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Forecasting Performance of an Open Economy Dynamic Stochastic General Equilibrium Model

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  • Mattias Villani

    (Sveriges Riksbank)

  • Malin Adolfson

    (Sveriges Riksbank)

  • Jesper Linde

    (Sveriges Riksbank)

Abstract

This paper analyzes the forecasting performance of an open economy DSGE model, estimated with Bayesian methods, for the Euro area during 1994Q1-2002Q4. We compare the DSGE model and a few variants of this model to various reduced form forecasting models such as vector autoregressions (VAR) and vector error correction models (VECM), estimated both by maximum likelihood and two different Bayesian approaches, and traditional benchmark models, e.g. the random walk. The accuracy of point forecasts, interval forecasts and the predictive distribution as a whole are assessed in an out-of-sample rolling event evaluation using several univariate and multivariate measures. The results show that the open economy DSGE model compares well with more empirical models and thus that the tension between rigor and fit in older generations of DSGE models is no longer present. We also critically examine the role of Bayesian model probabilities and other frequently used low-dimensional summaries, e.g. the log determinant statistic, as measures of overall forecasting performance.

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Bibliographic Info

Paper provided by Money Macro and Finance Research Group in its series Money Macro and Finance (MMF) Research Group Conference 2005 with number 32.

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Date of creation: 03 Sep 2005
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Handle: RePEc:mmf:mmfc05:32

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  1. Christopher J. Erceg & Dale W. Henderson & Andrew T. Levin, 1999. "Optimal monetary policy with staggered wage and price contracts," International Finance Discussion Papers 640, Board of Governors of the Federal Reserve System (U.S.).
  2. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, April.
  3. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Paper Series WP-01-08, Federal Reserve Bank of Chicago.
  4. Anderson, Gary & Moore, George, 1985. "A linear algebraic procedure for solving linear perfect foresight models," Economics Letters, Elsevier, vol. 17(3), pages 247-252.
  5. Adolfson, Malin & Laseen, Stefan & Linde, Jesper & Villani, Mattias, 2007. "Bayesian estimation of an open economy DSGE model with incomplete pass-through," Journal of International Economics, Elsevier, vol. 72(2), pages 481-511, July.
  6. Smets, Frank & Wouters, Raf, 2004. "Forecasting with a Bayesian DSGE model: an application to the euro area," Working Paper Series 0389, European Central Bank.
  7. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," Working Papers 284, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    • Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 161-224 National Bureau of Economic Research, Inc.
  8. Marco Del Negro & Frank Schorfheide, 2002. "Priors from general equilibrium models for VARs," Working Paper 2002-14, Federal Reserve Bank of Atlanta.
  9. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Raf, 2005. "On the fit and forecasting performance of New-Keynesian models," Working Paper Series 0491, European Central Bank.
  10. Kadiyala, K. Rao & Karlsson, Sune, 1994. "Numerical Aspects of Bayesian VAR-modeling," Working Paper Series in Economics and Finance 12, Stockholm School of Economics.
  11. Pierpaolo Benigno, 2008. "Price stability with imperfect financial integration," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
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Cited by:
  1. Frank Schorfheide & Keith Sill & Maxym Kryshko, 2009. "DSGE Model-Based Forecasting of Non-modelled Variables," NBER Working Papers 14872, National Bureau of Economic Research, Inc.
  2. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Villani, Mattias, 2007. "Evaluating An Estimated New Keynesian Small Open Economy Model," CEPR Discussion Papers 6027, C.E.P.R. Discussion Papers.
  3. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2008. "A Comparison Of Forecast Performance Between Federal Reserve Staff Forecasts, Simple Reduced-Form Models, And A Dsge Model," CAMA Working Papers 2009-03, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  4. Rumler, Fabio & Valderrama, Maria Teresa, 2010. "Comparing the New Keynesian Phillips Curve with time series models to forecast inflation," The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 126-144, August.
  5. Lavan Mahadeva & Juan Carlos Parra Alvarez, . "Testing a DSGE model and its partner database," Borradores de Economia 479, Banco de la Republica de Colombia.
  6. Garratt, Anthony & Mise, Emi, 2014. "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, vol. 37(C), pages 32-40.
  7. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
  8. Siok Kun, Sek, 2009. "The impacts of economic structures on the performance of simple policy rules in a small open economy," MPRA Paper 25065, University Library of Munich, Germany.
  9. Rochelle M. Edge & Refet S. Gurkaynak, 2011. "How useful are estimated DSGE model forecasts?," Finance and Economics Discussion Series 2011-11, Board of Governors of the Federal Reserve System (U.S.).
  10. Kirdan Lees & Troy Matheson & Christie Smith, 2007. "Open Economy Dsge-Var Forecasting And Policy Analysis: Head To Head With The Rbnz Published Forecasts," CAMA Working Papers 2007-05, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

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