## Annex I. Data Sources

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### I. Introduction and objectives
- The informal economy represents a significant share of output and employment across North Africa:
  - "Informal activities account for about one third of GDP, on average."
  - "Informal employment accounts for nearly two thirds of total employment (see IMF, 2022)."
- Drivers of informality noted: flexibility, taxation, regulatory impediments (Maloney 2004; Loayza, Oviedo, and Servén 2006).
- Key research questions:
  - How does informality affect the response of the labor market to output fluctuations?
  - How does employment informality change during economic upswings and downswings?
  - Have the 2020 covid recession and post-pandemic recovery been different?
- Methods: regression-based estimates, correlation analysis, event studies, Okun’s law framework.

### II. Labor markets in North Africa — stylized facts and overview
- High and stable unemployment:
  - "Unemployment rates in North Africa have been some of the highest in the world over the past two decades, averaging nearly 11 percent in 2019 (Figure 16)."
- Low participation and employment-to-population ratios:
  - "The average labor force participation rate has remained broadly stable over the past decade, averaging about 45 percent in" [text ends].
- Female labor force participation and informality:
  - Female labor force participation rate in the region: about 22 percent in 2019.
  - Average female labor force participation in EMDEs: about 50 percent.
  - Informal employment (proxied by share of self-employed in total employment) in North Africa, 2019: about 40 percent of total employment.
  - Average self-employment in EMDEs: 50 percent of total employment.
- Labor market indicators have shown little variability over the business cycle; informal employment remained relatively high despite a downward trend over two decades.

### III. Informal employment and Okun’s law — framework and main findings
- Okun’s gap specification: ut − ut* = βg(yt − yt*) + εt.
- Okun’s change specification: ut − ut−1 = α + βc(yt − yt−1) + ωt.
- Trend computed with a Hodrick-Prescott filter with smoothing parameter of 100.
- Main findings:
  - Okun’s coefficients are statistically significant and negative for most country groups.
  - Okun’s coefficients are lower (unemployment responds less to output fluctuations) in countries with high informality compared with countries with low informality.
  - Okun’s coefficient in advanced economies is about 3 and 30 times larger than that in emerging markets and LICs, respectively.
- North Africa-specific estimates:
  - Mauritania: labor market "barely responds" to output.
  - Morocco: a 1 percentage point increase in output above its trend → a 0.1 percentage point reduction in cyclical unemployment.
  - Algeria, Egypt, and Tunisia: a 1 percentage point deviation of output above its trend → a 0.4–0.5 percentage point decline in cyclical unemployment.

### IV. Determinants of Okun’s coefficients — selected regression highlights
- Labor market informality is negatively correlated with Okun’s coefficient; a larger degree of employment informality contributes to weakening Okun’s coefficient.
- Quality of institutions (legal system) has a positive association with responsiveness.
- Labor market regulation variable not statistically significant in multivariate regressions.
- Selected regression coefficients (Table 1, preserved exactly):
  - Labor market informality: -0.00387*** (column (1)); -0.00309*** (column (2)).
  - Legal system: 0.0728*** (column (5)); 0.0760*** (column (8)).
  - GDP per capita: 0.00327*** (column (4)); -0.00264** (column (6)).
  - Public wage bill, % total expenditures: -0.00507*** (column (7)).
  - Observations and fit examples:
    - Observations: 150 (column (1)); 136 (column (2)); 116 (column (9)).
    - R-squared: 0.265 (column (1)); 0.023 (column (2)); 0.438 (column (9)).
- Robust standard errors in parentheses; significance: *** p<0.01, ** p<0.05, * p<0.1.

### V. Informal employment and the business cycle — dynamics and elasticities
- Countercyclicality:
  - Informal employment appears more countercyclical in economies with higher informality.
  - Simple correlation: informal employment vs cyclical output = –0.3 in medium- and high-informality countries (compared with –0.1 for low-informality countries).
  - Within North Africa, informal employment is countercyclical in Algeria, Mauritania, and Morocco.
- Elasticities and country examples:
  - Elasticity of informal employment to cyclical output is larger (in absolute value) in the medium- and high-informality groups.
  - In Mauritania and Morocco, the share of informal employment can make overall employment countercyclical.
- Event-study evidence (downswing vs upswing):
  - During downturns:
    - Informal employment growth exceeded its long-run trend by about 0.6 percentage points in medium- and high-informality groups.
    - The rise in unemployment is more limited in these countries compared with low-informality ones.
  - During upturns:
    - Informal employment falls modestly below its long-run trend by about 0.3 and 0.1 percentage points in high- and medium-informality groups, respectively.
    - Asymmetric behavior consistent with incomplete return to formality and potential hysteresis.
- Sectoral dynamics:
  - Employment is generally procyclical across sectors except agriculture (and non-market services).
  - During downturns, agricultural employment in high- and medium-informality groups behaved countercyclically.
  - During upturns, agricultural employment falls only slightly below trend in high- and medium-informality groups.

