ARIMA forecasts of the number of beneficiaries of social security grants in South Africa

Luruli, Fululedzani Lucy

dc.contributor.advisor	Ndlovu, P.
dc.contributor.author	Luruli, Fululedzani Lucy
dc.date.accessioned	2012-06-13T08:55:58Z
dc.date.available	2012-06-13T08:55:58Z
dc.date.issued	2011-12
dc.identifier.citation	Luruli, Fululedzani Lucy (2011) ARIMA forecasts of the number of beneficiaries of social security grants in South Africa, University of South Africa, Pretoria, <http://hdl.handle.net/10500/5810>	en
dc.identifier.uri	http://hdl.handle.net/10500/5810
dc.description.abstract	The main objective of the thesis was to investigate the feasibility of accurately and precisely fore- casting the number of both national and provincial bene ciaries of social security grants in South Africa, using simple autoregressive integrated moving average (ARIMA) models. The series of the monthly number of bene ciaries of the old age, child support, foster care and disability grants from April 2004 to March 2010 were used to achieve the objectives of the thesis. The conclusions from analysing the series were that: (1) ARIMA models for forecasting are province and grant-type spe- ci c; (2) for some grants, national forecasts obtained by aggregating provincial ARIMA forecasts are more accurate and precise than those obtained by ARIMA modelling national series; and (3) for some grants, forecasts obtained by modelling the latest half of the series were more accurate and precise than those obtained from modelling the full series.	en
dc.format.extent	1 online resource (i, 42 leaves)	en
dc.language.iso	en	en
dc.subject	Social security grants	en
dc.subject	Autoregressive integrated moving average models	en
dc.subject	Forecast	en
dc.subject	Social pension systems	en
dc.subject	Portmanteau test	en
dc.subject	Model identification	en
dc.subject	Standard error	en
dc.subject	Mean square error	en
dc.subject	Autocorrelation function	en
dc.subject	Akaike's information criterion	en
dc.subject.ddc	519.5
dc.subject.lcsh	Box-Jenkins forecasting	en
dc.subject.lcsh	Social security -- South Africa -- Forecasting	en
dc.subject.lcsh	Social security beneficiaries -- South Africa -- Forecasting	en
dc.subject.lcsh	Forecasting -- Statistical methods	en
dc.subject.lcsh	Akaike Information Criterion	en
dc.subject.lcsh	Mathematical models	en
dc.title	ARIMA forecasts of the number of beneficiaries of social security grants in South Africa	en
dc.type	Dissertation	en
dc.description.department	Department of Statistics	en
dc.description.degree	M.Sc. (Statistics)