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Food expenditure patterns of the Hispanic population in the United States

Author

Listed:
  • Bruno A. Lanfranco

    (University of Georgia, Department of Agricultural and Applied Economics, Conner Hall, Athens, GA 30602-7509)

  • Glenn C.W. Ames

    (University of Georgia, Department of Agricultural and Applied Economics, Conner Hall, Athens, GA 30602-7509)

  • Chung L. Huang

    (University of Georgia, Department of Agricultural and Applied Economics, Conner Hall, Athens, GA 30602-7509)

Abstract

Food expenditure patterns were analyzed for Hispanic households in the United States. Engel curves for three food categories-total food (TF), food eaten at home (FAH), and food eaten away from home (FAFH)-were estimated using a semilogarithmic functional form. The models for TF and FAH were estimated by OLS, using heteroscedasticity consistent estimators. The equation for FAFH was estimated using a two-part model, with the level equation estimated by least squares with corrections for heteroscedasticity, using only the observations for which a positive amount of expenditures on FAFH was reported. The estimated income elasticity of demand for food for Hispanic households were 0.29 for TF, 0.21 for FAH, and 0.49 for FAFH. Household size elasticities were 0.32, 0.40, and 0.07, respectively. Our analysis indicates that Hispanic households devoted a higher proportion of their budget to FAH, 25.8%, than the average American household, while the proportion spent on FAFH was only 3.6%.[EconLit citations: L610.] © 2002 Wiley Periodicals, Inc.

Suggested Citation

  • Bruno A. Lanfranco & Glenn C.W. Ames & Chung L. Huang, 2002. "Food expenditure patterns of the Hispanic population in the United States," Agribusiness, John Wiley & Sons, Ltd., vol. 18(2), pages 197-211.
    • Handle: RePEc:wly:agribz:v:18:y:2002:i:2:p:197-211
    DOI: 10.1002/agr.10011
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    Cited by:

    1. Arjun Gupta & Soudeh Mirghasemi & Mohammad Arshad Rahman, 2021. "Heterogeneity in food expenditure among US families: evidence from longitudinal quantile regression," Indian Economic Review, Springer, vol. 56(1), pages 25-48, June.

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