### VI. The pandemic recession (2020) and post-pandemic recovery (2021)
- Pandemic recession (2020):
  - Contrary to past recessions, informality did not provide a buffer in 2020; informal employment contracted sharply in countries with relatively higher informality, including North Africa.
  - Causes: lockdowns and social-distancing measures; high-contact services disproportionately affected; small informal firms had limited access to support.
- Post-pandemic recovery (2021):
  - High informality countries:
    - Informal employment rebounded strongly in 2021 as containment measures were lifted.
    - Rebound reflected transitions from outside the labor force into informal employment and a strong increase in labor force participation; formal employment also rebounded.
    - Sectoral drivers: services, and to a lesser extent agriculture.
  - Medium informality countries (including North African economies):
    - Informal employment recovery was weak in 2021 and fell slightly below long-run trend.
    - Formal employment and labor force participation rebounded sharply.
    - Interpretation: formal firms in medium-informality countries may have weathered the crisis better because of access to government support measures (tax reliefs, credit guarantees, loan payment facilities).
    - In North Africa, formal job recovery was very sluggish, indicating risks of labor market hysteresis due to labor and product market rigidities.
- Overall implication:
  - The pandemic and subsequent shocks presage persistence of a large informal sector in medium- and high-informality countries, potentially halting or reversing the long-run downward trend in informality.

### VII. Policy implications and recommendations
- Short- to medium-term:
  - Extend social safety nets to informal workers using targeted cash transfer programs, leveraging financial innovation and digitalization (examples noted for Egypt, Morocco, and Tunisia).
- Medium- to long-term priority: encourage formalization through a tailored policy package, including:
  - Reducing burdens from cumbersome government regulations and distortionary taxation.
  - Strengthening the quality of governance.
  - Removing unnecessary rigidities in labor market codes.
  - Invigorating private sector activity.
  - Facilitating access to financial services.
- Rationale:
  - Formalization can improve labor market responsiveness to growth, raise productivity, and reduce persistence of informal employment traps and hysteresis.

### VIII. Data sources, sample and scope (Table A.1 and overview)
- Primary data sources:
  - IMF’s World Economic Outlook database
  - ILO’s ILOSTAT and modeled estimates
  - World Bank’s World Development Indicators
  - Fraser Institute’s Economic Freedom of the World
- Database comprises 155 countries, including advanced, emerging market economies, and developing and low-income countries.
- Country sample determined by availability of continuous annual data for real GDP, the unemployment rate and self-employment.
- Time period: 1991-2019.
- Available data for 2020 and 2021 is added for the analysis of the Covid shock.
- Indicator sources (preserved exactly as listed):
  - Real GDP — IMF, World Economic Outlook database
  - GDP per capita, PPP (constant 2017 international $) — IMF, World Economic Outlook database
  - Share of agriculture value added in GDP — World Development Indicators database
  - Share of manufacturing value added in GDP — World Development Indicators database
  - Public wages (% of total expenditure) — World Development Indicators database
  - Population, total (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
  - Population ages 15+, total (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
  - Population ages 15-64, total (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
  - Population, male (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
  - Population ages 15+, male (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
  - Population ages 15+, female (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
  - Labor force, total (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
  - Labor force, male (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
  - Labor force, female (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
  - Labor force participation rate, total (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
  - Labor force participation rate, male (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
  - Labor force participation rate, female (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
  - Employment, total (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
  - Employment, male (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
  - Employment, female (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
  - Employment rate, total (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
  - Employment rate, male (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
  - Employment rate, female (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
  - Self-employed, male (% of male employment) (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
  - Self-employed, female (% of female employment) (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
  - Self-employed, total (% of total employment) (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
  - Hiring and firing regulations — World Economic Forum, Global Competitiveness Report
  - Administrative requirements — World Economic Forum, Global Competitiveness Report
  - Protection of property rights — World Economic Forum, Global Competitiveness Report

*IMF staff compilation.*

### Annex I. Data Sources ..................................................................................................

