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Combining forecasts based on multiple encompassing tests in a macroeconomic core system

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  • Mauro Costantini
  • Robert M. Kunst

Abstract

This paper investigates whether and to what extent multiple encompassing tests may help determine weights for forecast averaging in a standard vector autoregressive setting. To this end we consider a new test-based procedure, which assigns non‐zero weights to candidate models that add information not covered by other models. The potential benefits of this procedure are explored in extensive Monte Carlo simulations using realistic designs that are adapted to UK and to French macroeconomic data, to which trivariate vector autoregressions (VAR) are fitted. Thus simulations rely on potential data‐generating mechanisms for macroeconomic data rather than on simple but artificial designs. We run two types of forecast ‘competitions’. In the first one, one of the model classes is the trivariate VAR, such that it contains the generating mechanism. In the second specification, none of the competing models contains the true structure. The simulation results show that the performance of test‐based averaging is comparable to uniform weighting of individual models. In one of our role model economies, test‐based averaging achieves advantages in small samples. In larger samples, pure prediction models outperform forecast averages. Copyright (C) 2010 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1190
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 30 (2011)
Issue (Month): 6 (September)
Pages: 579-596

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Handle: RePEc:jof:jforec:v:30:y:2011:i:6:p:579-596

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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Keywords: combining forecasts ; encompassing tests ; model selection ; time series ;

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Cited by:
  1. Antonis Michis, 2012. "Monitoring Forecasting Combinations with Semiparametric Regression Models," Working Papers 2012-02, Central Bank of Cyprus.
  2. Costantini, Mauro & Kunst, Robert M., 2011. "On the Usefulness of the Diebold-Mariano Test in the Selection of Prediction Models," Economics Series 276, Institute for Advanced Studies.
  3. Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2012. "Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System," Economics Series 292, Institute for Advanced Studies.
  4. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
  5. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
  6. Bergmeir, Christoph & Costantini, Mauro & Benítez, José M., 2014. "On the usefulness of cross-validation for directional forecast evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 132-143.

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