## _wp07139

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---

### I. Research question and motivation
- Research question: Why are credit markets in some countries deeper than in others, and what explains cross-country differences in the amount of domestic credit to the private sector (measured as a percentage of GDP)?
- Stylized empirical observation:
  - Correlation between per capita GDP and the credit-to-GDP ratio was as high as 0.8 in a large sample of countries in 2004.
  - Notable deviations at similar income levels (examples: Panama vs. Costa Rica; Malaysia vs. Mexico).
- Motivation: Cultural, institutional, and legal aspects emphasized in recent literature (La Porta and others, 1997, 1998; Jappelli and Pagano, 2002; Stulz and Williamson, 2003; Galindo and Micco, 2004; Djankov, McLiesh, and Shleifer, 2005).

### Links emphasized in literature and by the paper
- Institutional/micro factors:
  - Protection of creditor rights and availability of credit history information are positively associated with higher credit-to-GDP ratios (Djankov, McLiesh, and Shleifer (2005) using panel data on 129 countries).
  - Stronger creditor rights contribute to lower volatility of credit to the private sector (Galindo and Micco (2005)).
- Macroeconomic factors:
  - Macroeconomic stability matters because high inflation erodes real financial assets and raises uncertainty about borrowers’ ability to repay (Moore, 1986).
  - Higher uncertainty reallocates resources away from risky projects, producing credit-constrained equilibria where creditworthy projects fail to obtain financing.
- Gap in the literature:
  - Interaction between macro factors and creditor-rights protections has not been closely analyzed previously.

### Theoretical framing and key mechanisms
- Joint roles:
  - Macroeconomic policies influence dispersion of private-sector project outcomes primarily through variability of relative prices of inputs and outputs (linked to inflation and volatility of the real effective exchange rate).
  - Micro regulation (creditor rights, credit information) affects costs of screening, monitoring, and repossession for delinquent borrowers.
- Interaction effect:
  - The marginal effect of improvements in creditor rights protection declines as the overall level of risk in the economy rises.

### Theoretical model — setup and implications
- Model type: Standard banking loan with monitoring costs, following Williamson (1987). Investment normalized to unity.
- Project return: p_i uniformly distributed on (μ – b; μ + b) with μ (μ > 1) and b (b > 0); variance = 3/2 b (as presented).
- Monitoring cost: Bank incurs project-specific cost c_i γ to learn realized project value; γ_i uniformly distributed on (0; 2(μ – i)). Aggregate creditor-rights parameter c (0 < c ≤ 1) proxies strength of creditor rights (higher c = stronger rights).
- Optimal interest rate (equation (2)):
  - r_i* – 1 = (μ – 1) + b – c_i γ
  - Implications:
    - r_i* increases with μ and with b.
    - r_i* decreases with higher monitoring/repossession costs c_i γ (higher monitoring costs lead banks to lower rates to reduce bankruptcy probability).
- Participation constraint and cutoff (equation (4)):
  - Critical γ* = 2b c [ (1 – i)/(μ – b – 1) ] (as presented)
  - Bank lends to entrepreneurs with γ_i ≤ γ* and rejects those with γ_i > γ*.
- Credit market depth (share of approved applications D) (equation (5)):
  - D = [ i/(b c) – μ ] [ (1 – i)/(μ – b – 1) ]  (as presented)
- Comparative statics (Proposition 1):
  - b ∂D/∂b < 0 (higher project risk reduces depth)
  - c ∂D/∂c > 0 (stronger creditor rights increase depth)
  - c b ∂^2 D / ∂c ∂b < 0 (marginal effectiveness of creditor rights declines with overall risk)

### Empirical approach, data, and specification
- Empirical specification (equation (6)):
  - CREDIT_it = α + β CRI_it + θ CII_it + δ INF_it + φ ERV_it + λ GDP_it + ε_it
  - Variables:
    - CREDIT_it: ratio of credit to the private sector to GDP
    - CRI: creditor rights index (0 to 10)
    - CII: credit information index (0 to 6)
    - INF: inflation
    - ERV: volatility of real effective exchange rate
    - GDP: log PPP-adjusted GDP per capita
- Data:
  - Panel of 120 industrial and developing countries, 1997–2004.
  - REER volatility measured as coefficient of variation of monthly REER over preceding four years.
  - Episodes of hyperinflation (over 50 percent a year) excluded.

