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Differences In Decline: Quantile Regression Of Male–Female Earnings Differential In Malaysia

Author

Listed:
  • SIEW CHING GOY

    (Faculty of Social Sciences, Universiti Malaysia Sarawak, Kota Samarahan 94300, Sarawak, Malaysia)

  • GERAINT JOHNES

    (Department of Economics, Management School, Lancaster University, Lancaster LA1 4YX, UK)

Abstract
Semiparametric estimation has gained significant attention in the study of wage inequality between men and women in recent years. By extending the wage gap at the mean towards the entire wage distribution using quantile regression, it enables researchers to ascertain the direction and the proportions of differences in characteristics and returns to these characteristics at different parts of the wage distribution. This line of research has been prominent in western society but has not yet been explored in the context of the Malaysian labor market. To fill the gap, this paper examines the gender earnings gap in Malaysia between 1994 and 2004 using Malaysia Population and Family Survey data. The gender earnings differential, as measured by the log percentage point is 53% in 1994. The difference reduces to 45% for a restricted sample and 42% for the unrestricted sample in 2004. However, it was found that the gender wage gap reduces as we move up the wage distribution. This suggests that women suffer from a sticky floor effect, i.e., the gender wage gap is bigger at the bottom of distribution. More importantly, the observed gender wage differentials do not reflect differences in the productive characteristics of the workers. In fact, it accounts for very little, if any, of the gap in Malaysia. However, the extent of the price effect is larger at the bottom end of the distribution than at the top.

Suggested Citation

  • Siew Ching Goy & Geraint Johnes, 2015. "Differences In Decline: Quantile Regression Of Male–Female Earnings Differential In Malaysia," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 60(04), pages 1-20.
    • Handle: RePEc:wsi:serxxx:v:60:y:2015:i:04:n:s021759081550054x
    DOI: 10.1142/S021759081550054X
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    References listed on IDEAS

    as
    1. Florentino Felgueroso & Juan Prieto Rodríguez & María José Pérez-Villadóniga, 2007. "Collective Bargaining and the GenderWage Gap: A Quantile Regression Approach," Working Papers 2007-06, FEDEA.
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    5. James Albrecht & Aico van Vuuren & Susan Vroman, 2004. "Decomposing the Gender Wage Gap in the Netherlands with Sample Selection Adjustments," Tinbergen Institute Discussion Papers 04-123/3, Tinbergen Institute.
    6. James Albrecht & Aico van Vuuren, 2004. "Gender Wage Gaps in the Netherlands with Sample Selection Adjustments," Econometric Society 2004 North American Winter Meetings 504, Econometric Society.
    7. Sandrine Rospabe & Robert Breunig, 2004. "The male-female wage gap in France: an analysis using non-parametric methods," Econometric Society 2004 Australasian Meetings 205, Econometric Society.
    8. Manquilef-Bächler, Alejandra A. & Arulampalam, Wiji & Smith, Jennifer C., 2009. "Differences in Decline: Quantile Regression Analysis of Union Wage Differentials in the United Kingdom, 1991-2003," IZA Discussion Papers 4138, Institute of Labor Economics (IZA).
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    Cited by:

    1. Seneviratne, Prathi, 2020. "Gender wage inequality during Sri Lanka’s post-reform growth: A distributional analysis," World Development, Elsevier, vol. 129(C).

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    More about this item

    Keywords

    Earnings; discrimination; gender; J16; J31; J71;
    All these keywords.

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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