| We generalize the Tobit censored regression to permit unique unobserved censoring thresholds conditioned by covariates and a set of common response coefficients. This situation , we argue, is one arising frequently in applications of censored regression and we provide three diverse examples to motivate the theory. We derive a robust estimation algorithm with three noteworthy features. First, by augmenting the observed-data likelihood with the censored observations, the estimation strategy is the same as Chib (1992) who derives Bayes estimates of the conventional censored regression. Second, by virtue of its generality, the model is applicable to a much broader set of circumstances than the conventional Tobit regression, which is nested as a special case of... |