### Key empirical estimates and statistics
- Effects on credit-to-GDP:
  - A 1 percentage point increase in inflation → a 1.4 percent of GDP decrease in credit to the private sector.
  - A one-step improvement in creditor rights index → a 5 percent of GDP increase in domestic private credit.
  - A one-step improvement in credit information index → a 2.8 percent of GDP increase in domestic private credit (occasionally significant at the 10 percent level).
  - Doubling GDP per capita → a 17 percent of GDP increase in credit to the private sector.
- Model fit and other variables:
  - Exchange rate volatility had a small and highly statistically insignificant coefficient and was dropped from later specifications.
  - Regression explanatory power: these factors together explain about 65 percent of variation in credit-to-GDP ratios (R2 ~ 0.65).

### Interaction: creditor rights × inflation
- Augmented specification (equations (7)–(8)):
  - CREDIT_it = α + β CRI_it + δ INF_it + η CRI_it * INF_it + θ CII_it + λ GDP_it + ε_it
  - Marginal effect of creditor-rights improvement: ∂CREDIT_it/∂CRI_it = β + η INF_it
- Empirical findings on interaction:
  - The marginal effect of creditor-rights improvements decreases as inflation rises.
  - In Column D estimates:
    - The marginal effect of a one-step improvement in creditor rights is estimated at 8 percent of GDP in the absence of inflation.
    - The statistically significant negative interaction term implies the marginal effect reaches zero at 16 percent inflation (i.e., when INF_it = 16 percent the overall marginal effect ≈ 0).

### Subsample analyses
- Low-inflation vs high-inflation (Table 3):
  - Low-inflation countries: creditor rights and credit information have large, statistically significant positive coefficients.
  - High-inflation countries: coefficients for creditor rights and credit information are smaller and statistically insignificant.
  - Differences between low- and high-inflation subsamples are statistically significant at the 5 percent level.
- Income split (rich vs poor):
  - Creditor-rights and information effects are larger in rich countries but differences are much less pronounced than the low- vs high-inflation split; differences not statistically significant at 10 percent for creditor-rights and information indices.
- Distribution of sample by subsample (Table 4):
  - High inflation: Poor = 39, Rich = 21, Total = 60
  - Low inflation: Poor = 21, Rich = 39, Total = 60
  - Overall total = 120 countries

### Main findings and policy implications
- Main findings:
  - Both strong creditor rights and low overall project risk (proxied by relative price stability / low inflation) are important for financial deepening.
  - Empirically, a one-step improvement in creditor rights from low to medium has approximately the same positive impact on the credit-to-GDP ratio as a permanent 18 percentage point reduction in the rate of inflation.
  - The positive effect of stronger creditor rights on financial deepening is particularly strong in low-inflation countries; as inflation reaches about 15 percent (empirical breakpoint reported as 16 percent in regression inference), improvements in creditor rights no longer have a positive effect on credit-to-GDP.
  - Credit information availability positively affects credit-to-GDP, especially in low-inflation environments.
- Policy implications and sequencing:
  - Both micro-level regulation (strengthening creditor rights, improving credit information systems) and macroeconomic stabilization (reducing inflation and relative price variability) matter for financial deepening.
  - Prioritization:
    - In high-inflation environments: controlling inflation and attaining macroeconomic stability should be given priority, because high macro risk undermines effectiveness of micro-level reforms.
    - In lower-inflation environments (after macro stability is achieved): focus should shift to improving creditor rights protection and credit information management to deepen financial markets.

*Source: _wp07139 (PDF chapter/section).*

### References .............................................................................................................

### _wp07139 - References

### I. Introduction — research question and motivation
- Research question: Why are credit markets in some countries deeper than in others, and what explains cross-country differences in the amount of domestic credit to the private sector (measured as a percentage of GDP)?
- Stylized empirical observation:
  - Correlation between per capita GDP and the credit-to-GDP ratio was as high as 0.8 in a large sample of countries in 2004.
  - Notable deviations at similar income levels (example comparisons cited: Panama vs. Costa Rica; Malaysia vs. Mexico).
- Motivation for going beyond income: cultural, institutional, and legal aspects have been emphasized in recent literature (La Porta and others, 1997, 1998; Jappelli and Pagano, 2002; Stutz and Williamson, 2003; Galindo and Micco, 2004; Djankov, McLiesh, and Shleifer, 2005).

