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

作     者：Ahmadov, Vugar Huseynov, Salman Adigozalov, Shaig Mammadov, Fuad Rahimov, Vugar 

作者机构：Center for Research and Development Central Bank of Azerbaijan Baku Azerbaijan Centre for Research and Development Central Bank of Azerbaijan and Institute of Control Systems National Academy of Sciences Baku Azerbaijan 

出 版 物：《Journal of Economics and Finance》 (J. Econ. Financ.)

年 卷 期：2018年第42卷第2期

页      面：369-385页

学科分类：0202[经济学-应用经济学] 02[经济学] 1202[管理学-工商管理] 0201[经济学-理论经济学] 0701[理学-数学] 

主　　题：Bayesian methods Forecasting Inflation Regime switching models 

摘      要：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. © 2017, Springer Science+Business Media, LLC.