Using simulation methods for Bayesian econometric models: inference, development, and communication
This paper surveys the fundamental principles of subjective Bayesian inference in econometrics and the implementation of those principles using posterior simulation methods. The emphasis is on the combination of models and the development of predictive distributions. Moving beyond conditioning on a fixed number of completely specified models, the paper introduces subjective Bayesian tools for formal comparison of these models with as yet incompletely specified models. The paper then shows how posterior simulators can facilitate communication between investigators (for example, econometricians) on the one hand and remote clients (for example, decision makers) on the other, enabling clients to vary the prior distributions and functions of interest employed by investigators. A theme of the paper is the practicality of subjective Bayesian methods. To this end, the paper describes publicly available software for Bayesian inference, model development, and communication and provides illustrations using two simple econometric models.
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- Anglin, Paul M & Gencay, Ramazan, 1996. "Semiparametric Estimation of a Hedonic Price Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 633-648, Nov.-Dec..
- Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
- Roberts, G. O. & Smith, A. F. M., 1994. "Simple conditions for the convergence of the Gibbs sampler and Metropolis-Hastings algorithms," Stochastic Processes and their Applications, Elsevier, vol. 49(2), pages 207-216, February.
- Geweke, John, 1996.
"Monte carlo simulation and numerical integration,"
Handbook of Computational Economics,
in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 15, pages 731-800
- Geweke, John, 1988. "Antithetic acceleration of Monte Carlo integration in Bayesian inference," Journal of Econometrics, Elsevier, vol. 38(1-2), pages 73-89.
- Kiefer, Nicholas M & Salmon, Mark, 1982.
"Testing Normality in Econometric Models,"
The Warwick Economics Research Paper Series (TWERPS)
216, University of Warwick, Department of Economics.
- Poirier, Dale J., 1997. "Comparing and choosing between two models with a third model in the background," Journal of Econometrics, Elsevier, vol. 78(2), pages 139-151, June.
- Engle, Robert F & Hendry, David F & Richard, Jean-Francois, 1983.
Econometric Society, vol. 51(2), pages 277-304, March.
- ENGLE, Robert F. & HENDRY, David F. & RICHARD, Jean-François, "undated". "Exogeneity," CORE Discussion Papers RP 516, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Engle, Robert F & Hendry, David F & Richard, Jean-Francois, 1979. "Exogeneity," The Warwick Economics Research Paper Series (TWERPS) 162, University of Warwick, Department of Economics.
- Steel, Mark F. J. & Richard, Jean-Francois, 1991.
"Bayesian multivariate exogeneity analysis : An application to a UK money demand equation,"
Journal of Econometrics,
Elsevier, vol. 49(1-2), pages 239-274.
- Steel, M.F.J. & Richard, J., 1989. "Bayesian multivariate exogeneity analysis : An application to a UK money demand equation," Discussion Paper 1989-29, Tilburg University, Center for Economic Research.
- Steel, M.F.J. & Richard, J.F., 1989. "Bayesian Multivariate Exogeneity Analysis: An Application To A Uk Money Demand Equation," Papers 8929, Tilburg - Center for Economic Research.
- Chib, Siddhartha & Greenberg, Edward, 1996.
"Markov Chain Monte Carlo Simulation Methods in Econometrics,"
Cambridge University Press, vol. 12(03), pages 409-431, August.
- Siddhartha Chib & Edward Greenberg, 1994. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometrics 9408001, EconWPA, revised 24 Oct 1994.
- Zellner, Arnold, 1985. "Bayesian Econometrics," Econometrica, Econometric Society, vol. 53(2), pages 253-269, March.
- 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.
- Geweke, John, 1989. "Exact predictive densities for linear models with arch disturbances," Journal of Econometrics, Elsevier, vol. 40(1), pages 63-86, January.
- Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1.
- repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
- John F. Geweke, 1991. "Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments," Staff Report 148, Federal Reserve Bank of Minneapolis.
- Poirier, Dale J, 1988. "Frequentist and Subjectivist Perspectives on the Problems of Model Building in Economics," Journal of Economic Perspectives, American Economic Association, vol. 2(1), pages 121-144, Winter.
- John F. Geweke & Michael P. Keane, 1997. "Mixture of normals probit models," Staff Report 237, Federal Reserve Bank of Minneapolis.
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