### Links emphasized in literature and by the paper
- Institutional/micro factors:
  - Protection of creditor rights and availability of credit history information are positively associated with higher credit-to-GDP ratios (Djankov, McLiesh, and Shleifer (2005) using panel data on 129 countries).
  - Stronger creditor rights also contribute to lower volatility of credit to the private sector (Galindo and Micco (2005)).
- Macroeconomic factors:
  - Macroeconomic stability matters because high inflation erodes real financial assets and raises uncertainty about borrowers’ ability to repay (Moore, 1986).
  - Higher uncertainty can reallocate resources away from risky projects, producing credit-constrained equilibria where creditworthy projects fail to obtain financing.
- Gap in the literature:
  - While prior work documents impacts of macro factors and creditor rights separately, the interaction between the two and their joint importance has not been closely analyzed.

### Theoretical framing and key mechanisms
- Joint roles:
  - Macroeconomic policies influence the dispersion of outcomes of private sector projects primarily through variability of relative prices of inputs and outputs (linked to inflation and volatility of the real effective exchange rate).
  - Micro regulation (creditor rights, credit information) affects costs of screening, monitoring, and repossession for delinquent borrowers.
- Interaction effect:
  - Macro and micro factors interact; the marginal effect of improvements in creditor rights protection declines as the overall level of risk in the economy rises.

### Empirical approach and headline empirical findings
- Data and sample:
  - Panel data on 120 countries in 1997–2004.
- Main empirical results:
  - Stronger creditor rights and lower inflation are associated with higher credit-to-GDP ratios.
  - The marginal effect of stronger creditor rights is declining with higher inflation, hitting zero as inflation rate reaches approximately 16 percent.
- Subsample evidence:
  - Estimated differences in coefficients across high-inflation and low-inflation country subsamples suggest priorities differ by inflation environment.

### Policy implications and recommendations (as presented)
- In high-inflation economic environments:
  - Controlling inflation and attaining macroeconomic stability should be given priority, because high macro risk undermines the effectiveness of micro-level reforms.
- In lower-inflation environments (after macro stability is achieved):
  - Focus should shift to improving creditor rights protection and credit information management to deepen financial markets.

*Source: _wp07139 - References (PDF chapter/section).*

### conclusions.

### _wp07139 - conclusions

### Determinants of financial deepening: creditor rights and relative price stability
- Creditor rights: Strong creditor rights, supported by appropriate regulation and efficient law enforcement, facilitate repossession of assets, reduce monitoring costs, and improve initial screening of borrowers.
- Information: Efficient exchange of information (credit agencies, credit history) reduces initial screening costs and promotes credit market development.
- Relative price stability: Lower relative price variability reduces project risk, lowers the costs associated with screening, monitoring, and repossession, and therefore supports deeper credit markets.
- Interaction: Stronger creditor rights have a larger impact on availability of credit when the overall level of risk is lower, and vice versa.

### Theoretical model — setup and implications
- Model type: Standard banking loan with monitoring costs, following Williamson (1987). Investment normalized to unity. Project return p_i uniformly distributed on (μ – b; μ + b) with μ (μ > 1) and b (b > 0); variance = 3/2 b (as presented).
- Monitoring cost: Bank incurs project-specific cost c_i γ to learn realized project value; γ_i uniformly distributed on (0; 2(μ – i)). Aggregate creditor-rights parameter c (0 < c ≤ 1) proxies strength of creditor rights (higher c = stronger rights).
- Optimal interest rate (equation (2)):
  - r_i* – 1 = (μ – 1) + b – c_i γ
  - Implications:
    - r_i* increases with μ and with b.
    - r_i* decreases with higher monitoring/repossession costs c_i γ (higher monitoring costs lead banks to lower rates to reduce bankruptcy probability).
- Participation constraint and cutoff (equation (4)):
  - Critical γ* = 2b c [ (1 – i)/(μ – b – 1) ] (as presented in text)
  - Bank lends to entrepreneurs with γ_i ≤ γ* and rejects those with γ_i > γ*.
- Credit market depth (share of approved applications D) (equation (5)):
  - D = [ i/(b c) – μ ] [ (1 – i)/(μ – b – 1) ]  (as presented)
- Comparative statics (Proposition 1):
  - b ∂D/∂b < 0 (higher project risk reduces depth)
  - c ∂D/∂c > 0 (stronger creditor rights increase depth)
  - cb ∂^2 D / ∂c ∂b < 0 (marginal effectiveness of creditor rights declines with overall risk)

