Combining inflation density forecasts

Christian Kascha () and Francesco Ravazzolo

No 2008/22, Working Paper from Norges Bank

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 data sets 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. Combining with equal weights often outperforms other weighting schemes. Also, logarithmic combinations can be advantageous, in particular if symmetric densities are preferred.

Keywords: Forecast Combination; Logarithmic Combinations; Density Forecasts; Inflation Forecasting (search for similar items in EconPapers)
JEL-codes: C53 E37 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2008-12-12
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-ets, nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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https://www.norges-bank.no/en/news-events/news-pub ... pers/2008/WP-200822/

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Journal Article: Combining inflation density forecasts (2010)
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