## _wp1632

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---

### I. Introduction and research objective
- Literature described as "still nascent."
- Paper assesses "the impact of the different dimensions of financial development on both the level of income inequality and the level of poverty," using "a large sample of 143 countries taken from the period 1961 to 2011."

### Theoretical perspectives on finance and inequality
- Greenwood and Jovanovic (1990)
  - Predict "a nonlinear relationship between finance and inequality," specifically an "inverted-U relationship" where early-stage financial access favors the rich (fixed cost of joining the financial coalition), widening inequality; later broader access reduces inequality.
- Galor and Zeira (1993) and Galor and Moav (2004)
  - Posit "a linear relationship between financial development and income distribution," arguing "financial deepening eases credit constraints, which benefits low-income groups through the channels of human capital and capital accumulation."

### Data and methodology
- Sample and period
  - 143 countries; period 1961 to 2011.
- Key dependent variables
  - Income inequality: Gini coefficient scaled from 0 to the 100th percentile.
  - Poverty: poverty gap index (average income shortfall of the poor from the poverty line of $1.25 a day).
- Financial development dimensions and indicators (five dimensions, 10 variables from GFDD)
  - Access: bank accounts per 1,000 adults; value traded of the top 10 trading companies to total value traded.
  - Depth: banks’ private credit to GDP; stock market total value traded to GDP.
  - Efficiency: net interest margin; stock market turnover ratio (stock traded/capitalization).
  - Stability: ratio of regulatory capital to risk-weighted assets; volatility of the stock price index.
  - Liberalization: domestic liberalization (aggregate index of credit control, interest rate control, entry barriers, privatization); external liberalization (consolidated foreign claims of BIS-reporting banks to GDP).
- Controls and expected signs
  - Real GDP per capita (log): expected negative.
  - Government expenditures to GDP: expected negative.
  - Trade openness: expected negative.
  - Inflation: expected positive.
- Estimation strategy
  - Baseline regressions for Gini and poverty gap with FD (10 indicators) and controls.
  - IV regressions to address endogeneity/reverse causation:
    - Instruments: lagged values (second lags and higher) and structural instruments (ethnic fractionalization, linguistics, religious composition, legal systems).
    - Hansen’s J-test used to check over-identifying restrictions; LM under-identification test used for identification.
  - Heterogeneity analysis by low-income, middle-income, and high-income groups via interaction terms.
  - Institutional quality: rule of law used; interactions test governance effects.
  - Robustness: re-estimation using non-overlapping five-year average data.

### Key descriptive statistics and correlations (selected)
- Table 1 — Summary statistics (selected variables)
  - Gini coefficient: Obs 1759; Mean 39.39; sd 10.91; Min 15.90; Max 76.70
  - Poverty gap: Obs 804; Mean 7.30; sd 10.34; Min 0.00; Max 63.34
  - Log GDP per capita: Obs 7885; Mean 7.63; sd 1.60; Min 4.00; Max 11.59
  - Inflation: Obs 6438; Mean 33.82; sd 487.15; Min -21.68; Max 24411.00
  - Trade openness: Obs 7427; Mean 76.83; sd 49.13; Min 0.31; Max 460.47
  - Bank accounts per 1,000 adults: Obs 434; Mean 333.97; sd 276.46; Min 0.72; Max 988.15
  - Private credit to GDP (%): Obs 5844; Mean 35.91; sd 35.63; Min 0.12; Max 434.09
  - Net interest margin (%): Obs 3807; Mean 4.68; sd 3.48; Min -12.01; Max 40.63
  - Regulatory capital to risk-weighted assets (%): Obs 1276; Mean 15.77; sd 5.23; Min 2.50; Max 48.60
  - External financial liberalization (%): Obs 4482; Mean 36.07; sd 75.59; Min 0.01; Max 957.14
- Table 2 — Selected correlations
  - Gini with Poverty gap: 0.18
  - Gini with Bank accounts per 1,000 adults: -0.28
  - Gini with Private credit to GDP (%): -0.24
  - Gini with Net interest margin (%): 0.19
  - Poverty gap with Bank accounts per 1,000 adults: -0.49
  - Bank accounts per 1,000 adults with Private credit to GDP (%): 0.71