### Empirical evidence — strategy, data, and key estimates
- Empirical specification (equation (6)):
  - CREDIT_it = α + β CRI_it + θ CII_it + δ INF_it + φ ERV_it + λ GDP_it + ε_it
  - Variables:
    - CREDIT_it: ratio of credit to the private sector to GDP
    - CRI: creditor rights index (0 to 10)
    - CII: credit information index (0 to 6)
    - INF: inflation
    - ERV: volatility of real effective exchange rate
    - GDP: log PPP-adjusted GDP per capita
- Data:
  - Panel of 120 industrial and developing countries, 1997–2004.
  - REER volatility measured as coefficient of variation of monthly REER over preceding four years.
  - Episodes of hyperinflation (over 50 percent a year) excluded.
- Key empirical estimates (from Table 2 and descriptive text):
  - A 1 percentage point increase in inflation → a 1.4 percent of GDP decrease in credit to the private sector.
  - A one-step improvement in creditor rights index → a 5 percent of GDP increase in domestic private credit.
  - A one-step improvement in credit information index → a 2.8 percent of GDP increase in domestic private credit (occasionally significant at the 10 percent level).
  - Doubling GDP per capita → a 17 percent of GDP increase in credit to the private sector.
  - Exchange rate volatility had a small and highly statistically insignificant coefficient and was dropped from later specifications.
  - Regression explanatory power: these factors together explain about 65 percent of variation in credit-to-GDP ratios (R2 ~ 0.65).
- Interaction between creditor rights and inflation (equations (7)–(8)):
  - Augmented specification: CREDIT_it = α + β CRI_it + δ INF_it + η CRI_it * INF_it + θ CII_it + λ GDP_it + ε_it
  - Marginal effect of creditor-rights improvement: ∂CREDIT_it/∂CRI_it = β + η INF_it
  - Empirical finding: the marginal effect of creditor-rights improvements decreases as inflation rises. In Column D estimates:
    - The marginal effect of a one-step improvement in creditor rights is estimated at 8 percent of GDP in the absence of inflation.
    - Statistically significant negative interaction term implies the marginal effect reaches zero at 16 percent inflation (i.e., when INF_it = 16 percent the overall marginal effect ≈ 0).
- Subsample analysis (low-inflation vs high-inflation; Table 3):
  - Low-inflation countries: creditor rights and credit information have large, statistically significant positive coefficients.
  - High-inflation countries: coefficients for creditor rights and credit information are smaller and statistically insignificant.
  - Differences between low- and high-inflation subsamples are statistically significant at the 5 percent level.
  - Comparisons by income (rich vs poor): creditor-rights and information effects are larger in rich countries but differences are much less pronounced than the low- vs high-inflation split; differences not statistically significant at 10 percent for creditor-rights and information indices.
- Distribution of countries by subsamples (Table 4):
  - High inflation: Poor = 39, Rich = 21, Total = 60
  - Low inflation: Poor = 21, Rich = 39, Total = 60
  - Overall total = 120 countries

### Main findings and policy implications
- Main findings:
  - Both strong creditor rights and low overall project risk (proxied by relative price stability / low inflation) are important for financial deepening.
  - Empirically, a one-step improvement in creditor rights from low to medium has approximately the same positive impact on the credit-to-GDP ratio as a permanent 18 percentage point reduction in the rate of inflation.
  - The positive effect of stronger creditor rights on financial deepening is particularly strong in low-inflation countries; as inflation reaches about 15 percent (empirical breakpoint reported as 16 percent in regression inference), improvements in creditor rights no longer have a positive effect on credit-to-GDP.
  - Credit information availability positively affects credit-to-GDP, especially in low-inflation environments.
- Policy implications and sequencing:
  - Both micro-level regulation (strengthening creditor rights, improving credit information systems) and macroeconomic stabilization (reducing inflation and relative price variability) matter for financial deepening.
  - Prioritization: In high-inflation environments, policy efforts should first focus on controlling inflation and ensuring macroeconomic stability. Once relative price stability is achieved, attention should shift to strengthening creditor rights and improving credit information management.

