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Bayesian Analysis of a Japanese Meat Demand System: A Robust Likelihood Approach

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  • Heckelei, Thomas
  • Mittelhammer, Ronald C.
  • Wahl, Thomas I.

Abstract

This paper presents an application of Bayesian analysis to an AIDS model of Japanese meat demand extending previous approaches in three ways: (1) The methodology employed is robust with respect to the likelihood function but retains the generic, easily programmable character of algorithms offered by Monte Carlo Integration approaches based on the normal likelihood function. (2) In addition to inequality constraints, linear exact restrictions and stochastic prior information are subjected to a Bayesian posterior analysis of validity and incorporated into Bayesian point estimates of model parameters and elasticities. (3) In order to assess the influence of the prior density on posterior distributions of model parameters relative to the likelihood, a measure quantifying the "degree of prior influence" on the posterior is defined. Das Diskussionspapier stellt eine Bayes'sche Analyse eines AIDS Modells Japanischer Fleischnachfrage vor, die eine Erweiterung fruherer Ansatze in den folgenden drei Punkten darstellt:(1) Die verwendete Methode ist robust bezuglich der Likelihood Funktion, erhalt dabei aber die Flexibilitat und einfache Umsetzung von Algorithmen basierend auf Monte Carlo Integration und der Annahme der Normalverteilung. (2) Zusatzlich zu Ungleichheitsbedingungen werden exakte Restriktionen und stochastische a-priori Information einer Bayes'schen a-posteriori Analyse unterzogen und in die Bayes'sche Punktschatzung von Parametern und Elastizitaten einbezogen. (3) Ein Index zur Messung des Einflusses der a-priori Information auf die a-posteriori Verteilung der Modellparameter wird vorgestellt.

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Bibliographic Info

Paper provided by University of Bonn, Institute for Food and Resource Economics in its series Discussion Papers with number 18783.

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Date of creation: 1997
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Handle: RePEc:ags:ubfred:18783

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Web page: http://www.ilr1.uni-bonn.de/
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Related research

Keywords: Demand and Price Analysis;

References

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  1. Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January.
  2. Hayes, Dermot J. & Wahl, Thomas I. & Williams, Gary W., 1990. "Testing Restrictions on a Model of Japanese Meat Demand," Staff General Research Papers 10940, Iowa State University, Department of Economics.
  3. Koop, Gary, 1994. " Recent Progress in Applied Bayesian Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 8(1), pages 1-34, March.
  4. Wahl, Thomas I. & Hayes, Dermot J., 1990. "Demand System Estimation with Upward-Sloping Supply," Staff General Research Papers 292, Iowa State University, Department of Economics.
  5. van Dijk, H. K. & Kloek, T., 1980. "Further experience in Bayesian analysis using Monte Carlo integration," Journal of Econometrics, Elsevier, vol. 14(3), pages 307-328, December.
  6. Gallant, A. Ronald & Golub, Gene H., 1984. "Imposing curvature restrictions on flexible functional forms," Journal of Econometrics, Elsevier, vol. 26(3), pages 295-321, December.
  7. Woodland, A. D., 1979. "Stochastic specification and the estimation of share equations," Journal of Econometrics, Elsevier, vol. 10(3), pages 361-383, August.
  8. Capps, Oral, Jr. & Tsai, Reyfong & Kirby, Raymond & Williams, Gary W., 1994. "A Comparison Of Demands For Meat Products In The Pacific Rim Region," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 19(01), July.
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Citations

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Cited by:
  1. von Lampe, Martin, 1998. "Veranderung von Einkommenselastizitaten im Verlauf der wirtschaftlichen Entwicklung - Problematik und Umsetzung im WATSIM," Discussion Papers 18780, University of Bonn, Institute for Food and Resource Economics.
  2. von Lampe, Martin, 1998. "The World Agricultural Trade Simulation System WATSIM: An Overview," Discussion Papers 18788, University of Bonn, Institute for Food and Resource Economics.

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