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Counterfactual Distributions in Bivariate Models—A Conditional Quantile Approach

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  • Javier Alejo

    (Center for Distributive, Labor and Social Studies (CEDLAS) and CONICET, Facultad de Ciencias Económicas, Universidad Nacional de La Plata (UNLP), La Plata 1900, Argentina)

  • Nicolás Badaracco

    (Center for Distributive, Labor and Social Studies (CEDLAS), Facultad de Ciencias Económicas, Universidad Nacional de La Plata (UNLP), La Plata 1900, Argentina)

Abstract

This paper proposes a methodology to incorporate bivariate models in numerical computations of counterfactual distributions. The proposal is to extend the works of Machado and Mata (2005) and Melly (2005) using the grid method to generate pairs of random variables. This contribution allows incorporating the effect of intra-household decision making in counterfactual decompositions of changes in income distribution. An application using data from five latin american countries shows that this approach substantially improves the goodness of fit to the empirical distribution. However, the exercise of decomposition is less conclusive about the performance of the method, which essentially depends on the sample size and the accuracy of the regression model.

Suggested Citation

  • Javier Alejo & Nicolás Badaracco, 2015. "Counterfactual Distributions in Bivariate Models—A Conditional Quantile Approach," Econometrics, MDPI, vol. 3(4), pages 1-14, November.
  • Handle: RePEc:gam:jecnmx:v:3:y:2015:i:4:p:719-732:d:58510
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    References listed on IDEAS

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