EconPapers    
Economics at your fingertips  
 

Do we need a global VAR model to forecast inflation and output in South Africa?

Annari De Waal, Renee van Eyden () and Rangan Gupta

Applied Economics, 2015, vol. 47, issue 25, 2649-2670

Abstract: This study determines whether the global vector autoregressive (GVAR) approach provides better forecasts of key South African variables than a vector error correction model (VECM) and a Bayesian vector autoregressive (BVAR) model augmented with foreign variables. The article considers both a small GVAR model and a large GVAR model in determining the most appropriate model for forecasting South African variables. We compare the recursive out-of-sample forecasts for South African GDP and inflation from six types of models: a general 33 country (large) GVAR, a customized small GVAR for South Africa, a VECM for South Africa with weakly exogenous foreign variables, a BVAR model, autoregressive (AR) models and random walk models. The results show that the forecast performance of the large GVAR is generally superior to the performance of the customized small GVAR for South Africa. The forecasts of both the GVAR models tend to be better than the forecasts of the augmented VECM, especially at longer forecast horizons. Importantly, however, on average, the BVAR model performs the best when it comes to forecasting output, while the AR(1) model outperforms all the other models in predicting inflation. We also conduct ex ante forecasts from the BVAR and AR(1) models over 2010:Q1-2013:Q4 to highlight their ability to track turning points in output and inflation, respectively.

Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2015.1008769 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Do we need a global VAR model to forecast inflation and output in South Africa? (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:47:y:2015:i:25:p:2649-2670

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2015.1008769

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2023-11-30
Handle: RePEc:taf:applec:v:47:y:2015:i:25:p:2649-2670