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Revisiting trade and environment nexus in South Africa: fresh evidence from new measure

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Abstract

The paper revisits the dynamic effect of trade openness on environmental quality in South Africa by employing a fresh proxy of trade openness suggested by Squalli and Wilson (The World Economy 34:1745–1770, 2011) over the period 1960–2016. Contrary to the previous literature, the new proxy is constructed to take into consideration both South Africa’s trade share of its GDP and its relative size of trade in relation to the world trade in a specified period of time. Adopting this novel approach to capture openness, the study applies the autoregressive distributed lag (ARDL) bounds test for cointegration approach to investigate the long-run association between trade openness and environmental quality. Our findings show that the results of the long run are materially different from those of the short run. While trade openness has a significantly beneficial impact on CO2 emissions in the short run, it has a measurably detrimental consequence on it in the long run. These findings are new to the literature and contrast with the previous studies. While confirming the existence of an inverted U-shaped curve that validates the existence of environmental Kuznets curve (EKC) hypothesis for South Africa, our results are further supported by the non-linear ARDL model, which reveals evidence of asymmetric pass-through effects of changes in trade openness on CO2 emissions. This paper suggests that South Africa’s policymakers must continue to improve trade policy reform with complementary policies to create a less carbon-intensive environment and promote lasting value for reductions of greenhouse gas (GHG) emissions and constantly support the establishment of greener technologies that ultimately lower CO2 emissions.

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Notes

  1. This proxy sharply contradicts with other indicators employed by other empirical studies such as the arbitrary binary (1.0) indicator proposed by Sachs and Warner (1995).

  2. Shin et al. (2014) argue that, because of dependency between the two variables, such a treatment is crucial.

  3. The validation of this year 1982 as a structural break point can also be observed from Figs. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,, 11 and 12.

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  1. School of Economics, College of Business and Economics, University of Johannesburg, P.O Box 524, Auckland Park, 2006, South Africa

    Maxwell Chukwudi Udeagha & Nicholas Ngepah

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  1. Maxwell Chukwudi Udeagha
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Appendix

Appendix

Fig. 1
figure 1

CO2 emissions during 1960-2016

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Fig. 2
figure 2

Real GDP per capita during 1960-2016

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Fig. 3
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Trade openness during 1960-2016

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Fig. 4
figure 4

Energy consumption during 1960-2016

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Fig. 5
figure 5

Capital-labour ratio during 1960-2016

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Fig. 6
figure 6

Financial sector development 1960-2016

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Fig. 7
figure 7

Foreign direct investment 1960-2016

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Fig. 8
figure 8

Agricultural GDP during 1960-2016

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Fig. 9
figure 9

Industrial GDP during 1960-2016

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Fig. 10
figure 10

Service sector GDP during 1960-2016

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Fig. 11
figure 11

Technological innovation 1960-2016

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Fig. 12
figure 12

Comparative advantage effect 1960-2016

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Udeagha, M.C., Ngepah, N. Revisiting trade and environment nexus in South Africa: fresh evidence from new measure. Environ Sci Pollut Res 26, 29283–29306 (2019). https://doi.org/10.1007/s11356-019-05944-y

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