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Information Based Model Averaging And Internal Metanalysis In Seemingly Unrelated Regressions With An Application To A Demand System

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  • Bryant, Henry L.
  • Davis, George C.

Abstract

This paper presents an information based model averaging and internal meta-analysis procedure that is easily applied to a large model space. In the application, the procedure is used to investigate the efficacy of some recently contested commodity promotion programs. The investigated model space consists of 576 demand systems. The internal meta-analysis indicates that theoretical restrictions and evaluation points are more important than alternative functional forms and explanatory variables in determining the elasticity values. The model averaging weights strongly support the theoretically consistent classical demand systems without promotion. The weighted or meta-price and meta-expenditure elasticities are presented and discussed.

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Bibliographic Info

Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2003 Annual meeting, July 27-30, Montreal, Canada with number 21918.

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Date of creation: 2003
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Handle: RePEc:ags:aaea03:21918

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Keywords: Demand and Price Analysis;

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  1. Chow, Gregory C., 1981. "A comparison of the information and posterior probability criteria for model selection," Journal of Econometrics, Elsevier, vol. 16(1), pages 21-33, May.
  2. T. D. Stanley, 2001. "Wheat from Chaff: Meta-analysis as Quantitative Literature Review," Journal of Economic Perspectives, American Economic Association, vol. 15(3), pages 131-150, Summer.
  3. Granger, Clive W. J. & King, Maxwell L. & White, Halbert, 1995. "Comments on testing economic theories and the use of model selection criteria," Journal of Econometrics, Elsevier, vol. 67(1), pages 173-187, May.
  4. Kinnucan, Henry W. & Chang, Hui-Shung (Christie) & Venkateswaran, Meenakshi, 1993. "Generic Advertising Wearout," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 61(03), December.
  5. Keller, W.J. & Van Driel, J., 1985. "Differential consumer demand systems," European Economic Review, Elsevier, vol. 27(3), pages 375-390.
  6. Philip Crooke & Luke Froeb & Steven Tschantz & Gregory Werden, 1999. "Effects of Assumed Demand Form on Simulated Postmerger Equilibria," Review of Industrial Organization, Springer, vol. 15(3), pages 205-217, November.
  7. Nishii, R., 1988. "Maximum likelihood principle and model selection when the true model is unspecified," Journal of Multivariate Analysis, Elsevier, vol. 27(2), pages 392-403, November.
  8. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
  9. W. E. Griffiths, 1999. "Estimating consumer surplus comments on "using simulation methods for bayesian econometric models: inference development and communication"," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 75-87.
  10. John D. Jackson, 1997. "Effects of Health Information and Generic Advertising on U.S. Meat Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 13-23.
  11. Davis, George C., 1997. "The Formal Logic Of Testing Structural Change In Meat Demand: A Methodological Analysis," Faculty Paper Series 23975, Texas A&M University, Department of Agricultural Economics.
  12. Neves, Pedro Duarte, 1994. "A class of differential demand systems," Economics Letters, Elsevier, vol. 44(1-2), pages 83-86.
  13. 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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