Temporal Aggregation and Treatment of Zero Dependent Variables in the Estimation of Food Demand using Cross-Sectional Data

dc.creatorLeffler, Kristyn K.
dc.creatorCarpio, Carlos E.
dc.creatorBoonsaeng, Tullaya
dc.date2017-04-01T20:06:47Z
dc.date.accessioned2026-07-09T06:08:25Z
dc.descriptionThis study analyzes U.S. consumers' demand for eight food commodity groups: Cereal and Bakery goods, Meat and Eggs, Dairy, Fruits and Vegetables, Nonalcoholic Beverages, Fats and Oils, Sugar and Sweets, and Miscellaneous goods. The data used in this study is Nielsen Homescan data for the period 2002-2006. Two different levels of temporal aggregation, monthly and the average month within a year, referred to as "annual" were considered. We conclude that the models using monthly data closely approximate the underlying annual expenditure elasticities, but do a poor job of estimating own- and -cross price elasticities and marginal effects. This finding is true for both the uncensored model of Blundell and Meghir (1987), and the two-step censored model of Shonkwiler and Yen (1999). We also find that the more complex two-step censored model does not improve precision of the estimates over the simpler model.
dc.identifierdoi:10.22004/ag.econ.124913
dc.identifierhttps://ageconsearch.umn.edu/record/124913/files/Carpio.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/124913
dc.identifier.urihttp://hdl.handle.net/123456789/572799
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/124913
dc.titleTemporal Aggregation and Treatment of Zero Dependent Variables in the Estimation of Food Demand using Cross-Sectional Data
dc.typeText

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