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Combining inflation density forecasts


Kascha, Christian; Ravazzolo, Francesco (2010). Combining inflation density forecasts. Journal of Forecasting, 29(1-2):231-250.

Abstract

In this paper, we empirically evaluate competing approaches for combining inflation density forecasts in terms of Kullback–Leibler divergence. In particular, we apply a similar suite of models to four different datasets and aim at identifying combination methods that perform well throughout different series and variations of the model suite. We pool individual densities using linear and logarithmic combination methods. The suite consists of linear forecasting models with moving estimation windows to account for structural change. We find that combining densities is a much better strategy than selecting a particular model ex ante. While combinations do not always perform better than the best individual model, combinations always yield accurate forecasts and, as we show analytically, provide insurance against selecting inappropriate models. Logarithmic combinations can be advantageous, in particular if symmetric densities are preferred.

Abstract

In this paper, we empirically evaluate competing approaches for combining inflation density forecasts in terms of Kullback–Leibler divergence. In particular, we apply a similar suite of models to four different datasets and aim at identifying combination methods that perform well throughout different series and variations of the model suite. We pool individual densities using linear and logarithmic combination methods. The suite consists of linear forecasting models with moving estimation windows to account for structural change. We find that combining densities is a much better strategy than selecting a particular model ex ante. While combinations do not always perform better than the best individual model, combinations always yield accurate forecasts and, as we show analytically, provide insurance against selecting inappropriate models. Logarithmic combinations can be advantageous, in particular if symmetric densities are preferred.

Citations

23 citations in Web of Science®
32 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Language:English
Date:6 January 2010
Deposited On:21 Jan 2011 13:40
Last Modified:05 Apr 2016 14:34
Publisher:Wiley-Blackwell
ISSN:0277-6693
Publisher DOI:https://doi.org/10.1002/for.1147

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