Forecasting inflation in post-oil boom years: A case for regime switches?
Shaig Adigozalov (),
Fuad Mammadov () and
Vugar Rahimov ()
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Shaig Adigozalov: Central Bank of Azerbaijan
Journal of Economics and Finance, 2018, vol. 42, issue 2, 369-385
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)
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