## wp1863 - 18.4 percent of firms exports their prodcution, and only 11.7 percent of firms have access to

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### Summary statistics (Table 2)
- Firms’ size (mean, Std. Dev.)
  - Share of microenterprises: 37.55, 0.48
  - Share of small firms: 39.88, 0.49
  - Share of medium firms: 15.41, 0.36
  - Share of large firms: 7.16, 0.25
- Firms’ age (mean, Std. Dev.)
  - Share of young firms: 15.54, 0.36
  - Share of mature firms: 45.13, 0.5
  - Share of old firms: 39.32, 0.49
- Connection to foreign market
  - Proportion of firms exporting: 18.41, 0.39
- Financial access
  - Proportion of firms having a credit line or an overdraft facility: 11.65, 22.98
- Ownership
  - Average foreign share: 8.66, 26.26
  - Average government/states share: 0.51, 5.39
- Macroeconomic variables
  - GDP growth: 4.54, 2.77
  - Inflation: 7.13, 6.12
  - Quality of regulation: -0.46, 0.41
- Note: All variables are in percent, except the quality of regulation. The summary statistics are at the firm level.

### Data patterns and descriptive observations
- Structural reforms in the sample comprise mostly fiscal and financial reforms.
- IMF programs are mostly dominated by fiscal and financial measures; the real and trade sectors are often categorized under business climate improvement.
- Reforms spiked in 2009 with the significant increase in IMF programs after the global financial crisis.
- There is a positive correlation between LPG and structural reforms.

### Methodology: multilevel mixed model
- Key modeling choices and identification:
  - Two-level multilevel mixed model: highest level = country; lowest level = firm. Intercept allowed to vary across countries.
  - Outcome: firm labor productivity growth, LPLG_{ict}. Key regressor: 3-year lagged successful structural reforms index, RmR_{c,(t-1,t-3)}.
  - Controls: firm characteristics X_{ict}, macro variables γ_c_t, country random effect ϖ_{ct}, firm error ε_{ict}; country, sector, and year fixed effects.
  - Matching strategy: approval year of each IMF program corresponds exactly or before the reference year of labor productivity growth to limit reverse causality.
  - Standard errors clustered at the country level (robustness when clustering at country-sector and country-sector-year levels).
  - Sample balance tests (Table A.1, Table A.2) show no statistical pre-treatment differences between program and non-program countries and between strong and weak reformers.

### Baseline estimation results (Table 3) — key coefficients and magnitudes
- Aggregate structural reform index:
  - Structural reforms (aggregate) — standardized coefficient: 0.284*** (0.0160).
  - A one standard deviation increase in the reform index raises firm-level LPG by 0.284 percentage point (reported as standardized coefficient).
- Subcomponents (standardized coefficients, selected):
  - Financial reforms — 0.0380 (0.0763)
  - Fiscal reforms — 0.370*** (0.0209)
  - Real sector reforms — 0.344*** (0.0194)
  - Trade reforms — 9.674*** (0.546) in one specification and 0.266*** (0.0150) in another specification
- Firm-level covariates (relative to large firms where applicable):
  - Micro-firms: -0.429*** (0.0519)
  - Small firms: -0.294*** (0.0382)
  - Medium firms: -0.102*** (0.0218)
  - Exporting status dummy: 0.0491*** (0.0164)
  - Foreign share: 0.0715*** (0.0180)
  - Log. real sales (3 years ago): -0.616*** (0.0528)
- Macroeconomic and institutional influences:
  - GDP growth: e.g., 0.526*** (0.0301) in one specification; coefficients vary across specifications.
  - Inflation: large negative coefficients reported, e.g., -10.74*** (0.414) in one specification and other large negatives across columns.
  - Quality of regulation: e.g., 2.772*** (0.0922) in one specification; other positive coefficients reported across specifications.
- Sample and fit:
  - Observations: 10,822 in all specifications shown.
  - R-squared values reported: 0.236, 0.236, 0.240, 0.240, 0.240, 0.240 across columns.

### Heterogeneity: “Strong reformer” vs. “Weak reformer”
- Classification: countries above the median reform index = “strong reformer”; below median = “weak reformer.”
- Findings:
  - Strong reformer dummy: -0.0693 (0.0632) (not significant).
  - Interaction (Strong reformer * Structural reforms): 0.257*** (0.0455) — gains from structural reforms in LPG between a firm in the “strong reformer” group and the control group are about 0.257 percentage point.
  - Net effect in strong reformer countries is very close to the baseline estimate.
  - Sample balance (Table A.2) indicates no statistical pre-treatment macroeconomic differences between strong and weak reformers.