### Empirical results — main findings and quantitative estimates
- General pattern
  - Most financial variables negatively correlated with the Gini coefficient and the poverty gap, except some liberalization measures and inflation which suggest widening inequality.
- Financial access
  - Bank accounts per 1,000 adults reduces income inequality:
    - Coefficients: -0.022*** (OLS, Gini) and -0.019*** (IV, Gini).
  - Poverty impact:
    - Coefficients: -0.007* (OLS, Poverty gap) and -0.007* (IV, Poverty gap).
    - "An additional banking account opened per 1,000 people tends to reduce the poverty gap by a percentage point of 0.007."
  - Market access (value traded in top 10 trading companies) shows limited effect on inequality and no significant poverty-reducing coefficients.
- Financial depth
  - Banks’ private credit to GDP (%):
    - Coefficients: -0.045*** (OLS, Gini) and -0.041*** (IV, Gini).
    - Poverty: a 1 percentage point increase in private credit to GDP tends to reduce the poverty gap by a percentage point of 0.019.
    - Quantified inequality effect: "A 1 percentage point increase in private credit to GDP tends to reduce the Gini coefficient by more than 0.041%."
  - Stock market total value traded to GDP (%):
    - Negative and significant coefficients for both Gini and poverty gap (examples: -0.019*, -0.022** in Gini specifications).
- Financial efficiency
  - Net interest margin (%):
    - Positive coefficients associated with higher inequality: 0.359*** (OLS, Gini) and 0.440** (IV, Gini).
    - "A reduction of 1 percentage point in the net interest margin can reduce inequality by a percentage point of 0.44."
  - Stock market turnover ratio (%):
    - Negative and significant in all regressions.
    - "A 1 percent increase in the stock market turnover ratio can reduce the Gini coefficient by a percentage point of 0.055 (Column 4), and reduce the poverty gap by a percentage point of 0.016."
- Financial stability
  - Regulatory capital to risk-weighted assets (%):
    - Coefficients: -0.238*** (OLS, Gini) and -0.375*** (IV, Gini).
    - "A 1 percent increase in the ratio of regulatory capital to risk-weighted assets can lower the Gini coefficient and poverty gap by percentage points of 0.375 and 0.342, respectively."
  - Stock price volatility associated with worsening income distribution.
- Financial liberalization
  - Domestic financial liberalization:
    - Coefficients: 0.479*** (OLS, Gini) and 0.501*** (IV, Gini) — suggests worsening Gini; not significant on poverty gap in main specifications.
  - External financial liberalization (consolidated foreign claims of BIS-reporting banks to GDP):
    - Coefficients: 0.022*** and 0.024*** (Gini specifications); associated with increases in both inequality and poverty.
- Controls
  - GDP per capita, government consumption, and trade openness negatively correlated with inequality and poverty.
  - Inflation positively correlated with inequality and poverty.
- Examples from selected tables (significance: * p<0.10, ** p<0.05, *** p<0.01)
  - Table 3: Bank accounts per 1,000 adults: -0.022*** (OLS, Gini); -0.007* (OLS, Poverty gap).
  - Table 4: Private credit to GDP (%): -0.045*** (OLS, Gini); Government Consumption: -0.500*** (Gini).
  - Table 5: Net Interest Margin (%): 0.359*** (OLS, Gini); Stock market turnover ratio (%): -0.037*** (OLS, Gini).
  - Table 6: Regulatory capital to risk-weighted assets (%): -0.238*** (OLS, Gini); Volatility of stock price index: -0.043*** (OLS, Poverty gap) in one specification.
  - Table 7: Domestic financial liberalization: 0.479*** (OLS, Gini); External financial liberalization: 0.022*** (Gini).