*Source: _wp07139 - conclusions.*

### REFERENCES

### _wp07139 - REFERENCES

### References
- Aghion, Philippe, and Patrick Bolton, 1992, “An Incomplete Contracts Approach to Corporate Bankruptcy,” Review of Economic Studies, Vol. 59, pp. 473–94.
- Beck, Thorsten, Asli Demirgüç-Kunt, and Ross Levine, 2000, "A New Database on Financial Development and Structure," World Bank Economic Review, Vol. 14, pp. 597–605.
- Cagan, Phillip, 1956, “The Monetary Dynamics of Hyperinflation,” in Studies in the Quantity Theory of Money, ed. by Milton Friedman (Chicago: University of Chicago Press), pp. 25–117.
- Debelle, Guy, and Owen Lamont, 1997, “Relative Price Variability and Inflation: Evidence from U.S. Cities,” Journal of Political Economy, Vol. 105, No 1, pp. 132–52.
- Djankov, Simeon, Caralee McLiesh, and Andrei Shleifer, 2005, “Private Credit in 129 Countries,” National Bureau of Economic Research Working Paper 11078.
- Druck, Pablo, and Pietro Garibaldi, 2000, “Inflation Risk and Portfolio Allocation in the Banking Sector,” Buenos Aires, CEMA University Working Paper 181.
- Galindo, Arturo, and Alejandro Micco, 2004, “Creditor Protection and Financial Markets: Empirical Evidence and Implications for Latin America,” Federal Reserve Bank of Atlanta Economic Review, Q2, pp. 29–37.
- Galindo, Arturo, and Alejandro Micco, 2005, “Creditor Protection and Credit Volatility,” IDB Working Paper 528.
- Jaffe, Dwight M., and Thomas Russell, 1976, “Imperfect Information, Uncertainty and Credit Rationing,” Quarterly Journal of Economics, Vol. 90, pp. 651–66.
- Jappelli, Tullio, and Marco Pagano, 2002, “Information Sharing, Lending, and Defaults: Cross-country Evidence,” Journal of Banking and Finance, Vol. 26, pp. 2017–45.
- Jaramillo, Carlos F., 1999, “Inflation and Relative Price Variability: Reinstating Parks’ Results,” Journal of Money, Credit and Banking, Vol. 31, No 3, pp. 375–85.
- Lach, Saul, and Daniel Tsiddon, 1992, “The Behavior of Prices and Inflation: An Empirical Analysis of Disaggregated Price Data,” Journal of Political Economy, Vol. 100, No. 2, pp. 349–89.
- La Porta, Rafael, Florencio Lopez-de-Silanes, Andrei Shleifer, and Robert W. Vishny, 1997, “Legal Determinants of External Finance,” Journal of Finance, Vol. 52, pp. 1131–50.
- La Porta, Rafael, Florencio Lopez-de-Silanes, Andrei Shleifer, and Robert W. Vishny, 1998, “Law and Finance,” Journal of Political Economy, Vol. 106, No 6, pp. 1113–55.
- Moore, B.J., 1986, “Inflation and Financial Deepening,” Journal of Development Economics, Vol. 20, pp. 125–33.
- Stiglitz, Joseph, and Andrew Weiss, 1981, “Credit Rationing in Market with Imperfect Information,” American Economic Review, Vol. 71, pp. 393-410.
- Stulz, Rene, and Rohan Williamson, 2003, “Culture, Openness, and Finance,” Journal of Financial Economics, Vol. 70, pp. 313–49.
- Townsend, Robert M., 1979, “Optimal Contracts and Competitive Markets with Costly State Verification,” Journal of Economic Theory, Vol. 21, pp. 265–93.
- Williamson, Stephen D., 1987, “Costly Monitoring, Loan Contracts, and Equilibrium Credit Rationing,” Quarterly Journal of Economics, Vol. 102, No 1, pp. 135–46.

### Appendix — Key derivations, conditions, and propositions
- Derivation of equation (2):
  - ρ_i = r_i ⎟⎟⎠⎞ ⎜⎜⎝⎛ − ∫_{−i}^{r} b dppf μ)(1 + ∫_{−i}^{r} b dpppf μ)( – c_i γ ∫_{−i}^{r} b dppf μ)( = b^2 1 ⎟⎟⎠⎞ ⎜⎜⎝⎛ ⎟⎠⎞ ⎜⎝⎛ − −−+ ⎟⎠⎞ ⎜⎝⎛ −++− 2 )( 2 2 b c b r c b r i i i i μ γ μ γ μ
  - First-order condition for profit maximization:
    - ∂ρ_i / ∂r_i = b c br i i 2 γ μ−++− = 0
    - Hence r_i* = b + μ – c_i / γ.
  - Second-order condition:
    - ∂^2 ρ_i / ∂r_i^2 = – b^2 1 < 0

