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The ARDL Test of Gender Kuznets Curve for G7 Countries

Author

Listed:
  • Dilara Kilinc

    (Department of Economics, Izmir University of Economics, Izmir-Turkey)

  • Esra Onater

    (Department of Economics, Izmir University of Economics, Izmir-Turkey)

  • Hakan Yetkiner

    (Department of Economics, Izmir University of Economics, Izmir-Turkey)

Abstract

The Gender Kuznets Curve (GKC) hypothesis argues that economic development has a nonlinear effect on the female share of workers. There is, however, growing debate on the exact shape of this non-linear relationship. The aim of this paper is to test the GKC hypothesis in order to determine whether data supports a quadratic or a cubic GKC for each G7 countries in the long run. The ARDL bounds testing approach of cointegration yields evidence for the following: Canada, United Kingdom and United States have an inverted U-shaped GKC; Japan has an S-shaped GKC, France has an inverted-S shaped GKC, and Italy and Germany have no long run GKC relationship in the respective periods of countries considered. We conclude that gender equality is not a direct result of development, and therefore policy makers having a gender equalization policy need to subsidize the employment of female workers in periods of downfall

Suggested Citation

  • Dilara Kilinc & Esra Onater & Hakan Yetkiner, 2015. "The ARDL Test of Gender Kuznets Curve for G7 Countries," The Journal of European Theoretical and Applied Studies, The Center for European Studies at Kirklareli University - Turkey, vol. 3(2), pages 37-56.
    • Handle: RePEc:kir:journl:v:3:y:2015:i:2:p:37-56
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    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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