Bayesian Estimation of a Censored AIDS Model for Whole Grain Products

When using household-level data in examining consumer's demand it is common to find that consumers purchase only a subset of the available goods, setting the demand for the remaining goods to zero. Ignoring such censoring of the dependent variables in the estimation can lead to biased parameter estimates. In this paper we investigate the household's demand for six types of whole grain and non-whole grain breakfast cereals and products using a censored Almost Ideal Demand System (AIDS) and estimate the parameters of the demand system via Bayesian methods. Using 2006 ACNielsen Homescan data we find that demand for whole grain and non-whole grain ready-to-eat cereals is less responsive to changes in prices; demand for whole-grain bars and non-whole grain hot cereals is relatively price sensitive. The elasticity estimates show that whole grain ready-to-eat cereals and whole grain bars have relatively higher expenditure elasticities than is the case for the other goods.