- Derivation of equation (4):
  - ρ_i (r_i*, γ_i) – i = b^2 1 ⎟⎟⎟⎟⎠⎞ ⎜⎜⎜⎜⎝⎛ ⎟⎠⎞ ⎜⎝⎛ − −−+ ⎟⎠⎞ ⎜⎝⎛ −++ ⎟⎠⎞ ⎜⎝⎛ −+ − 2 )( 2 2 2 b c b c b c b i i i i μ γ μ γ μ γ μ – i = = ()(44 4 1 22 2 i b c b c b c i i −+− μ γ γ ≥ 0
  - If c_i γ ≥ 2b, the costs of monitoring and repossession exceed the difference between the best and the worst outcome of the project. Therefore the bank will have to assume that the project always fails and will refrain from lending to customers with γ_i ≥ 2 b c.

- Nontrivial cases:
  - If γ_i < 2 b c and b > μ – i, then solution to inequality is γ_i ≤ γ*, where:
    - γ* = 2 b c ⎟⎟⎠⎞ ⎜⎜⎝⎛ − −− b i μ 11

- Derivation of equation (5):
  - D = )(2 * i−μ γ = i b c − μ ⎟⎟⎠⎞ ⎜⎜⎝⎛ − −− b i μ 11
  - D is well-defined (i.e. D∈[0; 1]), since +−→)( lim_{ibμ} i b c − μ ⎟⎟⎠⎞ ⎜⎜⎝⎛ − −− b i μ 11 = c and 0 < c ≤ 1.

- Proof of proposition 1 (partial derivatives and signs preserved):
  - b D ∂/∂ = b i i c − −− μ μ 1)( ⎟⎟⎠⎞ ⎜⎜⎝⎛ − +− − − b i b i μ μ μ 212 = – b i i b i c − −− ⎟⎟⎠⎞ ⎜⎜⎝⎛ − −− μ μ μ 1)( 11 2 < 0
  - c D ∂/∂ = i b − μ ⎟⎟⎠⎞ ⎜⎜⎝⎛ − −− b i μ 11 > 0
  - c b D ∂∂ ∂^2 = – b i i b i − −− ⎟⎟⎠⎞ ⎜⎜⎝⎛ − −− μ μ μ 1)( 11 2 < 0

### Table A1 — Countries in the Sample
- Albania
- Algeria
- Angola
- Argentina
- Armenia
- Australia
- Austria
- Bangladesh
- Belgium
- Benin
- Bolivia
- Botswana
- Brazil
- Bulgaria
- Burkina Faso
- Burundi
- Cambodia
- Cameroon
- Canada
- Central African Republic
- Chad
- Chile
- China, Hong Kong
- Colombia
- Congo, Democratic Rep.
- Congo
- Costa Rica
- Côte d'Ivoire
- Croatia
- Czech Republic
- Denmark
- Dominican Republic
- Ecuador
- Egypt
- El Salvador
- Ethiopia
- Finland
- France
- Georgia
- Germany
- Ghana
- GreeceNorway
- Guatemala
- Haiti
- Honduras
- Hong KongLithuania
- IndiaParaguay
- Indonesia
- IrelandPoland
- Israel
- ItalyRomania
- Jamaica
- Japan
- Jordan
- Kazakhstan
- Kenya
- KuwaitSingapore
- Kyrgyz Republic
- LaoSlovenia
- Latvia
- Lesotho
- Libya
- Lithuania
- Macedonia
- Madagascar
- Malawi
- Mali
- Mauritania
- MexicoTunisia
- Moldova
- Mongolia
- Morocco
- Mozambique
- Namibia
- NepalVenezuela
- Netherlands
- New Zealand
- Nicaragua
- Niger
- Nigeria
- Oman
- Pakistan
- Panama
- Papua New Guinea
- Peru
- Philippines
- Poland
- Portugal
- Romania
- Russia
- Rwanda
- Saudi Arabia
- Senegal
- Sierra Leone
- Singapore
- Slovak Republic
- Slovenia
- South Africa
- Spain
- Sri Lanka
- Sweden
- Switzerland
- Syrian Arab Republic
- Tanzania
- Thailand
- Togo
- Tunisia
- Turkey
- Uganda
- United Kingdom
- United States
- Uruguay
- Vietnam
- Yemen
- Zambia
- Zimbabwe

*Source: Authors.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2007/_wp07139.pdf_