## GOLDEN VISION 2045: STRUCTURAL REFORMS TO ACHIEVE HIGH-INCOME STATUS

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### Objective and framing
- Indonesia aims to become a high-income country by 2045 (President Joko Widodo’s 2019 Golden Indonesia Vision; restated in the 2024–29 program).
- Analysis benchmarks Indonesia against 19 “success” countries to identify structural drivers of sustained high growth and to prioritize reforms across: external sector regulation and openness, governance, business regulation, labor and credit markets, human capital, infrastructure, demographics, poverty and gender inequalities, and economic complexity.

### Growth requirements and projections
- To reach high-income status by 2045 (assuming global GNI per capita thresholds move as in the last two decades and annual population growth of 1 percent), Indonesia requires:
  - An annual GNI growth rate of around 8 percent (in current US$).
  - Roughly equivalent to 5.5-6 percent real annual GDP growth (assuming annual inflation stays at its target, 2.5 percent).
  - Sustained over two decades to level up Indonesia's GNI per capita by 50 percent by 2045.
- Current estimated potential growth and benchmarks:
  - Current estimated potential growth: around 5 percent.
  - Hausman’s predicted medium-term growth for Indonesia based on Economic Complexity: 5.6 percent.

### Success countries: identification and methodology
- Two comparator groups:
  - Group 1 (“growth-for-long”, GFL): 11 EMEs/AEs with at least 11 consecutive years of nominal annual GNI growth > 8 percent and that became AE or HI EME by 2022 or earlier.
  - Group 2 (“fast convergence”, FC): 10 EMs/AEs that transitioned from LMI to HI since 1960 and durably remain HI in the latest World Bank classification (Chile and Panama appear in both groups).
- Data span begins in 1962; classifications use IMF’s WEO and World Bank GNI-based HI classification.

### Indonesia’s starting conditions and structural gaps (comparisons with success countries’ starts)
- GDP composition and openness:
  - Imports: 21 percent of GDP (Indonesia) vs. 50 percent (success countries at their starts).
  - Domestic consumption: 61 percent of GDP vs. 80 percent.
  - Exports of services: 2 percent of GDP vs. 11 percent.
  - Economic openness (exports + imports over GDP): 21.1 percent vs. 46.4 percent.
  - Net FDI inflows: 1.6 percent of GDP vs. 4.9 percent of GDP.
  - Simple mean tariff rate: 6.3 percent vs. 5.0 percent.
  - External sector reform index: 0.67 vs. 0.83.
  - Hausman Economic Complexity Index (ECI) in 2022: −0.1 (Indonesia) vs. 0.7 (success cases average).
  - Note: Hirschman-Herfindahl export product concentration index: very close to success countries’ initial average (no divergence in diversification).
- Governance and institutional quality:
  - Indonesia ranks in the bottom quarter of the WGI distribution across: control of corruption, government effectiveness, political stability, regulatory quality, rule of law, voice and accountability—below where success countries were at their growth starts.
- Human capital and demographics:
  - Share of population aged ≥25 with at least primary education: "82 percent" (Indonesia) vs. "almost 87 percent" (success case average at the start).
  - Adult literacy rate: "96 percent" (Indonesia) vs. "97 percent" (success case average).
  - School enrollment rate cited: 100.6 percent (Indonesia) vs. 103.1 percent (comparators).
  - Life expectancy at birth: Indonesia is lower by "10 years" relative to success countries at the start.
  - Human Development Index: below the average of success countries at the start, but within UNDP range considered "high human development".
  - Demographics described as offering a “window opportunity” in coming years.
- Labor market and productivity:
  - Unemployment rate (2022): "5.9 percent" (Indonesia) vs. "8.2" (success countries at the start).
  - Labor force participation: "67 percent" vs. "58 percent".
  - Share of vulnerable employment (ILO estimate): "50" (Indonesia) vs. "18 percent".
  - Hours worked per employee: "38" vs. "42".
  - Output per worker (GDP at constant international US$, PPP) in 2022: "26,000" (Indonesia) vs. "around 38,000" (comparator group at the start).
- Infrastructure, logistics, and inclusion:
  - Mobile subscriptions per 100 people: "115" (Indonesia) vs. "20" (average starting conditions in success countries).
  - Electricity access: "99 percent" vs. "97 percent".
  - Access to drinking water: "94 percent" vs. "96 percent".
  - Logistics Performance Index: Indonesia lags all comparator medians; transportation costs singled out as particularly high.
  - Financial inclusion: lower share of people storing money in a financial account or having a bank account; lower private credit to GDP than comparators; one of the largest unbanked populations globally.
- Trade and trade policy:
  - Non-tariff measures (NTMs) average tariff equivalent: "30 percent" for Indonesia—higher than peers in the region.
  - Trade facilitation performance weaker than OECD countries.

### Empirical approach and methodological notes
- Comparative empirical strategy uses the 19 success cases and structural indicators drawn from literature and Budina et al. (2023).
- Key indices constructed:
  - Governance reform index: simple average of six WGI indices.
  - External sector index: average of tariffs, non-tariff barriers, black-market exchange rate, and controls on movement of capital and people.
  - Credit market regulation index: ownership of banks, size of private sector borrowing, interest rate controls.
  - Labor market regulation index: hiring/firing regulation and degree of centralized collective wage bargaining.
  - Business regulation index: bureaucracy costs, administrative requirements, impartial public administration.
  - Fraser Institute–sourced subcomponents scaled 0 to 1 (higher = higher freedom).
- Regressions and local projections:
  - Sample period for regressions: "1996-2022".
  - Major reform defined as improvement ≥ two standard deviations of annual changes distribution across AE and EM sample.
- Data interpolation and assignment rules applied for missing years (WGI, Fraser, LPI etc.); for some 2022 indicators, latest available values (2021 or 2020) used for Indonesia.

### Key empirical findings on reform impacts
- Individual reform effects:
  - Governance reforms and human development reforms: immediate, positive, significant effect on real output.
  - External sector regulation and credit market regulation reforms: gradual positive effect over years.
  - Labor market regulation reforms: not found to have a significant effect on employment in this sample.
  - Business regulation reforms: overall non-significant (and positive), but positive impact becomes significant after two years conditional on being an EME.
- Packaged reforms (first-generation package: external sector regulation, governance, business regulation, human development):
  - A package characterized by an increase of two standard deviations of the average of underlying reform indices could raise output levels by "around 1.5-2 percent" after two years.
  - The effect could rise to "around 3 percent" after four years conditional on implementing all reforms simultaneously.
  - Packaged reforms are effective irrespective of past reform progress (below or above median).

