Bayesian Model Averaging in Consumer Demand Systems with Inequality Constraints
AbstractShare 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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Bibliographic InfoPaper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 806.
Length: 34 pages
Date of creation: 2001
Date of revision:
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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
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Web page: http://www.economics.unimelb.edu.au
More information through EDIRC
conditional prior; Marginal likelihood; Metropolis-Hastings algorithm;
Other versions of this item:
- 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.
- 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
- E21 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- GORDON, Stephen, 1995. "Using Mixtures of Flexible Functional Forms to Estimate Factor Demand Elasticities," Cahiers de recherche 9502, Université Laval - Département d'économique.
- Danilov, D.L. & Magnus, J.R., 2001. "On the Harm that Pretesting Does," Discussion Paper 2001-37, Tilburg University, Center for Economic Research.
- 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.
- David L. Ryan & Terence J. Wales, . "A Simple Method For Imposing Local Curvature In Some Flexible Consumer Demand Systems," Old UBC Departmental Papers 9625, UBC Department of Economics.
- 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.
- Moschini, GianCarlo, 1999. "Imposing Local Curvature Conditions in Flexible Demand System," Staff General Research Papers 1745, Iowa State University, Department of Economics.
- 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.
- Kleibergen, F.R., 1996.
"Equality Restricted Random Variables: Densities and Sampling Algorithms,"
Econometric Institute Report
EI 9662-/A, Erasmus University Rotterdam, Econometric Institute.
- Frank Kleibergen, 1997. "Equality Restricted Random Variables: Densities and Sampling Algorithms," Tinbergen Institute Discussion Papers 97-005/4, Tinbergen Institute.
- Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
- 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.
- Hendrik Wolff & Thomas Heckelei & Ron Mittelhammer, 2010. "Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach," Computational Economics, Society for Computational Economics, vol. 36(4), pages 309-339, December.
- 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.
- 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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