## Annex 5 — Institutional determinants of unemployment and Tunisia case study

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### Main empirical approach and data
- Panel estimations use a broad set of institutional indicators from multiple sources and include sub-indicators to identify policies with significant impacts on the unemployment rate.
- Cross-country Okun’s coefficient estimation: dynamic common-correlated effects model with heterogeneous coefficients on an (unbalanced) panel over 21 time periods (from 1996 to 2017) for up to 151 countries.
  - Regression: Δu(i,t) = λ(i) Δu(i,t−1) + β(i) Δy(i,t) + ϑ(i,t) where β(i) is the country-specific Okun’s coefficient.
- Instrumental-variable augmented specifications (first four lags of output change) showed no significant difference from baseline; main results use effective variables without instruments.

### Key empirical findings on institutional determinants of unemployment
- Overall contribution of institutional deterioration:
  - Deterioration of institutional factors that affected labor demand explains directly about a quarter of the unemployment rate increase in Tunisia during the last decade.
- Product market regulation:
  - Greater flexibility in the product market is associated with less unemployment.
  - Deterioration of product market regulation is identified as the most relevant institutional factor for Tunisia’s unemployment increase between 2009 and 2017.
  - About 20 percent of the increase in the unemployment rate in Tunisia during the last decade is attributable to the deterioration of product markets (based on specifications 4 and 6).
- Credit market conditions:
  - Flexibility of credit market regulations affects unemployment significantly and negatively.
  - About 5 percent of the unemployment increase in Tunisia between 2009 and 2017 is attributable to credit market conditions.
- Labor market regulation:
  - Firing procedures and costs matter: augmented severance payments or more stringent dismissal procedures are associated with higher unemployment (specifications 2 to 5).
  - De jure employment protection legislation (ILO indicator) remained unchanged in Tunisia during 2009–2017, explaining its lack of impact on unemployment change in estimations.
  - Estimate (specification 4): alleviation of dismissal procedures by one score point leads to a decrease in the unemployment rate by 4 ½ percent. (The ILO index used in specification 4 (EPLEX) ranges from 0 to 1 and one score point is equal to 0.25.)
  - No significant direct effect of wage bargaining on the unemployment level; wage bargaining may increase persistence of unemployment via insider–outsider dynamics.
- Taxation:
  - Estimations do not show any significant impact of the level of taxation on unemployment. Alternative measures (profit tax as a percentage of total profits, labor market taxation from World Bank Doing Business) also show no significant impact.
- Persistence and output gap:
  - Lagged unemployment is significant in regressions, indicating persistence in unemployment.
  - The output gap and persistence of unemployment explain most of the unemployment increase between 2009 and 2017 in Tunisia; the output gap contributed a cumulative 11 percent to the unemployment increase in Tunisia between 2009 and 2017.
- Heterogeneity by gender and age:
  - Institutional impacts on the unemployment increase in Tunisia between 2009 and 2017 are more pronounced for males than for females and youths, implying female and youth employment are more influenced by economic cycles.

### Selected regression evidence (high-level summary of Table 1 results)
- Lagged Unemployment coefficients across specifications (1) to (6): 0.5664***, 0.6030***, 0.6063***, 0.5817***, 0.5721***, 0.6947***.
- Output gap coefficients across specifications (1) to (6): -0.0769***, -0.0765***, -0.0800***, -0.0767***, -0.0751***, -0.0526***.
- Procedural requirements for dismissals (ILO) coefficients (specs where included): 0.0370***, 0.0449***, 0.0427***, 0.0440***.
- Severance payments (ILO) coefficients (specs where included): 0.0101, 0.0112**, 0.0090, 0.0105*.
- Goods market efficiency (WEF) coefficients (specs where included): -0.0110***, -0.0107***, -0.0069***.
- Credit market regulations (Fraser) coefficients (specs where included): -0.0018**, -0.0016*, -0.0015*, -0.0021***.
- Observations and fit examples:
  - Observations: 745, 769, 750, 752, 754, 1,376 across specifications.
  - R-squared examples: 0.5908, 0.5990, 0.6026, 0.6016, 0.6015, 0.6592.

