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

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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(02), December.
  • Handle: RePEc:ags:jlaare:31126
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    References listed on IDEAS

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    1. Maasoumi, Esfandiar, 2001. "On the relevance of first-order asymptotic theory to economics," Journal of Econometrics, Elsevier, vol. 100(1), pages 83-86, January.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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. 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), June.
    2. 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).
    3. 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.
    4. repec:oup:revage:v:31:y:2009:i:3:p:424-445. is not listed on IDEAS
    5. 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).

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    Keywords

    Research Methods/ Statistical Methods;

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