Sample selection in unconditional quantile models

• Grant number: 19/20277-3
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date: January 01, 2020
• End date: 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

Abstract

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)