The Role of Financial Development in the Relationship Between Income Inequality and Economic Growth: Evidence from Method of Moments Quantile Regression

Abstract

This study sheds light on the linear and nonlinear relationship between financial development level and income inequality across 79 countries within a period of 1995 to 2016. To test this relationship panel the Method of Moments Quantile Regression (MMQR), which was recently published by Machado and Silva (2019), has been employed. Besides Pedroni and GUV cointegration tests, FMOLS and DOLS have been administered. Although traditional mean estimators can explain the heterogonous nature of analysed countries, since their results depend on conditional mean they fall short in making the responses heterogonous. In that sense, the effects of specific factors such as financial and economic developments which also impact income inequality have been inspected via MMQR, which also takes into account certain econometric difficulties such as heterogeneity and endogeneity in various quantiles. Compared to other methods, another advantage of MMQR is that by providing information on how explanatory variables can influence the entire conditional distribution, it allows the use of methods only valid in the estimation of conditional means, such as difficulty in noticing heterogeneity and endogeneity problems in panel data models. According to the results obtained from the MMQR model, Greenwood and Jovanovic’s (1990) inverted U hypothesis was accepted only in countries with an inequality income distribution between financial development and income inequality, whereas in counties with equal income distribution the income inequality widening hypothesis was confirmed. According to Panel FMOLS and Panel DOLS and also coefficient estimations, Greenwood and Jovanovic (1990)’s inverted U hypothesis was confirmed in the relationship between financial development and income.

Keywords

• Financial development
• Income inequality
• Kuznets Curve

Gelir Eşitsizliği ve Ekonomik Büyüme Arasındaki İlişkide Finansal Gelişmenin Rolü: Moment Kantil Regresyon Yönteminden Bulgular

Abstract

Bu çalışma finansal gelişmişlik düzeyi ile gelir arasındaki doğrusal ve doğrusal olmayan ilişkiyi 79 ülkede 1995-2016 yılları arasında incelemektedir. Bu ilişkiyi test etmek için literatüre Machado ve Silva (2019) tarafından tanıtılan panel Moment Kantil Regresyon Yöntemi (MMQR) ile Pedroni ve GUV eşbütünleşme testleri, FMOLS ve DOLS kullanılmıştır. Geleneksel ortalama tahmin ediciler, ele alınan ülkelerin heterojen doğasını açıklasalar da sonuçları koşullu ortalamaya dayalı olduğundan yanıtların heterojen olmasını sağlayamazlar. Bu amaçla, gelir eşitsizliğini etkileyen finansal ve ekonomik kalkınma gibi faktörlerin etkisi çeşitli kantillerde heterojenlik ve içsellik gibi ekonometrik zorlukları da dikkate alan MMQR yöntemi ile analiz edilmiştir. MMQR’ in diğer yöntemlere göre avantajı ise, açıklayıcı değişkenlerin tüm koşullu dağılımı nasıl etkilediği bilgisini sağlayarak, panel veri modellerinde heterojenlik ve içsellik problemlerini dikkate alma zorluğu gibi sadece koşullu ortalamaların tahmininde geçerli olan metotları kullanmasına izin vermesidir. MMQR model sonuçlarına göre finansal kalkınma ile gelir eşitsizliği arasında yalnızca gelir dağılımı eşit olmayan ülkelerde Greenwood ve Jovanovic (1990)’in ters U hipotezi kabul edilmişken, eşit gelir dağılıma sahip ülkelerde ise gelir eşitsizliğini genişletici hipotez doğrulanmıştır. Panel FMOLS ve Panel DOLS ile katsayılar tahminlerine göre finansal gelişme ile gelir arasındaki ilişkide Greenwood ve Jovanovic (1990)’nin ters U hipotezini desteklemektedir.

Keywords

• Finansal Gelişmişlik
• Gelir Eşitsizliği
• Kuznet Eğrisi

References

1. Alhassan, A., Usman, O., Ike, G. N., Sarkodie, S. A. (2020). Impact assessment of trade on environmental performance: accounting for the role of government integrity and economic development in 79 countries. Heliyon, 6(9), e05046.
2. Altunbaş, Y., Thornton, J. (2018). The impact of financial development on income inequality: A quantile regression approach. Economics Letters, 175, 51-56.
3. Banerjee, A. V., Newman, A. F. (1993). Occupational choice and the process of development. Journal of political economy, 101(2), 274-298.
4. Batuo, M. E., Guidi, F., Mlambo, K. (2010). Financial development and income inequality: Evidence from African Countries. African Development Bank, 44, 1-27.
5. Beck, T., Demirguc-Kunt, A., Levine, R. (2004). Finance, inequality, and poverty: Cross-country evidence (No. w10979). National Bureau of Economic Research.
6. Bittencourt, M., Chang, S., Gupta, R., Miller, S. M. (2019). Does financial development affect income inequality in the US States? Journal of Policy Modeling, 41(6), 1043-1056.
7. Breitung, J., Das, S., 2005. Panel unit root tests under cross‐sectional dependence. Statistica Neerlandica, 59(4), 414-433.
8. Canay, I. A. (2011). A simple approach to quantile regression for panel data. The Econometrics Journal, 14(3), 368-386.

