The goal of this paper is to introduce a partially adaptive estimator for the censored regression model based on an error structure described by a mixture of two normal distributions. The model we introduce is easily estimated by maximum likelihood using the EM algorithm adapted from the work of Bartolucci and Scaccia (2004). A Monte Carlo study is conducted to examine the small sample properti...

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...

When no discharge record is available for a site, a regional regression relationship can be used to estimate low-flow quantiles. Problems arise in the derivation of such models when some at-site quantile estimates are reported as zero. One concern is that quantile estimates reported as zero may be in the range from zero to the measurement threshold. A second concern is that a logarithmic transf...

Most of the population of Nigeria is rural and agriculture is the mainstay of the impoverished people’s livelihood. This paper estimated the determinants of rural poverty in Nigeria using the Tobit regression model. Through the multistage sampling technique, primary data were obtained from 150 rural farming households using a questionnaire. The Result of Tobit regression analysis shows that inc...

We consider the Bayes estimation of the Tobit censored regression model with normally distributed errors. A simple condition for the existence of posterior moments is provided. Suitable versions of Monte Carlo procedures based on symmetric multivariate-t distributions, and Laplacian approximations in a certain parametrization, are developed and illustrated. Ideas involving data augmentation and...

In this paper, we use a semi-parametric two-stage model to examine the effect of bankspecific, industry-specific and macroeconomic determinants of bank efficiency. This method, proposed by Simar and Wilson (2007), relaxes several deficiencies of previous two-stage analyses, which regress non-parametric estimates of bank efficiency on exogenous determinants. In particular, we propose a bootstrap...

most of the population of nigeria is rural and agriculture is the mainstay of the impoverished people’s livelihood. this paper estimated the determinants of rural poverty in nigeria using the tobit regression model. through the multistage sampling technique, primary data were obtained from 150 rural farming households using a questionnaire. the result of tobit regression analysis shows that inc...

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...

We propose a new family of error distributions for model-based quantile regression, which is constructed through a structured mixture of normal distributions. The construction enables fixing specific percentiles of the distribution while, at the same time, allowing for varying mode, skewness and tail behavior. It thus overcomes the severe limitation of the asymmetric Laplace distribution – the ...