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    Household Fruit and Vegetable Demand Estimation and Forecasting: A Revealed Preference Approach

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    Author
    Blumberg, Joseph E.
    Issue Date
    2019
    Keywords
    Demand Forecasting
    Elasticity
    Revealed Prerence
    Segmentation
    Advisor
    Thompson, Gary
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    Applying 2016-2017 household scanner data from market research firm IRI, we combine parametric and nonparametric techniques in estimating demands and forecasting consumption for six aggregated fruit and vegetable categories. The 2016 data is segmented by revealed preference (RP) such that the behavior in each subset of households is consistent with traditional utility theory, and a nonlinear Almost Ideal Demand System (NL-AIDS) model is estimated for all subsets. For comparison, demands are also estimated when the data is segmented separately on geography and household demographics. Own-price and expenditure elasticities generated across RP-consistent subsets indicate a wide range of demand responsiveness, whereas geographic and demographic subsets show similar behavior. Demand is generally more elastic for perishable goods than non-perishable. All methods of segmentation perform similarly when forecasting consumption into 2017.
    Type
    text
    Electronic Thesis
    Degree Name
    M.S.
    Degree Level
    masters
    Degree Program
    Graduate College
    Agricultural & Resource Economics
    Degree Grantor
    University of Arizona
    Collections
    Master's Theses

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