### Reform sequencing and priorities (policy guidance)
- Priority reforms: external sector regulation and economic openness; governance; business regulation; human development (including human capital).
- Principles:
  - Implement the priority group in tandem to ensure growth gains are broadly shared; reforms are complementary and mutually reinforcing with governance as foundational.
  - Most priority reforms (except business regulation) have immediate, significant effects on real output.
  - Some reforms require financing — short-term expansion of fiscal space through domestic revenue mobilization recommended.
  - Credit market regulation reforms likely deliver stronger output effects after the first set of reforms is implemented.
- Implementation actions and complementarities:
  - Finalize Job Creation Omnibus Law implementation regulations; streamline regulations; improve business certainty; ease trade and logistics processes; level up learning outcomes; enhance social protection.
  - Laying groundwork to support stronger activity and ensure evenly shared growth gains is crucial for Indonesia’s ambition.

### Roadmap: Short-term and Medium-term priorities (Table 2 synthesis)
- A. Fiscal Policy
  - Short-term:
    - 1. Increase domestic tax revenue to bolster fiscal space.
    - 2. Prioritize high-quality spending supportive of development and monitor fiscal risks.
    - 3. Increase coverage and adequacy of the social safety net; improve subsidy targeting.
  - Medium-term:
    - 1. Boost size and quality of health spending and social protection.
    - 2. Boost education spending, improve learning time and quality to reduce skill mismatch and increase productivity and knowledge capabilities/economic sophistication.
    - 3. Tackle gender inequality to further increase the labor force and potential growth.
- C. Governance
  - Strengthen governance and anti-corruption framework; improve legal system to support accountability and business certainty.
- D. Trade and Foreign Investment Policy
  - 1. Avoid intensifying restrictive trade policies (including in the IP context) and transition away from NTMs that distort trade and investment decisions and risk international spillovers.
  - 2. Foster openness in trade and FDI; increase trade facilitation to reduce time, cost and uncertainty of crossborder transactions.
  - 4. Better align retail fuel prices with international prices.
  - 5. Enhance strategic direction of MTFF and its articulation with the annual budget and long-term plans; ensure General Government accounts comprehensively reflect fiscal activities.
  - 6. Strengthen SNG's own-revenue sources and PFM, including current and investment spending execution and service delivery capacities.
- E. Business climate
  - 1. Reduce regulatory uncertainty, bureaucracy costs and administrative hurdles.
  - 2. Strengthen infrastructure and logistics.
- F. Credit Market (selected items)
  - 1. Develop regulation to strengthen credit scores; establish oversight for Credit Reporting Systems.
  - 2. Reforms to enhance capital market development (e.g., repo market, interest rate and forex derivatives).
  - 3. Strengthen regulatory approach to alternative financing models (DFS).
  - 4. Introduce a regulatory green taxonomy and update reporting requirements for firms and financial institutions.
  - 5. Expand (direct) access to the fast payment system (BI-FAST) and build on the National Standard for Payment Open API (SNAP) toward open banking/finance.
  - 6. Foster institutional investor presence in the domestic market.
  - 7. Enhance financial literacy and reduce the digitalization gap across provinces.
  - 8. Explore ways to scale and utilize the domestic banking system to mobilize climate finance.
- G. Labor market
  - 1. Enhance hiring and firing regulation; assess whether wage determination encourages informality.
  - 2. Tackle labor informality and duality, while ensuring worker protection.

### MSMEs: financing barriers, performance, and firm-level evidence
- MSME importance and challenges:
  - MSMEs contribute 61 percent of Indonesia's GDP.
  - MSMEs absorb 97 percent of the nation's workforce.
  - MSMEs represent 99 percent of all business units.
  - 67 percent of MSMEs operate within the informal sector.
  - Indonesia's MSMEs contribute only 15.8 percent to exports.
- Access-to-finance quantitative findings:
  - Substantial credit gap: "47 percent of demand unmet" (EY Parthenon, 2023).
  - State-owned banks, especially Bank Rakyat Indonesia, dominate MSME lending; lending concentrated in Java.
  - MSME constraints reported: high interest rates, lack of collateral, low financial literacy, complex application processes, frequent rejected proposals.
  - MSME distribution and market orientation:
    - "95 percent of Indonesian firm’s products are sold in the domestic market."
    - Retail services represent "about 45 percent of the economy."
    - Java (including Jakarta) accounts for "almost one-sixth of all non-agricultural firms."
- WBES survey coverage:
  - WBES waves in Indonesia: 2009 ("1,444" firms), 2015 ("1,320"), 2023 ("2,955").
- Key firm-level patterns and determinants:
  - Firm age: mature firms (> 20 years) less likely to report access to finance as an obstacle; young firms (<= 5 years) coefficients generally insignificant.
  - Foreign ownership: strong positive relationship with export diversification; evidence of easier access to finance (coefficients such as "-1.305**", "-1.486*").
  - Digital presence: firms with a website associated with lower perception of access to finance as an obstacle (coefficients include "-0.445**", "-0.810***", "-1.199***").
  - Infrastructure disruptions (power outages): associated with reporting access to finance as an obstacle (coefficients "0.774***", "0.917***", "0.738***").
  - Financial inclusion among firms:
    - Small firms with checking/savings account rose from "43 percent in 2009" to "almost 76 percent in 2023".
    - Only "6.3 percent" of small firms have an overdraft facility.
    - About "35 percent" of small firms report insufficient capital; complex procedures often cited as reason not to apply.
- Effects of constrained finance on firm performance (endogenous treatment estimation):
  - Firms reporting access to finance as a major constraint experience:
    - Lower nominal sales growth by 17 percentage points (columns 1-2: -16.945**, -16.571**).
    - Lower real sales growth by 17 percentage points (columns 3-4: -17.193**, -16.761**).
    - Lower productivity (real sales per employee) by 24 percentage points (columns 5-6: -24.158**, -24.545**).
    - Employment coefficient negative but insignificant (columns 7-8: -7.382, -7.266).
  - Effects stronger for domestic firms; foreign-owned firms (≥ 10 percent) less sensitive.
  - Manager experience mitigates negative impact: coefficient becomes insignificant by 25 years of manager experience.
- Export diversification drivers:
  - U-shaped relationship with firm age: both young (<= 5 years) and mature (> 20 years) firms more likely to pursue export diversification (coefficients for young firms: "4.869***", "5.105***", "8.022***"; for mature firms: "2.838***", "3.199***", "2.626**").
  - Foreign ownership and website presence strongly positive for export diversification (coefficients include "3.900***", "4.820***", "4.146***", "6.781***").
  - Banking relationships show weak positive association with export diversification in some specifications.
- Robustness and SMEs-only results:
  - SMEs-only sample shows similar main findings; access-to-finance coefficients remain negative and significant for sales and productivity (e.g., -18.362**, -24.554**).
  - Export orientation coefficients for sales larger in magnitude in the SMEs sample (around -20 percentage points); exporters’ R&D effort coefficients turn significantly negative in SMEs sample.
- MSME-specific conclusions:
  - Young, domestically owned firms, and firms facing inadequate infrastructure experience significant barriers to financial access.
  - Limited financial access adversely affects sales growth and labor productivity, particularly for domestic firms.
  - Managerial experience can mitigate adverse effects.
  - Firm age, foreign ownership, and website availability positively affect export diversification.

