). This estimate is slightly above an earlier World Bank study.107 The study used global modeling to estimate the impact of prolonged school closure on students’ future earnings and this indicated that learning loss would reduce an students’ future annual earnings between US$408 and US$578 per student (IDR 5.8 million to IDR 8.3 million equivalent108). Learning loss also affects the probably of obtaining full time waged employment. According to an analysis of IFLS 2014, workers with one standard deviation lower cognitive and math skills were 5.8 percent less likely to have full employment. Estimated lifetime loss of Workers with lower productivity have lower lifetime earning profile. Figure B.8 earnings is 30.9 percent among provides a graphical presentation of the age-earning profile of workers who lost men and 39.2 percent among learning and hence the lower productivity and counterfactual scenario of workers women in comparison with the counterfactual no-learning-loss without learning loss for new labor market entrants. Assuming they work from age scenario if their learning losses 18 to 60, the new labor market entrants who lost 0.3 standard deviation equivalent are not remedied. of learning will have 30.9 percent (male) and 39.2 percent (female) lower lifetime earnings. Lower individual-level productivity among the pandemic-affected new labor market entrants will translate into a lower economic productivity. Figure B.8: Simulated age-earning profiles of workers with and without learning loss, by gender 45 Earning (Non-COVID-19 Annual Earning (IDR million, 2021 40 35 Counterfactual) 30 25 prices) 20 15 10 Earning (Loss Learning) 5 0 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 Male Female Source: Authors’ analysis using SDI Survey 2019 and Learning Loss Survey 2023, IFLS 2014 and WDI data. Note: Quantile regressions were run at the mean (counterfactual) and IDR 8.0 million lower from the mean (lost learning) to simulate the different earning growth curves, by including gender and years of education as control variables. 106 In 2014 nominal value, the 36 percent higher income due to one s.d. difference was equivalent to IDR 8.0 million (or US$ 674). This average was calculated by excluding workers who reported zero earnings. Calculated by using the GDP deflator and exchange rates from World Development Indicator (WDI) dataset published in July 2022. 2014 exchange rate was US$1=IDR11,865.21 and 2021 exchange rate was US$1=IDR14308.14. 107 Afkar & Yarrow (2021) 108 Using 2021 exchange rate of US$1= IDR14308.14. 44 Indonesia Economic Prospects June 2023 6. Conclusion and Policy Recommendations 6.1. Policy Recommendations – short-term actions for learning recovery in Indonesia The findings of the Learning Learning losses are likely to limit opportunities for students to advance to higher Loss Survey 2023 and this levels of schooling. Global study estimates that COVID-19 school closures will lead to report highlight the urgency significant long-term future earning losses associated with lost human capital.109 There of addressing learning loss; the need for deliberate actions is a globally established and used framework for learning recovery called the RAPID for learning recovery, and to Framework,110 which also offers a compilation of good practices and lessons learned address inequalities in the from the ongoing global learning recovery efforts during the COVID-19 pandemic.111 access to quality of education Using this framework as a basis and by reflecting on the results of the survey, this and in learning outcomes, report provides a set of policy recommendations for learning recovery in Indonesia. especially for disadvantaged populations who experience greater inequalities. Policy Recommendation 1: Initiate deliberate actions for learning recovery now, by prompting political commitment for learning recovery, allocating resources and engaging stakeholders. The emphasis of the first set Business-as-usual approaches do not help remediate learning losses.112 While the of recommendations is for GoI is advancing on implementation of the new Merdeka Belajar policy for learning policymakers to take deliberate recovery, deliberate actions specifically to address learning recovery in the short term actions now to support the ‘current cohort’ of students. are less explicit in current GoI policy. If learning loss is not remediated now, it could compound and grow over time and the student cohort that lost learning will never have an opportunity to catch up. 1. 1. Deliberately allocate budgets for immediate learning recovery actions and prompt political commitment for learning recovery. Recovering from pandemic-induced learning losses requires political alignment across multiple stakeholders, many of whom have different priorities.113 Political commitment, at all levels of the government (national, provincial, district) is necessary for learning recovery, and the most effective way to signal the policy priority for learning recovery actions is ‘allocating budgets for learning recovery’. While the GoI’s current policy can be the main vehicle for learning recovery, labeling specific programs as learning recovery programs with allocation budget will communicate the GoI’s commitment more clearly.114 1. 2. Raise awareness of teachers, principals, officials of subnational governments, and all education stakeholders about student learning loss and support them to teach students at the right level. Teachers have important roles in learning recovery and their understanding and commitment is also necessary (also see recommendation 2.3), as is raising awareness among education stakeholders and ensuring they take deliberate actions to support student learning. This includes a call to employ the assessment instruments and differentiated approach of Merdeka curriculum specifically to address learning recovery through targeted guidance in its adoption. 