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dc.date.accessioned 2019-12-12T17:38:58Z
dc.date.available 2019-12-12T17:38:58Z
dc.date.issued 2015
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/87327
dc.description.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. en
dc.format.extent 719-732 es
dc.language en es
dc.subject Counterfactual distributions es
dc.subject Grid method es
dc.subject Income distribution es
dc.subject Labor market es
dc.subject Numeric integration es
dc.subject Quantile regression es
dc.title Counterfactual distributions in bivariate models en
dc.type Articulo es
sedici.identifier.other doi:10.3390/econometrics3040719 es
sedici.identifier.other eid:2-s2.0-85063824477 es
sedici.identifier.issn 2225-1146 es
sedici.title.subtitle A conditional quantile approach en
sedici.creator.person Alejo, Javier es
sedici.creator.person Badaracco, Nicolás es
sedici.subject.materias Ciencias Económicas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Ciencias Económicas es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0/
sedici.description.peerReview peer-review es
sedici.relation.journalTitle Econometrics es
sedici.relation.journalVolumeAndIssue vol. 3, no. 4 es
sedici.rights.sherpa * Color: green * Pre-print del autor: can * Post-print del autor: can * Versión de editor/PDF:can * Condiciones: >>On open access repositories >>Publisher's version/PDF may be used >>Published source must be acknowledged >>Creative Commons Attribution License 4.0 >>Authors retain copyright >>Authors are encouraged to submit their published articles to institutional repositories >>All titles are open access journals * Link a Sherpa: http://sherpa.ac.uk/romeo/issn/2225-1146/es/


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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)