### Heterogeneity by country income level and institutional quality
- Income-level heterogeneity
  - Generally similar finance–inequality relationships across income groups, with notable exceptions.
  - Example: effect of private credit on Gini:
    - High-income group: a 1 percentage point increase in private credit reduces the Gini by a percentage point of 0.059.
    - Low-income group: the same effect increases the Gini by a percentage point of 0.029 (difference 0.088-0.059=0.029 noted in text).
  - Poverty reduction effects vary across income groups but are not consistently conclusive.
- Institutional quality interactions (Rule of Law)
  - Stronger rule of law can amplify favorable effects of financial efficiency and bank stability on reducing inequality and poverty in some specifications.
  - Improving rule of law can reduce the inequality-worsening effect of financial liberalization in some specifications.
  - Examples:
    - Table 10 (Column 5): interaction and finance terms both positive and significant for net interest margin effect — lower interest margins reduce inequality and effect is larger with stronger rule of law.
    - Table 11 (Columns 6 and 7): better rule of law tends to intensify favorable effects of market efficiency and bank stability on poverty reduction.
  - Reported Rule of Law coefficients include values such as -10.183, -7.123, -3.011***, -5.046***; FD*rule of law coefficients include values such as 0.028, -0.098, -0.047* depending on proxy.

### Robustness and instrument validity
- Robustness
  - Five-year average regressions largely confirm initial annual results (Tables 12 and 13).
  - Examples in 5-year averages:
    - Gini 5-year average: Private credit to GDP coefficient -0.067***; Stock market turnover ratio -0.069***; External financial liberalization 0.030***.
    - Poverty gap 5-year average: Log GDP per capita -4.605***; Bank accounts per 1,000 adults -0.008**; Regulatory capital to risk-weighted assets -0.404***; Domestic financial liberalization 0.040*** in one specification.
- Instrument validity
  - Hansen’s J-Statistics: unable to reject the null that instruments are uncorrelated with error terms for all IV regressions reported; instruments considered appropriate.

### Conclusions and policy recommendations
- Core conclusions
  - Most financial development dimensions (access, depth, efficiency, stability) help reduce income inequality and poverty on average.
  - External financial liberalization tends to widen income inequality and poverty on the global average.
  - Banking sector development exerts a stronger impact on income distribution and poverty than stock market development.
  - Per capita income, government expenditure, and trade openness help reduce inequality and poverty; inflation harms the poor.
- Policy implications
  - Steer financial system development in a pro-growth and pro-poor direction.
  - Encourage reforms to:
    - Expand financial access and depth.
    - Enhance financial efficiency and stability.
    - Relax credit and interest controls where appropriate.
    - Improve banking and securities market supervision.
  - Proceed carefully with capital account (external) liberalization:
    - Design and sequence capital account liberalization in a stable macroeconomic environment to avoid offsetting poverty-reducing gains from other financial-sector improvements.
  - Strengthen regulatory systems and financial infrastructure:
    - Improve credit information systems, collateral regimes, and insolvency regimes to limit risky bank behavior.
  - Prioritize banking sector development when the goal is poverty and income inequality alleviation.
- Further research
  - Focus on the policy settings and conditions under which financial liberalization could reduce poverty and income inequality.

*Source: Appendix 1: Variable Definition and Data Source and Section 4 conclusion excerpts, _wp1632 (pages excerpt).*

### Appendix 1: Variable Definition and Data Source ..................................................................27

### Appendix 1: Variable Definition and Data Source

### I. Introduction and research objective
- The literature on the nexus of financial development and income distribution is described as "still nascent."
- The paper assesses "the impact of the different dimensions of financial development on both the level of income inequality and the level of poverty," using "a large sample of 143 countries taken from the period 1961 to 2011."

