Employing Bayesian Vector Auto-Regression (BVAR) method as an altenative technique for forecsating tax revenue in South Africa

Molapo, Mojalefa Aubrey

dc.contributor.advisor	Olaomi, John
dc.contributor.author	Molapo, Mojalefa Aubrey
dc.date.accessioned	2018-11-28T11:27:12Z
dc.date.available	2018-11-28T11:27:12Z
dc.date.issued	2017-02
dc.date.submitted	2018-11
dc.identifier.citation	Molapo, Mojalefa Aubrey (2017) Employing Bayesian Vector Auto-Regression (BVAR) method as an altenative technique for forecsating tax revenue in South Africa, University of South Africa, Pretoria, <http://hdl.handle.net/10500/25083>
dc.identifier.uri	http://hdl.handle.net/10500/25083
dc.format.extent	1 online resource (x, 134 leaves) : color illustrations, color graphs	en
dc.language.iso	en	en
dc.subject	Corporate income tax	en
dc.subject	Personal income tax	en
dc.subject	Total tax revenue	en
dc.subject	Forecasting	en
dc.subject	Bayesian Vector Autoregressive (BVAR)	en
dc.subject	Error	en
dc.subject	Trend	en
dc.subject	Seasonal (ETS)	en
dc.subject	Autoregressive moving Average (ARMA)	en
dc.subject	Root mean squared error (RMSE)	en
dc.subject	Autocorrelation	en
dc.subject.ddc	519.542
dc.subject.lcsh	Bayesian statistical decision theory	en
dc.subject.lcsh	Vector automobile	en
dc.subject.lcsh	Tax revenue estimating	en
dc.subject.lcsh	Corporations -- Taxation	en
dc.subject.lcsh	Income tax	en
dc.subject.lcsh	Standard deviations	en
dc.title	Employing Bayesian Vector Auto-Regression (BVAR) method as an altenative technique for forecsating tax revenue in South Africa	en
dc.type	Dissertation	en
dc.description.department	Statistics	en
dc.description.degree	M. Sc. (Statistics)	en