Forecasting inflation in Russia using a TVP model with Bayesian shrinkage

Andrey Polbin and Andrei Shumilov
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Andrey Polbin: Gaidar Institute for Economic Policy

Working Papers from Gaidar Institute for Economic Policy

Abstract: Forecasting inflation is an important and challenging practical task. In particular, models with a large number of explanatory variables on relatively short samples can often overfit in-sample and, thus, forecast poorly. In this paper, we study the applicability of the model with Bayesian shrinkage of time-varying parameters based on hierarchical normal-gamma prior to forecasting inflation in Russia. Models of this type allow for possible nonlinearities in relationships between regressors and inflation and, at the same time, can deal with the problem of overfitting.

Keywords: Russian economy, inflation; forecasting; time-varying parameter model; Bayesian shrinkage; normal-gamma prior (search for similar items in EconPapers)
JEL-codes: C53 E37 (search for similar items in EconPapers)
Pages: 16 pages
Date: 2023, Revised 2023
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