109 Psacharopoulos et al. (2020) 110 World Bank et al. (2022) 111 The RAPID framework consists of the following five elements: (1) Reach every child and keep them in school; (2) Assess learning levels regularly; (3) Prioritize teaching the fundamentals; (4) Increase the efficiency of instruction including through catch-up learning; and (5) Develop psychosocial health and wellbeing. 112 Schady et al. (2023) 113 Ibid 114 MoECRT started a ‘quality reading book program’ in 2022 as part of overall Merdeka Belajar program, aiming to improve reading skills at early childhood education and primary education levels (https://itjen.kemdikbud.go.id/web/merdeka-belajar-episode-23-buku-bacaan-bermutu-untuk-lit- erasi-indonesia/ ). Such specific interventions would help teachers to understand what to do. Similar actions for math can be also considered. 45 Indonesia Economic Prospects June 2023 1.3. Raise awareness of parents to engage them in continued supplementary home-based learning. Schools alone are not enough to assure learning recovery, but parents and households play an important role in how students spend their time after regular school hours. While not all parents can teach at home, informed parents can nudge children to read at home or offer guided support to children doing homework for their learning recovery. Global evidence shows that effective home and remote learning requires engaged students, and parents need to be supported to help students access home learning opportunities and ensure their socio-emotional wellbeing.115 Parents would benefit from clear guidance and resources from GoI for continued ‘supplementary’ home learning. Education technology also provides opportunities for effective household engagement for learning recovery.116 Policy Recommendation 2: Catch up on lost learning time, teach at the right level for students, and track student performance improvement. 34. The second set of recommendations focus on improving service delivery at educational institution level, by catalyzing efforts by teachers and institutions.117 2.1. Catch up on lost learning hours by increasing class hours, offering remedial lessons during semester breaks, or leveraging private learning support outside regular class hours. Based on the global evidence, the simplest but perhaps most powerful approach for recovery learning is to catch up on learning hours. Some countries have already reacted by increasing school hours or introducing remedial lessons.118 Some 41 percent of the 143 countries interviewed in February 2021 claimed to be extending academic years instructional hours nationwide.119 Increasing learning hours for remedial purpose can be managed within the regulatory teaching hour responsibility of teachers if teachers’ capacity is underutilized or can be compensated as additional tasks (which requires additional resources). Remedial lessons provided through third parties (e.g., NGOs, private tutoring) can be possible options where available. The GoI can spearhead this movement through its flagship Kampus Mengajar (University Teach) program, which recruits university students to be temporary supplement teachers or tutors in disadvantaged regions, refocusing their roles in the short-term to identify and address learning losses in the area. 2.2. Emphasize Teaching at the Right Level and actively adaptive learning. Students’ learning levels are different even if they are sitting in the same classroom; hence it is important to focus on making progress in student learning rather than progress on curriculum completion, especially when many students are behind the standard curriculum competency for certain grades. This approach was introduced in Indonesia even before the pandemic, and it is compatible with the ongoing MoECRT Merdeka Belajar reform that promotes differentiated learning by paying attention to individual students’ strengths, abilities and interests. In particular, the Merdeka curriculum aims 115 Munoz-Najar et al. (2021) 116 Global studies in Italy and Botswana indicate interventions combining technology and direct instruction can improve learning of students. At a pri- mary education level, weekly SMS messages followed by a phone call with parents improves child’s foundational numeracy skills by 0.12 s.d., equivalent to almost 5 months of schooling, while SMS alone is not as effective. At a secondary education level, free individual tutoring online to disadvantaged students during the lock down by volunteer university students for 3 to 6 hours per week increased students’ academic performance by 0.26 s.d. (equivalent to 10.4 months of learning), and also improved students’ social-emotional skills, aspirations and psychological well-being. 117 This set of recommendations mainly corresponds to the elements (2), (3), and (4) of the RAPID framework. 