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Sample selection in unconditional quantile models

Grant number: 19/20277-3
Support Opportunities:Scholarships in Brazil - Doctorate (Direct)
Effective date (Start): January 01, 2020
Effective date (End): April 30, 2022
Field of knowledge:Applied Social Sciences - Economics - Quantitative Methods Applied to Economics
Principal Investigator:Sergio Pinheiro Firpo
Grantee:Stefanie Sayuri Sunao
Host Institution: Instituto de Ensino e Pesquisa (Insper). São Paulo , SP, Brazil


The objective of this project is to construct a consistent estimator that addresses the problem of sample selection in unconditional quantile models. The proposed approach is based on three steps: (i) estimation of a control function using a logistic distribution regression; (ii) construction of a counterfactual distribution of the latent dependent variable using the previously estimated control function; (iii) application of the Recentered Influence Function (RIF) on the variable recovered from the counterfactual distribution and, finally, we run an ordinary least square regression. Besides this theoretical contri-bution, we propose an empirical application to measure the impact of maternity in the gender gap in Brazil. (AU)

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