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The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study

  • Henzel, Steffen R.
  • Mayr, Johannes

This paper analyzes the mechanics of VAR forecast pooling and quantifies the forecast performance under varying conditions. To fill the gap between empirical and purely theoretical research we run a Monte Carlo study and simulate the data from different New Keynesian DSGE models. We find that equally pooling VAR forecasts outperforms single predictions in general and that the gains are substantial for sample sizes relevant in practice. In contrast, the estimation of theoretically optimal weights or model selection is advisable only for very large data sets hardly available in practice. Notably, equally pooling forecasts from small-scale VARs can even dominate forecasts from large VARs including all relevant variables. Given our results, we advocate the use of equally pooled predictions from parsimonious VARs as an easy to implement and competitive forecast approach.

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Article provided by Elsevier in its journal The North American Journal of Economics and Finance.

Volume (Year): 24 (2013)
Issue (Month): C ()
Pages: 1-24

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Handle: RePEc:eee:ecofin:v:24:y:2013:i:c:p:1-24
DOI: 10.1016/j.najef.2012.03.009
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  1. Richard Clarida & Jordi Galí & Mark Gertler, 1997. "Monetary policy rules and macroeconomic stability: Evidence and some theory," Economics Working Papers 350, Department of Economics and Business, Universitat Pompeu Fabra, revised May 1999.
  2. Bloor, Chris & Matheson, Troy, 2011. "Real-time conditional forecasts with Bayesian VARs: An application to New Zealand," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 26-42, January.
  3. Frank Smets & Raf Wouters, 2007. "Shocks and Frictions in US Business Cycles : a Bayesian DSGE Approach," Working Paper Research 109, National Bank of Belgium.
  4. Carlo Favero & Massimiliano Marcellino, 2005. "Modelling and Forecasting Fiscal Variables for the Euro Area," Working Papers 298, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  5. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2007. "Documentation of the Research and Statistics Division’s estimated DSGE model of the U.S. economy: 2006 version," Finance and Economics Discussion Series 2007-53, Board of Governors of the Federal Reserve System (U.S.).
  6. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2003. "The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting," LEM Papers Series 2003/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  7. Domenico Giannone & Martha Banbura & Lucrezia Reichlin, 2008. "Bayesian VARs with large panels," ULB Institutional Repository 2013/13388, ULB -- Universite Libre de Bruxelles.
  8. Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez & Thomas J. Sargent, 2005. "A, B, C’s (And D’s) For Understanding VARS," PIER Working Paper Archive 05-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  9. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
  10. Fabio Rumler & Maria Teresa Valderrama, 2008. "Comparing the New Keynesian Phillips Curve with Time Series Models to Forecast Inflation," Working Papers 148, Oesterreichische Nationalbank (Austrian Central Bank).
  11. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  12. Christoffel, Kai & Coenen, Günter & Warne, Anders, 2008. "The New Area-Wide Model of the euro area: a micro-founded open-economy model for forecasting and policy analysis," Working Paper Series 0944, European Central Bank.
  13. 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.
  14. Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City.
  15. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  16. Fagan, Gabriel & Henry, Jerome & Mestre, Ricardo, 2005. "An area-wide model for the euro area," Economic Modelling, Elsevier, vol. 22(1), pages 39-59, January.
  17. Erceg, Christopher J. & Henderson, Dale W. & Levin, Andrew T., 2000. "Optimal monetary policy with staggered wage and price contracts," Journal of Monetary Economics, Elsevier, vol. 46(2), pages 281-313, October.
  18. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
  19. Timmermann, Allan G, 2005. "Forecast Combinations," CEPR Discussion Papers 5361, C.E.P.R. Discussion Papers.
  20. Mestre, Ricardo & McAdam, Peter, 2008. "Is forecasting with large models informative? Assessing the role of judgement in macroeconomic forecasts," Working Paper Series 0950, European Central Bank.
  21. Stephen Murchison & Andrew Rennison, 2006. "ToTEM: The Bank of Canada's New Quarterly Projection Model," Technical Reports 97, Bank of Canada.
  22. Roy Batchelor & Pami Dua, 1995. "Forecaster Diversity and the Benefits of Combining Forecasts," Management Science, INFORMS, vol. 41(1), pages 68-75, January.
  23. Volker Wieland & Maik Wolters, 2011. "The diversity of forecasts from macroeconomic models of the US economy," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 47(2), pages 247-292, June.
  24. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Proceedings, Federal Reserve Bank of San Francisco, issue Jun.
  25. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting Using a Large Number of Predictors: Is Bayesian Regression a Valid Alternative to Principal Components?," CEPR Discussion Papers 5829, C.E.P.R. Discussion Papers.
  26. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
  27. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, 05.
  28. Rabanal, Pau & Rubio-Ramirez, Juan F., 2005. "Comparing New Keynesian models of the business cycle: A Bayesian approach," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1151-1166, September.
  29. David Hendry & Michael Clements, 2001. "Pooling of Forecasts," Economics Series Working Papers 2002-W09, University of Oxford, Department of Economics.
  30. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
  31. Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," MPRA Paper 36147, University Library of Munich, Germany.
  32. Francis X. Diebold, 1989. "Forecast combination and encompassing: reconciling two divergent literatures," Finance and Economics Discussion Series 80, Board of Governors of the Federal Reserve System (U.S.).
  33. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 123-143, April.
  34. Smets, Frank & Wouters, Raf, 2004. "Comparing shocks and frictions in US and euro area business cycles: a Bayesian DSGE approach," Working Paper Series 0391, European Central Bank.
  35. Massimiliano Marcellino, 2004. "Forecast Pooling for European Macroeconomic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(1), pages 91-112, 02.
  36. Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
  37. Gelain, Paolo, 2010. "The external finance premium in the Euro area: A dynamic stochastic general equilibrium analysis," The North American Journal of Economics and Finance, Elsevier, vol. 21(1), pages 49-71, March.
  38. Federico Ravenna, 2005. "Vector Autoregressions and Reduced Form Representations of DSGE Models," 2005 Meeting Papers 841, Society for Economic Dynamics.
  39. Jeffrey C. Fuhrer, 2000. "Habit Formation in Consumption and Its Implications for Monetary-Policy Models," American Economic Review, American Economic Association, vol. 90(3), pages 367-390, June.
  40. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
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