118 In Kenya and Mexico, the government has expanded the academic calendar by shortening holidays. (World Bank et al. 2021) 119 UNESCO et al. (2021) 46 Indonesia Economic Prospects June 2023 to empower teachers to provide differentiated learning to allow students to adjust to their learning speed and teach at the right level. To successfully implement this in every classroom, continued support to teachers, including the provision of guidance and regular monitoring, is necessary.120 2.3. Continuously assess student competency and monitor improvements. Teaching at the Right Level requires understanding of student current competency levels and their progress. National assessments, including MoECRT’s Asesmen National (AN) and MoRA’s Asesmen Kompetensi Madrasah Indonesia (AKMI) are both useful tools to objectively review student performance. In day-to-day practices, small daily assessments, such as checking homework and small assignments, is also critical for teachers to understand student competency. Full utilization of the assessment instrument sets available in the Merdeka curriculum platform should be further promoted, including specific guidance for teachers in employing them. Policy Recommendation 3: Address inequality in learning by allocating additional resources to support disadvantaged or underperforming students. The third set of Considering fiscal constraints, public policy could prioritize those who were most recommendations focuses on affected and most disadvantaged because their resilience is likely lower than relatively who to support and how to promote targeted support to better endowed groups. disadvantaged populations.121 3.1. Allocate additional resources to subnational governments and educational institutions for learning recovery activities where learning performance is particularly low or learning loss is particularly large. Students in rural areas and poor households perform particularly low and their learning loss is larger. These disadvantaged populations need to be prioritized for government support. While this has been partly addressed by the additional BOS (School Operational Funds) allocation to disadvantaged regions since 2021, further efforts should be made to identify disadvantaged populations outside of these groups. Interventions could include targeted financial subsidies, remedial or catch-up learning programs, highlighting the roles of schools and teachers to identify these marginalized individuals within schools. Equitable and effective provision of internet subsidies to promote additional remote learning could also be considered. 3.2. Provide implementation and capacity building support for subnational education officers to ensure effective use of resource and implementation of targeted interventions. Subnational governments are important actors for the service delivery of learning recovery. Educational offices of subnational governments need to be clearly informed about learning loss, and what activities are needed for learning recovery. For example, if remedial classes are to be offered, guidance is needed for teacher allowances for extra hours, additional teaching and learning resources, adequate supervision of additional classes, and monitoring of student performance among others. In the same vein, capacity building of school principals is essential to improve children’s learning experiences. 3. 3. Provide support to students with disabilities, out-of-school children, and those who may need psychological help. Educational support for children with disabilities should consider those both in-school and out-of- school,122 since they were most likely to drop out before completing primary 120 Beteille et al. (2020) 121 This set of recommendations mainly corresponds to the elements (1) and (5) of the RAPID framework. 122 UNICEF (2021b) 47 Indonesia Economic Prospects June 2023 education123 and this situation worsened during the pandemic in Indonesia.124 In educational institutions, students with disabilities can learn better if they receive individual lessons based on their needs. To support children who drop out of education, financial subsidies can be provided in a form of conditional cash transfers for educational access or reentry to educational institutions. Psychological support is necessary for those who may have suffered from pandemic- related difficulties, trauma from death of family members, and those who experienced Gender Based Violence (GBV) in educational institutions or online.125 123 UNICEF (2020) 124 Brenton, Ferrantino and Maliszewska 2022. 125 World Bank (forthcoming) 48 Indonesia Economic Prospects June 2023 A n nexes ANNEX A Annex A.1: Indonesia’s Competitiveness Indicators vs Peers Sound governance Macroeconomic stability High savings and investment But potential to enhance competition Including through international trade policies Note: The competitiveness assessments are based on composite indices 4 drivers of factor accumulation (basic governance, human capital, basic infrastructure, and macro stability) and 5 efficiency drivers (business regulations, labor markets, financial sector, competition, and trade openness). The composite indices are z scores, which assess Indonesia’s performance relative to 9 comparator countries (Brazil, China, Egypt, India, Indonesia, Republic of Korea, Nigeria, Mexico, Philippines, Türkiye). The z scores were calculated by: (i) subtracting the average from the series for each country’s value; and (ii) dividing by the standard deviation. 49 Indonesia Economic Prospects June 2023 ANNEX B Annex B.1: Technical Note on the Learning Loss Survey 2023 1. Context The Learning Loss Survey 2023 was designed as a follow-up to the Service Delivery Indicators (SDI) survey, last performed in Indonesia in early 2019.126 The instruments employed in the SDI survey included a measure of student learning outcomes in numeracy and literacy in Grade 4 for an almost nationally representative sample, offering an exceptional portrait of the education system immediately prior to the pandemic. The Learning Loss Survey 2023 was conducted from February to March 2023 to maintain the consistency of the timing of assessment with the SDI 2019 survey, which was completed during the same months in 2019. An adapted set of SDI 2019 instruments was employed, mainly to capture learning practices during the pandemic and allow the fieldwork to be accomplished under a compact timeline. 