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VOLATILITY MODELING OF REAL GDP GROWTH RATES IN SOUTH AFRICA

VOLATILITY MODELING OF REAL GDP GROWTH RATES IN SOUTH AFRICA An analysis of quarterly real gross domestic product (GDP) growth rates in South Africa for the period 1960 to 2011 is done using an autoregressive moving average-exponential generalized autoregressive conditional heteroskedasticity (ARMA-EGARCH) model and the extreme value theory (EVT) modeling framework. A two stage approach is used. An estimate of an ARMA-EGARCH model is done in stage one. In stage two, the EVT framework is applied to the lower tail of the distribution of the real GDP growth rates. The advantage of this approach lies in its ability to capture conditional heteroskedasticity in the data through the ARMAEGARCH model, while at the same time modeling the extreme tail behavior through the EVT framework. Empirical results show existence of volatility persistence and excess kurtosis in the real GDP growth rates. The generalized extreme value distribution (GEVD) produces more accurate estimates of extreme tails than a pure ARMA-EGARCH model. Modeling of extreme negative growth rates is very important for economic planners and the use of EVT-based approaches gives accurate estimates of extreme growth rates. JEL codes: D92, N1, O4 Keywords: tail quantiles, generalized extreme value distribution, GDP, EGARCH http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Economics, Management, and Financial Markets Addleton Academic Publishers

VOLATILITY MODELING OF REAL GDP GROWTH RATES IN SOUTH AFRICA

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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1842-3191
eISSN
1938-212X
Publisher site
See Article on Publisher Site

Abstract

An analysis of quarterly real gross domestic product (GDP) growth rates in South Africa for the period 1960 to 2011 is done using an autoregressive moving average-exponential generalized autoregressive conditional heteroskedasticity (ARMA-EGARCH) model and the extreme value theory (EVT) modeling framework. A two stage approach is used. An estimate of an ARMA-EGARCH model is done in stage one. In stage two, the EVT framework is applied to the lower tail of the distribution of the real GDP growth rates. The advantage of this approach lies in its ability to capture conditional heteroskedasticity in the data through the ARMAEGARCH model, while at the same time modeling the extreme tail behavior through the EVT framework. Empirical results show existence of volatility persistence and excess kurtosis in the real GDP growth rates. The generalized extreme value distribution (GEVD) produces more accurate estimates of extreme tails than a pure ARMA-EGARCH model. Modeling of extreme negative growth rates is very important for economic planners and the use of EVT-based approaches gives accurate estimates of extreme growth rates. JEL codes: D92, N1, O4 Keywords: tail quantiles, generalized extreme value distribution, GDP, EGARCH

Journal

Economics, Management, and Financial MarketsAddleton Academic Publishers

Published: Jan 1, 2013

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