Combining VAR Forecast Densities Using Fast Fourier Transform
AbstractIn this paper, I propose the use of fast Fourier transform (FFT) as a convenient tool for combining forecast densities of vector autoregressive models in a hybrid Bayesian manner. While a vast amount of papers comprises combinations based on normal approximations, Monte Carlo methods were fully utilized here, which made the analysis computationally demanding. For the sake of minimization of computational time, the FFT algorithm was used to combine the densities of poorly simulated partial models. As a result, a minor loss of quality in the final combined model was allowed, in contrast with the reduction in the necessary simulation time. However, it turns out in the end that the FFT-based approach exceeds ´brute-force´ simulation in all aspects. The suggested method is demonstrated on an ex ante prediction of the Czech GDP and on a pair of artificial examples.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by University of Economics, Prague in its journal Acta Oeconomica Pragensia.
Volume (Year): 2010 (2010)
Issue (Month): 5 ()
Postal: Redakce Acta Oeconomica Pragensia, Vysoká škola ekonomická v Praze, nám. W. Churchilla 4, 130 67 Praha 3
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Marianne Baxter & Robert G. King, 1999.
"Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series,"
The Review of Economics and Statistics, MIT Press,
MIT Press, vol. 81(4), pages 575-593, November.
- Marianne Baxter & Robert G. King, 1995. "Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series," NBER Working Papers 5022, National Bureau of Economic Research, Inc.
- Tom Doan, . "BKFILTER: RATS procedure to implement band pass filter using Baxter-King method," Statistical Software Components, Boston College Department of Economics RTS00026, Boston College Department of Economics.
- Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004.
"Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach,"
American Economic Review, American Economic Association,
American Economic Association, vol. 94(4), pages 813-835, September.
- Gernot Doppelhofer & Ronald I. Miller & Xavier Sala-i-Martin, 2000. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (Bace) Approach," OECD Economics Department Working Papers, OECD Publishing 266, OECD Publishing.
- Gernot Doppelhofer & Ronald I. Miller & Xavier Sala-i-Martin, 2000. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," NBER Working Papers 7750, National Bureau of Economic Research, Inc.
- Christian Kascha & Francesco Ravazzolo, 2010.
"Combining inflation density forecasts,"
Journal of Forecasting, John Wiley & Sons, Ltd.,
John Wiley & Sons, Ltd., vol. 29(1-2), pages 231-250.
- Wolden Bache, Ida & Sofie Jore, Anne & Mitchell, James & Vahey, Shaun P., 2011.
"Combining VAR and DSGE forecast densities,"
Journal of Economic Dynamics and Control, Elsevier,
Elsevier, vol. 35(10), pages 1659-1670, October.
- 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., John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
- Hugo Gerard & Kristoffer Nimark, 2008.
"Combining Multivariate Density Forecasts Using Predictive Criteria,"
RBA Research Discussion Papers, Reserve Bank of Australia
rdp2008-02, Reserve Bank of Australia.
- Hugo Gerard & Kristoffer Nimark, 2008. "Combining multivariate density forecasts using predictive criteria," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra 1117, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2008.
- Litterman, Robert B, 1986.
"Forecasting with Bayesian Vector Autoregressions-Five Years of Experience,"
Journal of Business & Economic Statistics, American Statistical Association,
American Statistical Association, vol. 4(1), pages 25-38, January.
- Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers, Federal Reserve Bank of Minneapolis 274, Federal Reserve Bank of Minneapolis.
- Andersson, Michael K & Karlsson, Sune, 2007.
"Bayesian forecast combination for VAR models,"
Working Paper Series, Sveriges Riksbank (Central Bank of Sweden)
216, Sveriges Riksbank (Central Bank of Sweden).
- Andersson, Michael K & Karlsson, Sune, 2007. "Bayesian Forecast Combination for VAR Models," Working Papers, Ãrebro University, School of Business 2007:13, Örebro University, School of Business.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Vaclav Subrta).
If references are entirely missing, you can add them using this form.