2. Instruments Some modifications were made to the original 2019 SDI survey. The revised instrument removed questions that are less relevant for the assessment of learning losses and included additional questions on learning practices during the pandemic. Test items for math and language were remained identical to SDI 2019 to allow direct comparison of items. The 2023 used a new classroom observation tool called TEACH127, which was developed by the World Bank to replace the former SDI classroom observation module. The methodology o collecting household data changed from house visits to a questionnaire to the students in order to facilitate the data collection. 3. Sampling, Matching and Weighting The sampling framework has been adjusted from that of the 2019 SDI survey. The main objective of the original 2019 SDI survey was to obtain a nationally representative sample of madrasahs under MORA, and it included a sample of 253 madrasahs across the country and a sample of 87 MoECRT schools located MoECRT within the immediate vicinity of sampled madrasahs (a total sample size was 350 educational institutions by including additional ten non-Islamic MoRA institutions). This suggests that the 2019 sample did not represent a true distribution of MoECRT schools, as it differs with that of MoRA madrasahs. Because the objective of 2023 learning loss survey was to obtain a nationally representative sample of all educational institutions (i.e. schools under MoECRT and madrasahs under MoRA) in the country, adjustment to the sampling frame was made to increase the coverage of MoECRT schools. Statistical adjustments were made to ensure national representation of the data by employing matching and weighting techniques. To account for the representation issue of the MoECRT schools in 2019 survey, matching is performed using the Mahalanobis Distance Matching technique, to adjust characteristics of the sample schools to be consistent with the national distribution. The list of provinces and districts selected are shown in Annex Figure B.1 and Annex Table B.1. The matching was mainly accomplished using school standardized accreditation scores available from the Indonesian National Accreditation Body for Schools and Madrasahs (BAN SM). This process generated a matching weight. The survey also employs student weights to account for different number of students across educational institutions, and a school weight to take into account the different number of schools each sample represents. These three weights are then multiplied together to yield a single individual weight employed in individual- level analysis, while analysis at the school level uses a consolidated matching and school weight. The final data set includes the following: (a) a panel sample (i.e. revisiting) of 296 educational institutions, which includes 200 MoRA madrasahs randomly selected from the 253 original SDI sample, 87 MoECRT schools, and nine non-Islamic MoRA schools; and (b) a newly identified 113 non-panel MoECRT schools that would ensure MoECRT schools 126 Further information on the 2019 SDI survey can be found on the following link: https://openknowledge.worldbank.org/entities/publication/f8d78c37-968a-55e2-96b4-9fc6067fce65 127 Further information on the instrument can be found in the following link: https://www.worldbank.org/en/topic/education/brief/teach-helping-countries-track-and-improve-teaching-quality 50 Indonesia Economic Prospects June 2023 Annex Figure B.1: Coverage of geographical areas under the 2023 Learning Loss survey Source: Prepared by the authors to be nationally representative.128 The final sample size of 2023 survey is 409 education institutions (see Annex Table B.2). At each educational institution visited, randomly selected 10 Grade 4 students are included for student assessment unless the number of Grade 4 students in the sample institution is less than 10. The total number of students interviewed and tested is 3,863 for 2023 (see Annex Table B.3).129 In each educational institution, at least one teacher was selected to be observed and interviewed. In educational institutions that practice the thematic teaching system—where a single teacher, usually the homeroom teacher, teach a set of basic education subjects, including language and mathematics—one Grade 4 teacher was randomly selected. In educational institutions where teachers teach by subject, two Grade 4 teachers were selected, one for each of the subjects. In both cases, ten Grade 4 students were randomly selected for the assessment and given a short questionnaire from the pool of students taught by the teachers. In schools with less than ten students, all Grade 4 students were included in the sample. 128 The 113 non-panel MoECRT schools were selected with the aim of making the combined sample of MoECRT schools nationally representative. Several balance checks were performed to maintain representativeness, achieved through balancing across several covariates on school character- istics, including school status, size, and sanitation facilities. The data to perform the exercise was obtained from the MoECRT administrative data bank (Data Pokok Pendidikan or Dapodik), using the 2019 point-in-time data to maintain consistency with the original survey. 129 The SDI 2019 data focused on 3,368 Grade 4 students to assess their learning results. 