Empirical Bayesian density forecasting in Iowa and shrinkage for the Monte Carlo era
AbstractThe track record of a sixteen-year history of density forecasts of state tax revenue in Iowa is studied, and potential improvements sought through a search for better performing "priors" similar to that conducted two decades ago for point forecasts by Doan, Litterman, and Sims (Econometric Reviews, 1984). Comparisons of the point- and density-forecasts produced under the flat prior are made to those produced by the traditional (mixed estimation) "Bayesian VAR" methods of Doan, Litterman, and Sims, as well as to fully Bayesian, "Minnesota Prior" forecasts. The actual record, and to a somewhat lesser extent, the record of the alternative procedures studied in pseudo-real-time forecasting experiments, share a characteristic: subsequently realized revenues are in the lower tails of the predicted distributions "too often". An alternative empirically-based prior is found by working directly on the probability distribution for the VAR parameters, seeking a betterperforming entropically tilted prior that minimizes in-sample mean-squared-error subject to a Kullback-Leibler divergence constraint that the new prior not differ "too much" from the original. We also study the closely related topic of robust prediction appropriate for situations of ambiguity. Robust "priors" are competitive in out-of-sample forecasting; despite the freedom afforded the entropically tilted prior, it does not perform better than the simple alternatives. --
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 Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 1: Economic Studies with number 2006,28.
Date of creation: 2006
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-09-23 (All new papers)
- NEP-ECM-2006-09-23 (Econometrics)
- NEP-ETS-2006-09-23 (Econometric Time Series)
- NEP-FOR-2006-09-23 (Forecasting)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Geweke, John & Amisano, Gianni, 2008.
"Comparing and evaluating Bayesian predictive distributions of assets returns,"
Working Paper Series
0969, European Central Bank.
- Geweke, John & Amisano, Gianni, 2010. "Comparing and evaluating Bayesian predictive distributions of asset returns," International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
- Andrea Carriero & Todd Clark & Massimiliano Marcellino, 2011.
"Bayesian VARs: specification choices and forecast accuracy,"
1112, Federal Reserve Bank of Cleveland.
- Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2011. "Bayesian VARs: Specification Choices and Forecast Accuracy," CEPR Discussion Papers 8273, C.E.P.R. Discussion Papers.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics).
If references are entirely missing, you can add them using this form.