The usual decomposition of effects in corner solution models into extensive and intensive margins is generally incompatible with a causal interpretation. This paper proposes a decomposition based on the joint distribution of potential outcomes which is meaningful in a causal sense. The difference between decompositions can be substantial and yield diametrically opposed results, as shown in a st...

In this paper I propose a computationally practical simulation estimator for large categories of the dynamic panel Tobit model with complicated dependence structures. I first apply the sequential decomposition methods introduced by Hendry and Richard (1992) to obtain the tractable simulated log-likelihood function of the dynamic panel Tobit model. I then maximize this log-likelihood function si...

Our primary objective is to assess the role of culture by linking college students’ current consumption of fruits and vegetables with their produce consumption levels while with family. Using a Tobit model, we analyzed data from an online survey with college students. Family consumption of fruits was highly predictive of the individual’s consumption of fruits. For each unit increase in the repo...

Ownership structure and industry characteristics as internal and external factors respectively significantly impact the export performance of Chinese manufacturing firms. Three different yet related models, namely, logit, tobit and ordered probit models, that correspond to three different indicators of export performance are considered. It was found that the export performance of Chinese manufa...

Emergency events have been known more quickly and attained more attention than they did ever before. However, the public opinion on Internet usually exerts a heavy impact on the development of the emergency events as well as the social psychology. Aiming to provide a practical methodology for the management of Internet spread of emergency events, this paper presented a cycle model to describe t...

We use a dynamic panel Tobit model with heteroskedasticity to generate forecasts for large cross‐section of short time series censored observations. Our fully Bayesian approach allows us flexibly estimate the cross‐sectional distribution heterogeneous coefficients and then implicitly this as prior construct Bayes individual series. In addition density forecasts, we set that explicitly target av...

The standard tobit or censored regression model is typically utilized for regression analysis when the dependent variable is censored. This model is generalized by developing a conditional mixture, maximum likelihood method for latent class censored regression. The proposed method simultaneously estimates separate regression functions and subject membership in K latent classes or groups given a...

The purpose of this study is designing a model based on Tobit regression, DEA, Artificial Neural Network, Genetic Algorithm and Particle Swarm Optimization to evaluate the efficiency and also benchmarking the efficient and inefficient units. This model has three stages, and it uses the data envelopment analysis combined model with neural network, optimized by genetic algorithm, to evaluate the ...

Absenteeism research has often been criticized for using inappropriate analysis. Characteristics of absence data, notably that it is usually truncated and skewed, violate assumptions of OLS regression; however, OLS and correlation analysis remain the dominant models of absenteeism research. This piece compares eight models that may be appropriate for analyzing absence data. Specifically, this p...