### Conditional factors shaping reform effects (section D — main interaction findings)
- Conditional factors studied: exporting status, financial access (credit line or overdraft), distortions (top fourth quintile), firm size categories.
- Exporting status:
  - Main exporting dummy: ~0.04367*** to 0.0493*** across specifications.
  - Interaction terms (Reforms * Exporting) not statistically significant — being connected to foreign markets does not generate statistically significant additional LPG gains from structural reforms.
- Financial access:
  - Financial access main effect: ~0.0492*** (0.0163) across specifications.
  - Reforms * Financial access:
    - Financial reforms * Financial access: -0.135*** (0.0414) — financially included firms benefit less from financial reforms; magnitude: being financially included reduces productivity gain by 0.135 percentage point for a one standard deviation increase in financial reforms.
    - Fiscal reforms * Financial access: 0.0891*** (0.0323) — financial access strengthens fiscal reforms’ effect by 0.089 for a one standard deviation increase in fiscal reforms.
    - Real and Trade interactions with financial access: not significant.
  - Interpretation: financial reforms disproportionately benefit financially excluded firms; fiscal reforms produce additional gains for firms with financial access.
- Distortions:
  - Fiscal reforms * Distortions: -0.0424** (0.0170) — negative and significant: distortions hinder fiscal reform gains (magnitude: a 0.042 standard deviation decrease in productivity for a one standard deviation increase in fiscal reforms in high-distortion firms).
  - Other Reforms * Distortions: not significant.
- Small firms:
  - Financial reforms * Small firms: 0.0375* (0.0225) — small firms gain more from financial reforms (0.038 standard deviation increase for a one standard deviation increase in financial reforms).
  - Other interactions with small firms: not significant.
- Overall conditional conclusions:
  - Financial access and being a small firm enhance the impact of financial reforms.
  - Financial access improves fiscal reforms’ impact; distortions hinder fiscal reforms’ impact.
  - Trade reforms’ effect on LPG is sensitive to distortions though interaction coefficients often not significant.

### Complementarities and substitutability between reforms (section E — Table 5)
- Interaction (phi) coefficients (standardized):
  - Financial * Fiscal: 0.213*** (0.0655) — complementary
  - Financial * Real sector: 1.122*** (0.0357) — complementary
  - Financial * Trade: -0.170*** (0.0407) — substitutable
  - Fiscal * Real sector: 0.341*** (0.0211) — complementary
  - Fiscal * Trade: 0.288*** (0.0231) — complementary
  - Real sector * Trade: 2.720*** (0.125) — complementary
- Interpretation:
  - Except for the financial–trade pair, pairs of reforms are bilaterally complementary in raising firm-level LPG.
  - Negative financial–trade interaction may reflect sample countries’ development stage where finance does not yet reinforce trade reform effects.
  - Policy implication: implementing reform packages jointly can amplify productivity gains, but sequencing and country context matter, especially for financial vs. trade reforms.

### Robustness and sensitivity checks (Appendix B and elsewhere)
- Crisis and recovery controls:
  - Inclusion of 2008-09 crisis dummy does not alter the positive impact of structural reforms; the crisis itself has a negative effect on productivity growth (examples: The 2008-2009 financial crisis coefficients reported as large negative values in Table B.1 and B.3).
  - Table B.1 examples: Financial reforms 0.370*** (0.021) while The 2008-2009 financial crisis −12.00*** (0.029) in one specification.
- Additional controls (capital and investment):
  - Panel B (sample size 2,880) includes Log. Net book value of capital and Log. Investment in capital; reform coefficients remain positive and significant (e.g., Financial reforms 0.244*** (0.063)).
- Alternative index construction:
  - Min-max normalized reform indexes (Panel C) yield similar positive coefficients (e.g., Fiscal reforms 0.671*** (0.0378); Real sector reforms 2.043*** (0.115)).
- Alternative productivity measures:
  - Value Added per worker (Panel D; Observations 9. 942; R-squared 0.80): Financial 0.116*** (0.007); Fiscal 0.125*** (0.008); Real 3.264*** (0.210); Trade 0.0898*** (0.006).
  - Total Factor Productivity (Panel E; Observations 4,965; R-squared 0.3398): Financial 0.122*** (0.0271); Fiscal 0.114*** (0.0253); Real 3.204*** (0.709); Trade 0.0882*** (0.0165).
- Difference-in-difference checks (Table B.4; Observations 11,807) corroborate interaction patterns: firms with financial access benefit less from financial reforms; fiscal reforms benefit firms with financial access more; fiscal reforms yield lower gains for firms facing high distortions.
- Unsuccessful reforms as counterfactual (Table B.5):
  - Unsuccessful financial reforms: Reforms −1.121*** (0.091) — negative impact.
  - Unsuccessful real sector reforms: Reforms −3.975*** (0.308) — negative impact.
  - Unsuccessful fiscal reforms: Reforms 0.705*** (0.044) — positive result interpreted in context of parallel successful fiscal reforms.
- Low Income Countries (Table B.6; Observations 10,822; R-squared 0.2608):
  - Financial reforms: 1.475*** (0.0407)
  - Fiscal reforms: 0.438*** (0.0121)
  - Real sector reforms: 5.432*** (0.150)
  - Trade reforms: 0.385*** (0.0106)

