Estimation of Semiparametric Censored Regression Models: An Application to Changes in Black-White Earnings Inequality during the 1960s
利用个体面板数据，通过半参数删失回归模型估计民权政策对黑人经济进步的影响，发现1960年代南方黑白收入显著趋同，并指出半参数方法有助于识别模型设定错误。
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.