### Theoretical perspectives on finance and inequality
- Greenwood and Jovanovic (1990):
  - Predict "a nonlinear relationship between finance and inequality," specifically an "inverted-U relationship" where at early stages only the rich can access financial services because of the "fixed cost of joining the financial coalition," widening income inequality; as the economy develops, financial access becomes more widespread and inequality declines.
- Galor and Zeira (1993) and Galor and Moav (2004):
  - Posit "a linear relationship between financial development and income distribution," arguing "financial deepening eases credit constraints, which benefits low-income groups through the channels of human capital and capital accumulation."

### Empirical evidence and measures used in prior work
- Cross-country empirical studies cited:
  - Beck and others (2004), Beck and others (2007), Honohan (2004), Li and others (1998), and Rajan and Zingales (2003) find that "expanding private credit can stimulate income growth for the poorest quintiles and reduce income inequality," which "strongly refut[es]" Greenwood and Jovanovic (1990).
  - A common measure used in these studies is "the ratio of private credit to GDP" as "a measure of financial development," which the paper notes "covers only one dimension of financial development: financial system depth while overlooking access, efficiency, and stability."
- Studies incorporating other dimensions:
  - Claessens and Perotti (2007) and Demirguc-Kunt and others (2008) find "the importance of access to finance in reducing poverty and inequality."
  - Jeanneney and Kpodar (2011) establish that "financial instability worsens poverty."
  - Kunieda and others (2011) find that "financial integration aggravates income inequality by benefiting the most privileged."
  - Furceri and Loungani (2015) find that "liberalizing domestic financial systems can aggravate income inequality, both in the short and medium run."

### Key findings reported for the global sample
- Three interrelated findings on the global sample are summarized:
  - "Strengthening financial access, depth, stability, and efficiency contributes to reducing income inequality and poverty, which is robust to different datasets and measurements."
  - "Financial sector liberalization, particularly capital account liberalization, widens inequality and the poverty gap."
  - "Financial institution development exerts a stronger impact on income distribution and poverty than financial market development."

### Structure of the paper (as described)
- Section 2 describes "the data and methodology."
- Section 3 presents "the empirical results as well as the robustness checks."

*Source: Appendix 1: Variable Definition and Data Source (pages excerpt), _wp1632 - Appendix 1: Variable Definition and Data Source.*

### Section 4 offers a conclusion.

### _wp1632 - Section 4 offers a conclusion.

### Data and methodology
- Sample and period
  - Data on 143 countries, both developing and developed.
  - Sample spans from 1961 to 2011.
- Key dependent variables
  - Income inequality: Gini coefficient scaled from 0 to the 100th percentile.
  - Poverty: poverty gap index (average income shortfall of the poor from the poverty line of $1.25 a day).
- Financial development dimensions and indicators (five dimensions, 10 variables from GFDD)
  - Access: bank accounts per 1,000 adults; value traded of the top 10 trading companies to total value traded.
  - Depth: banks’ private credit to GDP; stock market total value traded to GDP.
  - Efficiency: net interest margin; stock market turnover ratio (stock traded/capitalization).
  - Stability: ratio of regulatory capital to risk-weighted assets; volatility of the stock price index.
  - Liberalization: domestic liberalization (aggregate index of credit control, interest rate control, entry barriers, privatization); external liberalization (consolidated foreign claims of BIS-reporting banks to GDP).
- Controls
  - Real GDP per capita (log), government expenditures to GDP, trade openness, inflation.
  - Expected signs: GDP per capita negative; government expenditure and trade openness negative; inflation positive.
- Estimation strategy
  - Baseline regressions for Gini and poverty gap with FD (10 indicators) and controls.
  - Address endogeneity/reverse causation using IV regressions:
    - Instruments: lagged values (second lags and higher) and structural instruments (ethnic fractionalization, linguistics, religious composition, legal systems).
    - Hansen’s J-test used to check over-identifying restrictions; LM under-identification test used for identification.
  - Heterogeneity analysis
    - Countries divided into low-income, middle-income, and high-income groups using interaction terms.
  - Institutional quality
    - Rule of law used as indicator; interaction terms test how governance modifies finance–inequality–poverty links.
  - Robustness
    - Re-estimation using non-overlapping five-year average data confirms most annual results.

