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

Show simple item record De Waal, Annari Van Eyden, Renee Gupta, Rangan 2015-05-19T12:38:43Z 2015-05-19T12:38:43Z 2015
dc.description.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. en_ZA
dc.description.embargo 2016-08-31 en_ZA
dc.description.librarian hb2015 en_ZA
dc.description.sponsorship Commonwealth Scholarship Commission in the UK and the Cambridge Commonwealth Trust. en_ZA
dc.description.uri en_ZA
dc.identifier.citation Annari De Waal, Reneé Van Eyden & Rangan Gupta (2015) Do we need a global VAR model to forecast inflation and output in South Africa?, Applied Economics, 47:25, 2649-2670, DOI:10.1080/00036846.2015.1008769 en_ZA
dc.identifier.issn 0003-6846 (print)
dc.identifier.issn 1466-4283 (online)
dc.identifier.other 10.1080/00036846.2015.1008769
dc.language.iso en en_ZA
dc.publisher Routledge en_ZA
dc.rights © 2015 Taylor and Francis. This is an electronic version of an article published in Applied Economics, vol. 47, no. 25, pp. 2649-2670, 2015. doi : 10.1080/00036846.2015.1008769. Applied Economics is available online at : http://www.tandfonline.comloi/raec20 en_ZA
dc.subject Global vector autoregressive (GVAR) model en_ZA
dc.subject Bayesian vector autoregressive (BVAR) model en_ZA
dc.subject Forecasting en_ZA
dc.subject South Africa (SA) en_ZA
dc.title Do we need a global VAR model to forecast inflation and output in South Africa? en_ZA
dc.type Postprint Article en_ZA

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