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Prior parameter uncertainty: Some implications for forecasting and policy analysis with VAR models

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  • John C. Robertson
  • Ellis W. Tallman

Abstract

Models used for policy analysis should generate reliable unconditional forecasts as well as policy simulations (conditional forecasts) that are based on a structural model of the economy. Vector autoregression (VAR) models have been criticized for having inaccurate forecasts as well as being difficult to interpret in the context of an underlying economic model. In this paper, we examine how the treatment of prior uncertainty about parameter values can affect forecasting accuracy and the interpretation of identified structural VAR models. ; Typically, VAR models are specified with long lag orders and a diffuse prior about the unrestricted coefficients. We find evidence that alternatives that emphasize nonstationary aspects of the data as well as parsimony in parameterization have better out-of-sample forecast performance and smoother and more persistent responses to a given exogenous monetary policy change than do unrestricted VARs.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Atlanta in its series Working Paper with number 99-13.

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Date of creation: 1999
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Handle: RePEc:fip:fedawp:99-13

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Keywords: Forecasting ; Vector autoregression ; Econometric models;

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References

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  1. Christopher A. Sims & Tao Zha, 1996. "Bayesian methods for dynamic multivariate models," Working Paper 96-13, Federal Reserve Bank of Atlanta.
  2. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
  3. 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.
  4. Christopher A. Sims, 1992. "A Nine Variable Probabilistic Macroeconomic Forecasting Model," Cowles Foundation Discussion Papers 1034, Cowles Foundation for Research in Economics, Yale University.
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  7. Christopher A. Sims & Tao Zha, 1994. "Error Bands for Impulse Responses," Cowles Foundation Discussion Papers 1085, Cowles Foundation for Research in Economics, Yale University.
  8. David B. Gordon & Eric M. Leeper, 1992. "The dynamic impacts of monetary policy: an exercise in tentative identification," Working Paper 92-13, Federal Reserve Bank of Atlanta.
  9. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148 Elsevier.
  10. 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.
  11. Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
  12. 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.
  13. Daniel F. Waggoner & Tao Zha, 1998. "Conditional forecasts in dynamic multivariate models," Working Paper 98-22, Federal Reserve Bank of Atlanta.
  14. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
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  16. Christopher A. Sims, 1998. "Role of interest rate policy in the generation and propagation of business cycles: what has changed since the '30s?," Conference Series ; [Proceedings], Federal Reserve Bank of Boston, vol. 42(Jun), pages 121-175.
  17. James E. Kennedy, 1989. "The effect of Bayesian priors on the moving-average representation of vector autoregressions," Finance and Economics Discussion Series 79, Board of Governors of the Federal Reserve System (U.S.).
  18. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December.
  19. repec:wop:humbsf:1999-4 is not listed on IDEAS
  20. Highfield, Richard A. & O'Hara, Maureen & Wood, John H., 1991. "Public ends, private means : Central banking and the profit motive 1823-1832," Journal of Monetary Economics, Elsevier, vol. 28(2), pages 287-322, October.
  21. Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-16.
  22. Dreze, Jacques H. & Richard, Jean-Francois, 1983. "Bayesian analysis of simultaneous equation systems," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 9, pages 517-598 Elsevier.
  23. Robert B. Litterman, 1979. "Techniques of forecasting using vector autoregressions," Working Papers 115, Federal Reserve Bank of Minneapolis.
  24. John C. Robertson & Ellis W. Tallman, 1999. "Vector autoregressions: forecasting and reality," Economic Review, Federal Reserve Bank of Atlanta, issue Q1, pages 4-18.
  25. Canova, Fabio, 1991. "The Sources of Financial Crisis: Pre- and Post-Fed Evidence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 689-713, August.
  26. Jon Faust, 1998. "The robustness of identified VAR conclusions about money," International Finance Discussion Papers 610, Board of Governors of the Federal Reserve System (U.S.).
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Cited by:
  1. Kaabia, Olfa & Abid, Ilyes & Guesmi, Khaled, 2013. "Does Bayesian shrinkage help to better reflect what happened during the subprime crisis?," Economic Modelling, Elsevier, vol. 31(C), pages 423-432.
  2. Summers, Peter M., 2001. "Forecasting Australia's economic performance during the Asian crisis," International Journal of Forecasting, Elsevier, vol. 17(3), pages 499-515.
  3. Andrea Brischetto & Graham Voss, 1999. "A Structural Vector Autoregression Model of Monetary Policy in Australia," RBA Research Discussion Papers rdp1999-11, Reserve Bank of Australia.

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