Beating random walk: “hard times†for forecasting inflation in post†oil boom years?

Salman Huseynov (), Vugar Ahmadov and Shaig Adigozalov ()
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Salman Huseynov: Central Bank of Azerbaijan Republic
Vugar Ahmadov: Central Bank of Azerbaijan Republic
Shaig Adigozalov: Central Bank of Azerbaijan Republic

No 1505, Working Papers from Central Bank of Azerbaijan Republic

Abstract: In this study, we investigate forecasting performance of various univariate and multivariate models in predicting inflation for different horizons. We design our forecast experiment for the post-oil boom years of 2010-2014 and compare forecasting ability of the different models with that of naïve ones. We find that for all forecast horizons simple naive models have equal forecasting ability with relatively sophisticated models which allow for richer economic dynamics. To check whether forecasting ability of naïve models has not been inferior to relatively sophisticated ones in boom and pre-boom years as well, we repeat our forecast experiment and estimate the models for the period 2003-2006 and keep the years 2006-2010 for undertaking pseudo out-of-sample exercise. Our experiment reveals that surprising forecasting performance of naïve models in post-oil boom years is a new phenomenon and in fact, the employed models have exhibited significant forecasting advantage over naïve ones in boom and pre-boom years. We find that despite declining volatility in inflation over the post-oil boom years, it has become considerably difficult for our models to beat naïve ones due to recently unpredictable behavior of inflation.

Keywords: Inflation; Forecasting; Time Series methods; Bayesian methods (search for similar items in EconPapers)
JEL-codes: C11 E31 E37 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2015-02-15
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