### Empirical results — main findings and quantitative estimates
- General correlations
  - Most financial variables are negatively correlated with the Gini coefficient and the poverty gap, except some liberalization measures and inflation which suggest widening inequality.
- Financial access
  - Increasing bank accounts per 1,000 adults reduces income inequality (OLS and IV).
  - An additional banking account opened per 1,000 people tends to reduce the poverty gap by a percentage point of 0.007.
  - Value traded in the top 10 trading companies (market access) is less likely to affect income inequality and shows no significant poverty-reducing coefficients.
- Financial depth
  - Banks’ private credit to GDP: coefficients negative and highly significant at the 1 percent level for both inequality and poverty.
    - A 1 percentage point increase in private credit to GDP tends to reduce the Gini coefficient by more than 0.041%.
    - A 1 percentage point increase in private credit to GDP tends to reduce the poverty gap by a percentage point of 0.019.
  - Stock market total value traded to GDP: negative and significant coefficients for both Gini and poverty gap.
- Financial efficiency
  - Net interest margin: positive coefficients (less efficiency implies higher inequality); significant in Gini regressions.
    - A reduction of 1 percentage point in the net interest margin can reduce inequality by a percentage point of 0.44.
  - Stock market turnover ratio: negative and significant in all regressions.
    - A 1 percent increase in the stock market turnover ratio can reduce the Gini coefficient by a percentage point of 0.055 (Column 4), and reduce the poverty gap by a percentage point of 0.016.
- Financial stability
  - Stability of financial institutions (regulatory capital to risk-weighted assets) reduces inequality and poverty.
    - A 1 percent increase in the ratio of regulatory capital to risk-weighted assets can lower the Gini coefficient and poverty gap by percentage points of 0.375 and 0.342, respectively.
  - Stock price volatility associated with worsening income distribution.
- Financial liberalization
  - Domestic financial liberalization: positive coefficients suggest aggregation of credit control, interest rate control, entry barriers, and privatization indices can significantly worsen the Gini coefficient (not significant on poverty gap).
  - External financial liberalization: consolidated foreign claims of BIS-reporting banks to GDP (%) associated with increases in both inequality and poverty.
- Income-level heterogeneity
  - In most cases finance–inequality relationships are similar across income groups, but notable exceptions exist.
    - Example: a 1 percentage point increase in private credit reduces the Gini by a percentage point of 0.059 in the high-income group; the same effect increases the Gini by a percentage point of 0.029 in low-income countries (0.088-0.059=0.029), indicating financial depth affects inequality differently by income level.
  - Poverty reduction effects of financial indicators vary across income groups, but differences are not consistently conclusive.
- Institutional quality interactions
  - Stronger rule of law can amplify favorable effects of financial efficiency and bank stability on reducing inequality and poverty in some specifications.
  - Improving rule of law can reduce the inequality-worsening effect of financial liberalization in some specifications.
  - Examples:
    - Columns (5) in Table 10: interaction and finance terms both positive and significant for net interest margin effect — lower interest margins reduce inequality and effect is larger with stronger rule of law.
    - Columns (6) and (7) in Table 11: better rule of law tends to intensify favorable effects of market efficiency and bank stability on poverty reduction.
- Controls
  - GDP per capita, government consumption, and trade openness negatively correlated with inequality and poverty.
  - Inflation positively correlated with inequality and poverty (inflation hurts the poor more).
- Robustness
  - Five-year average regressions largely confirm initial annual results (Tables 12 and 13).
- Instrument validity
  - Hansen’s J-Statistics: unable to reject the null that instruments are uncorrelated with error terms for all IV regressions reported; instruments considered appropriate.