### Okun’s coefficient findings and Tunisia’s sensitivity to the output gap
- Cross-country Okun’s estimates (Table 2, Equation 2):
  - All-sample (151 countries): Δ GDP(t) coefficient = -0.094*** (standard error 0.016).
  - Middle-income countries (including Tunisia): Δ GDP(t) coefficient = -0.073*** (standard error 0.014).
  - High-income countries: Δ GDP(t) coefficient = -0.244*** (standard error 0.035).
  - First lag of Δ GDP: -0.026*** (0.011) for all sample; -0.02 (0.015) for middle-income; -0.057* (0.032) for high-income.
  - Lagged Δ Unemployment examples: 0.118*** (0.034) for all sample; 0.142*** (0.047) for middle-income; 0.175*** (0.071) for high-income.
- Tunisia-specific insights:
  - Tunisia’s responsiveness of unemployment to the business cycle is substantially higher than the average of middle-income countries and comparable to high-income countries.
  - Tunisia’s Okun’s coefficient is 69 percent higher than the average of middle-income countries.
  - Decomposition of the difference between Tunisia and middle-income countries:
    - 48 percent of the difference in Okun’s coefficient is attributable to Tunisia’s higher unemployment level (Tunisia’s unemployment level is 69 percent higher than the average of middle-income countries).
    - 22 percent is attributable to higher flexibility in business regulation in Tunisia.
    - 3 percent is attributable to lower informality in Tunisia.
    - Slightly higher flexibility in Tunisian labor market regulation and higher trade openness reduce the difference between Tunisia and middle-income countries.

### Cross-country determinants of Okun’s coefficient (summary of Tables 3 and 4)
- Informal sector size:
  - Larger informal sector is associated with less responsiveness of unemployment to business cycles (informality acts as a buffer).
  - Informal size coefficients examples: 0.005*** (0.0012) in specification (1); 0.003** (0.0015) in specification (3).
- Business regulation flexibility:
  - More flexibility in business regulation is associated with stronger responsiveness of unemployment to business cycles.
  - Business regulation coefficient examples: -0.043*** (0.0111) in specification (2); -0.0392** (0.0171) in specification (5).
- Labor market regulation and subcomponents:
  - Hiring and firing regulation subcomponent shows a positive association with the Okun’s coefficient when significant: 0.041*** (0.0164) in a subcomponent regression (Table 4).
  - Interaction and complementarity between business and labor regulations matter; combined measures (e.g., [(hiring/firing)+(centralized bargaining)]/2) show significant coefficients in some specifications.
- Trade openness and unemployment level:
  - Trade openness has mixed/small coefficients in some specifications (e.g., -0.0001** (0.0005) in Table 3 specification (7)).
  - Higher unemployment level is associated with stronger Okun’s responsiveness (unemployment rate coefficient example: -0.012** (0.0065)).

### Mechanisms and interpretation
- Complementarity of policies:
  - Product market deregulation can incentivize labor market deregulation, improving aggregate employment, but product market flexibilization alone can increase sensitivity of unemployment to cycles if not matched by labor market flexibility or reductions in informality.
- Informality as an adjustment margin:
  - In economies with higher informality, adjustment to downturns occurs more through wages and working hours in the informal sector rather than reductions in employment, damping the Okun’s response.
- Persistence and hysteresis:
  - Significant lagged unemployment coefficients reflect persistence and potential hysteresis in unemployment (insider–outsider bargaining can raise the natural unemployment rate).
- Tunisia-specific institutional context:
  - Despite adoption of competition and investment laws, survey-based indicators show deterioration in competition and administrative requirements between 2009 and 2017.
  - Perceived reinforcement of market power by monopolies/oligopolies and burdensome administrative requirements impeded investment and business creation.
  - Banking sector perceptions deteriorated due to public sector crowding out, shocks affecting bank soundness (weakened tourism, increase in NPLs), and lack of progress in credit access, constraining job creation.

### Policy implications (for Tunisia)
- Main recommendations:
  - Improve the business environment (product market flexibility) to reduce unemployment, while ensuring:
    - Product market improvements are accompanied by increased labor market flexibility and reductions in informality to avoid raising sensitivity of unemployment to economic cycles.
  - Increase labor market flexibility, particularly easing dismissal procedures and reducing firing costs; empirical estimate in specification 4: easing dismissal procedures by one score point → unemployment decrease by 4 ½ percent.
  - Reduce financial constraints and improve credit access to support job creation, especially for new and innovative firms.
- Cautionary note:
  - Because of complementarities, implementing product market reforms alone could increase unemployment volatility during downturns in Tunisia given its already high Okun’s coefficient and labor market characteristics.
- Research implications:
  - Future work should further explore how institutional factors can be addressed to reduce unemployment persistence in Tunisia.

