Semiparametric Censored Regression Models
Bibliographic Data
| ID | 4030338 |
|---|---|
| Authors | Kenneth Y Chay (University of California, Berkeley, California.), James L Powell (0000-0002-8362-6863, University of California, Berkeley, California.) |
| Year | 2001 |
| Volume | 15 |
| Issue | 4 |
| Pages | 29-42 |
| Publication date | 2001-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The Journal of Economic Perspectives (JOURNAL) |
| Journal identifiers | ISSN: 0895-3309 • E-ISSN: 1944-7965 |
| Publisher | American Economic Association (PUBLISHER • US) |
| DOI | 10.1257/jep.15.4.29 |
| OpenAlex | W2115016757 |
| Language | EN |
| Citations received | 21 |
| References cited | 15 |
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
Asymptotic distribution · Censored regression model · Earnings · Econometrics · Economics · Estimator · Ordinary least squares · Regression · Regression analysis · Semiparametric model · Semiparametric regression · Standard error · Statistics · Income, Poverty, and Inequality · Mathematics · School Choice and Performance · Urban, Neighborhood, and Segregation Studies · Finance
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| Citations per year | 0.91 |
|---|---|
| Citation span | 2003 - 2020 (18) |
| Highly cited | No |