Heterogeneity and nonconstant effect in two-stage quantile regression
Christophe Muller ()
Econometrics and Statistics, 2018, vol. 8, issue C, 3-12
Heterogeneity in how some independent variables affect a dependent variable is pervasive in many phenomena. In this respect, this paper addresses the question of constant versus nonconstant effect through quantile regression modelling. For linear quantile regression under endogeneity, it is often believed that the fitted-value setting (i.e., replacing endogenous regressors with their exogenous fitted-values) implies constant effect (that is: the coefficients of the covariates do not depend on the considered quantile, except for the intercept). Here, it is shown that, under a weakened instrumental variable restriction, the fitted-value setting can allow for nonconstant effect, even though only the constant-effect coefficients of the model can be identified. An application to food demand estimation in 2012 Egypt shows the practical potential of this approach.
Keywords: Two-stage estimation; Quantile regression; Fitted-value setting; Nonconstant effect; Partial identification (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only. Contains open access articles
Working Paper: Heterogeneity and nonconstant effect in two-stage quantile regression (2018)
Working Paper: Heterogeneity and Non-Constant Effect in Two-Stage Quantile Regression (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:8:y:2018:i:c:p:3-12
Access Statistics for this article
Econometrics and Statistics is currently edited by E.J. Kontoghiorghes, H. Van Dijk and A.M. Colubi
More articles in Econometrics and Statistics from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().