dc.creatorAlejo, Javier
dc.creatorBadaracco, Nicolás
dc.date2015
dc.date2019-12-12T17:38:58Z
dc.date.accessioned2023-07-14T17:29:46Z
dc.date.available2023-07-14T17:29:46Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/87327
dc.identifierissn:2225-1146
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7427701
dc.descriptionThis 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.
dc.descriptionFacultad de Ciencias Económicas
dc.formatapplication/pdf
dc.format719-732
dc.languageen
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.subjectCiencias Económicas
dc.subjectCounterfactual distributions
dc.subjectGrid method
dc.subjectIncome distribution
dc.subjectLabor market
dc.subjectNumeric integration
dc.subjectQuantile regression
dc.titleCounterfactual distributions in bivariate models : A conditional quantile approach
dc.typeArticulo
dc.typeArticulo


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