### Annex I. Data Sources

### I. Introduction
- The informal economy represents a significant share of output and employment across North Africa:
  - "Informal activities account for about one third of GDP, on average."
  - "Informal employment accounts for nearly two thirds of total employment (see IMF, 2022)."
- Drivers of informality noted: flexibility, taxation, regulatory impediments (Maloney 2004; Loayza, Oviedo, and Servén 2006).
- Informal sector is main income source in less developed economies with large agricultural sectors and high shares of unskilled workers (World Bank, 2019).
- Literature on informality and business cycle:
  - Some studies: informal employment rises during downturns, providing a buffer for displaced formal workers (Loayza and Rigolini 2011; Ohnsorge and Yu 2021).
  - Other studies using output-informality indicators find informality behaves procyclically (Ferreira-Tiryaki 2008; Ohnsorge and Yu 2021).
- Paper objectives and questions:
  - How does informality affect the response of the labor market to output fluctuations?
  - How does employment informality change during economic upswings and downswings?
  - Have the 2020 covid recession and post-pandemic recovery been different?
- Methods employed: regression-based estimates, correlation analysis, event studies, Okun’s law framework.
- Key empirical findings summarized:
  - Labor market response to business cycle fluctuations is relatively more muted in countries with relatively higher informality levels, like North African economies.
  - Informality remains an important determinant of Okun’s coefficients even after controlling for other structural factors.
  - Regression results find evidence that informal employment is more countercyclical in economies with a large share of employment informality (medium- and high-informality).
  - Event studies confirm informal employment is countercyclical and acts as a buffer during downturns in countries with relatively higher informality (including North African economies).
  - Contrary to past recessions, informality did not provide much of a buffer to the 2020 pandemic shock: "Informal employment contracted sharply in countries with relatively higher informality, including those in North Africa, as informal labor-intensive sectors were hit harder than in the past."
  - Role of informality during upturns is less straightforward:
    - Informal employment tends to fall only modestly during upturns in economies with relatively large informal sectors, consistent with incomplete return to formal jobs after downturns.
    - During the post-pandemic recovery, informal employment followed a similar pattern in medium informality countries (like North African economies), while it rebounded in high informality countries.

### II. Labor markets in North Africa: High unemployment and low cyclicality
- Overview of key labor market characteristics across North Africa over the past two decades; informal employment expected to play an important role in adjustment.
- Stylized facts:
  - High and stable unemployment rates:
    - "Unemployment rates in North Africa have been some of the highest in the world over the past two decades, averaging nearly 11 percent in 2019 (Figure 16)."
  - Low participation and employment-to-population ratios:
    - "The average labor force participation rate has remained broadly stable over the past decade, averaging about 45 percent in" [text ends].
- Implication: Given the large informal sector, informality should be expected to influence labor market responses to cyclical shocks in the region.

*IMF Working Papers — Informality, Labor Market Dynamics, and Business Cycles in North Africa (excerpts contained in source PDF)*

### 2019. The low overall participation rate in the region is largely due to the much lower female labor force

### Informality, Labor Market Dynamics, and Business Cycles in North Africa

### Labor market overview
- Female labor force participation rate in the region: about 22 percent in 2019 compared with an average of about 50 percent in emerging markets and developing economies (EMDEs).
- Female and youth unemployment rates have remained stubbornly high across the region, indicating elevated structural unemployment.
- Labor market indicators have shown little variability over the business cycle:
  - Employment rates expanded slightly during the pre–global financial crisis period, remained resilient during the crisis (except in Tunisia), and were broadly steady in the prepandemic period.
  - Unemployment rates fell during the precrisis period and have shown little variation since, except in a few countries during the crisis (mainly Egypt and Tunisia).
  - Labor force participation rates have been on a slight downward trend in most countries.
- Informal employment (proxied by share of self-employed in total employment) remained relatively high in North Africa, representing about 40 percent of total employment in 2019.
  - This level is lower than the average for EMDEs, where self-employment represents on average 50 percent of total employment.
  - Despite a downward trend over the past two decades, informality remains significant.

