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...

abstract the purpose of this study is investigating factors affect on probability of willingness to pay sugar beet farmers for taking of agricultural extension services. logit model was used for cross sectional data in 2009 between 150 sugar beet farmers that were selected by random sampling in the city of mashhad. in addition, tobit model was used to analyse factors affecting on willingness to...

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...

The inability of households to save over time has significant influence on the rate of capital accumulation and economic growth in developing countries. In order to understand this trend, this research assesses savings rates and its correlates in rural Kwara state, Nigeria. A multistage sampling procedure was used to obtain data from 120 households. This was then analyzed using two descriptive ...

Hospital expenses are a major cost driver of healthcare systems in Europe, with motor injuries being the leading mechanism of hospitalizations. This paper investigates the injury characteristics which explain the hospitalization of victims of traffic accidents that took place in Spain. Using a motor insurance database with 16,081 observations a generalized Tobit regression model is applied to a...

A Bayesian approach is proposed for coefficient estimation in Tobit quantile regression model. The proposed approach is based on placing a g-prior distribution depends on the quantile level on the regression coefficients. The prior is generalized by introducing a ridge parameter to address important challenges that may arise with censored data, such as multicollinearity and overfitting problems...