Posterior Simulators in Econometrics
AbstractEconomics is the discipline of using data to revise beliefs about economic issues. In Bayesian econometrics, the revision is conducted in accordance with the laws of probability, conditional on what has been observed. The normative appeal of Bayesian econometrics is the same as that of expected utility maximization and Bayesian learning, the dominant paradigms in economic theory. The questions that econometrics ultimately addresses are similar to those faced by economic agents in models, as well. Given the observed data, what decisions should be made? After bringing data to bear on two alternative models, how is their relative plausibility changed? Any survey of the introductory and concluding sections of papers in the academic literature should provide more examples and illustrate the process of formally or informally updating beliefs. Until quite recently, applied Bayesian econometrics was undertaken largely by those primarily concerned with contributing to the theory, and the proportion of applied work that was formally Bayesian was rather small. There are several reasons for this. First, Bayesian econometrics demands both a likelihood function and a prior distribution, whereas non-Bayesian methods do not. Second, the subjective prior distribution has to be defended, and if the reader (or worse, the editor) does not agree, then the work may be ignored. Third, most posterior moments can't be obtained anyway because the requisite integrals can't be evaluated.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 1996 with number _019.
Date of creation:
Date of revision:
Contact details of provider:
Postal: Department of Econometrics, University of Geneva, 102 Bd Carl-Vogt, 1211 Geneva 4, Switzerland
Web page: http://www.unige.ch/ce/ce96/welcome.html
More information through EDIRC
Other versions of this item:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Chris Otrok, 1999.
"On Measuring the Welfare Cost of Business Cycles,"
Virginia Economics Online Papers
318, University of Virginia, Department of Economics.
- Christopher Otrok, 2000. "On Measuring the Welfare Cost of Business Cycles," Econometric Society World Congress 2000 Contributed Papers 1094, Econometric Society.
- Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
- Ruud, Paul A., 1995.
"Restricted Least Squares Subject to Monotonicity and Concavity Constraints,"
University of California Transportation Center, Working Papers
qt71z2n16p, University of California Transportation Center.
- Paul Ruud, . "Restricted Least Squares Subject to Monotonicity and Concavity Constraints," Working Papers _007, University of California at Berkeley, Econometrics Laboratory Software Archive.
- John F. Geweke & Michael P. Keane, 1997. "Mixture of normals probit models," Staff Report 237, Federal Reserve Bank of Minneapolis.
- John F. Geweke & Michael P. Keane, 1997.
"An empirical analysis of income dynamics among men in the PSID: 1968-1989,"
233, Federal Reserve Bank of Minneapolis.
- J. Geweke & M. Keane, . "An Empirical Analysis of Income Dynamics among Men in the PSID: 1968–1989," Institute for Research on Poverty Discussion Papers 1127-97, University of Wisconsin Institute for Research on Poverty.
- Susan Athey & Guido W. Imbens, 2007.
"Discrete Choice Models With Multiple Unobserved Choice Characteristics,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1159-1192, November.
- Susan Athey & Guido Imbens, 2006. "Discrete Choice Models with Multiple Unobserved Choice Characteristics," Levine's Bibliography 122247000000001040, UCLA Department of Economics.
- Christopher Otrok & Charles H. Whiteman, 1996. "Baynesian Leading Indicators: Measuring and Predicting Economic Conditions," Macroeconomics 9610002, EconWPA.
- Fernández, C. & Osiewalski, J. & Steel, M.F.J., 1996. "On the Use of Panel Data in Bayesian Stochastic Frontier Models," Discussion Paper 1996-17, Tilburg University, Center for Economic Research.
- Gautam Gowrisankaran & Robert J. Town, 2000. "Inferring Hospital Quality from Patient Discharge Records Using a Bayesian Selection Model," Econometric Society World Congress 2000 Contributed Papers 1773, Econometric Society.
- Lutz Kilian & Tao Zha, 2002. "Quantifying the uncertainty about the half-life of deviations from PPP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 107-125.
- Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.