Impacts of Overall Financial Development, Access and Depth on Income Inequality
Abstract
:1. Introduction
2. Theoretical Framework and Review of Literature
2.1. Theoretical Framework
2.2. Review of Literature
2.2.1. Financial Sector Development and Economic Growth
2.2.2. Financial Sector Development and Income Inequality
2.2.3. Empirical Evidence on Financial Access and Income Inequality
2.2.4. The Stylized Facts on Financial Sector Development and Inequality
3. Methodology and Data
3.1. Methodology
3.2. Data
4. Results
5. Discussion
6. Conclusions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Full Sample | County Codes | Region Names 1 | Income Levels 2 | Gini Category 3 | High Inequality Countries | Low Inequality Countries |
---|---|---|---|---|---|---|
Angola | AGO | SSA | LMC | HI | ✓ | |
Albania | ALB | ECA | UMC | MI | ||
Armenia | ARM | ECA | UMC | MI | ||
Australia | AUS | EAP | HIC | MI | ||
Austria | AUT | ECA | HIC | MI | ||
Burundi | BDI | SSA | LIC | LI | ||
Belgium | BEL | ECA | HIC | MI | ||
Benin | BEN | SSA | LMC | MI | ||
Burkina Faso | BFA | SSA | LIC | MI | ||
Bangladesh | BGD | SA | LMC | VLI | ||
Bulgaria | BGR | ECA | UMC | LI | ||
Bolivia | BOL | LAC | LMC | MI | ||
Brazil | BRA | LAC | UMC | VHI | ✓ | |
Barbados | BRB | LAC | HIC | MI | ||
Botswana | BWA | SSA | UMC | VHI | ✓ | |
Canada | CAN | NA | HIC | MI | ||
Switzerland | CHE | ECA | HIC | VLI | ||
Chile | CHL | LAC | HIC | HI | ✓ | |
China | CHN | EAP | UMC | LI | ||
Cameroon | CMR | SSA | LMC | MI | ||
Congo | COG | SSA | LMC | |||
Colombia | COL | LAC | UMC | HI | ||
Cyprus | CYP | ECA | HIC | MI | ||
Czech Republic | CZE | ECA | HIC | MI | ||
Germany | DEU | ECA | HIC | MI | ||
Denmark | DNK | ECA | HIC | LI | ✓ | |
Dominican Republic | DOM | LAC | UMC | MI | ||
Algeria | DZA | MENA | LMC | VLI | ||
Ecuador | ECU | LAC | UMC | MI | ||
Egypt | EGY | MENA | LMC | MI | ||
Spain | ESP | ECA | HIC | LI | ||
Estonia | EST | ECA | HIC | MI | ||
Ethiopia | ETH | SSA | LIC | VLI | ||
Finland | FIN | ECA | HIC | LI | ✓ | |
Fiji | FJI | EAP | UMC | LI | ||
France | FRA | ECA | HIC | LI | ✓ | |
Gabon | GAB | SSA | UMC | |||
United Kingdom | GBR | ECA | HIC | HI | ||
Ghana | GHA | SSA | LMC | MI | ||
Gambia | GMB | SSA | LIC | MI | ||
Greece | GRC | ECA | HIC | MI | ||
Guatemala | GTM | LAC | UMC | MI | ||
Hong Kong | HKG | EAP | HIC | MI | ||
Honduras | HND | LAC | LMC | MI | ||
Croatia | HRV | ECA | HIC | LI | ✓ | |
Hungary | HUN | ECA | HIC | LI | ✓ | |
Indonesia | IDN | EAP | UMC | LI | ||
India | IND | SA | LMC | MI | ||
Ireland | IRL | ECA | HIC | MI | ||
Iran | IRN | MENA | UMC | LI | ||
Iceland | ISL | ECA | HIC | LI | ✓ | |
Israel | ISR | MENA | HIC | MI | ||
Italy | ITA | ECA | HIC | MI | ||
Jamaica | JAM | LAC | UMC | LI | ||
Jordan | JOR | MENA | UMC | VLI | ||
Japan | JPN | EAP | HIC | LI | ✓ | |
Kazakhstan | KAZ | ECA | UMC | VLI | ||
Kenya | KEN | SSA | LMC | MI | ||
Kyrgyzstan | KGZ | ECA | LMC | LI | ||
Cambodia | KHM | EAP | LMC | VLI | ||
Korea | KOR | EAP | HIC | VLI | ||
Laos | LAO | EAP | LMC | VLI | ||
Sri Lanka | LKA | SA | LMC | LI | ||
Lesotho | LSO | SSA | LMC | HI | ✓ | |
Lithuania | LTU | ECA | HIC | MI | ||
Luxembourg | LUX | ECA | HIC | LI | ✓ | |
Latvia | LVA | ECA | HIC | MI | ||
Morocco | MAR | MENA | LMC | LI | ||
Moldova | MDA | ECA | LMC | HI | ||
Madagascar | MDG | SSA | LIC | MI | ||
Maldives | MDV | SA | UMC | LI | ||
Mexico | MEX | LAC | UMC | MI | ||
