This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of the coefficients in a truncated regression model. The distribution of the errors is unknown and permits general forms of unknown heteroskedasticity. Also provided is an instrumental variables based...

We propose an estimation procedure for a semiparametric panel data censored regression model in which the error terms may be subject to general forms of nonstationarity. Specifically, we allow for heteroskedasticity over time and a time varying factor load on the individual specific effect....

Given the existence of non-selective universities, the question of whether to employ racial preferences in college admissions reduces to one of optimal allocation of a finite resource: students who are members of under-represented racial or ethnic groups. In this paper, we assess recent legal...

We quantify the identifying power of special regressors in heteroskedastic binary regressions with median-independent or conditionally symmetric errors. We measure the identifying power using two criteria: the set of regressor values that help point identify coefficients in latent payoffs as in...

We consider identification and estimation of a Roy model that includes a common nonpecuniary utility component associated with each choice alternative. This augmented Roy model has broader applications to many polychotomous choice problems in addition to occupational sorting. We develop a pair...