This paper investigates the empirical relevance of structural breaks in forecasting stock return volatility using both in-sample and out-of-sample tests and daily returns for the Johannesburg Stock Exchange (JSE) All Share Index from 07/02/1995 to 08/25/2010. We find evidence of structural breaks in the unconditional variance of the stock returns series over the period, with high levels of persistence and variability in the parameter estimates of the GARCH (1, 1) model across the sub-samples defined by the structural breaks. This indicates that structural breaks are empirically relevant to stock return volatility in South Africa. In out-of-sample tests, we find that combining forecasts from different benchmark and competing models that accommodate structural breaks in volatility improves the accuracy of volatility forecasting. Furthermore, for shorter horizons, the MS-GARCH model better captures asymmetry in stock return volatility than the GJR-GARCH (1, 1) model, which better suited to longer horizons, but in general, the asymmetric models fail to outperform the GARCH (1,1) model. Keywords: stock return volatility, structural breaks, in-sample tests, out-of-sample tests, GARCH Models.JEL classification: C22, C53, G11, G12 ♦ We would like to thank Professor Mehmet Bacilar for many helpful comments. However, any errors are solely ours.
This study aims to quantify the extent of catastrophic household health expenditures on welfare and determine factors influencing it. A logistic regression model based on the logit link function was used to predict the probability of catastrophic health expenditure occurrence. A comparison between 2008 and 2012 health status of adults shows that there was a sizable improvement of the health status of individuals. The high level of catastrophic health expenditure may be associated with the low share of prepayment in national health expenditure, adequate availability of services and a high level of poverty which for South Africa is 46.2% according to the Statistics South Africa report (2015). Major factors determining the catastrophic expenditure besides poverty were spending on hospitalisation and medical supplies. Thus, reducing catastrophic expenditures requires an increase in financial protection offered to the poor through expanding government-financed benefits for the poor such as implementation of the Social Health Insurance (SHI) scheme, which will cover all poor households.
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