### MSME policy recommendations (selected)
- Establish a national credit reporting system strategy and simplify registration for the collateral registry.
- Improve the ease of doing business to stimulate foreign participation.
- Improve connectivity through infrastructure and digitalization.
- Implement financial sector reforms to deepen credit, expand access to overdraft and other facilities, and enhance financial literacy.

### Data sources and selected variables (time periods preserved)
- Gross National Income (World Bank (World Development Indicators)): 1962-2022
- Public and private investment (IMF WEO Database): 1969-2023 (not for all countries)
- Public and private consumption (World Bank (World Development Indicators)): 1960-2022
- Exports of goods and export of services (IMF WEO Database): 1960-2023 (not for all countries)
- Imports of goods and services (World Bank (World Development Indicators)): 1960-2022
- Measure of Aggregate Trade Restrictions (MATR) (IMF AREAER Database): 1999-2021
- IMF External sector reform index (Fraser Institute...): 1970-2021 (not in all years)
- OECD Trade Facilitation Performance Index (OECD): 2017, 2019 and 2022 (Survey-based)
- Tariff rate (simple mean on all products) (World Bank): 1990-2020 (not in all years)
- FDI (share of GDP) (World Bank (World Development Indicators)): 1970-2022
- Hausman Complexity Outlook Index (COI) (Atlas of Economic Complexity (Hausman)): 1995-2021
- Worldwide Governance Indicators (WGI): 1996-2022 (every 2 years at the start)
- IMF Credit market regulation index (Fraser Institute...): 1970-2021 (not in all years)
- Domestic credit to private sector (% of GDP) (World Bank): 1990-2022 (not for all countries)
- Financial inclusion: % of respondents having a bank account (Global Financial Inclusion Database): 2011, 2014, 2017 and 2021
- Infrastructure: Mobile cellular subscriptions (World Bank): 1980-2022
- Infrastructure: Access to electricity (World Bank): 1990-2021
- IMF Business regulation index (Fraser Institute...): 1970-2021 (not in all years)
- Unemployment rate (IMF WEO Database): 1960-2023 (not for all countries)
- Labor Force participation rate (ILO): 1991-2022
- Out. per worker (thousands, const. p., PPP) (ILO): 1991-2024
- Human Development Index (HDI, UNDP): 1990-2022
- Poverty headcount ratio at $2.15 a day (2017 PPP, % of population) (World Bank): 1980-2022 (not for all countries)
- GINI coefficient (World Inequality Database): 1990-2022
- Gender Inequality Index (GII, UNDP): 1990-2022

*Source: IMF staff analysis as presented in content unit: 1idnea2024002-print-pdf.*

### References ______________________________________________________________________________ 29

### GOLDEN VISION 2045: STRUCTURAL REFORMS TO ACHIEVE HIGH-INCOME STATUS

### Objective and framing
- Indonesia aims to become a high-income country by 2045, reiterated in President Joko Widodo’s 2019 Golden Indonesia Vision and restated in the 2024–29 program.
- The paper identifies “success countries” that transitioned into high-income status to draw lessons on structural drivers of sustained high growth and to benchmark Indonesia’s structural gaps.
- The analysis focuses on structural areas: external sector regulation and openness, governance, business regulation, labor and credit markets, human capital, infrastructure, demographics, poverty and gender inequalities, and economic complexity.

### Growth requirements and projections
- Reaching high-income status by 2045, assuming global GNI per capita thresholds move as in the last two decades and annual population growth of 1 percent, requires:
  - An annual GNI growth rate of around 8 percent (in current US$).
  - Roughly equivalent to 5.5-6 percent real annual GDP growth (assuming annual inflation stays at its target, 2.5 percent).
  - Sustained over two decades, which would level up Indonesia's GNI per capita by 50 percent by 2045.
- Current estimated potential growth is around 5 percent; Hausman’s predicted medium-term growth for Indonesia based on Economic Complexity is 5.6 percent.

### Success countries: identification and methodology
- Two groups of “success” countries are defined:
  - Group 1 (“growth-for-long”, GFL): EMEs and AEs experiencing at least 11 consecutive years of strong nominal annual GNI growth higher than 8 percent, and that became either an AE or a HI EME by 2022 or earlier. There are 11 such countries.
  - Group 2 (“fast convergence”, FC): EMs and AEs that transitioned from LMI to HI since 1960 and durably remain HI in the latest World Bank classification. There are 10 such countries; two (Chile and Panama) are also in Group 1.
- Data span begins in 1962 (excludes certain low-income countries and some with missing GNI data). EMEs/AEs classification is from the IMF’s WEO; HI from the World Bank’s GNI-based classification.

### Indonesia’s starting conditions and gaps relative to success countries
- GDP composition:
  - Indonesia is less reliant on imports: 21 percent of GDP vs. 50 percent for success countries at their starts.
  - Domestic consumption: 61 percent of GDP vs. 80 percent for success countries at their starts.
  - Exports of services: 2 percent of GDP vs. 11 percent for success countries at their starts.
- Exports, complexity, and openness:
  - Hausman’s Economic Complexity Index (ECI) in 2022: Indonesia at -0.1 vs. success countries’ average at 0.7.
  - Net FDI inflows: 1.6 percent of GDP vs. 4.9 percent of GDP for comparators’ starting points.
  - Economic openness (exports + imports over GDP): 21.1 percent vs. 46.4 percent of GDP for comparators’ starting points.
  - Simple mean tariff rate: 6.3 percent vs. 5.0 percent for comparators’ starting points.
  - External sector reform index: 0.67 vs. 0.83 for comparators’ starting points.
  - Note: Indonesia’s Hirschman-Herfindahl export product concentration index is very close to the success countries’ initial conditions’ average (no divergence in diversification).
- Governance:
  - Indonesia ranks in the bottom quarter of the distribution across WGI indicators: control of corruption, government effectiveness, political stability, regulatory quality, rule of law, and voice and accountability—below where success countries were at their growth starts.
- Human capital and demographics:
  - Education: Indonesia is in the second quartile (Q2) of the distribution and below average for most education outcome indicators; school enrollment rate cited: 100.6 percent vs. 103.1 percent for comparators (exact figures preserved as presented).
  - Demographics described as offering a “window opportunity” in coming years.
- Economic complexity trend:
  - Indonesia’s economy has gradually become less complex over the last decade, driven by lack of export diversification, yet is slightly more complex than expected given its current income level.