### Conclusions and policy recommendations
- Main summary
  - Most financial development dimensions (access, depth, efficiency, stability) help reduce income inequality and poverty on average.
  - External financial liberalization tends to widen income inequality and poverty on the global average.
  - Banking sector development has a stronger positive effect on income distribution than stock market development.
  - Per capita income, government expenditure, and trade openness help reduce inequality and poverty; inflation harms the poor.
- Policy implications
  - Policymakers should steer financial system development in a pro-growth and pro-poor direction.
  - Encourage financial reform policies that:
    - Expand financial access and depth.
    - Enhance financial efficiency and stability.
    - Relax credit and interest controls (where appropriate).
    - Improve banking and securities market supervision.
  - Capital account (external liberalization) should proceed carefully:
    - Design and sequence capital account liberalization in a stable macroeconomic environment to avoid offsetting poverty-reducing gains from other financial-sector improvements.
  - Strengthen regulatory systems and financial infrastructure:
    - Improve credit information systems, collateral regimes, and insolvency regimes to limit risky bank behavior.
  - Prioritize banking sector development when the goal is poverty and income inequality alleviation, given its larger impact relative to stock markets.
- Further research
  - Focus on the policy settings and conditions under which financial liberalization could reduce poverty and income inequality.

*Source: _wp1632 - Section 4 offers a conclusion.*

### References

### _wp1632 - References

### Key bibliographic sources
- Abiad, A., Detragiache, E., Tressel,T., (2008). A New Database of Financial Reforms. IMF Working Papers 08/266. International Monetary Fund.
- Alesina, A., Devleeschauwer,A., Easterly, W., Kurlat, S., and Wacziarg, R. (2003). “Fractionalization.” J. Econ. Growth 8 (June): 155–94.
- Beck, T., Demirguc-Kunt, A., and Levine, R. (2004). Finance, Inequality, and Poverty: Cross-Country Evidence. NBER Working Paper No. 10979.
- Beck, T., Demirguc-Kunt, A., and Levine, R. (2007). Finance, Inequality, and Poor. Journal of Economic Growth, 12(1), 27-49.
- Claessens, S., and Perotti, E. (2007). Finance and Inequality: Channels and Evidence. Journal of Comparative Economics, 35(4), 748-773.
- Demirguc-Kunt, A., Beck, T., Honohan, P. (2008). Finance for All: Policies and Pitfalls in Expanding Access. The World Bank, Washington, DC.
- Easterly, W., & Fischer, S. (2001). Inflation and the Poor. Journal of Money, Credit and Banking, 33(2), 160-178.
- Furceri, D., & Loungani, P.(2015). Capital Account Liberalization and Inequality. IMF working paper.
- Galor, O., and Moav, O. (2004). From Physical to Human Capital Accumulation: Inequality and the Process of Development. The Review of Economic Studies, 71(4), 1001-1026.
- Galor. O., and Zeira. J. (1993). Income Distribution and Macroeconomics. Review of Economic Studies, Bol. 60, pp. 35-52.
- Greenwood, J., and Jovanovic, B. (1990). Financial Development, Growth, and the Distribution of Income. Journal of Political Economy, 98(5), 1076-1107.
- Honohan, P. (2004). Financial Development, Growth and Poverty: How Closer are the Links? World Bank Policy Research Working Paper 3203.
- Jeanneney, S. G., and Kpodar, K. (2011). Financial Development and Poverty Reduction: Can There Be a Benefit Without a Cost? The Journal of Development Studies, 47(1), 143-163.
- Kunieda. T., Okada. K., and Shibata. A. (2011). Finance and Inequality: How Does Globalization Change Their Relationship? MPRA Paper No.35358.
- Rajan, Raghuram G. and Luigi Zingales. (2003). The Great Reversals: The Politics of Financial Development in the 20th Century. Journal of Financial Economics 69, 1: 5-50.