9. Chakroun, M. (2019). Threshold effects in the relationship between financial development and income inequality. International Journal of Finance & Economics, 25(3), 365-387.
10. Clarke, G. R., Zou, H. F., Xu, L. C. (2003). Finance and income inequality: test of alternative theories (Vol. 2984). World Bank Publications.
11. Clarke, G. R., Xu, L. C., Zou, H. F. (2006). Finance and income inequality: what do the data tell us? Southern economic journal, 578-596.
12. De Haan, J., Sturm, J. E. (2017). Finance and income inequality: A review and new evidence. European Journal of Political Economy, 50, 171-195.
13. Demirgüç-Kunt, A., Levine, R. (2009). Finance and inequality: Theory and evidence. Annu. Rev. Financ. Econ., 1(1), 287-318.
14. Galor, O., Zeira, J. (1993). Income distribution and macroeconomics. The review of economic studies, 60(1), 35-52.
15. Gengenbach, C., Urbain, J. P., Westerlund, J. (2016). Error correction testing in panels with common stochastic trends. Journal of Applied Econometrics, 31(6), 982-1004.
16. Greenwood, J., Jovanovic, B. (1990). Financial development, growth, and the distribution of income. Journal of political Economy, 98(5, Part 1), 1076-1107.
17. Im, K. S., Pesaran, M. H., Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of econometrics, 115(1), 53-74.
18. Jauch, S., Watzka, S. (2015). Financial development and income inequality: a panel data approach. Empirical Economics, 51(1), 291-314.
19. Kaidi, N., Mensi, S., Amor, M. B. (2019). Financial development, institutional quality and poverty reduction: worldwide evidence. Social Indicators Research, 141(1), 131-156.
20. Kim, D. H., Lin, S. C. (2011). Nonlinearity in the financial development–income inequality nexus. Journal of Comparative Economics, 39(3), 310-325.
21. Koçak, E., Uzay, N. (2019). The effect of financial development on income inequality in Turkey: An estimate of the Greenwood-Jovanovic hypothesis. Review of Economic Perspectives, 19(4), 319-344.
22. Kuznets, S. (1955). Economic growth and income inequality. The American economic review, 45(1), 1-28.
23. Levine, R. (2005). Finance and growth: theory and evidence. Handbook of economic growth, 1, 865-934.
24. Liang, Z. (2008). Financial development and income inequality in rural China 1991–2000. In Understanding Inequality and Poverty in China (pp. 72-88). Palgrave Macmillan, London.
25. Machado, J. A., Silva, J. S. (2019). Quantiles via moments. Journal of Econometrics, 213(1), 145-173.
26. Nasreddine, K., Mensi, S. (2016). Financial development and income inequality: The linear versus the nonlinear hypothesis. Economics Bulletin, 36(2), 609-626.
27. Nikoloski, Z. (2012). Financial sector development and inequality: is there a financial Kuznets curve? Journal of International Development, 25(7), 897-911.
28. Pesaran, M. H. (2004). General diagnostic tests for cross-sectional dependence in panels. Empirical Economics, 1-38.
29. Rehman, H. U., Khan, S., Ahmed, I. (2008). Income distribution, growth and financial development: A cross countries analysis. Pakistan Economic and Social Review, 1-16.
30. Rötheli, T. F. (2011). The Kuznets curve: determinants of its shape and the role of finance. Studies in Economics and Finance.
31. Satti, S. L., Mahalik, M. K., Shahbaz, M. (2015). Dynamics of income inequality, finance and trade in Kazakhstan: Empirical evidence from a new transition economy with policy prescriptions. Monash Univ., Department of Economics.
32. Sethi, P., Bhattacharjee, S., Chakrabarti, D., Tiwari, C. (2021). The impact of globalization and financial development on India’s income inequality. Journal of Policy Modeling.
33. Shahbaz, M. (2010). Income inequality‐economic growth and non‐linearity: A case of Pakistan. International Journal of Social Economics.
34. Shahbaz, M., Islam, F. (2011). Financial development and income inequality in Pakistan: an application of ARDL approach.
35. Shahbaz, M., Loganathan, N., Tiwari, A. K., Sherafatian-Jahromi, R. (2014). Financial development and income inequality: Is there any financial Kuznets curve in Iran? Social Indicators Research, 124(2), 357-382.
36. Shin, H., Lee, K. (2019). Impact of financialization and financial development on inequality: Panel cointegration results using OECD data. Asian Economic Papers, 18(1), 69-90.
37. Thornton, J., Di Tommaso, C. (2019). The long-run relationship between finance and income inequality: Evidence from panel data. Finance Research Letters, 32, 101180.
38. Topuz, A. G. D. S. G., Dağdemir, Ö. (2016). Financial development and the income inequality: a panel data analysis. Anadolu University Journal of Social Sciences, 16(3), 19-34.
39. Younsi, M., Bechtini, M. (2018). Economic Growth, Financial Development and Income Inequality in BRICS Countries: Evidence from Panel Granger Causality Tests.