### Selected statistics and coefficients (compact)
- Lagged Unemployment: 0.5664***; 0.6030***; 0.6063***; 0.5817***; 0.5721***; 0.6947***.
- Output gap: -0.0769***; -0.0765***; -0.0800***; -0.0767***; -0.0751***; -0.0526***.
- Goods market efficiency (WEF): -0.0110***; -0.0107***; -0.0069***.
- Credit market regulations (Fraser): -0.0018**; -0.0016*; -0.0015*; -0.0021***.
- Okun’s Δ GDP(t): -0.094*** (0.016) all-sample; -0.073*** (0.014) middle-income; -0.244*** (0.035) high-income.

*Source: Annex 5 and Annex 1, wpiea2023219-print-pdf*

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### Annex 1: Employment protection legislation in Tunisia

### Overview of legislative framework
- Tunisian labor market legislation comprises:
  - The labor code,
  - Several specific laws and sectoral agreements (specific laws for government employees and associated benefits; specific statutes for SOE employees; legislation for the private sector and norms within including 56 collective agreements “conventions collectives”, 54 sectorial agreements and 2 global/framework agreements “convention cadre”).
- The labor code regulates the minimum wage (“SMIG” and “SMAG” for the agricultural sector), social security, and hiring and dismissal rules.
- The labor code has not been revised since 1996; two amendments in 1996 added more flexibility:
  - More room for fixed term contracts and less reliance on permanent employment contracts,
  - Specified procedures in case of layoffs for economic reasons,
  - Rules setting a maximum severance payment in case of firing.

### Gap between open-end and fixed-term contracts
- Important gap in protection between open-end and fixed-term contracts (referenced Figure 8 and Figure 8.1).
- Liberalizing fixed term contracts while maintaining stricter regulation on permanent contracts, coupled with cumbersome procedures (Figure 8.3), creates:
  - Substitution from permanent to fixed term contracts,
  - More difficulty moving from fixed term to permanent, turning fixed term employment into a trap rather than a springboard to stable employment (OECD, 2013; Blanchard and Landier, 2002).

### Table 6: Comparison of EPL between open-ended and fixed-term contracts in Tunisia
- Salaries and bonuses:
  - Both fixed term and open-end contracts should be treated equally if both coexist in the enterprise for the same qualification and job.
  - Salary grid, when available in collective agreements, applies to open end and fixed term contracts.
- Notice period:
  - Open end: 1   month   or   more   if   specified   in   the   collective agreement.
  - Fixed term: 1   month   or   more   if   specified   in   the   contract.
- Dismissal rules:
  - Open end:
    - Dismissal possible in 3 cases: agreement between employer and employee; serious misconduct; collective dismissals for economic reasons (strictly regulated and cumbersome; employer must consider length of service, family duties; decision submitted to the mixed committee (commission paritaire)).
  - Fixed term:
    - Dismissal possible after the notice period determined by contract.
- Severance payment:
  - Open end: Abusive dismissal 1 to 2 months per year, max of 3 years.
  - Fixed term: Theoretically same as open-end (1 to 2 months per year, max of 3 years), but employer has the possibility to fire after the notice period.
- Individual dismissal:
  - Open end: Not allowed except serious misconduct or force majeure; noncompliance considered abusive dismissal.
  - Fixed term: [No separate text beyond severance and dismissal after notice period].
- Economic reasons:
  - Open end: 12 days per year, with max of 3 months. Amount is always greater in collective agreements: up to 30 days per year with a max of 6-month salary.
  - Fixed term: [Table indicates differences; text reiterates higher amounts in collective agreements].

### Implications highlighted
- Combination of more flexible fixed-term contracts and stricter open-ended contract protections, plus cumbersome redundancy procedures, leads to:
  - Substitution toward fixed-term contracts,
  - Reduced mobility into permanent employment,
  - Fixed-term employment becoming a trap rather than a pathway to stability (citing OECD, 2013; Blanchard and Landier, 2002).