### Empirical approach to prioritize reforms
- The paper uses the 19 success cases as comparators to identify structural features that preceded and accompanied sustained growth trajectories.
- Structural variables and indicators are drawn from existing literature and from indices described in Budina et al. (2023) and include:
  - Governance reform index: simple average of six WGI indices.
  - External sector index: average of four indicators (tariffs, non-tariff barriers, black-market exchange rate, and controls on movement of capital and people).
  - Credit market regulation index: three components (ownership of banks, size of private sector borrowing, interest rate controls).
  - Labor market regulation index: hiring/firing regulation and degree of centralized collective wage bargaining.
  - Business regulation index: average of bureaucracy costs, administrative requirements, and impartial public administration.
  - All Fraser Institute–sourced subcomponents are scaled 0 to 1 (higher values indicate higher degree of freedom).

### Key findings on reform priorities
- The analysis indicates that the following structural areas should be implemented in priority:
  - External sector regulation and economic openness.
  - Governance.
  - Business regulation.
  - Human development (including human capital).
- These areas are expected to:
  - Enhance inclusiveness and support leveling up of living standards across the country.
  - Deliver stronger output effects when reforms are complementary and bundled together.

### Analytical annexes and firm-level work
- The publication includes an Annex I: Data and Results and a separate section on “FINANCING BARRIERS AND PERFORMANCE OF MICRO, SMALL, AND MEDIUM ENTERPRISES” with:
  - Sections A–F covering introduction, enterprise landscape, determinants of access to finance, drivers of export diversification, firm performance and financial access, and conclusions and policy recommendations.
  - Figures and tables including determinants of access to finance, determinants of export diversification, endogenous treatment regressions on firm performance (including SMEs only), and additional estimation results in an appendix.

*Source: IMF staff analysis as presented in the provided content unit.*

### 9.2 years), and adult literacy rate (96 percent, vs. 97 percent). Indonesia also has a lower

### C. A Granular Look into Current Structural Gaps

### Human capital and education
- Share of people aged 25 years or more that have completed at least primary education: "82 percent" (Indonesia) vs. "almost 87 percent" (average success case at the start).
- Adult literacy rate: "96 percent" (Indonesia) vs. "97 percent" (success case average).
- Duration of compulsory education and share of population with at least a Bachelor’s degree: Indonesia exhibits important gaps relative to G20 and OECD EMs (no numeric value given in excerpt).
- Economic Complexity Index (ECI): Indonesia "−0.1" vs. "0.7" (average success case).
- Life expectancy at birth: Indonesia is lower by "10 years" relative to the success countries at the start.
- Human Development Index: below the average of success countries at the start, but still in the UNDP range considered as "high human development".
- Policy emphasis: urgently invest in human capital (education and health), increase education funding, improve learning time (including catching up learning time lost during the pandemic), increase access to early childhood education and broaden secondary education attendance, raise quality of learning (teachers’ accountability and service delivery).

### Labor market and employment quality
- Unemployment rate (as of 2022): "5.9 percent" (Indonesia) vs. "8.2" (average for success countries at the start).
- Labor force participation: "67 percent" (Indonesia) vs. "58 percent" (success country average).
- Share of vulnerable employment (ILO estimate): "50" (Indonesia) vs. "18 percent" (success countries at the start). Note: vulnerable employment = own-account workers + contributing family workers; series part of ILO modeled estimates and to be used with caution.
- Hours worked per employee: "38" (Indonesia) vs. "42" (success countries average).
- Output per worker (GDP at constant international US dollars, PPP): "26,000" for Indonesia in 2022 vs. "around 38,000" on average for the comparator group at the start.
- Finding: Indonesia has strong participation but lower labor productivity and more vulnerable employment than success cases at the start; recommended actions include promoting job quality, social protection, reduce informality, and increase labor market flexibility.

### Infrastructure services and utilities
- Mobile subscriptions per 100 people: "115" (Indonesia) vs. "20" (average starting conditions in the success countries).
- Electricity access: "99 percent" (Indonesia) vs. "97 percent" (success countries average).
- Access to drinking water: "94 percent" (Indonesia) vs. "96 percent" (comparator countries at start).
- Logistics Performance Index: Indonesia lags all comparator medians on the WB's logistics performance index and its infrastructure subindex; gaps across infrastructure, customs, shipping, tracking and tracing, and timeliness.
- Transportation costs: singled out as particularly high (no numeric value in excerpt) and a contributor to headline inflation in 2022/2023.
- Financial inclusion: lower share of people storing money in a financial account or having a bank account; lower private credit to GDP than comparators; Indonesia noted as having one of the largest unbanked populations in the world.

### Trade and economic openness
- Economic openness (sum of exports and imports over GDP): Indonesia significantly lower than in G20 EMs and OECD countries; close to other ASEAN-6 members.
- Non-tariff measures (NTMs): average tariff equivalent of "30 percent" for Indonesia—higher than other countries in the region.
- Trade facilitation performance: weaker than OECD countries; calls for improvements in logistics and trade facilitation to reduce time, costs, and uncertainty of cross-border transactions.

### Economic sophistication and productive capabilities
- Export diversification: economy is diversified by HHI export product concentration, but largest exports remain in low-complexity products (agriculture and minerals).
- Trend: Indonesia’s economic complexity has fallen over time; exports are the least sophisticated within ASEAN-6.
- Linkage: low economic sophistication likely linked to gaps in human capital and lower labor productivity.
- Policy emphasis: deliberate actions to increase education funding, improve learning time and quality to raise human capital and economic sophistication.

### Governance and institutional quality
- Governance gaps: Indonesia lags the OECD median significantly in WDI governance areas—Government Effectiveness, Regulatory Quality, Voice and Accountability, Political Stability, Controlling Corruption and the Rule of Law.
- Finding: strengthening governance and anti-corruption efforts, and enhancing the legal system, would support accountability and business certainty.

### Investment climate and business environment
- Business and credit regulation indices: Indonesia fares relatively well compared to peers but lags OECD median in business regulation liberalization.
- Infrastructure and individual connectivity: gaps in access to drinking water, lower individual connectivity via cell phone subscription (despite high mobile subscription per 100 people noted above in comparisons), and substantial deficits in logistics and infrastructure scores.
- Consequences: these gaps contribute to a less conducive and less attractive business environment.

