A new approach to estimate household food demand with panel data

Dong Diansheng, Stewart Hayden and McLaughlin Patrick

Journal of Applied Economics, 2018, vol. 21, issue 1, 122-136

Abstract: This article develops a model of food demand in which the quality and quantity of food purchased and the inter-purchase time are determined simultaneously. We use this model to explore the relationship between a household’s cereal purchases and its demographic variables. Households eligible to participate in the U.S. Government Special Supplemental Nutrition Program for Women, Infants, and Children are found to purchase a larger quantity of cereals when making a purchase and also buy more often. The model is estimated using data from Information Resources Inc.’s National Consumer Panel. These data are heavily censored at zero. The traditional approach for working with such data in demand estimation usually involves accounting for the missing unit value for non-purchase occasions and the evaluation of multivariate probabilities. However, our methodology overcomes these problems by modeling the inter-purchase time rather than modeling whether or not a purchase is made in a given time period.

Date: 2018
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DOI: 10.1080/15140326.2018.1526869

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