*Source: Annex 5 and Annex 1, wpiea2023219-print-pdf*

### Annex 5.  Table 1 presents  several  specifications  including  different  variants  of  the  variables  below,

### Annex 5 — Institutional determinants of unemployment and Tunisia case study

### Main empirical approach and data
- Panel estimations use a broad set of institutional indicators from multiple sources to check robustness and include sub-indicators to identify policies with significant impacts on the unemployment rate.  
- For cross-country Okun’s coefficient estimation, a dynamic common-correlated effects model with heterogeneous coefficients is used on an (unbalanced) panel over 21 time periods (from 1996 to 2017) for up to 151 countries. The regression format is:
  - Δu(i,t) = λ(i) Δu(i,t−1) + β(i) Δy(i,t) + ϑ(i,t) where β(i) is the country-specific Okun’s coefficient.
- Instrumental-variable augmented specifications (first four lags of output change) were estimated and showed no significant difference from baseline, so the main results use effective variables without instruments.

### Key empirical findings on institutional determinants of unemployment
- Overall contribution of institutional deterioration:
  - During the last decade, deterioration of institutional factors that affected labor demand explains directly about a quarter of the unemployment rate increase in Tunisia.
- Product market regulation:
  - A greater flexibility in the product market is associated with less unemployment.
  - Deterioration of product market regulation is identified as the most relevant institutional factor for Tunisia’s unemployment increase between 2009 and 2017.
  - About 20 percent of the increase in the unemployment rate in Tunisia during the last decade is attributable to the deterioration of product markets (based on specifications 4 and 6).
- Credit market conditions:
  - Flexibility of credit market regulations affects unemployment significantly and negatively.
  - About 5 percent of the unemployment increase in Tunisia between 2009 and 2017 is attributable to credit market conditions.
- Labor market regulation:
  - Firing procedures and costs matter: augmented severance payments or more stringent dismissal procedures are associated with higher unemployment (specifications 2 to 5).
  - De jure employment protection legislation (ILO indicator) remained unchanged in Tunisia during 2009–2017, explaining its lack of impact on unemployment change in estimations.
  - Estimates (specification 4) indicate that an alleviation of dismissal procedures by one score point leads to a decrease in the unemployment rate by 4 ½ percent. (The ILO index used in specification 4 (EPLEX) ranges from 0 to 1 and one score point is equal to 0.25.)
  - No significant direct effect of wage bargaining on the unemployment level is found, although wage bargaining may increase persistence of unemployment via insider–outsider dynamics.
- Taxation:
  - Estimations do not show any significant impact of the level of taxation on unemployment. Alternative measures (profit tax as a percentage of total profits, labor market taxation from World Bank Doing Business) also show no significant impact.
- Persistence and output gap:
  - Lagged unemployment is significant in regressions, indicating persistence in unemployment.
  - The output gap and persistence of unemployment explain most of the unemployment increase between 2009 and 2017 in Tunisia; the output gap contributed a cumulative 11 percent to the unemployment increase in Tunisia between 2009 and 2017.
- Heterogeneity by gender and age:
  - The impact of institutional factors on the unemployment increase in Tunisia between 2009 and 2017 is more pronounced for males than for females and youths, implying female and youth employment are more influenced by economic cycles.

### Selected regression evidence (high-level summary of Table 1 results)
- Lagged Unemployment coefficients across specifications (1) to (6): 0.5664***, 0.6030***, 0.6063***, 0.5817***, 0.5721***, 0.6947*** (robust standard errors in parentheses).
- Output gap coefficients across specifications (1) to (6): -0.0769***, -0.0765***, -0.0800***, -0.0767***, -0.0751***, -0.0526***.
- Procedural requirements for dismissals (ILO) coefficients (specs where included): 0.0370***, 0.0449***, 0.0427***, 0.0440***.
- Severance payments (ILO) coefficients (specs where included): 0.0101, 0.0112**, 0.0090, 0.0105*.
- Goods market efficiency (WEF) coefficients (specs where included): -0.0110***, -0.0107***, -0.0069***.
- Credit market regulations (Fraser) coefficients (specs where included): -0.0018**, -0.0016*, -0.0015*, -0.0021***.
- Observations range and model fit examples:
  - Observations: 745, 769, 750, 752, 754, 1,376 across specifications.
  - R-squared examples: 0.5908, 0.5990, 0.6026, 0.6016, 0.6015, 0.6592.

