Quantile Regression Estimation of Panel Duration Models with Censored Data

• Activity Number: 60
• Type: Topic Contributed
• Date/Time: Sunday, July 29, 2012 : 4:00 PM to 5:50 PM
• Sponsor: Section on Nonparametric Statistics
• Author(s): Carlos Lamarche*+ and Matthew Harding
• Companies: University of Oklahoma and Stanford University
• Keywords: Quantile Regression ; Duration Models ; Panel Data

Abstract

This paper studies the estimation of quantile regression panel duration models. We allow for the possibility of endogenous covariates and endogenous individual effects in the quantile regression models. We propose a quantile regression approach for panel duration models under conditionally independent censoring. The procedure involves minimizing $\ell_1$ convex objective functions and is motivated by a martingale property associated with survival data in models with endogenous covariates. We carry out a series of Monte Carlo simulations to investigate the small sample performance of the proposed approach in comparison with other existing methods. An empirical application of the method illustrates the approach.