Forecasting inflation in post-oil boom years: A case for non-linear models?

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 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 advantage over both linear and random walk models in predicting forecast density.