51 Indonesia Economic Prospects June 2023 Annex Table B.1: List of surveyed province and districts Province Districts Aceh Pidie, Aceh Tenggara Bali Karangasem, Bangli Banten Kota Serang Dki Jakarta Kota Jakarta Pusat Jambi Sarolangun, Tanjung Jabung Barat Jawa Barat Karawang, Pangandaran, Kota Bekasi, Bandung Barat, Sumedang Jawa Tengah Wonogiri, Blora, Temanggung, Karanganyar Jawa Timur Jombang, Trenggalek, Ponorogo Kalimantan Barat Ketapang, Sambas, Sekadau, Landak Kalimantan Selatan Tabalong, Hulu Sungai Tengah Kalimantan Tengah Katingan, Kotawaringin Timur Kepulauan Bangka Belitung Bangka Selatan Kepulauan Riau Bintan Lampung Tanggamus Nusa Tenggara Timur Alor, Flores Timur Sulawesi Selatan Pangkajene Dan Kepulauan, Kepulauan Selayar, Gowa, Tana Toraja Sulawesi Tengah Sigi, Tojo Una-Una Sulawesi Tenggara Buton Tengah, Buton Selatan, Konawe Sulawesi Utara Kepulauan Sangihe, Bolaang Mongondow Utara, Bolaang Mongondow Selatan, Minahasa Sumatera Selatan Ogan Komering Ilir, Muara Enim Sumatera Utara Asahan, Nias Barat, Tapanuli Utara, Samosir Annex Table B.2: Number of educational institutions surveyed in 2023 and number of SDI 2019 institutions used for the Learning Loss analysis Public Private Total Urban Rural Sub-Total Urban Rural Sub-Total 2019 MoECRT 37 42 79 4 2 6 85 MoRA Islamic 17 25 42 64 95 159 201 MoRA Non-Islamic 7 2 9 9 Total 54 67 121 75 99 174 295 2023 MoECRT 83 93 176 19 4 23 199 MoRA Islamic 17 25 42 64 95 159 201 MoRA Non-Islamic 7 2 9 9 Total 100 118 218 90 101 191 409 Source: Authors’ analysis using SDI Survey 2019 and Learning Loss Survey 2023 52 Indonesia Economic Prospects June 2023 Annex Table B.3: Number of students surveyed in 2023 and SDI 2019 students used for the Learning Loss analysis Public Private Total Urban Rural Sub-Total Urban Rural Sub-Total 2019 MoECRT 362 395 757 40 20 60 817 MoRA Islamic 170 249 419 632 902 1,534 1,953 MoRA Non-Islamic 46 14 60 60 Total 532 644 1,176 718 936 1,654 2,830 2023 MoECRT 799 851 1,650 190 37 227 1,877 MoRA Islamic 170 250 420 618 892 1,510 1,930 MoRA Non-Islamic 39 13 52 52 Total 969 1,101 2,070 847 942 1,789 3,859 Source: Authors’ analysis using SDI Survey 2019 and Learning Loss Survey 2023 Annex B.2: Detailed description of data analysis 1. Descriptive analysis of test items Item comparison shows that Grade 4 student competency on specific tasks of math and language deteriorated between 2019 and 2023. The test assessed if students are able to perform basic arithmetic operations. Some key parameters are displayed in Annex Table B.4. For example, the percentage of Grade 4 students who correctly answered 2-digit and 3-digit multiplications dropped from 14.0 to 9.2 and 7.7 to 5.9 percent, respectively. On the test of Indonesian language (bahasa Indonesia),130 the percentages were lower for all tasks compared to 2019 although the language tests focuses on a relatively simple task to measure most fundamental reading skills, and the result shows over 90 percent of Grade 4 students being able to demonstrate abilities to recognize alphabets and simple words and read a simple sentence and a simple passage (Annex Table B.5). Reading fluency, measured by the time of reading a simple passage of 60 words, also slowed down to an average of 58.1 seconds in 2023 from 47.7 seconds in 2019. Annex Table B.4: Percentage of Grade 4 students answering specific math tasks correctly Addition subtraction Multiplication Multiplication Division (2 digits Simple math (3 digits) (2 digits) (2 digits) (3 digits) divided by 1 digit) problem 2019 65.5 34.2 14.0 7.7 31.2 15.7 2023 56.5 26.9 9.2 5.9 19.6 9.3 2023 (panel*) 55.5 25.9 8.6 4.9 19.4 8.9 Source: Authors’ analysis using SDI Survey 2019 and Learning Loss Survey 2023 Note: The examples of test items (not actually used) are the following. 3-digit addition: 245+135; 2-digit subtraction: 86-39; 2-digit multiplication: 47*20; 3-digit multiplication: 413*203; 2 digits divided by 1 digit – 65/5; simple math problem: “There are 12 apples in a box and if there are 10 boxes, how many apples are there in total?” * Panel sample means restricting the analysis to the educational institutions that were visited in both 2019 and 2023, including 200 madrasahs and 87 schools for the purpose of robustness check. 130 There are many local languages commonly used and spoken in different districts and provinces. This survey collects the information about the students’ mother tongues and languages commonly used in classroom instructions. However, this analysis focuses only on performance in Bahasa Indonesia. 53 Indonesia Economic Prospects June 2023 Annex Table B.5: Percentage of Grade 4 students answering specific language tasks correctly Alphabet Identifying words Word identification Read a sentence Read a passage** identification for pictures 2019 90.6 98.9 99.4 97.7 96.1 2023 93.1 97.8 86.4 95.7 92.8 2023 (panel*) 93.4 98.0 86.6 96.0 93.4 Source: Authors’ analysis using SDI Survey 2019 and the Learning Loss Survey 2023 Note: The result for 2019 in this table consists of different samples from published results in Yarrow et al. (2020). This result shows the national average by weighting MoECRT schools. See Annex 1 for the technical note about matching and sampling. * Panel sample means restricting the analysis to the educational institutions that were visited in both 2019 and 2023, including 200 madrasahs and 87 schools for the purpose of robustness check. **This item is used for testing reading speed and is described in the subsequent paragraph. 