### Human development, inequality, and inclusiveness
- Demographics: Indonesia has a lower age dependency ratio than average and a stronger demographic dividend proxied by the share of the population aged 15–64 years; a window of opportunity exists to strengthen health and education spending before aging increases dependency.
- Inequality: GINI coefficient similar to success countries’ starting conditions; survey-based GINI appears better than median ASEAN-6 and median G20-EM but may understate regional, gender, formal/informal, and service access inequalities.
- Informality: high informality and vulnerable employment rates; Ma et al. (2023) cited on widespread informality across regions, demographic categories and sectors.
- Policy recommendations: promote job quality and social protection, reduce informality, and increase labor market flexibility to boost productivity and inclusiveness.

### Effects of structural reforms on growth and policy sequencing
- Methodology: local projection method by Jordà (2005), following Budina et al. (2023); reform indicators by area (governance, external sector, business, credit market, labor market), and an additional human development indicator based on the Human Development Index.
- Sample period: regressions run over "1996-2022".
- Definition of major reform: episodes where improvement in an indicator is at least two standard deviations of the distribution of annual changes across the AE and EM sample.
- Key empirical findings:
  - Governance reforms and human development reforms have an immediate, positive, significant effect on real output.
  - External sector regulation and credit market regulation reforms have a more gradual positive effect over the years.
  - Labor market regulation reforms are not found to have a significant effect on employment in this sample.
  - Business regulation reforms: non-significant (and positive) on the whole sample, but the positive impact becomes significant after two years conditional on being an EME.
- Packaged reforms:
  - A package of "first-generation" structural reforms (external sector regulation, governance, business regulation, and human development), characterized by an increase of two standard deviations of the average of the underlying reform indices, could raise output levels by "around 1.5-2 percent" after two years.
  - The effect could rise to "around 3 percent" after four years conditional on implementing all reforms simultaneously.
  - The positive effect of packaged reforms does not significantly depend on past reform progress (below or above median), i.e., packages remain effective even for countries that have already made important reform progress.

### Synthesis and policy guidance
- Main structural gaps to bridge: human capital and education, economic openness and trade facilitation, governance and rule of law, labor vulnerability and informality, logistics and infrastructure, and financial inclusion.
- Timing: current demographics provide a window to invest in health and education upfront before population aging raises dependency ratios.
- Reform prioritization: emphasize governance and human development reforms for immediate output gains, implement external sector and credit market reforms for medium-term gains, and consider packaged reforms for stronger cumulative impact.
- Objective: improvements in horizontal areas (education and human capital, economic openness, labor vulnerability, and governance) should be part of Indonesia’s strategy to durably lift growth and resemble initial conditions of countries that entered strong growth trajectories.

*Source: Excerpt from IMF country analysis on Indonesia (content unit: 1idnea2024002-print-pdf).*

### 21.      These results help guide a possible sequencing of   structural reforms in Indonesia (see

### 21. These results help guide a possible sequencing of structural reforms in Indonesia

### Reform sequencing and priorities
- Reforms on external sector regulation, governance, business regulation and human development-related reforms should be implemented in priority.
- Implementing this group of reforms in tandem would help ensure that any upcoming growth gains are broadly shared.
- These reforms are complementary and mutually reinforcing, with:
  - governance being foundational,
  - business regulation efforts making it easier for firms to operate and expand, and
  - external sector reforms supporting competitiveness.
- All reforms (except on business regulation) would have immediate, significant effects on real output.
- Because some of these reforms will require financing, they will need to be supported by upfront efforts to further expand the fiscal space in the short-term, particularly with domestic revenue mobilization.
- Reforms in other areas, such as credit market regulation reforms, are likely to deliver stronger output effects once the first set of reforms has been implemented. 20

### Implementation and complementary actions
- While the comprehensive Job Creation Omnibus Law was enacted during the pandemic with the objective of improving the investment climate and generate new job opportunities, more is needed to finalize implementation regulations and:
  - streamline regulations further,
  - improve business certainty,
  - ease trade and logistics processes,
  - level up learning outcomes, and
  - enhance social protection.
- Laying the ground to support stronger activity and ensure the growth gains are evenly shared will be crucial to help reach Indonesia’s ambition.

### Table 2 — Indonesia: A Roadmap for Structural Reforms (Short-term / Medium-term)
- A. Fiscal Policy
  - Short-term:
    - 1. Increase domestic tax revenue to bolster fiscal space. This should also endure beyond the short-term.
    - 2. Prioritize high-quality spending supportive of Indonesia's development and closely monitor fiscal risks
    - 3. Increase coverage and adequacy of the social safety net, improve targeting of subsidies.
  - Medium-term:
    - 1. Boost size and quality of health spending and social protection, for a broadly shared growth.
    - 2. Boost education spending, improve learning time and quality to reduce skill mismatch and increase productivity and knowledge capabilities/economic sophistication.
    - 3. Tackle gender inequality, to further increase the labor force and potential growth.
- B. Inclusion and Development
  - (Items integrated into short- and medium-term fiscal and human development priorities above.)
- C. Governance
  - Strengthen governance and anti-corruption framework, improve legal system to support accountability and business certainty.
- D. Trade and Foreign Investment Policy
  - 1. Avoid intensifying restrictive trade policies (including in the IP context) and transition away from NTMs that distort trade and investment decisions and risk international spillovers.
  - 2. Foster openness in trade and FDI, and increase trade facilitation (e.g., to reduce time, cost and uncertainty of crossborder transactions)
  - 4. Better align retail fuel prices with international prices.
  - 5. Enhance the strategic direction of MTFF, and its articulation with the annual budget and long-term plans; ensure the General Government accounts comprehensively reflects fiscal activities.
  - 6. Strengthen SNG's own-revenue sources and PFM, including current and investment spending execution and service delivery capacities
- E. Business climate
  - 1. Reduce regulatory uncertainty, bureaucracy costs and administrative hurdles.
  - 2. Strengthen infrastructure and logistics
- F. Credit Market 1/
  - 1. Develop regulation to strengthen the development of credit scores; establish an oversight framework for the Credit Reporting Systems
  - 2. Reforms to enhance capital market development (e.g., repo market, development of interest rate and forex derivatives).
  - 3. Strengthen regulatory approach to alternative financing models (DFS)
  - 4. Introduce a regulatory green taxonomy and update reporting requirements for firms and financial institutions
  - 5. Expand (direct) access to the fast payment system (BI-FAST) and build on the National Standard for Payment Open API (SNAP) to develop a comprehensive approach to open banking/finance
  - 6. Foster the presence of institutional investors in the domestic market
  - 7. Enhance financial literacy and reduce the digitalization gap across Indonesian provinces
  - 8. Explore ways to scale and utilize the domestic banking system to mobilize climate finance.
  - 1/ See 2024 FSAP Recommendations, Annexes VII and VIII, and Selected Issues Paper on Access to Finance by SMEs.
- G. Labor market
  - 1. Enhance the hiring and firing regulation, assess the extent to which wage determination encourages informality.
  - 2. Tackle labor informality and duality, while ensuring the protection of workers.

