The relationship between Food Stamp Program (FSP) participation and household food insecurity (FI) is investigated using data from the 1996-1997 National Food Stamp Program Survey. Endogeneity of FSP participation is accommodated with an instrumental variables approach. In contrast to other...

A quasi-maximum-likelihood estimator is proposed and applied to a censored Translog demand system for foods, using a sample of food stamp recipients in the United States. The procedure produces remarkably close parameter and elasticity estimates to those of the simulated-maximum-likelihood...

A censored linear almost ideal demand system for food is estimated with a Bayesian Markov chain Monte Carlo procedure, using a sample of urban households from Pakistan. All own-price elasticities but one are found to be negative, and all total food expenditure elasticities are found to be...

The multivariate sample selection model is extended to a nonlinear equation system with partial selection and applied to household meat consumption in China. Elasticity estimates differ from those obtained from conventional maximum likelihood and Tobit estimates. Chinese meat products are gross...

A quasi-maximum-likelihood estimator is proposed and applied to a censored Translog demand system for foods, using a sample of food stamp recipients in the United States. The procedure produces remarkably close parameter and elasticity estimates to those of the simulated-maximum-likelihood...

The relationship between Food Stamp Program (FSP) participation and household food insecurity (FI) is investigated using data from the 1996–1997 National Food Stamp Program Survey. Endogeneity of FSP participation is accommodated with an instrumental variables approach. In contrast to other...

Heckman's sample-selection model is generalized to the multivariate case and used to estimate demands for cigarettes, beer, and wine by individuals in the United States. The specification allows correlations between the error terms of multiple selection and level equations, and nests the popular...