Resolving the energy-growth nexus in South Africa

Abstract

Energy use is a pivotal element in the economic life of any country, especially in a developing economy such as South Africa. Based on trends such as load-shedding and oil supply shocks, it is essential to investigate the relationship between electricity and oil consumption to economic growth. This is particularly relevant in the South African context, where policy-makers have had to grapple with excess demand for electricity. The Johansen cointegration and vector error correction model approaches have been used to examine a short- and long-run relationship between energy consumption and economic growth. It has been found that electricity consumption has a negative relationship with economic growth and oil consumption has a positive relationship. Therefore, conservation policies like electricity rationing may be implemented, thereby proving to be beneficial to the broader economy. To offset periodical effects such as oil supply shocks, the country should keep high or adequate amounts of oil reserves and/or invest in oil exploration. It is highly recommended, regarding electricity, that the government is to adopt policy measures and direct interventions to promote an efficient use of electricity.

Japan energy mix and economic growth nexus: Focus on natural gas consumption

“…This is supported by studies such as Etokakpan et al 3 ; Molele and Ncanywa. 66 The second category included additional variables such as capital and labour which were distinctly different from the first category. Rafindadi and Ozturk, 4 examine the relationship between natural gas consumption, economic growth, exports, capital, and labour within the periods 1971-2012 in Malaysia.…”

The Strategic Importance of Energy Consumption to Economic Growth: Evidence From the Uae

“…Alternatively, economic growth requires an uninterrupted supply of electricity to support the bilateral theory. Molele and Ncanywa (2018) stated that the vector error correction and co-integration models were invaluable in the context of the research hypotheses postulated for this study. Oil and electricity both would be consumed hugely along the economic growth.…”

A Sectoral Approach to the Electricity-Growth Nexus in the Eastern Cape Province of South Africa

“…To the very best of our search efforts, we are able to find 10 studies, a majority which have used ARDL or VECM cointegration models (Odhiambo (2009), Menyah and Wolde-Rufael ( 2010), Bildirici et al (2012), Dlamini et al (2015), Nyoni and Phiori (2016), Khobai et al (2017) and Moele and Ncanywa (2018)) whilst the remaining studies use nonlinear cointegration methods (Nyoni and Phiri, 2018) or various causality tests (Dlamini et al (2015) and Bah and Azam (2017)). Out of these 10 studies, 8 studies show a positive cointegration relationship (Odhiambo (2009), Menyah and Wolde-Rufael (2010), Bildirici et al (2012), Nyoni and Phiri (2016), Bah and Azam (2017), Khobai et al (2017) and Nyoni and Phiri (2018)) whereas the remaining two studies establish no such relationship (Dlamini et al (2015) and Moele and Ncanywa (2018)). By default, only the studies of Dlamini et al (2015) and Moele and Ncanywa (2018) advocate for the neutrality hypothesis in South Africa.…”

“…Out of these 10 studies, 8 studies show a positive cointegration relationship (Odhiambo (2009), Menyah and Wolde-Rufael (2010), Bildirici et al (2012), Nyoni and Phiri (2016), Bah and Azam (2017), Khobai et al (2017) and Nyoni and Phiri (2018)) whereas the remaining two studies establish no such relationship (Dlamini et al (2015) and Moele and Ncanywa (2018)). By default, only the studies of Dlamini et al (2015) and Moele and Ncanywa (2018) advocate for the neutrality hypothesis in South Africa. On the other hand, the feedback hypothesis receives the most empirical support in the literature (Odhiambo (2009), Khobai et al (2017) and Nyoni and Phiri (2018)), whilst the conservation hypothesis (Bildirici et al, 2012) and the growth hypothesis (Menyah and Wolde-Rufael, 2010) receive less empirical support.…”

“…Finally, our error correction terms produces its correct negative and statistically significant estimate of −0.02 which interprets to approximately 2% of deviations corrected per annum subsequent to a shock to the system. Bildirici et al (2012), Dlamini et al (2015), Dlamini et al (2015), Khobai et al (2017) and Moele and Ncanywa (2018), Nyoni and Phiri (2016;2018) and Bah and Azam (2017).…”