Forecasting inflation in Russia by Dynamic Model Averaging

Konstantin Styrin ()

No wps39, Bank of Russia Working Paper Series from Bank of Russia

Abstract: In this study, I forecast CPI inflation in Russia by the method of Dynamic Model Averaging (Raftery et al., 2010; Koop and Korobilis, 2012) pseudo out-of-sample on historical data. This method can be viewed as an extension of the Bayesian Model Averaging where the identity of a model that generates data and model parameters are allowed to change over time. The DMA is shown not to produce forecasts superior to simpler benchmarks even if a subset of individual predictors is pre-selected “with the benefit of hindsight” on the full sample. The two groups of predictors that feature the highest average values of the posterior inclusion probability are loans to non-financial firms and individuals along with actual and anticipated wages.

Keywords: Bayesian model averaging; model uncertainty; econometric modeling; high-dimension model; inflation forecast. (search for similar items in EconPapers)
JEL-codes: C5 C53 E37 (search for similar items in EconPapers)
Pages: 44 pages
Date: 2018-12
New Economics Papers: this item is included in nep-cba, nep-cis, nep-for, nep-mac, nep-ore and nep-tra
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Persistent link: https://EconPapers.repec.org/RePEc:bkr:wpaper:wps39

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