A two-step model with sample selection is applied to panel data of U.S. households to estimate at-home demand for fluid milk and cheese, incorporating advertising expenditures. The model consistently accounts for sample-selection bias, unobserved household heterogeneity, and temporal...

The modeling of micro-level food demand patterns requires not only allowing for household heterogeneity, but also addressing the problem of censoring. In this article, we present a variation of the Amemiya-Tobin framework for estimating a censored demand system that allows for household...

A two-step sample selection model is used to estimate household demand equations for fluid milk and cheese products incorporating national generic advertising. This approach allows us to disentangle the incidence of the advertising effect on the probability of purchase and changes in the level...

The modeling of micro-level food demand patterns requires not only allowing for household heterogeneity, but also addressing the problem of censoring. In this article, we present a variation of the Amemiya-Tobin framework for estimating a censored demand system that allows for household...

This study develops an empirical framework to estimate quality-adjusted price elasticities from cross-sectional data. The new approach shows the importance of properly adjusting for quality variation in both prices and quantities in demand analysis. When quality adjustment is concerned only with...

Consistent two-step censored estimation is applied to household demand equations for disaggregated milk and cheese products. The long-run advertising elasticity for total milk was positive, largely due to low fat milk; however the elasticity for cheese was not significant, and only shredded...

The use of household surveys for demand system estimation necessitates a recognition of purchase censoring that often arises within an analysis of a disaggregated set of commodities. We extend the Amemiya-Tobin demand system approach to an analysis of Mexican household food demand via the use of...