### Key policy-relevant takeaways and implications
- All four reform categories (financial, fiscal, real sector, trade) are associated with positive effects on firm-level productivity growth; real sector reform has the most sizeable impact in most specifications.
- Strong reformer countries: interaction term (Strong reformer * Structural reforms) 0.257*** (0.0455) — being a “strong reformer” is associated with stronger productivity gains from reforms.
- Conditional and nonlinear effects matter:
  - Financial reforms: largest benefits accrue to financially excluded firms and to small firms (Financial * Financial access: -0.135*** (0.0414); Financial * Small firms: 0.0375* (0.0225)).
  - Fiscal reforms: gains strengthened by financial access (0.0891*** (0.0323)) but hindered by distortions (Fiscal * Distortions: -0.0424** (0.0170)).
  - Trade reforms: overall positive but sensitive to distortions; estimated impacts close to average index estimates in several specifications.
- Complementarities imply integrated reform packages can amplify LPG gains, but the negative Financial * Trade interaction (-0.170*** (0.0407)) signals careful sequencing and country-context considerations when pairing financial and trade reforms.
- Limitations to consider in policy design:
  - WBES data cover the formal sector only; results reflect formal sector firm-level productivity gains.
  - Structural reforms outside IMF program coverage are not captured due to data constraints.
  - Future work should increase granularity to separate impacts of individual reforms where possible.

_Source: wp1863 (IMF Working Paper) — content as provided._

### 18.4 percent of firms exports their prodcution, and only 11.7 percent of firms have access to

### wp1863 - 18.4 percent of firms exports their prodcution, and only 11.7 percent of firms have access to

### Summary statistics (Table 2)
- Firms’ size (mean, Std. Dev.)
  - Share of microenterprises: 37.55, 0.48
  - Share of small firms: 39.88, 0.49
  - Share of medium firms: 15.41, 0.36
  - Share of large firms: 7.16, 0.25
- Firms’ age (mean, Std. Dev.)
  - Share of young firms: 15.54, 0.36
  - Share of mature firms: 45.13, 0.5
  - Share of old firms: 39.32, 0.49
- Connection to foreign market
  - Proportion of firms exporting: 18.41, 0.39
- Financial access
  - Proportion of firms having a credit line or an overdraft facility: 11.65, 22.98
- Ownership
  - Average foreign share: 8.66, 26.26
  - Average government/states share: 0.51, 5.39
- Macroeconomic variables
  - GDP growth: 4.54, 2.77
  - Inflation: 7.13, 6.12
  - Quality of regulation: -0.46, 0.41
- Note: All variables are in percent, except the quality of regulation. The summary statistics are at the firm level.

### Data patterns and descriptive observations
- Structural reforms in the sample comprise mostly fiscal and financial reforms (Figure 1).  
- IMF programs are mostly dominated by fiscal and financial measures; the real and trade sectors are often categorized under business climate improvement.  
- Reforms spiked in 2009 with the significant increase in IMF programs after the global financial crisis.  
- There is a positive correlation between LPG and structural reforms (Figure 2).

### Methodology: multilevel mixed model
- Key challenges addressed:
  - Clustering of firms within countries (shared contextual characteristics leading to potential downward-biased standard errors if ignored).
  - Potential endogeneity between structural reforms and firm-level productivity from omitted variables and reverse causality.
  - Pre-treatment macroeconomic differences (commodity price shocks, country-specific conditions) that could confound effects.
- Modeling approach:
  - Two-level multilevel mixed model: highest level = country; lowest level = firm.
  - Intercept allowed to vary across countries to capture country-level heterogeneity.
  - Inclusion of country-level variables and country, sector, and year fixed effects.
  - Matching strategy to ensure the approval year of each IMF program corresponds exactly or before the reference year of labor productivity growth (limits reverse causality).
  - Sample balance test (Table A.1) comparing countries under IMF program and those without three years prior to adoption shows no statistical difference in key macroeconomic variables.
  - Standard errors clustered at the country-level in all specifications; robustness noted when clustering at country-sector and country-sector-year levels.
- Model specification (as described in text):
  - Outcome: firm labor productivity growth, LPLG_{ict}
  - Key regressor: 3-year lagged successful structural reforms index, RmR_{c,(t-1,t-3)}
  - Controls: firm characteristics X_{ict}, macro variables γ_c_t, country random effect ϖ_{ct}, firm error ε_{ict}
  - Parameter of interest: β (impact of structural reforms on firm-level productivity)

### Baseline estimation results (Table 3)
- Structural reform index effect:
  - The structural reform variable has a positive impact on LPG. The associated coefficient is positive and statistically significant at the 1 percent level.
  - A one standard deviation increase in the reform index raises firm-level LPG by 0.284 percentage point.
- Firm-level controls and magnitudes:
  - Exporting and foreign-owned firms have a positive impact on LPG. Estimated coefficients significant at 1 percent with magnitudes between 0.05 and 0.072 standard deviation increase for a 1 standard deviation increase in the index of structural reforms.
  - Mature firms have lower LPG (coefficients significant at 1 and 5 percent levels).
  - Relative to large firms, gaps in LPG:
    - Micro-firms: 0.429 standard deviation lower
    - Small firms: 0.294 standard deviation lower
    - Medium firms: 0.102 standard deviation lower
  - Initial conditions: firms with large initial sales have lower LPG — 0.62 standard deviation decrease in LPG for a 1 standard deviation differential in real sales.
  - Location and ownership:
    - Large cities and government-owned firms are significant drivers of LPG (urbanization and localization economies cited).
- Macroeconomic influences:
  - GDP growth: a 1 standard deviation improvement in growth translates to 0.526 standard deviation increase in LPG (significant at 1 percent).
  - Inflation: an increase of inflation by 1 standard deviation decreases LPG by 10.74 standard deviation (significant at 1 percent).
  - Quality of regulation: an increase of 1 standard deviation in the quality of regulation raises LPG by 2.77 standard deviation (significant at 1 percent).

