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Bayesian Model Averaging in Consumer Demand Systems with Inequality Constraints

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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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Suggested Citation

  • C. L Chua & W. E. Griffiths & C. J O'Donnell, 2001. "Bayesian Model Averaging in Consumer Demand Systems with Inequality Constraints," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 49(3), pages 269-291, November.
    • Handle: RePEc:bla:canjag:v:49:y:2001:i:3:p:269-291
    DOI: j.1744-7976.2001.tb00306.x
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    Cited by:

    1. 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.
    2. 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.
    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.

    More about this item

    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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