Vol. 8 No. 3 (2020): Business & Management Studies: An International Journal
Articles

FINANCIAL KUZNETS CURVE, GLOBALISATION AND INCOME DISTRIBUTION: THE ELEMENTS OF TRIPARTITE RELATIONSHIP

PDF
  • Onur ÖZDEMİR
Onur ÖZDEMİR
Asst. Prof., Istanbul Gelisim University
DOI: https://doi.org/10.15295/bmij.v8i3.1570

Published 2020-09-25

Keywords

  • Labor Share of Income, Financial Kuznets Hypothesis, Financial Sector Development, Economic Globalization
  • Emek Gelir Payı, Finansal Kuznets Hipotezi, Finansal Sektör Gelişmesi, Ekonomik Küreselleşme

How to Cite

ÖZDEMİR, O. (2020). FINANCIAL KUZNETS CURVE, GLOBALISATION AND INCOME DISTRIBUTION: THE ELEMENTS OF TRIPARTITE RELATIONSHIP. Business & Management Studies: An International Journal, 8(3), 2868–2892. https://doi.org/10.15295/bmij.v8i3.1570

Abstract

This paper reexamines the empirical validity of financial Kuznets hypothesis in terms of looking for functional income distribution and economic globalisation for OECD countries over the 1980-2017 period. In doing so, the current study applies the panel fixed-effects and the system-GMM approaches to show that the estimates are complemented with the traditional assumptions on the financial Kuznets hypothesis. From a functional income distribution perspective, the empirical findings highlight the importance of financial sector development in reducing the income distribution between labor and capital. Also, the paper then provides new evidence on economic globalisation dynamics in exacerbating a more uneven distribution of income. Finally, the empirical findings imply that if any economic unit opens its borders without developing its financial sector, the labor’s share accruing in national income would be narrowed on behalf of capital over time.

PDF

Downloads

Download data is not yet available.

References

  1. Aizenman, J., Jinjarak, Y., and Park, D. (2015). Financial development and output growth in developing Asia and Latin America: A comparative sectoral analysis. NBER Working Paper 20917, National Bureau of Economic Research, Cambridge, Massachusetts.
  2. Arellano, M. and Bond, S. R. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58, 277-297.
  3. Arellano, M. and Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68, 29-51.
  4. Banerjee, A. V. and Newman, A. F. (1993). Occupational choice and the process of development. Journal of Political Economy, 101, 274-298.
  5. Blundell, R. and Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87, 115-143.
  6. Bumann, S. and Lensink, R. (2016). Capital account liberalisation and income inequality. Journal of International Money and Finance, 61, 143-162.
  7. Chinn, M. D. and Ito, H. (2006). What matters for financial development? Capital controls, institutions, and interactions. Journal of Development Economics, 81, 163-192.
  8. Čihák, M., Demirgüç-Kunt, A., Feyen, E., and Levine, R. (2012). Benchmarking financial development around the world. World Bank Policy Research Working Paper 6175, World Bank, Washington, DC.
  9. de Haan, J. and Sturm, J.-E. (2017). Finance and income inequality: A review and new evidence. European Journal of Political Economy, 50, 171-195.
  10. de Haan, J., Pleninger, R., and Sturm, J.-E. (2018). Does the impact of financial liberalisation on income inequality depend on financial development? Some new evidence. Applied Economic Letters, 25, 313-316.
  11. Driscoll, J. C. and Kraay, A. C. (1998). Consistent covariance matrix estimation with spatially dependent panel data. Review of Economics and Statistics, 80, 549-560.
  12. Feenstra, R. C., Inklaar, R., and Timmer, M. P. (2015). The next generation of the Penn World Table. American Economic Review, 105, 3150-3182.
  13. Galor, O. and Zeira, J. (1993). Income distribution and macroeconomics. Review of Economic Studies, 60, 35-52.
  14. Gollin, D. (2002). Getting income shares right. Journal of Political Economy, 110, 458-474.
  15. Greenwood, J. and Jovanovic, B. (1990). Financial development, growth, and the distribution of income. Journal of Political Economy, 98, 1076-1107.
  16. Gygli, S., Haelg, F., Potrafke, N., and Sturm, J-E. (2019). The KOF globalisation index – revisited. The Review of International Organizations, 14, 543-574.
  17. Hansen, L. P. (1982). Large sample properties of generalised method of moments estimators. Econometrica, 50, 1029-1054.
  18. Jauch, S. and Watzka, S. (2016). Financial development and income inequality: A panel data approach. Empirical Economics, 51, 291-314.
  19. Jaumotte, F., Lall, S., and Papageorgiou, C. (2008). Rising income inequality: Technology, or trade and financial globalisation? IMF Working Paper 08/185, International Monetary Fund.
  20. Jayadev, A. (2007). Capital account openness and the labor share of income. Cambridge Journal of Economics, 31, 423-443.
  21. Kappel, V. (2010). The effects of financial development on income inequality and poverty. CER-ETH Economics Working Paper Series 10/127, CER-ETH Center of Economic Research (CER-ETH) at ETH Zurich.
  22. Krueger, A. (1999). Measuring labor’s share. American Economic Review, 89, 45-51.
  23. Nikoloski, Z. (2012). Financial sector development and inequality: Is there a financial Kuznets curve? Journal of International Development, 25, 897-911.
  24. Rajan, R. G. (2010). Fault lines. Princeton: Princeton University Press.
  25. Roodman, D. (2006). How to do xtabond2: an introduction to “difference” and “system” GMM in Stata. Center for Global Development, Working Paper Number 103, December.
  26. Svirydzenka, K. (2016). Introducing a new broad-based index of financial development. IMF Working Paper 16/5, International Monetary Fund.
  27. Tan, H. B. and Law, S. H. (2012). Nonlinear dynamics of the finance-inequality nexus in developing countries. Journal of Economic Inequality, 10, 551-563.
  28. Windmeijer, F. (2005). A finite sample correction for the variance of linear efficient two-step GMM estimators. Journal of Econometrics, 126, 25-51.