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Identification and Estimation of Distributional Impacts of Interventions Using Changes in Inequality Measures

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  • Firpo, Sergio

    (Insper, São Paulo)

Abstract

This paper presents semiparametric estimators of distributional impacts of interventions (treatment) when selection to the program is based on observable characteristics. Distributional impacts of a treatment are calculated as differences in inequality measures of the potential outcomes of receiving and not receiving the treatment. These differences are called “Inequality Treatment Effects” (ITE). The estimation procedure involves a first non-parametric step in which the probability of receiving treatment given covariates, the propensity-score, is estimated. In the second step weighted sample versions of inequality measures are computed using weights based on the estimated propensity-score. Root-N consistency, asymptotic normality, semiparametric efficiency and validity of inference based on the bootstrap are shown for the semiparametric estimators proposed. In addition of being easily implementable and computationally simple, results from a Monte Carlo exercise reveal that its good relative performance in small samples is robust to changes in the distribution of latent selection variables. Finally, as an illustration of the method, we apply the estimator to a real data set collected for the evaluation of a job training program, using several popular inequality measures to capture distributional impacts of the program.

Suggested Citation

  • Firpo, Sergio, 2010. "Identification and Estimation of Distributional Impacts of Interventions Using Changes in Inequality Measures," IZA Discussion Papers 4841, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp4841
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    More about this item

    Keywords

    semiparametric efficiency; treatment effects; inequality measures; reweighting estimator;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

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