Forecasting using relative entropy
AbstractThe paper describes a relative entropy procedure for imposing moment restrictions on simulated forecast distributions from a variety of models. Starting from an empirical forecast distribution for some variables of interest, the technique generates a new empirical distribution that satisfies a set of moment restrictions. The new distribution is chosen to be as close as possible to the original in the sense of minimizing the associated Kullback-Leibler Information Criterion, or relative entropy. The authors illustrate the technique by using several examples that show how restrictions from other forecasts and from economic theory may be introduced into a model's forecasts.
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Bibliographic InfoPaper provided by Federal Reserve Bank of Atlanta in its series Working Paper with number 2002-22.
Date of creation: 2002
Date of revision:
Other versions of this item:
- NEP-ALL-2003-01-27 (All new papers)
- NEP-ETS-2003-01-27 (Econometric Time Series)
- NEP-RMG-2003-01-27 (Risk Management)
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- Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986.
"Forecasting and conditional projection using realistic prior distribution,"
93, Federal Reserve Bank of Minneapolis.
- Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
- Robertson, John C & Tallman, Ellis W, 2001.
"Improving Federal-Funds Rate Forecasts in VAR Models Used for Policy Analysis,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 19(3), pages 324-30, July.
- John C. Robertson & Ellis W. Tallman, 1999. "Improving forecasts of the federal funds rate in a policy model," Working Paper 99-3, Federal Reserve Bank of Atlanta.
- Neely, Christopher J & Roy, Amlan & Whiteman, Charles H, 2001. "Risk Aversion versus Intertemporal Substitution: A Case Study of Identification Failure in the Intertemporal Consumption Capital Asset Pricing Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 395-403, October.
- Daniel F. Waggoner & Tao Zha, 1998.
"Conditional forecasts in dynamic multivariate models,"
98-22, Federal Reserve Bank of Atlanta.
- Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
- Yuichi Kitamura & Michael Stutzer, 1997. "An Information-Theoretic Alternative to Generalized Method of Moments Estimation," Econometrica, Econometric Society, vol. 65(4), pages 861-874, July.
- Stutzer, Michael, 1996. " A Simple Nonparametric Approach to Derivative Security Valuation," Journal of Finance, American Finance Association, vol. 51(5), pages 1633-52, December.
- Rudebusch, Glenn D, 1998.
"Do Measures of Monetary Policy in a VAR Make Sense?,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 907-31, November.
- Rudebusch, G.D., 1996. "Do Measures of Monetary Policy in a VAR Make Sense?," Papers 269, Banca Italia - Servizio di Studi.
- Glenn D. Rudebusch, 1996. "Do measures of monetary policy in a VAR make sense?," Working Papers in Applied Economic Theory 96-05, Federal Reserve Bank of San Francisco.
- Charles L. Evans & Kenneth N. Kuttner, 1998.
"Can VAR's describe monetary policy?,"
Working Paper Series
WP-98-19, Federal Reserve Bank of Chicago.
- repec:wop:humbsf:1999-4 is not listed on IDEAS
- Sims, Christopher A & Zha, Tao, 1998.
"Bayesian Methods for Dynamic Multivariate Models,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-68, November.
- Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-39, November.
- Hansen, Lars Peter & Singleton, Kenneth J, 1983. "Stochastic Consumption, Risk Aversion, and the Temporal Behavior of Asset Returns," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 249-65, April.
- John C. Robertson & Ellis W. Tallman, 1999. "Vector autoregressions: forecasting and reality," Economic Review, Federal Reserve Bank of Atlanta, issue Q1, pages 4-18.
- Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
- Walker, Todd B & Haley, M. Ryan, 2009. "Alternative Tilts for Nonparametric Option Pricing," MPRA Paper 17140, University Library of Munich, Germany.
- Francesca Monti, 2008. "Forecast with judgment and models," Working Paper Research 153, National Bank of Belgium.
- Chalabi, Yohan & Wuertz, Diethelm, 2012. "Portfolio optimization based on divergence measures," MPRA Paper 43332, University Library of Munich, Germany.
- Smimou, K. & Bector, C.R. & Jacoby, G., 2007. "A subjective assessment of approximate probabilities with a portfolio application," Research in International Business and Finance, Elsevier, vol. 21(2), pages 134-160, June.
- Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
- Haley, M. Ryan & McGee, M. Kevin, 2011. ""KLICing" there and back again: Portfolio selection using the empirical likelihood divergence and Hellinger distance," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 341-352, March.
- Marco Del Negro & Frank Schorfheide, 2012. "DSGE model-based forecasting," Staff Reports 554, Federal Reserve Bank of New York.
- Harrison, Richard & Taylor, Tim, 2012. "Non-rational expectations and the transmission mechanism," Bank of England working papers 448, Bank of England.
- Cogley, Timothy W. & Morozov, Sergei & Sargent, Thomas J., 2003.
"Bayesian fan charts for UK inflation: Forecasting and sources of uncertainty in an evolving monetary system,"
CFS Working Paper Series
2003/44, Center for Financial Studies (CFS).
- Cogley, Timothy & Morozov, Sergei & Sargent, Thomas J., 2005. "Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1893-1925, November.
- Michal Franta & Jozef Barunik & Roman Horvath & Katerina Smidkova, 2011. "Are Bayesian Fan Charts Useful for Central Banks? Uncertainty, Forecasting, and Financial Stability Stress Tests," Working Papers 2011/10, Czech National Bank, Research Department.
- Shaun P Vahey & Elizabeth C Wakerly, 2013. "Moving towards probability forecasting," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 3-8 Bank for International Settlements.
- Salois, Matthew & Moss, Charles, 2010. "An Information Approach to the Dynamics in Farm Income: Implications for Farmland Markets," MPRA Paper 26850, University Library of Munich, Germany.
- Kenneth Beauchemin & Saeed Zaman, 2011. "A medium scale forecasting model for monetary policy," Working Paper 1128, Federal Reserve Bank of Cleveland.
- Eric Leeper, 2003. "An "Inflation Reports" Report," NBER Working Papers 10089, National Bureau of Economic Research, Inc.
- Manzan, Sebastiano & Zerom, Dawit, 2009. "Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?," MPRA Paper 14387, University Library of Munich, Germany.
- Carlo Altavilla & Raffaella Giacomini & Riccardo Costantini, 2013. "Bond returns and market expectations," CeMMAP working papers CWP20/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Andrew P Blake & Haroon Mumtaz, 2012. "Applied Bayesian econometrics for central bankers," Technical Books, Centre for Central Banking Studies, Bank of England, edition 1, number 4.
- Carlo Altavilla & Raffaella Giacomini & Giuseppe Ragusa, 2013. "Anchoring the yield curve using survey expectations," CeMMAP working papers CWP52/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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