966
Number: 01/2016
Author(s): Vugar Ahmadov, Shaig Adigozalov, Salman Huseynov, Fuad Mammadov, Vugar Rahimov
Language: English
Date: April 6, 2016
Abstract: In this study, we investigate 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 the 3 variables VARmodel. 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 advantage over both linear and random walk models in predicting forecast density.
Keywords: Forecasting; Bayesian methods; Non-linear models
JEL classification: C11, C13, C32, C53