### Table 1 — Summary statistics (selected variables)
- Gini coefficient: Obs 1759; Mean 39.39; sd 10.91; Min 15.90; Max 76.70
- Poverty gap: Obs 804; Mean 7.30; sd 10.34; Min 0.00; Max 63.34
- Log GDP per capita: Obs 7885; Mean 7.63; sd 1.60; Min 4.00; Max 11.59
- Inflation: Obs 6438; Mean 33.82; sd 487.15; Min -21.68; Max 24411.00
- Trade openness: Obs 7427; Mean 76.83; sd 49.13; Min 0.31; Max 460.47
- Government consumption: Obs 7100; Mean 15.89; sd 6.85; Min 1.38; Max 76.22
- Bank accounts per 1,000 adults: Obs 434; Mean 333.97; sd 276.46; Min 0.72; Max 988.15
- Private credit to GDP (%): Obs 5844; Mean 35.91; sd 35.63; Min 0.12; Max 434.09
- Stock market total value traded to GDP (%): Obs 1942; Mean 28.30; sd 58.09; Min 0.00; Max 754.03
- Net interest margin (%): Obs 3807; Mean 4.68; sd 3.48; Min -12.01; Max 40.63
- Regulatory capital to risk-weighted assets (%): Obs 1276; Mean 15.77; sd 5.23; Min 2.50; Max 48.60
- Domestic financial liberalization: Obs 2330; Mean 6.30; sd 3.87; Min 0.00; Max 12.00
- External financial liberalization (%): Obs 4482; Mean 36.07; sd 75.59; Min 0.01; Max 957.14

### Table 2 — Correlations (selected coefficients)
- Gini coefficient with:
  - Poverty gap: 0.18
  - Bank accounts per 1,000 adults: -0.28
  - Private credit to GDP (%): -0.24
  - Net interest margin (%): 0.19
- Poverty gap with:
  - Bank accounts per 1,000 adults: -0.49
  - Private credit to GDP (%): -0.27
  - Net interest margin (%): 0.21
- Bank accounts per 1,000 adults with:
  - Private credit to GDP (%): 0.71
  - External financial liberalization (%): 0.35

### Tables 3–7 — Selected regression findings (effects of financial dimensions on inequality and poverty)
- Table 3 (Effects of Financial Access on Income Inequality)
  - Bank accounts per 1,000 adults: coefficient -0.022*** (OLS, Gini) and -0.019*** (IV, Gini)
  - Bank accounts per 1,000 adults: coefficient -0.007* (OLS, Poverty gap) and -0.007* (IV, Poverty gap)
  - Trade openness: coefficients include -0.032*** and -0.029** (for poverty gap specifications)

- Table 4 (Effects of Financial Deepening on Income Inequality)
  - Private credit to GDP (%): coefficient -0.045*** (OLS, Gini) and -0.041*** (IV, Gini)
  - Stock market total value traded to GDP (%): coefficient -0.019* and -0.022** (Gini specifications)
  - Trade openness: coefficients include -0.029*** and -0.031*** (poverty gap specifications)
  - Government Consumption: coefficients include -0.500*** and -0.476*** (Gini specifications)

- Table 5 (Effects of Financial Efficiency on Income Inequality)
  - Net Interest Margin (%): coefficient 0.359*** (OLS, Gini) and 0.440** (IV, Gini) — higher net interest margin associated with higher Gini in these specifications
  - Stock market turnover ratio (%): coefficient -0.037*** (OLS, Gini) and -0.055*** (IV, Gini)
  - Trade openness: coefficients -0.037*** to -0.029*** across specifications

