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Optimal Forecast Combination Under Regime Switching

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  • Elliott, Graham
  • Timmermann, Allan G

Abstract

This 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.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 4649.

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Date of creation: Oct 2004
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Handle: RePEc:cpr:ceprdp:4649

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Related research

Keywords: forecast combination; Markov switching; survey data; time-varying combination weights;

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Cited by:
  1. 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.
  2. repec:dgr:uvatin:2010088 is not listed on IDEAS
  3. Timmermann, Allan G, 2005. "Forecast Combinations," CEPR Discussion Papers 5361, C.E.P.R. Discussion Papers.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. repec:amu:wpaper:2013-04 is not listed on IDEAS
  10. Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.
  11. 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.

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