### Heterogeneity: “Strong reformer” vs. “Weak reformer”
- Classification:
  - Countries above the median of the reform index are labeled “strong reformer”; below median labeled “weak reformer.”
  - (Text notes list of strong reformer countries for the period, but that list is part of the source and not reproduced here per overlay rules.)
- Findings:
  - The “strong reformer” dummy itself is negative and statistically not significant (firms in “strong reformer” countries do not appear more productive than counterfactual).
  - Interaction effect: gains from structural reforms in LPG between a firm in the “strong reformer” group and the control group are about 0.257 percentage point (coefficient associated with the interaction term).
  - The net effect of structural reform in “strong reformer” countries is very close to the baseline estimate.
  - Table A.2 shows “strong reformer” and “weak reformer” countries are not statistically different on pre-treatment macroeconomic conditions.

### Specific structural reforms (subcomponents)
- Reform subcomponents analyzed: financial sector reform, fiscal sector reform, real sector reform, trade sector reform.
- Main findings (Table 3, columns (3)–(6)):
  - All considered structural reforms have positive impacts on LPG; coefficients positive and significant at the 1 percent level.
  - Real sector reform:
    - Associated coefficient: 9.7
    - Interpretation in text: a one standard deviation increase in the real sector reform index leads to an improvement of 9.7 percentage points in LPG at the firm level, which is more than 34 times higher than the baseline estimate.
  - Financial and fiscal reforms:
    - Estimated impacts close in magnitudes at around 0.35, slightly above the average index baseline.

### Robustness and additional checks
- Addressed potential biases and endogeneity via:
  - Multilevel mixed model with country random effects and country, sector, year fixed effects.
  - Matching strategy aligning program approval year with productivity reference year.
  - Sample balance tests on pre-treatment macro conditions (Table A.1, Table A.2).
  - Further robustness checks reported in Appendix B: accounting for countries in crisis, accounting for unsuccessful reforms, adding control variables, and a difference-in-difference approach.
- Standard errors clustered at the country level; robustness to alternative clustering levels noted.

*Source: Authors’ calculations based on the IMF MONA and the WBES, as presented in wp1863.*

### 0.37 and 0.34 percentage point in LPG at the firm level. Finally, the impact of trade structural

### wp1863 - 0.37 and 0.34 percentage point in LPG at the firm level. Finally, the impact of trade structural reforms is close to the one estimated with the average index.

### Impact of structural reforms on labor productivity growth (summary of Table 3)
- Structural reforms (aggregate) — standardized coefficient: 0.284*** (0.0160).
- Financial reforms — standardized coefficient: 0.0380 (0.0763).
- Fiscal reforms — standardized coefficient: 0.370*** (0.0209).
- Real sector reforms — standardized coefficient: 0.344*** (0.0194).
- Trade reforms — standardized coefficient: 9.674*** (0.546) in one specification and 0.266*** (0.0150) in another specification (both reported across columns).
- Strong reformer dummy: -0.0693 (0.0632) (not significant in that column).
- Strong reformer dummy * Structural reforms: 0.257*** (0.0455).
- Firms’ size effects (relative to large firms reference implicit):
  - Micro-firms: -0.429*** (0.0519).
  - Small firms: -0.294*** (0.0382).
  - Medium firms: -0.102*** (0.0218).
- Firms’ age:
  - Young: -0.0174 (0.0114).
  - Mature: -0.0419*** (0.0097).
- Ownership:
  - Government share: 0.0087 (0.0104).
  - Foreign share: 0.0715*** (0.0180).
- Other firm characteristics:
  - Exporting status dummy: 0.0491*** (0.0164).
  - Financial access: 0.0162 (0.0140).
  - Log. real sales (3 years ago): -0.616*** (0.0528).
  - Large city: 0.0165 (0.0261).
- Macroeconomic variables (selected):
  - GDP growth (percent): coefficients vary by specification: 0.526*** (0.0301); -0.0395*** (0.009); 1.359*** (0.0299); 0.294*** (0.0412); -0.521*** (0.0848); 0.625*** (0.0259).
  - Inflation (percent): large negative coefficients in several specifications: -10.74*** (0.414); -0.0107 (0.009); -23.88*** (0.526); -7.741*** (0.549); -11.73*** (1.284); -8.398*** (0.327).
- Institutions:
  - Quality of regulation: 2.772*** (0.0922); other specifications report 0.0166 (0.0294); 6.058*** (0.169); 2.150*** (0.111); 4.394*** (0.099); 1.782*** (0.126).
- R-squared values reported: 0.236, 0.236, 0.240, 0.240, 0.240, 0.240 across columns.
- Observations: 10,822 in all specifications.
- Notes: Table presents standardized coefficients from multilevel mixed effects models with country, sector, and year fixed effects; robust standard errors clustered at the country level in parentheses; ***, **, * denote significance at the 1, 5, and 10 percent level.