- Table 6 (Effects of Financial Stability on Income Inequality)
  - Regulatory capital to risk-weighted assets (%): coefficient -0.238*** (OLS, Gini) and -0.375*** (IV, Gini)
  - Volatility of stock price index: coefficient -0.043*** (OLS, Poverty gap) in one specification
  - Trade openness and Government Consumption show consistent negative coefficients across specifications (e.g., Trade openness -0.038***)

- Table 7 (Effects of Financial Liberalization on Income Inequality)
  - Domestic financial liberalization: coefficient 0.479*** (OLS, Gini) and 0.501*** (IV, Gini)
  - External financial liberalization: coefficient 0.022*** and 0.024*** (Gini specifications)
  - Trade openness: coefficients -0.031*** to -0.066*** across specifications
  - Government Consumption: coefficient -0.727*** (OLS, Gini) and -0.687*** (IV, Gini)

(Note: tables report multiple model specifications (OLS and IV), dependent variables include Gini coefficient and Poverty gap; significance levels denoted * p<0.10, ** p<0.05, *** p<0.01.)

### Interaction and robustness tables (selected highlights)
- Table 8 (Inequality-FD add Country income level interaction)
  - Log GDP per capita coefficients: examples include 6.984***, 3.150***, 6.292*** across different FD proxies.
  - FD main effects and interactions: FD -0.057*** in one column; FD*low 0.035** in another; FD*mid shows N/A or various significant coefficients depending on FD proxy.

- Table 9 (Poverty-FD add Country income level interaction)
  - Log GDP per capita coefficients: examples include -3.084*, -5.034***, -5.096***.
  - FD main effects: FD -0.065*** in one specification; FD*low 0.060*** in another; FD*mid shows significant coefficients in several columns.

- Table 10–11 (Inequality/Poverty-FD add quality of institution interaction)
  - Rule of Law interactions: Rule of Law coefficients include -10.183, -7.123, -3.011***, -5.046***; FD*rule of law coefficients include values such as 0.028, -0.098, -0.047* depending on proxy.
  - Selected FD main effects: FD 1.537*** (in a Net Interest Margin column); FD -0.804** (in a Stock market turnover column).

- Table 12–13 (5 year average samples)
  - Gini coefficient 5 year average: Private credit to GDP coefficient -0.067***; Stock market total value traded to GDP -0.029**; Stock market turnover ratio -0.069***; External financial liberalization 0.030***.
  - Poverty gap 5 year average: Log GDP per capita consistently negative and significant (e.g., -4.605***); Bank accounts per 1,000 adults -0.008**; Private credit to GDP -0.054**; Regulatory capital to risk-weighted assets -0.404***; Domestic financial liberalization 0.040*** in one specification.

### Appendix 1 — Variable definitions and data sources (selected)
- Gini coefficient: World Bank, All the Gini database (2013). Definition: Gini coefficient measures income inequality, with 0 resembles perfectly equal outcome, while, 100 percent reflects extremely unequal condition.
- Poverty gap: World Bank, PovcalNet. Definition: Poverty Gap Index, measures the average income shortfall of the poor individual from the poverty line ($1.25 a day).
- Log GDP per capita: Log of GDP per capita (constant 2000 US$). Source: World Development Indicators (WDI).
- Inflation: Consumer prices (annual %). Source: WDI.
- Trade openness: Trade (% of GDP). Source: WDI.
- Government consumption: General government final consumption expenditure (% of GDP). Source: WDI.
- Bank accounts per 1,000 adults; Private credit to GDP (%); Stock market total value traded to GDP (%); Net interest margin (%); Stock market turnover ratio (%); Regulatory capital to risk-weighted assets (%); Volatility of stock price index; External financial liberalization (%): Source GFDD (World Bank, Global Financial Development Database) unless otherwise stated.
- Domestic financial liberalization: Aggregation of indices of credit control, interest rate control, entry barriers, and privatization. Source: Abiad, Detragiache and Tressel (2008).
- Ethnic, language, religion fractionalization measures: ADEKW(2003) (Alesina et al., 2003).

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