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Bayesian Model Averaging in Consumer Demand Systems with Inequality Constraints

Author

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  • 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.

Suggested Citation

  • Chua, C.L. & Griffiths, W.E. & O'Donnell, C.J., 2001. "Bayesian Model Averaging in Consumer Demand Systems with Inequality Constraints," Department of Economics - Working Papers Series 806, The University of Melbourne.
  • Handle: RePEc:mlb:wpaper:806
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    References listed on IDEAS

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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 717-736, August.
    2. 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 331-338, July.
    3. Moschini, Giancarlo, 1999. "Imposing Local Curvature Conditions in Flexible Demand Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 487-490, October.
    4. Danilov, D.L. & Magnus, J.R., 2001. "On the Harm that Pretesting Does," Discussion Paper 2001-37, Tilburg University, Center for Economic Research.
    5. James A. Chalfant & Richard S. Gray & Kenneth J. White, 1991. "Evaluating Prior Beliefs in a Demand System: The Case of Meat Demand in Canada," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(2), pages 476-490.
    6. John Geweke, 1999. "Using Simulation Methods for Bayesian Econometric Models," Computing in Economics and Finance 1999 832, Society for Computational Economics.
    7. 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 321-341, December.
    8. Alston, Julian M. & Chalfant, James A. & Piggott, Nicholas E., 1998. "A Globally Flexible Model of the Effects of Generic Advertising of Beef and Pork on U.S. Meat Demand," 1998 Annual meeting, August 2-5, Salt Lake City, UT 269838, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
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    Cited by:

    1. Hendrik Wolff & Thomas Heckelei & Ron Mittelhammer, 2010. "Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach," Computational Economics, Springer;Society for Computational Economics, vol. 36(4), pages 309-339, December.
    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).
    4. Claudia Schmidt & Steven C. Deller & Stephan J. Goetz, 2024. "Women farmers and community well‐being under modeling uncertainty," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 46(1), pages 275-299, March.
    5. Charles J. Romeo, 2016. "Incorporating Prior Information into A GMM Objective For Mixed Logit Demand Systems," Journal of Industrial Economics, Wiley Blackwell, vol. 64(2), pages 336-363, June.
    6. Sanvi Avouyi-Dovi & Christian Pfister & Franck Sédillot, 2019. "French Households’ Portfolio: The Financial Almost Ideal Demand System Appraisal," Working papers 728, Banque de France.

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    More about this item

    Keywords

    conditional prior; Marginal likelihood; Metropolis-Hastings algorithm;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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