1. Forecasting South African inflation using non-linearmodels: a weighted loss-based evaluation
- Author
-
Rangan Gupta, Patrick T. Kanda, Pejman Bahramian, and Mehmet Balcilar
- Subjects
Inflation ,Economics and Econometrics ,050208 finance ,Inflation targeting ,media_common.quotation_subject ,05 social sciences ,Non linear model ,Salient ,0502 economics and business ,Economics ,Econometrics ,Seasonal adjustment ,050207 economics ,Emerging markets ,Economic forecasting ,media_common - Abstract
The conduct of inflation targeting is heavily dependent on accurate inflation forecasts. Non-linear models have increasingly featured, along with linear counterparts, in the forecasting literature. In this study, we focus on forecasting South African inflation by means of non-linear models and using a long historical dataset of seasonally adjusted monthly inflation rates spanning from 1921:02 to 2013:01. For an emerging market economy such as South Africa, non-linearities can be a salient feature of such long data, hence the relevance of evaluating non-linear models’ forecast performance. In the same vein, given the fact that 1969:10 marks the beginning of a protracted rising trend in South African inflation data, we estimate the models for an in-sample period of 1921:02–1966:09 and evaluate 1, 4, 12, and 24 step-ahead forecasts over an out-of-sample period of 1966:10–2013:01. In addition, using a weighted loss function specification, we evaluate the forecast performance of different non-linear mo...
- Published
- 2016