2. Regression analysis for assessing the learning losses The learning losses were calculated by running the following model of regressions. The test scores were standardized for the mean of zero and standard deviation of one. The list of covariates used for this report were school type (public, private), school location (urban, rural), students’ gender (male, female), and students’ household asset index as a proxy for poverty (richest 20 percentile and poorest 20 percentile, measured by household assets). Regressions were run with both with and without weights, and the standard errors are clustered at school level. The detailed results are presented in Annex Table B.6. Learning losses in months are calculated by taking the ratio of zscore to 0.300 of standard deviation, the one-year equivalent learning used commonly in the literature. The impact of the learning loss on individual wage was calculated based on the wage regressions on Indonesia Family Life Survey (IFLS) data from 2014 (latest available). It had a module for an IQ-test, pattern recognition, and a simple math test. This study created a standardized score by using math items only, it and calculated the average wage for those who have performed with mean competency level and 0.3 standard deviation lower. A regression analysis on wage was conducted by controlling for age [which proxies the work experience] and gender to estimate the wage impact of 0.3 standard deviation change in math skills. Following the calculation of individual wage differences by competency, a further analysis on the impact of wage difference on the economy was conducted. By using the following model, three regressions were run, which were (1) the overall sample, (2) at the 70th quantile, and (3) at the 55th quantile. The 70th quantile regression was to estimate the age-earning profile of workers at the average wage, and 55th quantile regression was for the workers with 0.3 standard deviation lower competency (and or IDR 8.0 million lower wage than the average). Age-earning profile was constructed for male and female workers accordingly and adjusted for the price to 2021 constant price. 54 Indonesia Economic Prospects June 2023 Annex Table B.6: Descriptive statistics on Learning Loss derived from the results of regression analyses Literacy Numeracy Unweighted Weighted Unweighted Weighted 2019 2023 Diff 2019 2023 Diff 2019 2023 Diff 2019 2023 Diff Public -0.101 -0.407 -0.305*** -0.026 -0.361 -0.335*** -0.166 -0.377 -0.211*** -0.038 -0.332 -0.294*** (0.051) (0.045) (0.055) (0.059) (0.058) (0.066) (0.052) (0.035) (0.052) (0.069) (0.045) (0.068) School Private -0.224 -0.367 -0.143*** 0.072 -0.042 -0.115 -0.293 -0.462 -0.169*** 0.09 -0.18 -0.270** Status (0.049) (0.055) (0.048) (0.071) (0.064) (0.085) (0.047) (0.041) (0.041) (0.115) (0.074) (0.129) Diff 0.122* -0.04 -0.162** -0.099 -0.319*** -0.220** 0.127* 0.086 -0.042 -0.128 -0.152* -0.024 (0.071) (0.071) (0.073) (0.092) (0.087) (0.107) (0.070) (0.054) (0.066) (0.134) (0.087) (0.145) Urban 0.019 -0.201 -0.220*** 0.121 -0.139 -0.260** -0.065 -0.241 -0.177*** 0.161 -0.16 -0.321*** (0.048) (0.044) (0.051) (0.060) (0.059) (0.060) (0.051) (0.038) (0.050) (0.077) (0.050) (0.080) Regional Rural -0.319 -0.553 -0.234*** -0.201 -0.535 -0.333*** -0.373 -0.569 -0.196*** -0.278 -0.54 -0.262*** Status (0.049) (0.051) (0.051) (0.078) (0.066) (0.089) (0.045) (0.035) (0.042) (0.068) (0.047) (0.071) Diff 0.338*** 0.352*** 0.014 0.322*** 0.396*** 0.074 0.309*** 0.328*** 0.019 0.439*** 0.380*** -0.06 (0.068) (0.067) (0.072) (0.098) (0.088) (0.111) (0.069) (0.052) (0.065) (0.103) (0.068) (0.106) Male -0.327 -0.583 -0.257*** -0.142 -0.443 -0.302*** -0.371 -0.546 -0.175*** -0.176 -0.405 -0.229*** (0.047) (0.046) (0.054) (0.076) (0.064) (0.090) (0.041) (0.031) (0.043) (0.068) (0.046) (0.074) Female -0.011 -0.195 -0.184*** 0.13 -0.11 -0.240*** -0.102 -0.287 -0.185*** 0.153 -0.178 -0.331*** Gender (0.037) (0.036) (0.041) (0.043) (0.046) (0.056) (0.040) (0.032) (0.040) (0.082) (0.041) (0.084) Diff -0.316*** -0.388*** -0.073 -0.272*** -0.334*** -0.073 -0.269*** -0.259*** 0.01 -0.329*** -0.227*** 0.102 (0.047) (0.045) (0.065) (0.075) (0.062) (0.065) (0.040) (0.032) (0.052) (0.090) (0.040) (0.100) Top 20% 0.21 0.079 -0.131* 0.286 0.146 -0.14 0.133 -0.037 -0.169* 0.143 0.056 -0.087 (0.066) (0.048) (0.079) (0.086) (0.062) (0.098) (0.088) (0.052) (0.096) (0.136) (0.075) (0.148) Asset Bottom -0.362 -0.837 -0.476*** -0.181 -0.86 -0.680*** -0.383 -0.689 -0.306*** -0.204 -0.656 -0.455*** Index 20% (20%) (0.090) (0.058) (0.093) (0.106) (0.082) (0.128) (0.064) (0.038) (0.069) (0.093) (0.054) (0.106) Diff 0.572*** 0.917*** 0.345*** 0.467*** 1.006*** 0.539*** 0.516*** 0.652*** 0.137 0.347** 0.715*** 0.368** (0.113) (0.071) (0.124) (0.132) (0.093) (0.162) (0.109) (0.061) (0.119) (0.166) (0.086) (0.185) Overall -0.172 -0.389 -0.217*** -0.005 -0.276 -0.271*** -0.239 -0.416 -0.177*** -0.01 -0.291 -0.281*** (0.036) (0.035) (0.036) (0.049) (0.047) (0.055) (0.035) (0.027) (0.033) (0.060) (0.039) (0.061) Note: *** p < 0.01, ** p < 0.05, * p < 0.1. Standard errors in parentheses. Observations are weighted relative to their geographical location and characteristics. Standard errors are clustered at the school level. 55 Indonesia Economic Prospects June 2023 Re ference s PART A Dieppe, A. 2021. Global Productivity: Trends, Drivers, and Policies. Washington, DC: World Bank. Ikhsan, M., Indrawati, S. M., Virananda, I. G. S., and Abdi, Z. 2022. The Productivity and Future Growth Potential of Indonesia. Economics and Finance in Indonesia 67 (2): 235-256. International Monetary Fund. 2016. Guidance Note on the Assessment of Reserve Adequacy and Related Considerations. Washington, DC: IMF. International Monetary Fund. 2023. World Economic Outlook, April 2023: A Rocky Recovery. Washington, DC: IMF. Kumar, S., Li, A., Wong, H., Chauhan, H., Shubhankar, S., Oetama, I. 2023. Indonesia’s Fintech Industry Is Ready to Rise. Boston Consulting Group. Porter, M. E. 1990. The Competitive Advantage of Nations. New York: Macmillan, Inc. Rovo, Natasha. 