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Forecasting the Swiss Economy Using VECX* Models: An Exercise in Forecast Combination Across Modelsand Observation Windows

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Author Info

  • Katrin Assenmacher-Wesche
  • M. Hashem Pesaran

Abstract

This paper uses vector error correction models of Switzerland for forecasting output, inflation and the short-term interest rate. It considers three different ways of dealing with forecast uncertainties. First, it investigates the effect on forecasting performance of averaging over forecasts from different models. Second, it considers averaging forecasts from different estimation windows. It is found that averaging over estimation windows is at least as effective as averaging over different models and both complement each other. Third, it examines whether using weighting schemes from the machine learning literature improves the average forecast. Compared to equal weights the effect of alternative weighting schemes on forecast accuracy is small in the present application.

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File URL: http://www.snb.ch/n/mmr/reference/working_paper_2008_03/source/working_paper_2008_03.n.pdf
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Bibliographic Info

Paper provided by Swiss National Bank in its series Working Papers with number 2008-03.

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Length: 44 pages
Date of creation: 2008
Date of revision:
Handle: RePEc:snb:snbwpa:2008-03

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Keywords: Bayesian model averaging; choice of observation window; long-run structural vector autoregression;

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  1. Assenmacher-Wesche, K. & Pesaran, M.H., 2008. "A VECX* Model of the Swiss Economy," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 0809, Faculty of Economics, University of Cambridge.
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Cited by:
  1. M. Hashem Pesaran & Til Schuermann & L. Vanessa Smith, 2008. "Forecasting economic and financial variables with global VARs," Staff Reports, Federal Reserve Bank of New York 317, Federal Reserve Bank of New York.
  2. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009. "Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP," Economics Working Papers, European University Institute ECO2009/13, European University Institute.
  3. M. Hashem Pesaran & Andreas Pick, 2008. "Forecasting Random Walks Under Drift Instability," CESifo Working Paper Series, CESifo Group Munich 2293, CESifo Group Munich.
  4. Prasad S Bhattacharya & Dimitrios D Thomakos, 2011. "Improving forecasting performance by window and model averaging," Economics Series 2011_1, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
  5. Assenmacher-Wesche, K. & Pesaran, M.H., 2008. "A VECX* Model of the Swiss Economy," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 0809, Faculty of Economics, University of Cambridge.

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