Estimation of Semiparametric Censored Regression Models: An Application to Changes in Black-White Earnings Inequality during the 1960s

Abstract

Building on the work of Chay (1995), this study examines the impact of civil rights policies on black economic progress using individual-level panel data. Many earnings records are censored and the degree of censoring changed during the period of interest. Consequently, valid estimates of the program effects must account for this censoring. Maximum likelihood estimation can be used if the error terms of the model are identically normally distributed. We investigate the value of using weaker assumptions on the error process to estimate the laws impact. The analysis shows that there was significant black-white earnings convergence in the South during the 1960s. We also find that semiparametric estimation methods are informative in pinpointing which parts of the model are mis-specified.