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Efficient semiparametric estimation for Gini inequality treatment effects

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  • Lv, Xiaofeng
  • Li, Rui
  • Fang, Zheng

Abstract

This paper evaluates the effects of a program on Gini index where the selection to treatment depends on covariates. We propose a two-step nonparametric estimation procedure for the Gini inequality treatment effects. The proposed new estimator is shown to be consistent and has asymptotical normal distribution. We also show that the proposed estimator achieves semiparametric efficiency bound. Simulations confirm the theoretical results and show that the proposed estimator has good finite sample performance.

Suggested Citation

  • Lv, Xiaofeng & Li, Rui & Fang, Zheng, 2017. "Efficient semiparametric estimation for Gini inequality treatment effects," Economics Letters, Elsevier, vol. 154(C), pages 96-100.
    • Handle: RePEc:eee:ecolet:v:154:y:2017:i:c:p:96-100
    DOI: 10.1016/j.econlet.2017.02.038
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    References listed on IDEAS

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    1. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
    2. Qin, Yongsong & Rao, J.N.K. & Wu, Changbao, 2010. "Empirical likelihood confidence intervals for the Gini measure of income inequality," Economic Modelling, Elsevier, vol. 27(6), pages 1429-1435, November.
    3. Qi Li & Jeffrey S. Racine & Jeffrey M. Wooldridge, 2008. "Estimating Average Treatment Effects with Continuous and Discrete Covariates: The Case of Swan-Ganz Catheterization," American Economic Review, American Economic Association, vol. 98(2), pages 357-362, May.
    4. Davidson, Russell, 2009. "Reliable inference for the Gini index," Journal of Econometrics, Elsevier, vol. 150(1), pages 30-40, May.
    5. Newey, Whitney K, 1990. "Semiparametric Efficiency Bounds," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(2), pages 99-135, April-Jun.
    6. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    7. Rothe, Christoph, 2010. "Nonparametric estimation of distributional policy effects," Journal of Econometrics, Elsevier, vol. 155(1), pages 56-70, March.
    8. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
    9. Li, Qi & Racine, Jeffrey S. & Wooldridge, Jeffrey M., 2009. "Efficient Estimation of Average Treatment Effects with Mixed Categorical and Continuous Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 206-223.
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    Cited by:

    1. Roman Matkovskyy, 2020. "A measurement of affluence and poverty interdependence across countries: Evidence from the application of tail copula," Bulletin of Economic Research, Wiley Blackwell, vol. 72(4), pages 404-416, October.

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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