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Instrumental Variables Estimation of Quantile Treatment Effects

Author

Listed:
  • Alberto Abadie
  • Joshua D. Angrist
  • Guido W. Imbens

Abstract

This paper introduces an instrumental variables estimator for the effect of a binary treatment on the quantiles of potential outcomes. The quantile treatment effects (QTE) estimator accommodates exogenous covariates and reduces to quantile regression as a special case when treatment status is exogenous. Asymptotic distribution theory and computational methods are derived. QTE minimizes a piecewise linear objective function for which a local minimum can be obtained using a modified Barrodale-Roberts algorithm. The QTE estimator is illustrated by estimating the effect of childbearing on the distribution of family income.

Suggested Citation

  • Alberto Abadie & Joshua D. Angrist & Guido W. Imbens, 1998. "Instrumental Variables Estimation of Quantile Treatment Effects," NBER Technical Working Papers 0229, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberte:0229
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    Cited by:

    1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2008. "Nonparametric Tests for Treatment Effect Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 389-405, August.
    2. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    3. Kim, Taejong & Lee, Ju-Ho & Lee, Young, 2008. "Mixing versus sorting in schooling: Evidence from the equalization policy in South Korea," Economics of Education Review, Elsevier, vol. 27(6), pages 697-711, December.
    4. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521608275.
    5. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    6. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
    7. Denis Cogneau & Michael Grimm, 2007. "The Measurement Of Income Distribution Dynamics When Demographics Are Correlated With Income," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 53(2), pages 246-274, June.
    8. Adriana Kugler & Robert Sauer, 2002. "Doctors without borders: The returns to an occupational license for Soviet immigrant physicians in Israel," Economics Working Papers 648, Department of Economics and Business, Universitat Pompeu Fabra.
    9. Alberto Abadie, 2000. "Semiparametric Estimation of Instrumental Variable Models for Causal Effects," NBER Technical Working Papers 0260, National Bureau of Economic Research, Inc.
    10. Shlomo Yitzhaki & Edna Schechtman, 2004. "The Gini Instrumental Variable, or the “double instrumental variable” estimator," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 287-313.
    11. Klette, Tor Jakob & Moen, Jarle & Griliches, Zvi, 2000. "Do subsidies to commercial R&D reduce market failures? Microeconometric evaluation studies1," Research Policy, Elsevier, vol. 29(4-5), pages 471-495, April.
    12. Sergio Firpo & Cristine Pinto, 2016. "Identification and Estimation of Distributional Impacts of Interventions Using Changes in Inequality Measures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 457-486, April.
    13. Ana C. Dammert, 2009. "Heterogeneous Impacts of Conditional Cash Transfers: Evidence from Nicaragua," Economic Development and Cultural Change, University of Chicago Press, vol. 58(1), pages 53-83, October.
    14. Firpo, Sergio Pinheiro, 2010. "Identification and estimation of interventions using changes in inequality measures," Textos para discussão 214, FGV/EESP - Escola de Economia de São Paulo, Getulio Vargas Foundation (Brazil).

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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