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Aids Versus The Rotterdam Demand System: A Cox Test With Parametric Bootstrap

Author

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  • Dameus, Alix
  • Richter, Francisca G.-C.
  • Brorsen, B. Wade
  • Sukhdial, Kullapapruk Piewthongngam
Abstract
A Cox test with parametric bootstrap is developed to select between the linearized version of the First-Difference Almost Ideal Demand System (FDAIDS) and the Rotterdam model. A Cox test with parametric bootstrap has been shown to be more powerful than encompassing tests like those used in past research. The bootstrap approach is used with U.S. meat demand (beef, pork, chicken, fish) and compared to results obtained with an encompassing test. The Cox test with parametric bootstrap consistently indicates the Rotterdam model is preferred to the FDAIDS, while the encompassing test sometimes fails to reject FDAIDS.

Suggested Citation

  • Dameus, Alix & Richter, Francisca G.-C. & Brorsen, B. Wade & Sukhdial, Kullapapruk Piewthongngam, 2002. "Aids Versus The Rotterdam Demand System: A Cox Test With Parametric Bootstrap," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(2), pages 1-13, December.
    • Handle: RePEc:ags:jlaare:31126
    DOI: 10.22004/ag.econ.31126
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    References listed on IDEAS

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    1. N. Coulibaly & B. Wade Brorsen, 1999. "Monte carlo sampling approach to testing nonnested hypothesis: monte carlo results," Econometric Reviews, Taylor & Francis Journals, vol. 18(2), pages 195-209.
    2. Hashem Pesaran, M. & Pesaran, Bahram, 1993. "A simulation approach to the problem of computing Cox's statistic for testing nonnested models," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 377-392.
    3. Giancarlo Moschini & Karl D. Meilke, 1989. "Modeling the Pattern of Structural Change in U.S. Meat Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 253-261.
    4. Andrews, Donald W K, 2001. "Testing When a Parameter Is on the Boundary of the Maintained Hypothesis," Econometrica, Econometric Society, vol. 69(3), pages 683-734, May.
    5. M. H. Pesaran, 1974. "On the General Problem of Model Selection," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 41(2), pages 153-171.
    6. Maasoumi, Esfandiar, 2001. "On the relevance of first-order asymptotic theory to economics," Journal of Econometrics, Elsevier, vol. 100(1), pages 83-86, January.
    7. Terry L. Kastens & Gary W. Brester, 1996. "Model Selection and Forecasting Ability of Theory-Constrained Food Demand Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 301-312.
    8. Robert B. Davies, 2002. "Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case," Biometrika, Biometrika Trust, vol. 89(2), pages 484-489, June.
    9. Jeffrey T. LaFrance, 1998. "The Silence Bleating! of the Lambdas: Comment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 221-230.
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    Cited by:

    1. Laura Cornelsen & Mario Mazzocchi & Rosemary Green & Alan D. Dangour & Richard D. Smith, 2016. "Estimating the Relationship between Food Prices and Food Consumption—Methods Matter," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 38(3), pages 546-561.
    2. Taljaard, Pieter R. & van Schalkwyk, Herman D. & Alemu, Zerihun Gudeta, 2006. "Choosing between the AIDS and Rotterdam models: A meat demand analysis case study," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 45(2), pages 1-15, June.
    3. Stavroula Malla & K. K. Klein & Taryn Presseau, 2020. "Have health claims affected demand for fats and meats in Canada?," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 68(3), pages 271-287, September.
    4. Tonsor, Glynn T. & Marsh, Thomas L., 2005. "Comparing Heterogeneous Consumption in US and Japanese Meat and Fish Demand," 2005 Annual meeting, July 24-27, Providence, RI 19567, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Shida Rastegari Henneberry & Joao E. Mutondo, 2009. "Agricultural Trade among NAFTA Countries: A Case Study of U.S. Meat Exports," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(3), pages 424-445.
    6. Tonsor, Glynn T. & Kastens, Terry L., 2006. "How Much Do Starting Values Really Matter? An Empirical Comparison of Genetic Algorithm and Traditional Approaches," 2006 Annual meeting, July 23-26, Long Beach, CA 21252, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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