Semiparametric Censored Regression Models
回顾了几种无需设定误差分布形式的半参数删失回归估计量，并用其分析1960年代美国黑人与白人收入差距的变化，发现1964年民权法案通过后南方男性收入显著趋同。
When data are censored, ordinary least squares regression can provide biased coefficient estimates. Maximum likelihood approaches to this problem are valid only if the error distribution is correctly specified, which can be problematic in practice. We review several semiparametric estimators for the censored regression model that do not require parameterization of the error distribution. These estimators are used to examine changes in black-white earnings inequality during the 1960s based on censored tax records. The results show that there was significant earnings convergence among black and white men in the American South after the passage of the 1964 Civil Rights Act.