### Okun’s coefficient findings and Tunisia’s sensitivity to the output gap
- Cross-country Okun’s estimates (Table 2, Equation 2):
  - All-sample (151 countries): Δ GDP(t) coefficient = -0.094*** (standard error 0.016).
  - Middle-income countries (including Tunisia): Δ GDP(t) coefficient = -0.073*** (standard error 0.014).
  - High-income countries: Δ GDP(t) coefficient = -0.244*** (standard error 0.035).
  - First lag of Δ GDP: -0.026*** (0.011) for all sample; -0.02 (0.015) for middle-income; -0.057* (0.032) for high-income.
  - Lagged Δ Unemployment coefficient examples: 0.118*** (0.034) for all sample; 0.142*** (0.047) for middle-income; 0.175*** (0.071) for high-income.
- Tunisia-specific insights:
  - Tunisia’s responsiveness of unemployment to the business cycle is substantially higher than the average of middle-income countries and comparable to high-income countries.
  - Tunisia’s Okun’s coefficient is 69 percent higher than the average of middle-income countries.
  - Decomposition of the difference between Tunisia and middle-income countries:
    - 48 percent of the difference in Okun’s coefficient is attributable to Tunisia’s higher unemployment level (Tunisia’s unemployment level is 69 percent higher than the average of middle-income countries).
    - 22 percent is attributable to higher flexibility in business regulation in Tunisia.
    - 3 percent is attributable to lower informality in Tunisia.
    - Slightly higher flexibility in Tunisian labor market regulation and higher trade openness reduce the difference between Tunisia and middle-income countries.

### Cross-country determinants of Okun’s coefficient (summary of Tables 3 and 4)
- Informal sector size:
  - Larger informal sector is associated with less responsiveness of unemployment to business cycles (informality acts as a buffer).
  - Informal size coefficients reported (examples): 0.005*** (0.0012) in specification (1); 0.003** (0.0015) in specification (3).
- Business regulation flexibility:
  - More flexibility in business regulation is associated with a stronger responsiveness of unemployment to business cycles (business regulation coefficient examples): -0.043*** (0.0111) in specification (2); -0.0392** (0.0171) in specification (5).
- Labor market regulation and subcomponents:
  - Hiring and firing regulation subcomponent shows a positive association with the Okun’s coefficient when significant: 0.041*** (0.0164) in a subcomponent regression (Table 4).
  - Interaction and complementarity between business and labor regulations matter; combined measures (e.g., [(hiring/firing)+(centralized bargaining)]/2) show significant coefficients in some specifications.
- Trade openness and unemployment level:
  - Trade openness has mixed/significant small coefficients in some specifications (e.g., -0.0001** (0.0005) in Table 3 specification (7)).
  - Higher unemployment level is associated with stronger Okun’s responsiveness (unemployment rate coefficient examples: -0.012** (0.0065)).

### Mechanisms and interpretation
- Complementarity of policies:
  - Product market deregulation can incentivize labor market deregulation, improving aggregate employment, but product market flexibilization alone can increase sensitivity of unemployment to cycles if not matched by labor market flexibility or reductions in informality.
- Informality as an adjustment margin:
  - In economies with higher informality, adjustment to downturns occurs more through wages and working hours in the informal sector rather than reductions in employment, damping the Okun’s response.
- Persistence and hysteresis:
  - Significant lagged unemployment coefficients reflect persistence and potential hysteresis in unemployment (insider–outsider bargaining can raise the natural unemployment rate).
- Tunisia-specific institutional context:
  - Despite adoption of competition and investment laws (cited law numbers in text), survey-based indicators show deterioration in competition and administrative requirements between 2009 and 2017.
  - Perceived reinforcement of market power by monopolies/oligopolies and burdensome administrative requirements impeded investment and business creation.
  - Banking sector perceptions deteriorated during the last decade due to public sector crowding out, shocks affecting bank soundness (weakened tourism, increase in NPLs), and lack of progress in credit access, constraining job creation.

### Policy implications (for Tunisia)
- Main recommendations:
  - Improve the business environment (product market flexibility) to reduce unemployment, but:
    - Improvements in business regulation should be accompanied by increased labor market flexibility and reductions in informality to avoid raising the sensitivity of unemployment to economic cycles.
  - Increase labor market flexibility, particularly easing dismissal procedures and reducing firing costs, which empirical estimates link to lower unemployment (e.g., easing dismissal procedures by one score point → unemployment decrease by 4 ½ percent in specification 4).
  - Reduce financial constraints and improve credit access to support job creation, especially for new and innovative firms.
- Cautionary note:
  - Because of complementarities, implementing product market reforms alone could increase unemployment volatility during downturns in Tunisia given its already high Okun’s coefficient and labor market characteristics.
- Research implications:
  - Future work should further explore how institutional factors can be addressed to reduce unemployment persistence in Tunisia.

