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The Contribution of Work Experience on Earnings Inequality of Migrant Workers: Decompositions Based on the Quantile Regression Equation

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  • Peng, Jiaqi
  • Li, Jun
  • Ma, Ling
  • Lv, Zhiwang

Abstract

This paper aims at excavating the influence factors of earning inequality, due to the increasing contribution of earning inequality to income inequality in a rural region. The authors examine the contribution of work experience on earning inequality using survey data. Employing the quantile regression, they estimate the Mincer equation of migrant workers’ earnings and decompose earning inequality by the regression-based decomposition. It has been found that the effects of work experience had been one of the most important contributors to earnings inequality, and its contribution is close to 20%. Furthermore, the authors use the same method to examine the effects on male migrant workers. The results show that work experience had a steady contribution to earning inequality.

Suggested Citation

  • Peng, Jiaqi & Li, Jun & Ma, Ling & Lv, Zhiwang, 2023. "The Contribution of Work Experience on Earnings Inequality of Migrant Workers: Decompositions Based on the Quantile Regression Equation," Research on World Agricultural Economy, Nan Yang Academy of Sciences Pte Ltd (NASS), vol. 4(1), April.
    • Handle: RePEc:ags:reowae:333786
    DOI: 10.22004/ag.econ.333786
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    References listed on IDEAS

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    1. Guanghua Wan, 2002. "Regression-based Inequality Decomposition: Pitfalls and a Solution Procedure," WIDER Working Paper Series DP2002-101, World Institute for Development Economic Research (UNU-WIDER).
    2. Sergio P. Firpo & Nicole M. Fortin & Thomas Lemieux, 2018. "Decomposing Wage Distributions Using Recentered Influence Function Regressions," Econometrics, MDPI, vol. 6(2), pages 1-40, May.
    3. Zhang, Li & Sharpe, Rhonda Vonshay & Li, Shi & Darity, William A., 2016. "Wage differentials between urban and rural-urban migrant workers in China," China Economic Review, Elsevier, vol. 41(C), pages 222-233.
    4. Patrinos, Harry Anthony & Ridao-Cano, Cris & Sakellariou, Chris, 2006. "Estimating the returns to education : accounting for heterogeneity in ability," Policy Research Working Paper Series 4040, The World Bank.
    5. Anthony Shorrocks, 2013. "Decomposition procedures for distributional analysis: a unified framework based on the Shapley value," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 11(1), pages 99-126, March.
    6. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1.
    7. Wan, Guanghua, 2004. "Accounting for income inequality in rural China: a regression-based approach," Journal of Comparative Economics, Elsevier, vol. 32(2), pages 348-363, June.
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