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Bayesian Model Averaging in Consumer Demand Systems with Inequality Constraints

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Author Info

  • Chua, C.L.
  • Griffiths, W.E.
  • O'Donnell, C.J.

Abstract

Share equations for the translog and almost ideal demand systems are estimated using Markov Chain Monte Carlo. A common prior on the elasticities and budget shares evaluated at average prices and income is used for both models. It includes equality restrictions (homogeneity, adding up and symmetry) and inequality restrictions (monotonicity and concavity). Posterior densities on the elasticities and shares are obtained; the problem of choosing between the results from the two alternative functional forms is resolved by using Bayesian model averaging. The application is to USDA data for beef, pork and poultry. Estimation of elasticities and shares, evaluated at mean prices and expenditure, is insensitive to model choice. At points away from the means the estimates are sensitive, and model averaging has an impact.

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File URL: http://www.economics.unimelb.edu.au/downloads/wpapers-00-01/806.pdf
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Bibliographic Info

Paper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 806.

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Length: 34 pages
Date of creation: 2001
Date of revision:
Handle: RePEc:mlb:wpaper:806

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Postal: Department of Economics, The University of Melbourne, 5th Floor, Economics and Commerce Building, Victoria, 3010, Australia
Phone: +61 3 8344 5289
Fax: +61 3 8344 6899
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Web page: http://www.economics.unimelb.edu.au
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Keywords: conditional prior; Marginal likelihood; Metropolis-Hastings algorithm;

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References

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  1. Stephen Gordon, 1996. "Using Mixtures of Flexible Functional Forms to Estimate Factor Demand Elasticities," Canadian Journal of Economics, Canadian Economics Association, vol. 29(3), pages 717-36, August.
  2. Danilov, D.L. & Magnus, J.R., 2001. "On the Harm that Pretesting Does," Discussion Paper 2001-37, Tilburg University, Center for Economic Research.
  3. Ryan, David L & Wales, Terence J, 1998. "A Simple Method for Imposing Local Curvature in Some Flexible Consumer-Demand Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 331-38, July.
  4. Moschini, Giancarlo, 1999. "Imposing Local Curvature Conditions in Flexible Demand Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 487-90, October.
  5. Griffiths, William E & Chotikapanich, Duangkamon, 1997. "Bayesian Methodology for Imposing Inequality Constraints on a Linear Expenditure System with Demographic Factors," Australian Economic Papers, Wiley Blackwell, vol. 36(69), pages 321-41, December.
  6. Kleibergen, F.R., 1996. "Equality Restricted Random Variables: Densities and Sampling Algorithms," Econometric Institute Report EI 9662-/A, Erasmus University Rotterdam, Econometric Institute.
  7. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
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Cited by:
  1. Hendrik Wolff & Thomas Heckelei & Ron C. Mittelhammer, 2004. "Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach," Econometric Society 2004 North American Summer Meetings 450, Econometric Society.
  2. Griffiths, William E. & Newton, Lisa S. & O'Donnell, Christopher J., 2010. "Predictive densities for models with stochastic regressors and inequality constraints: Forecasting local-area wheat yield," International Journal of Forecasting, Elsevier, vol. 26(2), pages 397-412, April.
  3. Wolff, Hendrik & Heckelei, Thomas & Mittelhammer, Ronald C., 2004. "Imposing Monotonicity And Curvature On Flexible Functional Forms," 2004 Annual meeting, August 1-4, Denver, CO 20256, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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