### Data and methodological notes (selected)
- For structural variables with data gaps (WGI, Fraser Institute variables, and LPI, among others), gaps are filled either with the latest available value or with linear interpolation to maximize comparator countries.
- For WGI and education data, countries are assigned the first observation for years before 1997 (for WGI data) to the extent the first observation year is close enough to the start of the growth trajectory of the considered country.
- For data not available in 2022 (health and complexity indicators, financial inclusion, and electricity access for example), Indonesia is assigned the latest available value (2021 or 2020) for purposes of comparison.

### Data sources and selected variables (available time periods preserved)
- Gross National Income (World Bank (World Development Indicators)): 1962-2022
- Public and private investment (IMF WEO Database): 1969-2023 (not for all countries)
- Public and private consumption (World Bank (World Development Indicators)): 1960-2022
- Exports of goods and export of services (IMF WEO Database): 1960-2023 (not for all countries)
- Imports of goods and services (World Bank (World Development Indicators)): 1960-2022
- Measure of Aggregate Trade Restrictions (MATR) (IMF AREAER Database): 1999-2021
- IMF External sector reform index (Fraser Institute...): 1970-2021 (not in all years)
- OECD Trade Facilitation Performance Index (OECD): 2017, 2019 and 2022 (Survey-based)
- Taxes on International trade (% of revenues) (World Bank): 1990-2022 (not in all years)
- Tariff rate (simple mean on all products) (World Bank): 1990-2020 (not in all years)
- FDI (share of GDP) (World Bank (World Development Indicators)): 1970-2022
- Hausman Complexity Outlook Index (COI) (Atlas of Economic Complexity (Hausman)): 1995-2021
- Worldwide Governance Indicators (WGI): 1996-2022 (every 2 years at the start)
- IMF Credit market regulation index (Fraser Institute...): 1970-2021 (not in all years)
- Domestic credit to private sector (% of GDP) (World Bank): 1990-2022 (not for all countries)
- Financial inclusion: % of respondents having a bank account (Global Financial Inclusion Database): 2011, 2014, 2017 and 2021
- Infrastructure: Mobile cellular subscriptions (World Bank): 1980-2022
- Infrastructure: Access to electricity (World Bank): 1990-2021
- IMF Business regulation index (Fraser Institute...): 1970-2021 (not in all years)
- Unemployment rate (IMF WEO Database): 1960-2023 (not for all countries)
- Labor Force participation rate (ILO): 1991-2022
- Out. per worker (thousands, const. p., PPP) (ILO): 1991-2024
- Human Development Index (HDI, UNDP): 1990-2022
- Poverty headcount ratio at $2.15 a day (2017 PPP, % of population) (World Bank): 1980-2022 (not for all countries)
- GINI coefficient (World Inequality Database): 1990-2022
- Gender Inequality Index (GII, UNDP): 1990-2022

### Findings on MSMEs: Financing barriers and performance
- Using the World Bank Enterprise Survey (WBES), the analysis finds young, domestically owned firms, and those that face inadequate infrastructure experience significant barriers to financial access.
- Firm age, foreign ownership, and website availability positively affect export diversification.
- Limited financial access adversely affects sales growth and labor productivity, particularly for domestic firms, although managerial experience can mitigate these effects.

### MSMEs in Indonesia: key statistics and challenges
- MSMEs contribute 61 percent of Indonesia's GDP.
- MSMEs absorb 97 percent of the nation's workforce.
- MSMEs represent 99 percent of all business units.
- 67 percent of MSMEs operate within the informal sector.
- Indonesia's MSMEs contribute only 15.8 percent to exports.
- These outcomes reflect barriers in human capital, logistics, regulatory complexity, market access, and financing.

*International Monetary Fund — Indonesia Staff Report (selected chapter and annex material)*

### 3.      Access to finance for MSMEs lags peers and is a primary hurdle for their development

### 3.      Access to finance for MSMEs lags peers and is a primary hurdle for their development

### Overview and key quantitative findings
- Higher borrowing costs than peer countries and uneven distribution of financing across sectors exacerbate access challenges, leaving a substantial credit gap with "47 percent of demand unmet" (EY Parthenon, 2023).
- State-owned banks, particularly Bank Rakyat Indonesia, dominate lending to MSMEs, with loan disbursements concentrated in Java.
- MSME constraints reported: high interest rates, lack of collateral, low financial literacy, complex application processes, and frequent rejected proposals (Statistics Indonesia, 2019).
- Financial institutions struggle to assess MSMEs' creditworthiness; MSMEs show low participation in training programs and poor financial management (Ministry of Trade of Indonesia, 2019).
- Market orientation and firm activity:
  - "95 percent of Indonesian firm’s products are sold in the domestic market."
  - Retail services represent "about 45 percent of the economy."
  - Java, particularly Jakarta, accounts for "almost one-sixth of all non-agricultural firms in Indonesia."
- WBES survey coverage and timing:
  - WBES took place in Indonesia in 2009, 2015, and 2023 with "1,444", "1,320", and "2,955" firms respectively.
- SME demographics and behavior:
  - SMEs in the sample have been in operation "for 15-18 years on average."
  - Foreign ownership among SMEs is "1-2 percent" versus "about 7 percent" for large firms.
  - R&D and capital spending:
    - Small firms’ expenditure on machinery, vehicles, and equipment is "136 percent" of their gross revenue.
  - Financial inclusion improvements:
    - Proportion of small firms with a checking or savings account increased from "43 percent in 2009" to "almost 76 percent in 2023."
    - Only "6.3 percent" of small firms have an overdraft facility.
    - About "35 percent" of small firms report insufficient capital; among these, complex procedures are cited as a reason not to apply for loans or credit.
- COVID-19 impact:
  - Export-oriented firms’ weighted average sales growth in the sample stood at "-7.5 percent", while non-exporters were at "1.5 percent".
  - Small firms suffered most during COVID-19; firms hired more employees from 2019 to 2021 resulting in negative productivity growth; firms’ performance improved broadly from 2020 to 2022.

### Indonesian enterprises landscape (WBES-based)
- Survey design and stratification:
  - WBES samples are randomly selected with three levels of stratification: size, industry classification, and region.
  - Firm size in WBES is measured by full-time equivalent workers (permanent plus seasonal on full-time scale), with a convention that two full-time seasonal workers working for 6 months equal one full-time permanent worker.
- Firm characteristics:
  - Small and medium-sized firms are largely sole proprietorships.
  - SMEs have lower educational attainment, offer less on-the-job training, and managers have less experience than in medium and large firms.
  - More small firms are managed and fully or partly owned by females compared to medium and large firms.
- Governance:
  - Evidence indicates gratification payments and bribery are more prevalent among large firms compared to small and medium firms, though this may reflect informality and under-reporting among smaller firms.