### Conditional factors shaping reform effects (section D — key findings and magnitudes)
- Approach:
  - Conditional factors analyzed: access to international markets (exporting status), financial access (credit line or overdraft), distortions (top fourth quintile of distortions), and firm size (Micro: 1–10; Small: 11–50; Medium: 51–200; Large: >200).
  - Empirical model includes interaction terms between reform indices and conditional factors; controls for firm characteristics, macro variables, and fixed effects.
- Access to international markets (Table 4, conditional factor: Exporting firm dummy):
  - Reforms coefficients: Financial 0.376*** (0.0223); Fiscal 0.342*** (0.022); Real 9.670*** (0.543); Trade 0.266*** (0.017).
  - Reforms * Exporting firm dummy: Financial -0.010 (0.013); Fiscal 0.004 (0.018); Real -0.003 (0.019); Trade 0.001 (0.0192) — none statistically significant.
  - Exporting firm dummy main effect: 0.04367*** (0.0157); 0.0484*** (0.0180); 0.0493*** (0.0160); 0.0473*** (0.0163).
  - R-squared: 0.2361 across these specifications.
  - Conclusion: being connected to foreign markets does not generate statistically significant additional LPG gains from structural reforms.
- Financial access (Table 4, conditional factor: Financial access):
  - Reforms coefficients: Financial 0.505*** (0.040); Fiscal 0.261*** (0.0401); Real 9.678*** (0.566); Trade 0.220*** (0.0342).
  - Reforms * Financial access:
    - Financial: -0.135*** (0.0414) — financially included firms benefit less from financial reforms; magnitude: being financially included reduces productivity gain by 0.135 percentage point for a one standard deviation increase in financial reforms.
    - Fiscal: 0.0891*** (0.0323) — financial access strengthens fiscal reforms’ effect; magnitude: 0.089 for a one standard deviation increase in fiscal reforms.
    - Real: -0.007 (0.04593) (not significant).
    - Trade: 0.0514 (0.0376) (not significant).
  - Financial access main effect: ~0.0492*** (0.0163) across specifications.
  - R-squared: 0.2368, 0.2370, 0.2360, 0.2361.
  - Interpretation: financial reforms disproportionately benefit financially excluded firms; fiscal reforms produce additional gains for firms with financial access (e.g., via lower spreads, better functioning local currency markets).
- Distortions (Table 4, conditional factor: Distortions):
  - Reforms coefficients: Financial 0.358*** (0.0268); Fiscal 0.374*** (0.0224); Real 9.635*** (0.579); Trade 0.271*** (0.0193).
  - Reforms * Distortions:
    - Financial: 0.0133 (0.0111) (not significant).
    - Fiscal: -0.0424** (0.0170) — negative and significant at 5 percent: distortions hinder fiscal reform gains.
    - Real: -0.0150 (0.0219) (not significant).
    - Trade: -0.0101 (0.0138) (not significant).
  - Distortions main effects: varying, generally not significant.
  - R-squared: 0.2362, 0.2372, 0.2362, 0.2361.
  - Magnitudes noted in text: a one standard deviation increase in fiscal related structural reforms raises firm-level productivity by 0.342 standard deviation; being in the top 50 more distorted firms costs 0.042 standard deviation decrease in productivity for a one standard deviation increase in fiscal reforms.
  - Interpretation: higher distortion levels (crime, insecurity, power outages, bribes, etc.) mitigate the effects of fiscal reforms; fiscal reforms may reduce distortions and disadvantage firms that relied on corruption.
- Small firms (Table 4, conditional factor: Small firms):
  - Reforms coefficients: Financial 0.341*** (0.0334); Fiscal 0.353*** (0.0484); Real 9.634*** (0.529); Trade 0.282*** (0.055).
  - Reforms * Small firms:
    - Financial: 0.0375* (0.0225) — positive and significant at 10 percent: being a small firm improves LPG gains from financial reforms by 0.038 standard deviation for one standard deviation increase in financial reforms.
    - Fiscal: -0.0282 (0.0417) (not significant).
    - Real: 0.0267 (0.0409) (not significant).
    - Trade: -0.0180 (0.0393) (not significant).
  - Small firms main effects: around -0.290*** (0.0382) to -0.295*** (0.0386).
  - R-squared: 0.2364, 0.2370, 0.2361, 0.2361.
  - Interpretation: financial reforms disproportionately benefit small firms, consistent with small businesses having less access to formal finance pre-reform.
- Overall conditional-factor conclusion:
  - Structural reforms increase firm-level productivity in developing countries.
  - Financial access and being a small firm enhance the impact of financial reforms.
  - Financial access improves fiscal reforms’ impact; distortions hinder fiscal reforms’ impact.
  - Trade reforms’ effect on LPG is impaired by distortions in the business environment (text indicates impairment though several interaction coefficients not statistically significant).

