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Counterfactual distributions of wages via quantile regression with endogeneity

Author

Listed:
  • Elena Martínez Sanchis

    (Dpto. Fundamentos del Análisis Económico)

  • Ilker Kandemir

    (Department of Economics)

  • Juan Mora López

    (Universidad de Alicante)

Abstract

Counterfactual decompositions allow the researcher to analyze the changes in wage distributions by discriminating between the effect of changes in the population characteristics and the effect of changes in returns to these characteristics. In this paper, counterfactual distributions are derived by recovering the conditional distribution via a set of quantile regressions, and correcting for the endogeneity of schooling decisions using a control function approach. Our proposal enables us to isolate the effect on the wage distribution of changes in both the conditional and unconditional distribution of schooling and changes in the distribution of unobserved ability. This methodology is used to analyze the sources of the changes in wage distribution that took place in the United States between 1983 and 1993, using proximity to college for different parental background as instruments. Our results show that the change in the distribution of ability had a negative effect on wages at the low quantiles, which almost compensates the positive effect of the change in the schooling distribution over this period. It is also found that the impact on wages of changes in the conditional distribution of unobserved ability is larger than the impact of changes in the conditional distribution of distance to college.

Suggested Citation

  • Elena Martínez Sanchis & Ilker Kandemir & Juan Mora López, 2011. "Counterfactual distributions of wages via quantile regression with endogeneity," Working Papers. Serie AD 2011-25, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    • Handle: RePEc:ivi:wpasad:2011-25
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    References listed on IDEAS

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    Cited by:

    1. Martinez-Sanchis, Elena & Mora, Juan & Kandemir, Ilker, 2012. "Counterfactual distributions of wages via quantile regression with endogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3212-3229.
    2. Santiago Pereda-Fernández, 2024. "Estimation of counterfactual distributions with a continuous endogenous treatment," Econometric Reviews, Taylor & Francis Journals, vol. 43(8), pages 595-637, September.
    3. Jeremiah Richey & Alicia Rosburg, 2018. "Decomposing economic mobility transition matrices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 91-108, January.
    4. Raquel Carrasco & Juan F. Jimeno & A. Carolina Ortega, 2011. "Accounting for changes in the Spanish wage distribution: the role of employment Composition effects," Working Papers 1120, Banco de España.

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    More about this item

    Keywords

    Counterfactual Decomposition; Wage Inequality; Quantile Regression; Endogeneity;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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