Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment
AbstractIn this paper, we put dynamic stochastic general equilibrium DSGE forecasts in competition with factor forecasts. We focus on these two models since they represent nicely the two opposing forecasting philosophies. The DSGE model on the one hand has a strong theoretical economic background; the factor model on the other hand is mainly data-driven. We show that incorporating a large information set using factor analysis can indeed improve the short-horizon predictive ability, as claimed by many researchers. The micro-founded DSGE model can provide reasonable forecasts for US inflation, especially with growing forecast horizons. To a certain extent, our results are consistent with the prevailing view that simple time series models should be used in short-horizon forecasting and structural models should be used in long-horizon forecasting. Our paper compares both state-of-the-art data-driven and theory-based modelling in a rigorous manner. Copyright © 2008 John Wiley & Sons, Ltd.
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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.
Volume (Year): 28 (2009)
Issue (Month): 2 ()
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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966
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- Wang, Mu-Chun, 2008. "Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment," Discussion Paper Series 1: Economic Studies 2008,04, Deutsche Bundesbank, Research Centre.
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
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- Wolters, Maik H., 2011. "Forecasting under Model Uncertainty," Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48723, Verein für Socialpolitik / German Economic Association.
- Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011.
"Forecasting the US real house price index: Structural and non-structural models with and without fundamentals,"
Elsevier, vol. 28(4), pages 2013-2021, July.
- Rangan Gupta & Alan Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 1001, University of Nevada, Las Vegas , Department of Economics.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working papers 2009-42, University of Connecticut, Department of Economics.
- Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 200927, University of Pretoria, Department of Economics.
- Rangan Gupta & Alain Kabundi, 2009.
"A Large Factor Model for Forecasting Macroeconomic Variables in South Africa,"
137, Economic Research Southern Africa.
- Gupta, Rangan & Kabundi, Alain, 2011. "A large factor model for forecasting macroeconomic variables in South Africa," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1076-1088, October.
- Bušs, Ginters, 2009. "Comparing forecasts of Latvia's GDP using simple seasonal ARIMA models and direct versus indirect approach," MPRA Paper 16684, University Library of Munich, Germany.
- Wieland, Volker & Wolters, Maik H., 2010.
"The diversity of forecasts from macroeconomic models of the U.S. economy,"
CFS Working Paper Series
2010/08, Center for Financial Studies (CFS).
- Volker Wieland & Maik Wolters, 2011. "The diversity of forecasts from macroeconomic models of the US economy," Economic Theory, Springer, vol. 47(2), pages 247-292, June.
- Wieland, Volker & Wolters, Maik H, 2010. "The Diversity of Forecasts from Macroeconomic Models of the U.S. Economy," CEPR Discussion Papers 7870, C.E.P.R. Discussion Papers.
- Wolters, Maik Hendrik, 2012.
"Evaluating point and density forecasts of DSGE models,"
36147, University Library of Munich, Germany.
- Wolters, Maik H., 2013. "Evaluating point and density forecasts of DSGE models," Economics Working Papers 2013-03, Christian-Albrechts-University of Kiel, Department of Economics.
- Christoffel, Kai & Warne, Anders & Coenen, Günter, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
- Stelios Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Empirical Economics, Springer, vol. 45(1), pages 635-664, August.
- Poghosyan, K., 2012. "Structural and reduced-form modeling and forecasting with application to Armenia," Open Access publications from Tilburg University urn:nbn:nl:ui:12-5590845, Tilburg University.
- Skrove Falch, Nina & Nymoen, Ragnar, 2011. "The accuracy of a forecast targeting central bank," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 5(15), pages 1-36.
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