### Complementarities and substitutability between structural reforms (section E — Table 5 results)
- Method: interaction terms between pairs of structural reform indices estimated in multilevel models; complementarity coefficient (phi) positive implies complementarity; negative implies substitutability.
- Key interaction coefficients (standardized, Table 5):
  - Financial reform * Fiscal reform: 0.213*** (0.0655) — complementary.
  - Financial reform * Real sector reform: 1.122*** (0.0357) — complementary.
  - Financial reform * Trade reform: -0.170*** (0.0407) — substitutable (negative).
  - Fiscal reform * Real sector reform: 0.341*** (0.0211) — complementary.
  - Fiscal reform * Trade reform: 0.288*** (0.0231) — complementary.
  - Real sector * Trade reform: 2.720*** (0.125) — complementary.
- Other main effects reported in Table 5 (selected coefficients):
  - Financial reform main: 0.0422 (0.0568); 0.994*** (0.0444); -0.336*** (0.0239) across different columns.
  - Fiscal reform main: 0.231*** (0.0912); 0.237*** (0.0281); -0.892*** (0.162).
  - Real sector reform main: -5.239*** (0.282); 0.105 (0.108); 1.307*** (0.221).
  - Trade reform main: 0.630*** (0.0589); 0.533*** (0.0796); -1.376*** (0.0914).
- Observations: 10,822; R-squared: 0.2360 in all six specifications.
- Interpretation and implications:
  - Except for the financial–trade pair, the considered structural reforms are bilaterally complementary in improving firms’ labor productivity growth.
  - The negative interaction between financial and trade reforms may reflect the stage of development of sample countries, where finance may not yet be a key determinant to reinforce trade reform effects.
  - Policy implication: most structural reforms under IMF programs can be implemented jointly to maximize productivity effects, but attention to sequencing and country context (especially for financial vs. trade reforms) is warranted.

### Identification, robustness, and limitations
- Identification strategy:
  - Efforts to minimize endogeneity: sample balance tables show program countries are not statistically different from non-program countries on key macro variables; matching productivity data with reforms within the 3 previous years; approval year of IMF arrangement corresponds exactly or is after the reference year of labor productivity growth to limit reverse causality.
- Robustness:
  - Findings robust to alternative measures of productivity, methodologies, additional control variables, and counterfactual experiments based on unsuccessful reforms (reported in appendices).
- Limitations noted in conclusions:
  - WBES dataset focuses on the formal sector; results capture formal sector firm-level productivity gains only.
  - Structural reforms not supported by IMF programs are not accounted for due to lack of data on successful reforms.
  - Future research suggested: greater granularity to separate impacts of individual reforms.

### Concluding policy-relevant takeaways
- All four reform categories (financial, fiscal, real sector, trade) are associated with positive effects on firm-level productivity growth; real sector reform has the most sizeable impact.
- Being a “strong reformer” is associated with stronger productivity gains (interaction term positive and significant).
- Nonlinearities and conditional factors matter: financial inclusion, distortions, and firm size condition reform effects.
  - Financial reforms: largest benefits accrue to financially excluded firms and to small firms.
  - Fiscal reforms: gains strengthened by financial access but hindered by distortions.
  - Trade reforms: overall positive but sensitive to distortions; impact close to average index estimate.
- Complementarities: most reform pairs are complementary (positive interaction coefficients), implying integrated reform packages can amplify firm-level productivity gains; exception: financial and trade reforms show substitutability in this sample.
- Policy design implication: reforms should be comprehensive, account for complementarities and nonlinearities, and consider firm-level heterogeneity and country developmental stage.

*Italic line: Source: wp1863 (IMF Working Paper) — content as provided.*

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### Appendices

#### Appendix A – Sample balance checks

- Table A.1. Sample balance – Countries under program vs. Countries not under program
  - Countries not under program / Countries under program / p-value (diff ≠ 0)
  - Current account balance (% of GDP): -2.355  (24.378) / -4.986  (5.466) / 0.257
  - Public debt (% of GDP): 79.01  (90.057) / 67.67 (52.44) / 0.191
  - Overall balance (% of GDP): -1.879 (9.328) / -2.513 (3.378) / 0.466
  - Inflation rate (%): 14.005  (46.817) / 7.644  (7.730) / 0.166
  - GDP growth (%): 2.573  (5.338) / 3.207  (4.344) / 0.220
  - Official exchange rate (LCU per US $)): 139.10 5  (306.10 6 ) / 337.3  (473.50) / 0.613
  - Interest payment on external debt (% exports): 3.582  (5.523) / 3.544  (2.706) / 0.942
  - Notes: Public debt and fiscal balance data are from the World Economic Outlook 2017. The other variables are from the World Development Indicators. Standard errors in parentheses.

