Forecasting inflation in post-oil boom years: A case for regime switches?

Vugar Ahmadov, Salman Huseynov (), Shaig Adigozalov (), Fuad Mammadov () and Vugar Rahimov
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Salman Huseynov: Central Bank of Azerbaijan, and Institute of Control Systems, National Academy of Sciences
Shaig Adigozalov: Central Bank of Azerbaijan

Journal of Economics and Finance, 2018, vol. 42, issue 2, No 8, 369-385

Abstract: Abstract In this study, we investigate the relative performance of various non-linear models against that of an autoregressive model in forecasting future inflation. We find that non-linear models have trivial forecast superiority over the univariate autoregressive model in terms of central forecast accuracy. They also perform poorly when their forecasts are measured against those of a VAR model. In addition, we also show that non-linear models cannot beat the random walk in terms of central forecast accuracy, which is in line with the previous literature on Azerbaijan during the post-oil boom years. However, we also demonstrate that non-linear models still have clear forecast advantages over both linear and random walk models in predicting forecast density.

Keywords: Inflation; Forecasting; Bayesian methods; Regime switching models (search for similar items in EconPapers)
JEL-codes: C11 C13 C32 C53 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12197-017-9410-1

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