Malta | MLT | MENA | HIC | LI | ||
Myanmar | MMR | EAP | LMC | |||
Mongolia | MNG | EAP | LMC | VLI | ||
Mozambique | MOZ | SSA | LIC | MI | ||
Mauritania | MRT | SSA | LMC | LI | ||
Mauritius | MUS | SSA | HIC | VLI | ||
Malaysia | MYS | EAP | UMC | MI | ||
Namibia | NAM | SSA | UMC | VHI | ✓ | |
Niger | NER | SSA | LIC | LI | ||
Nigeria | NGA | SSA | LMC | MI | ||
Nicaragua | NIC | LAC | LMC | MI | ||
Netherlands | NLD | ECA | HIC | MI | ||
Norway | NOR | ECA | HIC | MI | ✓ | |
Nepal | NPL | SA | LMC | LI | ||
New Zealand | NZL | EAP | HIC | MI | ||
Pakistan | PAK | SA | LMC | VLI | ||
Panama | PAN | LAC | HIC | HI | ||
Peru | PER | LAC | UMC | HI | ✓ | |
Philippines | PHL | EAP | LMC | MI | ||
Poland | POL | ECA | HIC | MI | ||
Portugal | PRT | ECA | HIC | MI | ||
Paraguay | PRY | LAC | UMC | MI | ||
Qatar | QAT | MENA | HIC | LI | ||
Romania | ROU | ECA | HIC | LI | ||
Russia | RUS | ECA | UMC | MI | ||
Rwanda | RWA | SSA | LIC | HI | ✓ | |
Saudi Arabia | SAU | MENA | HIC | |||
Sudan | SDN | SSA | LIC | LI | ||
Senegal | SEN | SSA | LMC | LI | ||
Singapore | SGP | EAP | HIC | LI | ✓ | |
El Salvador | SLV | LAC | LMC | LI | ||
Serbia | SRB | ECA | UMC | MI | ||
Slovakia | SVK | ECA | HIC | LI | ✓ | |
Slovenia | SVN | ECA | HIC | VLI | ✓ | |
Sweden | SWE | ECA | HIC | MI | ✓ | |
Togo | TGO | SSA | LIC | |||
Thailand | THA | EAP | UMC | MI | ||
Tajikistan | TJK | ECA | LIC | VLI | ||
Tunisia | TUN | MENA | LMC | LI | ||
Turkey | TUR | ECA | UMC | LI | ||
Tanzania | TZA | SSA | LMC | LI | ||
Uganda | UGA | SSA | LIC | MI | ||
Ukraine | UKR | ECA | LMC | VLI | ||
Uruguay | URY | LAC | HIC | HI | ✓ | |
Vietnam | VNM | EAP | LMC | LI | ||
South Africa | ZAF | SSA | UMC | VHI | ✓ | |
Zambia | ZMB | SSA | LMC | HI | ✓ | |
Cote d’Iviore | CIV | SSA | LMC | HI | ✓ | |
Comoros 4 | COM | SSA | LMC | HI | ✓ |
Variable | Obs | Mean | Std. Dev. | Min | Max | Data Source |
---|---|---|---|---|---|---|
gini disp | 1962 | 0.386 | 0.082 | 0.23 | 0.674 | SWIID |
gini mkt | 1962 | 0.459 | 0.065 | 0.219 | 0.725 | SWIID |
GDP | 2272 | 1.885 | 2.036 | 0.025 | 16.652 | PWT |
ATMadult | 2110 | 0.46 | 0.459 | 0 | 2.886 | IMF |
Dom credit | 2309 | 0.568 | 0.465 | 0 | 3.046 | WDI |
Fin markets | 1034 | 0.727 | 1.311 | 0 | 13.496 | WDI |
FD | 2320 | 0.336 | 0.236 | 0.029 | 1 | IMF |
FIA | 2320 | 0.36 | 0.277 | 0.003 | 1 | IMF |
FMA | 2320 | 0.241 | 0.288 | 0 | 1 | IMF |
FID | 2320 | 0.279 | 0.271 | 0 | 1 | IMF |
FMD | 2320 | 0.245 | 0.287 | 0 | 1 | IMF |
Urban pop | 2320 | 0.578 | 0.23 | 0.091 | 1 | WDI |
Trade op | 2272 | 0.645 | 0.565 | 0.001 | 5.49 | PWT |
yr sch | 2016 | 8.242 | 3.342 | 0.759 | 15.802 | PWT |
CPI | 2240 | 1.662 | 1.16 | 0.99 | 25.777 | WDI |
Gov | 2127 | 0.157 | 0.053 | 0.035 | 0.435 | WDI |
corruption | 2320 | 0.018 | 1.012 | −1.681 | 2.47 | WGI |
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Study | Main Variables in the Model of FSD on Inequality | Geographical Area | Findings | |
---|---|---|---|---|
Financial narrowing hypothesis | Beck et al. (2004) | Credit to the private sector by financial intermediaries and poorest quintile income, Gini index. Legal origins, natural resource endowment, religious composition and ethnic fractionalization as instruments for endogeneity. | 52 developing and developed countries (1960 to 1999) 1. | Using instrumental variable regression, they found that FSD reduces inequality as it grows faster than average GDP per capita. |
