Blinder-Oaxaca Decomposition for Tobit Models In this paper, a decomposition method for Tobit-models is derived, which allows the differences in a censored outcome variable between two groups to be decomposed into a part that is explained by differences in observed characteristics and a part attributable to differences in the estimated coefficients. The method is applied to a decomposition of t...

This study focuses on a comparison and evaluation of models and estimators appropriate for time-use data. The tobit type I as well as different generalizations are used. According to our findings, a simple tobit I method can produce results that are similar and in some cases even better to the much more sophisticated methods. This is especially true if the participation or index equation is inc...

This study examined characteristics of individual bond and stock holders, using data from the 1989 Survey of Consumer Finances. The results of the tobit models showed bonds and stocks are more likely to be held by families with adequate financial resources to maintain daily lives and enough funds to meet short term financial needs. Households having a financial planning horizon of ten years or ...

This paper considers the censored regression model under the assumption that the regressors are integrated. We show that Maximum Likelihood estimation is superconsistent and asymptotically mixed normal, implying that standard inference techniques remain valid, and that in general least squares estimation based on the positive observations only is superconsistent, but not mixed normal. An except...

Abstract We propose a variational inference-based framework for training Gaussian process regression model subject to censored observational data. Data censoring is typical problem encountered during the data gathering procedure and requires specialized techniques perform inference since resulting probabilistic models are typically analytically intractable. In this article we exploit sparse ind...

Studies investigating crash rates by roadway classification are few and far between and even more so if extended to focus on heavy vehicles. This study explores and compares two advanced econometric methods, random-parameter Tobit regression and latent class Tobit regression, to determine contributing factors for heavy vehicle crashes per million-vehicle-miles-traveled while accounting for the ...