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Forecasting Performance of an Open Economy Dynamic Stochastic General Equilibrium Model

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  • Adolfson, Malin

    () (Research Department, Central Bank of Sweden)

  • Lindé, Jesper

    () (Research Department, Central Bank of Sweden)

  • Villani, Mattias

    () (Research Department, Central Bank of Sweden)

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.

Suggested Citation

  • Adolfson, Malin & Lindé, Jesper & Villani, Mattias, 2005. "Forecasting Performance of an Open Economy Dynamic Stochastic General Equilibrium Model," Working Paper Series 190, Sveriges Riksbank (Central Bank of Sweden), revised 01 Jun 2006.
  • Handle: RePEc:hhs:rbnkwp:0190
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Villani, Mattias, 2008. "Evaluating an estimated new Keynesian small open economy model," Journal of Economic Dynamics and Control, Elsevier, pages 2690-2721.
    2. Schorfheide, Frank & Sill, Keith & Kryshko, Maxym, 2010. "DSGE model-based forecasting of non-modelled variables," International Journal of Forecasting, Elsevier, vol. 26(2), pages 348-373, April.
    3. Wagner Piazza Gaglianone & Luiz Renato Lima, 2014. "Constructing Optimal Density Forecasts From Point Forecast Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 736-757, August.
    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. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2010. "A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 720-754.
    6. Lavan Mahadeva & Juan Carlos parra, 2008. "Testing a DSGE model and its partner database," BORRADORES DE ECONOMIA 004507, BANCO DE LA REPÚBLICA.
    7. 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.
    8. Garratt, Anthony & Mise, Emi, 2014. "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, vol. 37(C), pages 32-40.
    9. repec:eee:intfor:v:33:y:2017:i:3:p:707-728 is not listed on IDEAS
    10. 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.
    11. 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.).
    12. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.

    More about this item

    Keywords

    Bayesian inference; Forecasting; Open economy DSGE model; Vector autoregressive models;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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