### Informal employment and Okun’s law
- Framework:
  - Gap specification: ut − ut* = βg(yt − yt*) + εt.
  - Change specification: ut − ut−1 = α + βc(yt − yt−1) + ωt.
  - Benchmark uses the gap specification; trend computed with a Hodrick-Prescott filter with smoothing parameter of 100.
- Main finding:
  - Okun’s coefficients are statistically significant and negative for most country groups.
  - Okun’s coefficients are lower (unemployment responds less to output fluctuations) in countries with high informality compared with countries with low informality.
  - Okun’s coefficient in advanced economies is about 3 and 30 times larger than that in emerging markets and LICs, respectively.
- North Africa specific estimates:
  - Mauritania: labor market “barely responds” to output.
  - Morocco: a 1 percentage point increase in output above its trend corresponds to a 0.1 percentage point reduction in cyclical unemployment.
  - Algeria, Egypt, and Tunisia: on average, a 1 percentage point deviation of output above its trend is associated with a 0.4–0.5 percentage point decline in cyclical unemployment (broadly comparable with the average for advanced economies).
- Determinants of Okun’s coefficients (empirical results):
  - Labor market informality is negatively correlated with Okun’s coefficient; a larger degree of employment informality contributes to weakening Okun’s coefficient.
  - Quality of institutions (legal system) has the expected positive association with responsiveness.
  - Labor market regulation variable does not appear statistically significant in explaining Okun’s coefficient in the multivariate regressions.
  - Regression highlights (Table 1, selected results):
    - Labor market informality coefficient: -0.00387*** (column (1)); -0.00309*** (column (2)).
    - Legal system coefficient: 0.0728*** (column (5)); 0.0760*** (column (8)).
    - GDP per capita: 0.00327*** (column (4)); -0.00264** (column (6)).
    - Public wage bill, % total expenditures: -0.00507*** (column (7)).
    - Observations and fit examples:
      - Observations: 150 (column (1)); 136 (column (2)); 116 (column (9)).
      - R-squared: 0.265 (column (1)); 0.023 (column (2)); 0.438 (column (9)).
    - Robust standard errors in parentheses; significance: *** p<0.01, ** p<0.05, * p<0.1.

### Informal employment and the business cycle
- Countercyclicality:
  - Informal employment appears more countercyclical in economies with higher informality.
  - Simple correlation: informal employment vs cyclical output = –0.3 in medium- and high-informality countries (compared with –0.1 for low-informality countries).
  - Within North Africa, informal employment is countercyclical in Algeria, Mauritania, and Morocco.
- Elasticities and regressions:
  - The elasticity of informal employment to cyclical output is quantitatively larger (in absolute value) in the medium- and high-informality groups.
  - In Mauritania and Morocco, the share of informal employment can make overall employment countercyclical (a feature generally seen only in high-informality group countries).
- Event study findings (downswing vs upswing):
  - During downturns, informal employment tends to rise in medium- and high-informality groups, offsetting contraction in formal employment.
    - Informal employment growth exceeded its long-run trend by about 0.6 percentage points in medium- and high-informality groups during downturns.
    - The rise in unemployment is more limited in these countries compared with low-informality ones.
  - During upturns, informal employment falls only modestly below its long-run trend (about 0.3 and 0.1 percentage points in high- and medium-informality groups, respectively), less than the increase during downswings.
    - This asymmetric behavior is consistent with incomplete return to formality and potential hysteresis in labor markets.
- Sectoral dynamics:
  - Employment is generally procyclical across sectors except agriculture (and non-market services).
  - During downturns, agricultural employment in high- and medium-informality groups behaved countercyclically.
  - During upturns, agricultural employment falls only slightly below trend in high- and medium-informality groups, consistent with partial non-return to formal employment.

### The pandemic recession and post-pandemic recovery
- Pandemic recession (2020):
  - Contrary to past recessions, informality did not provide a buffer in 2020; informal employment contracted sharply in countries with relatively higher informality, including North Africa.
  - Causes: lockdowns and social-distancing measures shut down many formal and informal businesses; high-contact services were disproportionately affected; small informal firms had limited access to support.
  - Example: market services employment contracted where informality is widespread.
- Post-pandemic recovery (2021):
  - High informality countries: informal employment rebounded strongly in 2021 as containment measures were lifted.
    - Rebound partly reflected transition from outside the labor force into informal employment and strong increase in labor force participation.
    - Formal employment also rebounded with transitions from outside the labor force into formality.
    - Sectoral drivers: services, and to a lesser extent agriculture.
  - Medium informality countries (including North African economies): informal employment recovery was weak in 2021 and fell slightly below long-run trend; formal employment and labor force participation rebounded sharply.
    - Interpretation: formal firms in medium-informality countries may have weathered the crisis better because of access to government support measures (tax reliefs, credit guarantees, loan payment facilities).
    - In North Africa, formal job recovery was very sluggish, indicating risks of labor market hysteresis possibly due to labor and product market rigidities.
- Overall implication:
  - The pandemic and subsequent shocks (including the economic fallout of Russia’s war in Ukraine) presage persistence of a large informal sector in medium- and high-informality countries, potentially halting or reversing the long-run downward trend in informality.