Clarke et al. (2006) | The Gini coefficient and credit to the private sector by financial intermediaries over GDP (private credit). To control Kuznets effects, they include initial real GDP per capita and squared term. Other control variables include: inflation rate, government consumption, ethnolinguistic fractionalization and a measure of the protection of property rights. To control for endogeneity, the legal origins indicator is included. | Using data for 83 developed and developing countries between 1960 and 1995. | The study found that when there is greater/deepened FSD, inequality is less in the long run. The results confirming an inverted U-shaped curve of Greenwood and Jovanovic (1990) were not robust. | |
Kapingura (2017) | Gini index. FSD: domestic credit to bank sector as % of GDP, and ATM per 100,000 adults. | South Africa (1990–2012 yearly). | An increase in financial access (ATM) reduces inequality more than increasing financial depth. | |
Burgess and Pande (2005) 2 | FSD: the number of bank branches per 100 000 persons and number of banks opened in rural versus urban areas. | India (1977–1990). | Using OLS and IV, they found that financial access reduces poverty, especially in rural areas. | |
Liang (2008) | Provincial rural Gini index. FSD: constructed rural FSD based on the ratio of total loans to rural GDP. | China, based on provincial data from 1991 to 2000. | The GMM technique showed that increased access to financial services and credit in rural areas reduces inequality. | |
Shahbaz and Islam (2011) | Gini index, domestic credit to the private sector by financial intermediaries over GDP and financial stability measures developed by authors. | Pakistan (1971–2005). | Using ADRL methodology, they found that FSD reduces income inequality while financial instability increases inequality. | |
Prete (2013) | Growth of Gini. FSD: private credit as the ratio of GDP. | 30 countries from 1980 to 2005. | Using panel OLS, they find inequality narrowing. | |
Dollar and Kraay (2002) | GDP per capita and mean income in the poorest quintile. Commercial bank assets/total bank assets, human capital. Inflation, trade openness, the rule of law/property rights. | 137 countries (1950–1999) | FSD increases inequality by a small magnitude compared to the increasing impact on economic growth. | |
Hendel et al. (2005) | Developed a model similar to (Rajan and Zingales 2003) for general equilibrium. The model is based on the interest rate, skills premium, subsidies for higher education and wealth fundamentals. | In the United States of America (USA) | Inequality from wage income increases when financial constraints for post-secondary education are reduced as the uneducated pool is left behind. | |
Financial widening hypothesis | Wahid et al. (2012) | Gini index, domestic credit to the private sector by financial intermediaries over GDP. | Bangladesh (1985–2006). | Using ADRL methodology, they find that FSD increases inequality. |
Jaumotte et al. (2013) | Gin index. Financial openness is measured using the Chinn–Ito index of capital account openness, the ratios of various types of financial liabilities (FDI, portfolio equity and debt) to GDP and the stock of FDI assets expressed as a percentage of GDP. | A total of 51 countries—20 developed and 31 developing countries (1981–2003). | The results show that inequality increases with financial globalization and foreign direct investment, while education and shift from agricultural employment reduce inequality. | |
