Semiparametric Censored Regression Models

Kenneth Y. Chay

195 citations0/0 files storedThe Journal of Economic Perspectives

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Labor market dynamics and wage inequality Income, Poverty, and Inequality Statistical Methods and Inference

Abstract

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.

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References

2019American Economic Review 1994Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression 1987The Sensitivity of an Empirical Model of Married Women's Hours of Work to Economic and Statistical Assumptions 1992Trimmed Lad and Least Squares Estimation of Truncated and Censored Regression Models with Fixed Effects 1991Semiparametric ARCH Models 1973The Effect of Children on the Housewife's Value of Time

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