A Comparative Analysis of Forecast Performance between Sarima and Setar Models Using Macroeconomic Variables in Ghana - Ahmed, N.B. (University of Ghana, 2018)
Most macroeconomic variables such as; inflation, GDP and others have been described by most financial and economics time series analysts to exhibit nonlinear behaviour. Therefore, to cater for this behaviour, the nonlinear class of models have been largely adopted to model and forecast such time series. In this study, the Keenan and Tsay tests for linearity showed inflation and CIC rates follow threshold nonlinear processes. Hence, the two-regime SETAR model was adopted to accommodate these nonlinearities in the datasets. Using the linear SARIMA model as a benchmark for comparative analysis. Results from both in-sample and out- of- sample forecast performance using MAE and RMSE measures revealed that, the nonlinear SETAR model outperformed the linear SARIMA model for inflation. This was however different for CIC rates, since the Linear SARIMA model turned to outperform the nonlinear SETAR model. Further analysis of forecast accuracy using the Diebold- Mariano test showed there was no significant difference between the two models for inflation but, there was significant difference between both models for CIC rates. Nevertheless, it is recommended that, continuous monitoring of these models, review market conditions and necessary adjustments are vital to make realistic use of these models.
Thesis (MPhil) -University of Ghana
Keywords: Forecast; Performance; Macroeconomic; Models; Inflation; Financial