A BVAR model for the South African economy

dc.contributor.authorGupta, Rangan
dc.contributor.authorSichei, Moses Muse
dc.contributor.emailrangan.gupta@up.ac.zaen
dc.date.accessioned2007-08-17T09:13:51Z
dc.date.available2007-08-17T09:13:51Z
dc.date.issued2006-09
dc.description.abstractThe paper develops a Bayesian vector autoregressive (BVAR) model of the South African economy for the period of 1970:1-2000:4 and forecasts GDP, consumption, investment, short-term and long term interest rates, and the CPI. We find that a tight prior produces relatively more accurate forecasts than a loose one. The out-of-sample-forecast accuracy resulting from the BVAR model is compared with the same generated from the univariate and unrestricted VAR models. The BVAR model is found to produce the most accurate out of sample forecasts. The same is also capable of correctly predicting the direction of change in the chosen macroeconomic indicators.en
dc.format.extent422521 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.citationGupta, R & Sichei, MM 2006, 'A BVAR model for the South African economy', South African Journal of Economics, vol. 74, no. 3, pp. 391–409. [http://www.blackwellpublishing.com/journal.asp?ref=0038-2280&site=1]en
dc.identifier.issn0038-2280
dc.identifier.urihttp://hdl.handle.net/2263/3315
dc.language.isoenen
dc.publisherBlackwellen
dc.rightsBlackwell. This article is embargoed by the publisher until September 2007en
dc.subjectSouth African economyen
dc.subjectBayesian vector autoregressive (BVAR) modelen
dc.subjectEconomic forecastingen
dc.subjectVector autoregressive (VAR) modelen
dc.subject.lcshEconomic forecasting -- South Africa -- Econometric models
dc.subject.lcshSouth Africa -- Economic conditions -- Econometric models
dc.titleA BVAR model for the South African economyen
dc.typePostprint Articleen

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Gupta_BVAR(2006).pdf
Size:
412.62 KB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
2.42 KB
Format:
Item-specific license agreed upon to submission
Description: