Template-Type: ReDIF-Paper 1.0 Author-Name: Franz Ruch Author-Name-First: Franz Author-Name-Last: Ruch Author-Workplace-Name: South African Reserve Bank Author-Email: franz.ruch@resbank.co.za Author-Name: Mehmet Balcilar Author-Name-First Mehmet Author-Name-Last: Balcilar Author-Workplace-Name: Department of Economics, Eastern Mediterranean University, Famagusta, Northern Cyprus Author-Email: mehmet@mbalcilar.net Author-Name: Mampho P. Modise Author-Name-First: Mampho P. Author-Name-Last: Modise Author-Workplace-Name: National Treasury, 40 Church Square, Pretoria, 0002, South Africa Author-Email: mamphomodise@yahoo.com Author-Name: Rangan Gupta Author-Name-First: Rangan Author-Name-Last: Gupta Author-Workplace-Name: Department of Economics, University of Pretoria Author-Email: rangan.gupta@up.ac.za Title: Forecasting Core Inflation: The Case of South Africa Abstract: Forecasting and estimating core inflation has recently gained attention, especially for inflation targeting countries, following research showing that targeting headline inflation may not be optimal; a Central Bank can miss the signal due to the noise. Despite its importance there is sparse literature on estimating and forecasting core inflation in South Africa, with the focus still on measuring core inflation. This paper emphasises predicting core inflation using large time-varying parameter vector autoregressive models (TVP-VARs), factor augmented VAR, and structural break models using quarterly data from 1981Q1 to 2013Q4. We use mean squared forecast errors (MSFE) and predictive likelihoods to evaluate the forecasts. In general, we find that (i) small TVP-VARs consistently outperform all other models; (ii) models where the errors are heteroscedastic do better than models with homoscedastic errors; (iii) models assuming that the forgetting factor remains 0.99 throughout the forecast period outperforms models that allow for the forgetting factors to change with time; and (iv) allowing for structural break does not improve the predictability of core inflation. Overall, our results imply that additional information on the growth rate of the economy and interest rate is sufficient to forecast core inflation accurately, but the relationship between these three variables needs to be modelled in a time-varying (nonlinear) fashion. Length: 20 pages Creation-Date: 2015 File-URL: http://repec.economics.emu.edu.tr/RePEc/emu/wpaper/15-08.pdf File-Format: Application/pdf File-Function: First version, 2015 Number: 15-08 Classification-JEL: C22 C32 E27 E31 Keywords: Core inflation; forecasting; small- and large-scale vector autoregressive models; constant and time-varying parameters Handle: RePEc:emu:wpaper:15-08.pdf