### Determinants of firms’ access to finance (ordered/binary logit results and interpretation)
- Dependent variable:
  - "Access to finance" derived from ordinal responses to the question: To what degree is access to finance an obstacle? Responses range from "No obstacle" (0) to "Very severe obstacle" (4).
- Model approach:
  - Ordered logit (0 to 4) and binary logit (0/1) estimated by maximum pseudo-likelihood.
  - Explanatory variables include firm age, size, ownership, top manager characteristics, infrastructure, and others following Hosny (2020) and Islam and Meza (2023).
  - Causality interpretation limited due to cross-sectional data.
- Main empirical findings (Table 1 highlights and exact coefficients where reported):
  - Firm age:
    - Mature firms (> 20 years) tend to be less likely to report access to finance as an obstacle, with coefficients including "-0.400*" and "-0.558**" in specified models.
    - Young firms (<= 5 years) show negative coefficients (e.g., "-0.238", "-0.168", "-0.325"), but these are statistically insignificant across specifications.
  - Foreign ownership:
    - Some evidence of easier access to finance; coefficients reported such as "-1.305**" and "-1.486*" in columns 3-4.
  - Infrastructure and digital presence:
    - Firms that experienced power outages are associated with reporting access to finance as an obstacle; coefficients include "0.774***", "0.500*", "0.917***", "0.738***".
    - Firms with a website are associated with lower perception of access to finance as an obstacle; coefficients include "-0.445**", "-0.810***", "-0.780***", "-1.199***".
  - Credit constraint indicator:
    - Positive association with reporting access to finance as an obstacle; coefficient examples "0.644**", "0.729**".
  - Firm size:
    - Controlling for firm characteristics, no clear significant difference in perception of financial access by firm size across specifications; positive relationships between firm size and characteristics (age, foreign ownership, website) suggest larger firms are less likely to report access to finance as a constraint.
  - Robustness:
    - Limiting estimation to SMEs does not significantly change results (reference to Table AI.1).
- Model notes:
  - Standard errors reported in parentheses; significance levels: "* p<0.10, ** p<0.05, *** p<0.01".
  - Observations reported across model columns (as printed): e.g., "1763", "1763", "1763", "1600", "1600", "1763", "1680", "1600" (as in Table 1).

### Drivers of firm export diversification (logit analysis and findings)
- Dependent variable:
  - Export diversification = export orientation × indicator of diversification (1 for R&D or process improvement in last year; otherwise 0), following Hosny (2020).
- Key associations (Table 2 highlights and exact coefficients where reported):
  - Firm age:
    - U-shaped relationship: both young (<= 5 years) and mature (> 20 years) firms are more likely to pursue export diversification compared to growth-phase firms.
    - Coefficients for young firms: "4.869***", "5.105***", "8.022***".
    - Coefficients for mature firms: "2.838***", "3.199***", "2.626**".
    - Quadratic specification: log age and log age squared coefficients include "-3.816*" and "0.740**" (and other variants).
  - Foreign ownership:
    - Strong positive relationship with export diversification; coefficients reported: "3.900***", "4.820***", "8.790***", "3.189***", "4.297***", "7.004***", "3.793***".
  - Website presence:
    - Positive association with export diversification; coefficients include "4.146***", "3.993*", "6.781***", "3.737***", "4.705**", "7.512***", "4.599*".
  - Banked firms:
    - Weak evidence that establishment's checking or savings account is positively associated with export diversification; coefficients include "0.776", "1.180", "1.598", "2.132*", "2.803*", "1.880".
  - Access to finance as major constraint:
    - The indicator does not show a clear significant relationship with export diversification; coefficients include "-1.921", "-2.148", "2.421", "-3.146", "-2.861", "2.269", "-2.884".
  - Robustness:
    - Limiting the estimation sample to SMEs does not significantly change these results (reference to Table AI.2).
- Model notes:
  - Standard errors in parentheses; significance levels as reported "* p<0.10, ** p<0.05, *** p<0.01".
  - Observations listed in Table 2 columns: e.g., "1785", "785", "754", "790" (as printed).

### Firm performance and financial access (causal estimation approach and interpretation)
- Research question:
  - Investigate impact of limited access to finance on firm performance measured by annualized growth rates of nominal and real sales, productivity (real sales per employee), and employment over the last two years.
- Performance regression specification:
  - Y_irst = b1 AccessToFinance_irst + B'X_irst + a_s + a_r + a_t + e_irst
  - Y_ist measures include annualized growth rate of nominal and real sales, productivity, and employment.
  - Time dimension accounts for interview timing (performance relevant year either 2022 or 2021, compared to 2020 or 2019); time fixed effect a_t included.
- Endogeneity concerns and estimator:
  - Perception-based treatment (reporting access to finance as "major" or "very severe") may be endogenous (reverse causality, selection).
  - Endogenous treatment effects estimator (Heckman 1976, 1978; Cameron and Trivedi 2005; Wooldridge 2010) used to mitigate selection bias.
  - Instrumental variable: region × sector average value of AccessToFinance (AccessToFinance_rs) added in first-stage to isolate exogenous variation following Ayyagari et al. (2006).
  - Estimation done by maximum likelihood.
- Caution:
  - Even with the endogenous treatment effects model, interpretation of causality is cautious if endogeneity arises beyond the instrument's scope.

*Italic: IMF staff summary of chapter: 3. Access to finance for MSMEs lags peers and is a primary hurdle for their development (from WBES-based analysis and econometric results as presented in the chapter).*

### 18.      The estimation results suggest that firms with better financial access likely have a

### 1idnea2024002-print-pdf - 18.      The estimation results suggest that firms with better financial access likely have a

### Key findings on financial access and firm performance
- Firms that report access to finance as a major constraint experience lower (annualized) nominal sales growth by 17 percentage points (column 1-2).  
- The estimate on sales growth remains around 17 percentage points after inflation adjustment (column 3-4).  
- The negative impact of financial access constraints is mainly channeled through loss of labor productivity (real sales per employee), with the coefficient of financial obstacles at 24 percentage points (column 5-6).  
- The coefficient on employment is negative but insignificant (column 7-8).  
- The negative relationship between constrained financing and real sales and productivity is stronger in domestic firms; foreign-owned firms (≥ 10 percent) appear less sensitive (Figure 1 left panel).  
- Manager experience mitigates the negative impact of constrained access to finance on real sales: the size of the negative relationship (black line) decreases over years of manager experience, and the coefficient becomes insignificant in 25 years of manager experience, with 10 percent of significance level. Manager experience benefits employment (orange line), resulting in no significant change in loss of productivity (green line) (Figure 1 right panel).