Seven and Coskun (2016) | Gini index. FSD: ratio of private credit to GDP, deposit money bank assets to GDP, M3 to GDP, stock market capitalization to GDP, stock market turnover ratio. | 45 emerging market countries (1987–2001). | Using the GMM technique, they find that bank and stock market development increases inequality. | |
Chiu and Lee (2019) | Gini index. FSD: domestic credit to the private sector and market capitalization. | 59 countries, 1985–2015. Panel smooth transition regression model. | From the panel smooth transaction regression model, they find evidence of finance widening inequality in unstable economies, while high-inequality countries can reduce income inequality through FSD. | |
de Haan and Sturm (2017) Le and Nguyen (2020) | Gini index. FSD: private sector credit. Financial liberalization was measured with 6 sub-indices. Domestic credit is measured as commercial credit as a share of GDP and policy credit as a share of GDP. | 121 countries from 1975 to 2005. Using the FE model. Vietnam. Panel study based on 60 provinces. From 2002 to 2016. | They find that all financial variables increase income inequality. Their main findings are robust for using random effects, cross-country regressions and legal origin as financial development instruments. Commercial credit increases income inequality, while policy credit reduces income inequality. |
(1) | (2) | (3) | |
---|---|---|---|
Financial Development Index | Financial Institution Index | Financial Market Index | |
VARIABLES | |||
L.log_gini_ | 0.710 *** | 0.735 *** | 0.726 *** |
(0.125) | (0.105) | (0.121) | |
Findev | −0.0644 ** | −0.0615 * | −0.0434 ** |
(0.0261) | (0.0353) | (0.0187) | |
GDP | 0.00417 | 0.00295 | 0.00488 |
(0.00377) | (0.00347) | (0.00380) | |
Log_cpi | 0.0106 | 0.0133 | 0.00930 |
(0.00872) | (0.00820) | (0.00827) | |
Trade_op | −0.00238 | −0.00106 | −0.00444 |
(0.00706) | (0.00733) | (0.00700) | |
Log_Gov | 0.00769 | 0.0113 | 0.00262 |
(0.0188) | (0.0204) | (0.0180) | |
Log_Education | −0.0913 | −0.0803 | −0.0977 * |
(0.0582) | (0.0524) | (0.0580) | |
Constant | −0.0728 | −0.0590 | −0.0647 |
(0.0810) | (0.0774) | (0.0794) | |
Observations | 1508 | 1508 | 1508 |
Number of ccode | 120 | 120 | 120 |
AR 2 test (p-value) | 0.558 | 0.396 | 0.529 |
Sargan test (p-value) | 0.995 | 0.943 | 0.305 |
Hansen test(p-value) | 0.270 | 0.308 | 0.202 |
(1) | (2) | (3) | (4) | (5) | (6) | |
---|---|---|---|---|---|---|
Financial Institution Access Index | ATM per 100,000 Adults | Financial Market Access Index | Financial Institution Access Index | ATM per 100,000 Adults | Financial Market Access Index | |
VARIABLES | ||||||
L.log_gini | 0.754 *** | 0.801 *** | 0.812 *** | 0.744 *** | 0.794 *** | 0.853 *** |
(0.118) | (0.0852) | (0.0832) | (0.126) | (0.0834) | (0.0785) | |
Financial Access | −0.0542 ** | −0.0278 * | 0.00810 | −0.0270 | −0.0647 ** | 0.158 |
(0.0234) | (0.0145) | (0.00985) | (0.107) | (0.0316) | (0.100) | |
Financial Access2 | −0.0280 | 0.0216 | −0.123 | |||
(0.100) | (0.0161) | (0.0850) | ||||
GDP | 0.00144 | 0.00473 | 0.00363 | 0.00208 | 0.00159 | 0.00209 |
(0.00355) | (0.00341) | (0.00290) | (0.00372) | (0.00277) | (0.00276) | |
Log_CPI | 0.0183 * | 0.0205 ** | 0.0131 * | 0.0182 | 0.0221 ** | 0.0172 ** |
(0.0103) | (0.00875) | (0.00688) | (0.0110) | (0.00846) | (0.00808) | |
Trade_op | 0.00801 | 0.000966 | −0.00462 | 0.00783 | 0.00383 | −0.00766 |