*Source: Annex 5, wpiea2023219-print-pdf*

### Annex 1:

### Annex 1: Employment protection legislation in Tunisia

### Overview of legislative framework
- The Tunisian labor market legislation is a combination of:
  - The labor code,
  - Several specific laws and sectoral agreements:
    - Specific laws for government employees and specific associated benefits
    - Specific statutes for SOE employees
    - Legislation for the private sector and norms within (56 collective agreements “conventions collectives”, 54 sectorial agreements and 2 global/framework agreements “convention cadre”)
- The Tunisian labor code regulates the minimum wage (“SMIG” and “SMAG” for the agricultural sector), social security, and hiring and dismissal rules.
- The labor code has not been revised since 1996, when two amendments were passed that added more flexibility, including:
  - More room for fixed term contracts and less reliance on permanent employment contracts,
  - Specified procedures in case of layoffs for economic reasons,
  - Rules setting a maximum severance payment in case of firing.

### Gap between open-end and fixed-term contracts
- There is an important gap in Tunisia between open end and fixed term contracts in terms of protection legislation (Figure 8), further evidenced by an international comparison (Figure 8.1).
- Liberalizing fixed term contracts while maintaining stricter regulation on permanent contracts, coupled with cumbersome procedures (figure 8.3 on redundancy rules) creates:
  - A substitution effect from permanent to fixed term contracts,
  - More difficulty in movement from fixed term to permanent, transforming fixed term employment into a trap rather than a springboard to more stable employment (OECD, 2013; Blanchard and Landier, 2002).

### Table 6: A comparison of EPL between open ended and fixed term contracts in Tunisia
- Salaries and bonuses:
  - The labor code specifies that both employees with fixed term and open-end contracts should be treated equally if the two types of contracts coexist in the enterprise for the same qualification and job.
  - The salary grid, when available in collective agreements is applicable to open end, as well as fixed term contracts.
- Notice period:
  - Open end employment contract: 1   month   or   more   if   specified   in   the   collective agreement
  - Fixed term employment contract: 1   month   or   more   if   specified   in   the   contract.
- Dismissal rules:
  - Open end employment contract:
    - Dismissal is possible in 3 cases:
      - Agreement between the employer and the employee
      - Serious misconduct (cases enumerated in the labor code)
      - In case of collective dismissals for economic reasons, the procedure is strictly regulated and cumbersome. Furthermore, the employer should consider those criteria: length of service, family duties. The decision should be submitted for acceptance to the mixed committee (commission paritaire).
  - Fixed term employment contract:
    - The dismissal is possible after the notice period determined by contract
- Severance payment:
  - Open end employment contract: Abusive dismissal 1 to 2 months per year, max of 3 years
  - Fixed term employment contract: Theoretically the same case than the open-end contract (1 to 2 months per year, max of 3 years), but the employer has the possibility to fire after the notice period
- Individual dismissal:
  - Open end employment contract: Not allowed, except serious misconduct or force majeure. The noncompliance with the procedure is considered as an abusive dismissal.
  - Fixed term employment contract: [No separate text provided beyond severance and dismissal possibility after notice period]
- Economic reasons:
  - Open end employment contract: 12 days per year, with max of 3 months. The amount is always greater in collective agreements: up to 30 days per year with a max of 6-month salary
  - Fixed term employment contract: [Table indicates differences but text reiterates higher amounts in collective agreements]

### Implications highlighted in the annex
- The combination of more flexible fixed-term contracts and stricter/open-ended contract protections, plus cumbersome redundancy procedures, leads to:
  - Substitution toward fixed-term contracts,
  - Reduced mobility into permanent employment,
  - Fixed-term employment becoming a trap rather than a pathway to stability (citing OECD, 2013; Blanchard and Landier, 2002).
- International comparisons and figures referenced:
  - Figure 8, Figure 8.1, and Figure 8.3 are cited as evidence of the protection distribution and redundancy procedural burden.

*Source: Annex 1, wpiea2023219-print-pdf - Annex 1*

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_Source: https://www.imf.org/-/media/files/publications/wp/2023/english/wpiea2023219-print-pdf.pdf_