### Regression results (selected coefficients from Table 3)
- Access to finance as major constraints (Y/N):  
  - Nominal Sales (columns 1-2): -16.945**, -16.571** (standard errors: (7.353), (7.478))  
  - Real Sales (columns 3-4): -17.193**, -16.761** (standard errors: (7.637), (7.765))  
  - Productivity (columns 5-6): -24.158**, -24.545** (standard errors: (10.805), (10.965))  
  - Employment (columns 7-8): -7.382, -7.266 (standard errors: (5.906), (5.893))  
- Export oriented (Y/N): -10.287*, -9.867*, -10.453*, -9.856* (standard errors: (5.678), (5.141), (5.674), (5.131))  
- Export oriented * Improved methods: 40.651***, 40.989***, 48.048***, 26.387 (standard errors: (9.881), (9.945), (12.119), (22.806))  
- Young (<= 5 years) firm (Y/N): -2.176, -2.068, -2.188, -2.059 (sales); -19.751**, -19.944** (productivity); 17.755**, 17.854** (employment) (standard errors reported in table)  
- Foreign ownership (Y/N): 1.438, 1.810, 1.438, 1.906 (sales); 3.677, 1.726 (productivity); -11.601***, -10.067** (employment) (standard errors reported in table)  
- Log of manager experience years: -0.973, -0.925, -1.006, -0.962 (sales); -2.318, -2.157 (productivity); 2.379*, 2.291 (employment) (standard errors reported in table)  
- Last completed fiscal year: 14.879***, 15.063***, 19.089***, 19.277***, 15.015***, 14.807***, 5.389, 5.686 (standard errors reported in table)

### Endogeneity and statistical diagnostics
- Estimated correlation between treatment-assignment errors and outcome errors, Rho, is positive in all models. Reported Rho values (Table 3): 0.420, 0.408, 0.433, 0.420, 0.649, 0.655, 0.252, 0.252.  
- LR test for Rho=0 and reported p-values (Table 3): LR test statistics 3.168, 2.901, 2.985, 2.723, 5.006, 5.009, 4.803, 4.668 with p-value 0.075, 0.089, 0.084, 0.099, 0.025, 0.025, 0.028, 0.031 respectively.  
- Table AI.3 (first-stage regression) shows credit constrained (Y/N) coefficient 0.124, 0.129, 0.122, 0.128, 0.159, 0.165, 0.103, 0.106 (standard errors reported in table).  
- Without addressing endogeneity, OLS estimates are generally lower but still significantly negative for sales; productivity effects become insignificant (Table AI.4 note).

### Robustness: SMEs-only sample (Table 4)
- Access to finance as major constraints (Y/N) in SMEs: -18.362**, -17.392**, -18.625**, -17.597**, -24.554**, -24.510**, -8.299, -8.188 (standard errors reported in table).  
- Export oriented (Y/N) in SMEs: -23.526***, -18.857***, -23.551***, -18.770***, -16.702**, -7.439, 11.296, 11.601 (standard errors reported in table).  
- Export oriented * Improved methods (SMEs): 50.480***, 50.781***, 46.306***, 23.604 (standard errors reported in table).  
- Export oriented * R&D (SMEs): -35.627***, -36.541***, -37.738***, -17.896* (standard errors reported in table).  
- Rho values in SMEs sample (Table 4): 0.457, 0.429, 0.471, 0.442, 0.658, 0.655, 0.302, 0.300. LR test statistics and p-values in Table 4 are reported (3.311, 2.842, 3.169, 2.686, 5.174, 4.800, 4.482, 4.366 with p-value 0.069, 0.092, 0.075, 0.101, 0.023, 0.028, 0.034, 0.037 respectively).  
- Interpretation: Limiting the sample to SMEs does not significantly change the main results, but export orientation coefficients for sales are larger in magnitude (around -20 percentage points in SMEs sample) and exporter’s R&D effort coefficients turn significantly negative.

### Determinants of access to finance and export diversification (Appendix Tables)
- Determinants of access to finance (SMEs only, Table AI.1): Website (Y/N) shows negative and significant coefficients in several specifications: -0.447**, -0.842***, -0.386, -0.810***, -0.489, -1.113***, -0.627*, -1.331*** (standard errors reported). Experienced power outage (Y/N) positive and significant in some specifications: 0.787***, 0.479, 0.940***, 0.746***, etc. Mature (> 20 years) firm (Y/N) shows negative coefficients including -0.395*, -0.553** in some specifications.  
- Determinants of export diversification (SMEs only, Table AI.2): Young (<= 5 years) firm (Y/N) positive and significant: 5.266***, 5.487***, 11.084**. Foreign ownership (Y/N) strongly positive and significant across specifications: 4.385***, 5.816***, 35.901***, 3.228**, 5.801***, 5.989***. Website (Y/N) positive and significant in several specifications: 4.105***, 4.689*, 5.866, 4.352**, 4.667, 4.868*.

### Interpretation of control variables and contextual observations
- Coefficients for control variables align with expectations: export-oriented firms show negative coefficients for sales, likely reflecting vulnerability to the pandemic shock.  
- Export diversification efforts, especially process improvement, are associated with better performance mainly through enhanced productivity (column 6).  
- Young and mature firms record lower productivity growth compared to growth-phase firms; young firms’ employment tends to grow faster than other firms, partly due to small size. Sales growth does not show significant differences over firm age.  
- Foreign ownership is negatively associated with employment, possibly reflecting heterogenous responses of foreign-owned firms to the pandemic shock.  
- Strong evidence that growth rates for the period 2020-2022 are much higher than for 2019-2021 in terms of both sales and productivity (columns 1-6), reflecting the impact of COVID-19 in the earlier window.

### Conclusions and policy recommendations (Section F)
- Main conclusions: Young, domestically owned firms, and firms facing inadequate infrastructure experience significant barriers to financial access. Limited financial access adversely affects sales growth and labor productivity, particularly for domestic firms, while managerial experience can mitigate these effects. Firm age, foreign ownership, and website availability positively affect export diversification.  
- Policy recommendations:  
  - Establish a national credit reporting system strategy and simplify registration for the collateral registry.  
  - Improve the ease of doing business to stimulate foreign participation.  
  - Improve connectivity through infrastructure and digitalization.  

*Source: Indonesia chapter, INTERNATIONAL MONETARY FUND (content from 1idnea2024002-print-pdf).*

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_Source: https://www.imf.org/-/media/files/publications/cr/2024/english/1idnea2024002-print-pdf.pdf_