(0.00719) | (0.00660) | (0.00600) | (0.00753) | (0.00690) | (0.00674) | |
Log_Gov | 0.0253 | 0.0217 | 0.00193 | 0.0265 | 0.0185 | −0.00747 |
(0.0227) | (0.0201) | (0.0165) | (0.0221) | (0.0200) | (0.0160) | |
Log_Education | −0.0883 | −0.0891 * | −0.0892 ** | −0.0988 | −0.0652 * | −0.0891 ** |
(0.0542) | (0.0484) | (0.0433) | (0.0608) | (0.0367) | (0.0429) | |
Constant | −0.00868 | 0.0233 | −0.0131 | −0.000560 | −0.0270 | −0.00933 |
(0.0882) | (0.0854) | (0.0722) | (0.0877) | (0.0851) | (0.0721) | |
Observations | 1508 | 1416 | 1508 | 1508 | 1416 | 1508 |
Number of ccode | 120 | 119 | 120 | 120 | 119 | 120 |
AR 2 test (p-value) | 0.498 | 0.211 | 0.339 | 0.643 | 0.226 | 0.361 |
Sargan test (p-value) | 0.994 | 0.908 | 0.729 | 0.995 | 0.952 | 0.898 |
Hansen test (p-value) | 0.656 | 0.644 | 0.250 | 0.613 | 0.587 | 0.366 |
(1) | (2) | (3) | (4) | (5) | (6) | |
---|---|---|---|---|---|---|
Domestic Credit % of GDP | Financial Institution Depth Index | Financial Market Depth Index | Domestic Credit % of GDP | Financial Institution Depth Index | Financial Market Depth Index | |
VARIABLES | ||||||
L.log_gini | 0.763 *** | 0.821 *** | 0.782 *** | 0.764 *** | 0.761 *** | 0.774 *** |
(0.120) | (0.0661) | (0.0890) | (0.118) | (0.0813) | (0.0884) | |
Financial depth | −0.0221 ** | 0.0198 | −0.0100 | −0.0294 | −0.232 ** | −0.0329 |
(0.0110) | (0.0350) | (0.0114) | (0.0356) | (0.103) | (0.0298) | |
Financial depth2 | 0.00364 | 0.185 ** | 0.0215 | |||
(0.0175) | (0.0843) | (0.0259) | ||||
GDP | 0.00540 | 0.00340 | 0.00395 | 0.00535 | 0.000844 | 0.00383 |
(0.00422) | (0.00273) | (0.00306) | (0.00427) | (0.00285) | (0.00313) | |
Log_CPI | 0.0157 | 0.0137 | 0.0116 | 0.0158 | 0.00804 | 0.0113 |
(0.00977) | (0.00837) | (0.00733) | (0.00962) | (0.00772) | (0.00746) | |
Trade_op | 0.00109 | −0.00465 | −0.00630 | 0.00134 | 0.000720 | −0.00609 |
(0.00769) | (0.00561) | (0.00655) | (0.00819) | (0.00620) | (0.00664) | |
Log_Gov | 0.0259 | −0.00246 | 0.00160 | 0.0267 | 0.00837 | 0.00132 |
(0.0225) | (0.0182) | (0.0169) | (0.0214) | (0.0196) | (0.0169) | |
Log_Education | −0.111 * | −0.0929 * | −0.0882 * | −0.110 * | −0.0411 | −0.0873 * |
(0.0612) | (0.0485) | (0.0461) | (0.0643) | (0.0479) | (0.0467) | |
Constant | 0.0377 | −0.00852 | −0.0388 | 0.0385 | −0.101 | −0.0454 |
(0.101) | (0.0758) | (0.0739) | (0.0971) | (0.0751) | (0.0728) | |
Observations | 1465 | 1508 | 1508 | 1465 | 1508 | 1508 |
Number of ccode | 119 | 120 | 120 | 119 | 120 | 120 |
AR 2 test (p-value) | 0.769 | 0.281 | 0.355 | 0.712 | 0.185 | 0.385 |
Sargan test (p-value) | 0.997 | 0.726 | 0.822 | 0.994 | 0.923 | 0.805 |
Hansen test(p-value) | 0.450 | 0.275 | 0.177 | 0.413 | 0.224 | 0.218 |
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Mbona, N. Impacts of Overall Financial Development, Access and Depth on Income Inequality. Economies 2022, 10, 118. https://doi.org/10.3390/economies10050118
Mbona N. Impacts of Overall Financial Development, Access and Depth on Income Inequality. Economies. 2022; 10(5):118. https://doi.org/10.3390/economies10050118
Chicago/Turabian StyleMbona, Nokulunga. 2022. "Impacts of Overall Financial Development, Access and Depth on Income Inequality" Economies 10, no. 5: 118. https://doi.org/10.3390/economies10050118
APA StyleMbona, N. (2022). Impacts of Overall Financial Development, Access and Depth on Income Inequality. Economies, 10(5), 118. https://doi.org/10.3390/economies10050118