2020. Structural Reforms to Set the Growth Ambition. Policy Research Working Paper; No. 9175. Washington, DC: World Bank. Sala-I-Martin, X. and Artadi, E.V. 2004. The Global Competitiveness Index. The Global Competitiveness Report 2004– 2005. Hampshire: Palgrave Macmillan. World Bank. 2008. The growth Report: Strategies for Sustained Growth and Inclusive Development. Washington DC: World Bank. World Bank. 2017. Who Sponsors Infrastructure Projects? Disentangling public and private contributions. Washington, DC: World Bank. World Bank. 2022a. Global Economic Prospects, June 2022. Washington, DC: World Bank. World Bank. 2022b. Indonesia Economic Prospects, December 2022: Trade for Growth and Economic Transformation. Washington, DC: World Bank. World Bank. 2023a. Global Economic Prospects, June 2023. Washington, DC: World Bank. World Bank. 2023b. Indonesia Poverty Assessment: Pathway Towards Economic Security. Washington, DC: World Bank. World Bank. 2023c. Off the Books: Understanding and Mitigating the Fiscal Risks of Infrastructure. Sustainable Infrastructure Series. Washington, DC: World Bank. doi:10.1596/978-1-4648-1937-7. World Bank. 2023d. Reviving Growth: East Asia and Pacific Economic Update, April 2023. Washington, DC: World Bank. PART B Abidah, A., Hidaayatullaah, H. N., Simamora, R. M., Fehabutar, D., & Mutakinati, L. 2020. The Impact of Covid-19 to Indonesian Education and Its Relation to the Philosophy of “Merdeka Belajar”. Studies in Philosophy of Science and Education, 1(1), 38–49. https://doi.org/10.46627/sipose.v1i1.9 Afkar, R., Luque, J., Nomura, S., & Marshall, J. 2020. Revealing How Indonesia’s Subnational Governments Spend Their Money on Education: Indonesia Subnational Education Public Expenditure Review 2020. World Bank. https://doi. org/10.1596/34831 56 Indonesia Economic Prospects June 2023 Afkar, R., & Yarrow, N. 2021. Rewrite the Future: How Indonesia’s Education System Can Overcome the Losses from the COVID-19 Pandemic and Raise Learning Outcomes for All. World Bank. https://doi.org/10.1596/36327 Agostinelli, F., Doepke, M., Sorrenti, G., & Zilibotti, F. 2022. When the great equalizer shuts down: Schools, peers, and parents in pandemic times. Journal of Public Economics, 206, 104574. https://doi.org/10.1016/j.jpubeco.2021.104574 Azevedo, J. P., & Goldemberg, D. 2020. Estimating the Potential COVID-19 Impacts on Learning Poverty in Brazil. World Bank. Azevedo, J. P., Hasan, A., Goldemberg, D., Iqbal, S. A., & Geven, K. 2020. Simulating the Potential Impacts of COVID-19 School Closures on Schooling and Learning Outcomes: A Set of Global Estimates. World Bank, Washington, DC. https:// doi.org/10.1596/1813-9450-9284 Beatty, A., Berkhout, E., Bima, L., Pradhan, M., & Suryadarma, D. 2021. Schooling progress, learning reversal: Indonesia’s learning profiles between 2000 and 2014. International Journal of Educational Development, 85, 102436. https://doi. org/10.1016/j.ijedudev.2021.102436 Beteille, T., Ding, E., Molina, E., Pushparatnam, A., & Wilichowski, T. 2020. Three Principles to Support Teacher Effectiveness During COVID-19. World Bank, Washington, DC. https://doi.org/10.1596/33775 Butcher, N., Khairina, N. N., Kumala, C., & Loots, S. 2021. The struggle against COVID-19 in Indonesian Education: Responses, requirements, and policy needs for learning recovery. World Bank. Carlana, M., & Ferrara, E. L. 2021. Apart but Connected: Online Tutoring and Student Outcomes during the COVID-19 Pandemic. Engzell, P., Frey, A., & Verhagen, M. D. 2021. Learning loss due to school closures during the COVID-19 pandemic. Proceedings of the National Academy of Sciences, 118(17), e2022376118. https://doi.org/10.1073/pnas.2022376118 Filmer, D., Rogers, H., Angrist, N., & Sabarwal, S. 2020. Learning-adjusted years of schooling (LAYS): Defining a new macro measure of education. Economics of Education Review, 77, 101971. https://doi.org/10.1016/j.econedurev.2020.101971 Flynn, A., Powell, A., & Hindes, S. 2021. Technology-facilitated abuse: A survey of support services stakeholders. 60. Goldhaber, D., Kane, T. J., McEachin, A., Morton, E., Patterson, T., & Staiger, D. O. 2022. The Consequences of Remote and Hybrid Instruction During the Pandemic. Hanushek, E. A., & Wößmann, L. 2020. The economic impacts of learning losses (OECD Education Working Papers No. 225; OECD Education Working Papers, Vol. 225). https://doi.org/10.1787/21908d74-en Hata, A., Town, S., Yuwono, J., & Nomura, S. 2023. Inclusive Early Childhood Education for Children with Disabilities in Indonesia. World Bank. Hata, A., Wang, H., Yuwono, J., & Nomura, S. 2023. Assistive Technologies for Children with Disabilities in Inclusive and Special Schools in Indonesia. World Bank. Hata, A., Yuwono, J., Purwana, R., & Nomura, S. 2021. Embracing Diversity and Inclusion in Indonesian Schools: Challenges and Policy Options for the Future of Inclusive Education. World Bank. https://openknowledge.worldbank. org/handle/10986/36533 Hinson, L., Mueller, J., O’Brien-Milne, L., & Wandera, N. 2018. Technology-Facilitated GBV: What is it, and How do we measure it? https://www.icrw.org/publications/technology-facilitated-gender-based-violence-what-is-it-and-how-do- we-measure-it/ INOVASI. 2021. Learning Recovery: Time for Action Policy Brief—August 2021. Jones, S. 2017. Do schools in low income countries really produce so little learning? Lim, D., Rarasati, N., Ayu Tresnatri, F., & Rahmi Barasa, A. 2022. Learning Loss or Learning Gain? A Potential Silver Lining to School Closures in Indonesia. Research on Improving Systems of Education (RISE). https://doi.org/10.35489/BSG- RISE-RI_2022/041 57 Indonesia Economic Prospects June 2023 Munoz-Najar, A., Gilberto, A., Hasan, A., Cobo, C., Azevedo, J. P., & Akmal, M. 2021. Remote Learning During COVID-19: Lessons from Today, Principles for Tomorrow. World Bank. https://doi.org/10.1596/36665 NCVAW. 