### Policy implications and recommendations
- Short- to medium-term lessons from the pandemic:
  - Social safety nets can be extended to informal workers using targeted cash transfer programs, leveraging financial innovation and digitalization (examples noted for Egypt, Morocco, and Tunisia).
- Medium- to long-term priority: encourage formalization through a tailored policy package, including:
  - Reducing burdens from cumbersome government regulations and distortionary taxation.
  - Strengthening the quality of governance.
  - Removing unnecessary rigidities in labor market codes.
  - Invigorating private sector activity.
  - Facilitating access to financial services.
- Rationale:
  - Formalization can improve labor market responsiveness to growth, raise productivity, and reduce the persistence of informal employment traps and hysteresis.

### Key statistics and parameter estimates (preserved exactly as in source)
- Female labor force participation rate in North Africa in 2019: about 22 percent.
- Average female labor force participation in EMDEs: about 50 percent.
- Informal employment (self-employment) in North Africa, 2019: about 40 percent of total employment.
- Average self-employment in EMDEs: 50 percent of total employment.
- Morocco: a 1 percentage point increase in output above its trend → 0.1 percentage point reduction in cyclical unemployment.
- Algeria, Egypt, Tunisia: a 1 percentage point deviation of output above its trend → 0.4–0.5 percentage point decline in cyclical unemployment.
- Okun’s coefficient in advanced economies is about 3 and 30 times larger than that in emerging markets and LICs, respectively.
- Correlation between informal employment and cyclical output in medium- and high-informality countries: –0.3 (compared with –0.1 for low-informality countries).
- Event-study: informal employment growth exceeded its long-run trend by about 0.6 percentage points in medium- and high-informality groups during downturns; informal employment falls modestly below trend during upswings by about 0.3 and 0.1 percentage points in high- and medium-informality groups, respectively.
- Selected regression coefficients (Table 1):
  - Labor market informality: -0.00387*** (column (1)); -0.00309*** (column (2)).
  - Legal system: 0.0728*** (column (5)); 0.0760*** (column (8)).
  - Public wage bill, % total expenditures: -0.00507*** (column (7)).
  - Observations and R-squared examples: Observations 150 (column (1)); R-squared 0.265 (column (1)); Observations 116 (column (9)); R-squared 0.438 (column (9)).
- Event study cutoffs: 1.5 standard deviations in advanced economies; 1 standard deviation in emerging markets and LICs.

*IMF Working Paper: Informality, Labor Market Dynamics, and Business Cycles in North Africa (2019 content excerpt).*

### Annex I. Data Sources

### Annex I. Data Sources

### Overview
- Primary data sources:
  - IMF’s World Economic Outlook database
  - ILO’s ILOSTAT and modeled estimates
  - World Bank’s World Development Indicators
  - Fraser Institute’s Economic Freedom of the World
- Database comprises 155 countries, including advanced, emerging market economies, and developing and low-income countries.
- Country sample is dictated by data availability—the number of countries with continuous annual data for real GDP, the unemployment rate and self-employment.
- Time period: 1991-2019.
- Available data for 2020 and 2021 is added for the analysis of the Covid shock.
- Table A.1. Data sources

### Indicator sources (Table A.1)
- Real GDP — IMF, World Economic Outlook database
- GDP per capita, PPP (constant 2017 international $) — IMF, World Economic Outlook database
- Share of agriculture value added in GDP — World Development Indicators database
- Share of manufacturing value added in GDP — World Development Indicators database
- Public wages (% of total expenditure) — World Development Indicators database
- Population, total (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
- Population ages 15+, total (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
- Population ages 15-64, total (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
- Population, male (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
- Population ages 15+, male (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
- Population ages 15+, female (UN estimates and projections) — ILOSTAT, International Labour Organization modeled estimates
- Labor force, total (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
- Labor force, male (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
- Labor force, female (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
- Labor force participation rate, total (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
- Labor force participation rate, male (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
- Labor force participation rate, female (modeled ILO estimates) — ILOSTAT, International Labour Organization modeled estimates
- Employment, total (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
- Employment, male (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
- Employment, female (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
- Employment rate, total (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
- Employment rate, male (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
- Employment rate, female (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
- Self-employed, male (% of male employment) (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
- Self-employed, female (% of female employment) (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
- Self-employed, total (% of total employment) (modeled ILO estimate) — ILOSTAT, International Labour Organization modeled estimates
- Hiring and firing regulations — World Economic Forum, Global Competitiveness Report
- Administrative requirements — World Economic Forum, Global Competitiveness Report
- Protection of property rights — World Economic Forum, Global Competitiveness Report

*Sources: IMF staff compilation.*

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_Source: https://www.imf.org/-/media/files/publications/wp/2023/english/wpiea2023182-print-pdf.pdf_