Optimal Forecast Combination Under Regime Switching
AbstractThis Paper proposes a new forecast combination method that lets the combination weights be driven by regime switching in a latent state variable. An empirical application that combines forecasts from survey data and time series models finds that the proposed regime switching combination scheme performs well for a variety of macroeconomic variables. Monte Carlo simulations shed light on the type of data generating processes for which the proposed combination method can be expected to perform better than a range of alternative combination schemes. Finally, we show how time-variations in the combination weights arise when the target variable and the predictors share a common factor structure driven by a hidden Markov process.
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 InfoPaper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 4649.
Date of creation: Oct 2004
Date of revision:
Contact details of provider:
Postal: Centre for Economic Policy Research, 77 Bastwick Street, London EC1V 3PZ.
Phone: 44 - 20 - 7183 8801
Fax: 44 - 20 - 7183 8820
Other versions of this item:
- Graham Elliott & Allan Timmermann, 2005. "Optimal Forecast Combination Under Regime Switching ," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(4), pages 1081-1102, November.
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-02-13 (All new papers)
- NEP-ECM-2005-02-13 (Econometrics)
- NEP-ETS-2005-02-13 (Econometric Time Series)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Legerstee, R. & Franses, Ph.H.B.F., 2010.
"Does Disagreement Amongst Forecasters have Predictive Value?,"
Econometric Institute Research Papers
EI 2010-53, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Rianne Legerstee & Philip Hans Franses, 2010. "Does Disagreement amongst Forecasters have Predictive Value?," Tinbergen Institute Discussion Papers 10-088/4, Tinbergen Institute.
- repec:dgr:uvatin:2010088 is not listed on IDEAS
- Timmermann, Allan G, 2005.
CEPR Discussion Papers
5361, C.E.P.R. Discussion Papers.
- Valentina Corradi & Norman Swanson, 2004. "Bootstrap Procedures for Recursive Estimation Schemes With Applications to Forecast Model Selection," Departmental Working Papers 200418, Rutgers University, Department of Economics.
- Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
- Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2012.
"Is there an Optimal Forecast Combination? A Stochastic Dominance Approach to Forecast Combination Puzzle,"
Working Paper Series
17_12, The Rimini Centre for Economic Analysis.
- Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2012. "Is there an optimal forecast combination? A stochastic dominance approach applied to the forecast combination puzzle," Working Papers 1206, University of Guelph, Department of Economics and Finance.
- Chen Zhuo & Yang Yuhong, 2007. "Time Series Models for Forecasting: Testing or Combining?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(1), pages 56-90, March.
- Valentina Corradi & Norman R. Swanson, 2007.
"Nonparametric Bootstrap Procedures For Predictive Inference Based On Recursive Estimation Schemes,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(1), pages 67-109, 02.
- Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
- repec:amu:wpaper:2013-04 is not listed on IDEAS
- Giacomini, Raffaella & Rossi, Barbara, 2008.
"Forecast Comparisons in Unstable Environments,"
08-04, Duke University, Department of Economics.
- Valentina Corradi & Norman Swanson, 2013. "A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance," Departmental Working Papers 201309, Rutgers University, Department of Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If references are entirely missing, you can add them using this form.