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Forecasting using relative entropy

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  • John C. Robertson
  • Ellis W. Tallman
  • Charles H. Whiteman

Abstract

The 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 Info

Paper provided by Federal Reserve Bank of Atlanta in its series Working Paper with number 2002-22.

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Date of creation: 2002
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Handle: RePEc:fip:fedawp:2002-22

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Keywords: Forecasting;

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References

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  1. 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.
  2. 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.
  3. repec:wop:humbsf:1999-4 is not listed on IDEAS
  4. 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.
  5. Stutzer, Michael, 1996. " A Simple Nonparametric Approach to Derivative Security Valuation," Journal of Finance, American Finance Association, vol. 51(5), pages 1633-52, December.
  6. 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.
  7. 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.
  8. Charles Evans & Kenneth Kuttner, 1998. "Can VARs describe monetary policy?," Research Paper 9812, Federal Reserve Bank of New York.
  9. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-39, November.
  10. 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.
  11. John C. Robertson & Ellis W. Tallman, 1999. "Vector autoregressions: forecasting and reality," Economic Review, Federal Reserve Bank of Atlanta, issue Q1, pages 4-18.
  12. 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.
  13. 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.
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Cited by:
  1. Chalabi, Yohan & Wuertz, Diethelm, 2012. "Portfolio optimization based on divergence measures," MPRA Paper 43332, University Library of Munich, Germany.
  2. 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.
  3. 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.
  4. Harrison, Richard & Taylor, Tim, 2012. "Non-rational expectations and the transmission mechanism," Bank of England working papers 448, Bank of England.
  5. Marco Del Negro & Frank Schorfheide, 2012. "DSGE model-based forecasting," Staff Reports 554, Federal Reserve Bank of New York.
  6. 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.
  7. 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.
  8. 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.
  9. Walker, Todd B & Haley, M. Ryan, 2009. "Alternative Tilts for Nonparametric Option Pricing," MPRA Paper 17140, University Library of Munich, Germany.
  10. 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.
  11. 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.
  12. 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.
  13. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
  14. Kenneth Beauchemin & Saeed Zaman, 2011. "A medium scale forecasting model for monetary policy," Working Paper 1128, Federal Reserve Bank of Cleveland.
  15. 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.
  16. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
  17. 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.
  18. Eric Leeper, 2003. "An "Inflation Reports" Report," NBER Working Papers 10089, National Bureau of Economic Research, Inc.

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