- Table A.2. Sample balance - Strong reformers vs Weak reformers
  - Top reformer / Weak reformer / p-value (diff ≠ 0)
  - Current account balance (% of GDP): -4.568  (6.203) / -5.389  (4.668) / 0.429
  - Public debt (% of GDP): 66.94 (44.00) / 68.34 (59.50) / 0.3024
  - Overall balance (% of GDP): -2.448 (2.823) / -2.581 (3.902) / 0.831
  - Inflation rate (%): 6.789  (6.500) / 8.549  (8.826) / 0.2454
  - GDP growth (%): 3.532  (4.342) / 2.900  (4.357) / 0.4130
  - Official exchange rate (LCU per US $)): 328.58 (368.24) / 345.75 (559.52) / 0.841
  - Interest payment on external debt (% exports): 3.779  (2.729) / 3.317  (2.687) / 0.357
  - Notes: Public debt and fiscal balance data are from the World Economic Outlook 2017. The other variables are from the World Development Indicators. Standard errors in parentheses.

*Source: wp1863 - REFERENCES*

### Appendix B – Sensitivity analysis

### Appendix B – Sensitivity analysis

### Crisis and economic recovery
- Purpose: distinguish effects of structural reforms from effects of economic recovery, notably the 2008-09 financial crisis.
- Method: include dummy variable taking 1 during 2008-09 financial crisis and 0 otherwise; identify countries officially in crisis using Laeven and Valencia (2012); consider 8-year recovery window following Reinhart and Rogoff (2014).
- Key result: the 2008-09 financial crisis does not alter the positive impact of structural reforms on productivity growth, while the crisis itself has a negative effect on productivity growth.

- Table B.1 (standardized coefficients; multilevel mixed model; robust SEs clustered at country level):
  - Financial reforms: Reforms 0.370*** (0.021); The 2008-2009 financial crisis -12.00*** (0.029); Observations 10,822; R-squared 0.2360
  - Fiscal reforms: Reforms 0.344*** (0.0194); The 2008-2009 financial crisis -3.806*** (0.251); Observations 10,822; R-squared 0.2360
  - Real sector reforms: Reforms 9.674*** (0.546); The 2008-2009 financial crisis -1.912*** (0.345); Observations 10,822; R-squared 0.2360
  - Trade reforms: Reforms 0.266*** (0.0150); The 2008-2009 financial crisis -4.256*** (0.230); Observations 10,822; R-squared 0.2360

- Crisis countries identified (examples from Table B.2):
  - The Democratic Republic of Congo: Currency crisis 2009; Period of structural reforms 2009-2012
  - Dominican Republic: Currency crisis 2003; Sovereign debt restructuring 2005; Periods of structural reforms 2005-2008 and 2005-2008 (two entries)
  - Ghana: Currency crisis 2009; Period of structural reforms 2009-2012
  - Madagascar: Currency crisis 2004; Period of structural reforms 2006-2009
  - Moldavia: Sovereign Debt Restructuring 2002; Period of structural reforms 2006-2009
  - Mongolia: Systemic Banking crisis 2008; Period of structural reforms 2009-2010
  - Ukraine: Systemic Banking crisis 2008; Period of structural reforms 2010-2012

- Table B.3, Panel A (accounting for economic recovery; standardized coefficients):
  - Financial reforms: Reforms 0.986*** (0.0344); Dummy - crisis -2.651*** (0.0630); Observations 10,822; R-squared 0.2360
  - Fiscal reforms: Reforms 0.429*** (0.0150); Dummy - crisis -0.393*** (0.0259); Observations 10,822; R-squared 0.2360
  - Real sector reforms: Reforms 10.74*** (0.375); Dummy - crisis -0.176*** (0.0318); Observations 10,822; R-squared 0.2360
  - Trade reforms: Reforms 0.342*** (0.0120); Dummy - crisis -0.453*** (0.0244); Observations 10,822; R-squared 0.2360

### Additional control variables (capital and investment)
- Rationale: labor productivity is affected by stock of capital and investment; control for Log. Net book value of capital and Log. Investment in capital to avoid omitted variable bias.
- Table B.3, Panel B (standardized coefficients; sample size 2,880; robust SEs):
  - Financial reforms: Reforms 0.244*** (0.063); Log. Net book value of capital 0.020*** (0.006); Log. Investment in capital 0.005 (0.005); Observations 2880; R-squared 0.3470
  - Fiscal reforms: Reforms 0.227*** (0.0432); Log. Net book value of capital 0.018*** (0.006); Log. Investment in capital 0.005 (0.006); Observations 2880; R-squared 0.3470
  - Real sector reforms: Reforms 6.390*** (1.212); Log. Net book value of capital 0.018*** (0.06); Log. Investment in capital 0.005 (0.005); Observations 2880; R-squared 0.3470
  - Trade reforms: Reforms 0.176*** (0.033); Log. Net book value of capital 0.018*** (0.003); Log. Investment in capital 0.005 (0.005); Observations 2880; R-squared 0.3470

### Measuring structural reform: the “min-max” approach
- Alternative index construction: min-max normalization of country total number of successful structural reforms over a 3-year window.
- Re-estimate baseline equation (5) using min-max reform indexes.
- Table B.3, Panel C (standardized coefficients):
  - Financial reforms: Reforms 0.282*** (0.0159); Observations 10,822; R-squared 0.2360
  - Fiscal reforms: Reforms 0.671*** (0.0378); Observations 10,822; R-squared 0.2360
  - Real sector reforms: Reforms 2.043*** (0.115); Observations 10,822; R-squared 0.2360
  - Trade reforms: Reforms 0.253*** (0.0143); Observations 10,822; R-squared 0.2360