2020. CATAHU 2020: Kekerasan terhadap Perempuan Meningkat: Kebijakan Penghapusan Kekerasan Seksual Menciptakan Ruang Aman Bagi perempuan dan anak perempuan. Catatan Kekerasan Terhadap Perempuan Tahun 2019. https://komnasperempuan.go.id/catatan-tahunan-detail/catahu-2020-kekerasan-terhadap-perempuan-meningkat- kebijakan-penghapusan-kekerasan-seksual-menciptakan-ruang-aman-bagi-perempuan-dan-anak-perempuan- catatan-kekerasan-terhadap-perempuan-tahun-2019 OECD. 2019. PISA Results from PISA 2018- Country Note: Indonesia. OECD. Patrinos, H. A. 2023. The Longer Students Were Out of School, the Less They Learned. World Bank, Washington, DC. https://doi.org/10.1596/1813-9450-10420 Pradana, M., & Syarifuddin, S. 2021. The Struggle Is Real: Constraints of Online Education in Indonesia During the COVID-19 Pandemic. Frontiers in Education, 6, 753776. https://doi.org/10.3389/feduc.2021.753776 Psacharopoulos, G., Collis, V., & Patrinos, H. A. (n.d.). Lost Wages: The COVID-19 Cost of School Closures. Randall, R., Sukoco, G. A., Heyward, M., Purba, R., Arsendy, S., Zamjani, I., & Hafiszha, A. 2022. Reforming Indonesia’s curriculum: How Kurikulum Merdeka aims to address learning loss and learning outcomes in literacy and numeracy. INOVASI. Santosa, M. H. 2022. Freedom to Learn (Merdeka Belajar) [Preprint]. Open Science Framework. https://doi.org/10.31219/ osf.io/jkq7a Schady, N., Holla, A., Sabarwal, S., Silva, J., & Chang, A. Y. 2023. Collapse and Recovery: How the covid-19 pandemic eroded human capital and what to do about it. World Bank. Sekartini, R. 2021. Anak-anak Menghadapi Covid-19: Perawatan dan Dukungan. ABIP Workshop 3: Psychological Support for Students During and Post-Pandemic Covid-19. Singh, A. 2020. Learning More with Every Year: School Year Productivity and International Learning Divergence. Journal of the European Economic Association, 18(4), 1770–1813. https://doi.org/10.1093/jeea/jvz033 Spink, J., Cloney, D., & Berry, A. 2022. THE LEARNING GAP SERIES – ONE: Beyond letters and numbers: The COVID-19 pandemic and foundational literacy and numeracy in Indonesia. INOVASI and ACER. Sukmayadi, V., & Yahya, A. H. 2020. Indonesian Education Landscape and the 21st Century Challenges. Journal of Social Studies Education Research, 11(4), 219–234. UNESCO. 2019. New Methodology Shows that 258 Million Children, Adolescents and Youth Are Out of School. UNESCO; UNICEF; World Bank; OECD. 2021. What’s Next Lessons on Education Recovery: Findings from a Survey of Ministries of Education amid the COVID-19 Pandemic. UNICEF. 2020a. Children with Disabilities and Education (school aged, 7-18 years). UNICEF. https://www.unicef.org/ indonesia/media/2716/file/Children-with-Disabilites-and-Education-2020.pdf UNICEF. 2020b. Responding to the Shadow Pandemic: Taking stock of gender-based violence risks and responses during COVID-19. https://www.unicef.org/documents/responding-shadow-pandemic-taking-stock-gender-based-violence- risks-and-responses-during UNICEF. 2021a. Annual Report 2021. UNICEF. https://www.unicef.org/indonesia/media/13756/file/Annual%20Report%20 2021%20-%20Spread.pdf UNICEF. 2021b. Issue Brief: The Impact of the COVID-19 Pandemic on Children’s Learning in Indonesia. UNICEF. UNICEF. 2023. Discussion Paper: Key Issues for Children with Disabilities in Indonesia. UNICEF. UNICEF, UNDP, & SMERU. 2021. Analysis of the Social and Economic Impacts of COVID-19 on Households and Strategic Policy Recommendations for Indonesia. 58 Indonesia Economic Prospects June 2023 UNICEF, UNESCO, & World Bank. 2022. Where we are in education recovery? UNICEF. Woessmann, L. 2016. The Importance of School Systems: Evidence from International Differences in Student Achievement. Journal of Economic Perspectives, 30(3), 3–32. https://doi.org/10.1257/jep.30.3.3 World Bank. 2018. Learning to realize education’s promise. World Bank Group. https://doi.org/10.1596/978-1-4648- 1097-8 World Bank. 2020a. Indonesia High Frequency Monitoring of Covid-19 Impacts: Round 4, 3-15 November 2020. World Bank. https://www.worldbank.org/en/country/indonesia/brief/indonesia-covid-19-observatory World Bank. 2020b. Indonesia Public Expenditure Review: Spending for Better Results. World Bank. 2020c. The Promise of Education in Indonesia. World Bank. World Bank. 2020d. Towards a secure and fast recovery. World Bank. World Bank. 2021. Indonesia Learning Poverty Country Brief. World Bank. https://documents1.worldbank.org/curated/ en/579771624553117186/pdf/Indonesia-Learning-Poverty-Brief-2021.pdf World Bank. 2022. Trade for Growth and Economic Transformation: December 2022. World Bank. 2023. High-Frequency Monitoring of COVID-19 Impacts 2020-2022 [Data set]. World Bank, Development Data Group. https://doi.org/10.48529/1D1V-AY29 World Bank. (forthcoming). Cyber gender-based violence among high school girls and boys in Indonesia. World Bank. World Bank, the Bill & Melinda Gates Foundation, FCDO, UNESCO, UNICEF, & USAID. 2022. Guide for Learning Recovery and Acceleration: Using the RAPID Framework to Address COVID-19 Learning Losses and Build Forward Better. World Bank, UNESCO, & UNICEF. 2021. The State of the Global Education Crisis: A Path to Recovery. The World Bank, UNESCO, and UNICEF. Yarrow, N., Masood, E., & Afkar, R. 2020. Estimates of COVID-19 Impacts on Learning and Earning in Indonesia: How to Turn the Tide. 59 Supported by funding from the Australian Government through the Australia-World Bank Indonesia Partnership (ABIP) program