### Alternative measures of firm-level productivity
- Value Added (VA) per worker:
  - Computation: annual sales minus costs of raw and energy, normalized by number of employees.
  - Table B.3, Panel D (standardized coefficients; Observations 9. 942; R-squared 0.80):
    - Financial reforms: Reforms 0.116*** (0.007)
    - Fiscal reforms: Reforms 0.125*** (0.008)
    - Real sector reforms: Reforms 3.264*** (0.210)
    - Trade reforms: Reforms 0.0898*** (0.006)

- Total Factor Productivity (TFP):
  - Approach: derive TFP from Cobb-Douglas production function Y = K^α L^β; estimate TFP as residual using ln(Y) = θ + α ln(K) + β ln(L) + γZ + ε; use cost of energy as proxy for unobservable productivity shocks per Levinsohn and Petrin (2003) intuition and Saliola and Seker (2012).
  - Limitations: inability to compute lagged TFP growth because WBES does not report previous net book value of capital; firm-level TFP calculated for a specific year.
  - Table B.3, Panel E (standardized coefficients; Observations 4,965; R-squared 0.3398):
    - Financial reforms: Reforms 0.122*** (0.0271)
    - Fiscal reforms: Reforms 0.114*** (0.0253)
    - Real sector reforms: Reforms 3.204*** (0.709)
    - Trade reforms: Reforms 0.0882*** (0.0165)

- Overall: VA per worker and TFP robustness checks confirm that financial, fiscal, real sector, and trade structural reforms increase firm-level productivity; real sector reforms have the largest impact.

### Alternative methodology: Difference-in-difference (Rajan and Zingales (1998) style)
- Purpose: assess robustness of findings to methodology choice by estimating interaction of reforms with conditional exposure variables using OLS difference-in-difference specification.
- Key patterns (Table B.4; standardized coefficients; robust SEs clustered at country level; Observations 11,807):
  - Financial sector reforms interacting with Financial access:
    - Reforms*Conditional factor -0.103** (0.0452)
    - Conditional factor 0.001 (0.0147)
    - R-squared 0.221
  - Financial sector reforms interacting with Small firms:
    - Reforms*Conditional factor 0.0358 (0.0216)
    - Conditional factor -0.292*** (0.0347)
    - R-squared 0.220
  - Fiscal reforms interacting with Distortions:
    - Reforms*Conditional factor -0.0450*** (0.0160)
    - Conditional factor 0.0656 (0.0147)
    - R-squared 0.221
  - Fiscal sector reforms interacting with Financial access:
    - Reforms*Conditional factor 0.831*** (0.0236)
    - Conditional factor 0.009 (0.0142)
    - R-squared 0.221

- Interpretation: interaction terms statistically significant; firms with financial access benefit less from financial reforms; fiscal reforms benefit firms with financial access more; fiscal reforms yield lower gains for firms facing significant distortions.

### Unsuccessful structural reforms (Not Met) as counterfactual
- Rationale: test whether unsuccessful reforms (not met) affect firm-level labor productivity growth; expectation: no impact or negative impact if successful reforms drive positive effects.
- Estimation: Z-score approach to compute index of unsuccessful structural reforms; same controls as baseline.
- Table B.5 (standardized coefficients; robust SEs clustered at country level):
  - Financial reforms (Not Met): Reforms -1.121*** (0.091); Observations 5,126; R-squared 0.2376
  - Fiscal reforms (Not Met): Reforms 0.705*** (0.044); Observations 8,347; R-squared 0.2516
  - Real sector reforms (Not Met): Reforms -3.975*** (0.308); Observations 7,987; R-squared 0.2535
  - Trade reforms (Not Met): Reforms 0.115* (0.060); Observations 2,615; R-squared 0.1783

- Key findings:
  - Unsuccessful financial and real sector reforms have negative impacts on firm-level productivity:
    - A one standard deviation increase in unsuccessful financial reforms decreases labor productivity growth by 1.121 standard deviation.
    - A one standard deviation increase in unsuccessful real sector reforms decreases labor productivity growth by 3.975 standard deviation.
  - Unsuccessful fiscal and trade structural reforms show positive impacts on labor productivity growth (trade barely significant at 10 percent). The positive fiscal result may reflect externality effects from high proportion of successful fiscal reforms implemented in parallel.

### Low Income Countries
- Table B.6 (standardized coefficients; multilevel mixed model; robust SEs clustered at country level; Observations 10,822; R-squared 0.2608 for each column):
  - Financial reforms: Reforms 1.475*** (0.0407)
  - Fiscal reforms: Reforms 0.438*** (0.0121)
  - Real sector reforms: Reforms 5.432*** (0.150)
  - Trade reforms: Reforms 0.385*** (0.0106)

- Interpretation: in Low Income Countries, structural reforms positively and significantly impact firm-level labor productivity growth, with real sector reforms having the largest standardized coefficient.

*Source: Appendix B – Sensitivity analysis (wp1863).*

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_Source: https://www.imf.org/-/media/files/publications/wp/2018/wp1863.pdf_