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The influence of renewable energy use, human capital, and trade on environmental quality in South Africa: multiple structural breaks cointegration approach

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A Correction to this article was published on 03 December 2020

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Abstract

Recent economic and environmental literature suggests that the current state of energy use in South Africa amidst rapid growing population is unsustainable. Researchers in this area mostly focus on the effect of fossil energy use on carbon (CO2) emission, which represents only an aspect of environmental quality. In contrast, the current study evaluates the influence of renewable energy use, human capital, and trade on ecological footprint––a more comprehensive measure of environmental quality. To this end, the study employs multiple structural breaks cointegration tests (Maki cointegration tests), dynamic unrestricted error correction model through Autoregressive Distributed Lag (ARDL) model, and VECM Granger causality tests. The results of the Maki cointegration tests reveal the existence of a cointegration between the variables in all the models with evidence of multiple structural breaks. Further, the ARDL results divulge that an increase in renewable energy use, human capital, and trade improves environmental quality through a decrease in ecological footprint, while an increase in income stimulates ecological footprint. Moreover, causal relationship is found, running from all the variables to renewable energy and trade flow in the long run, while in the short run, economic growth causes ecological footprint. Trade is found to Granger-cause human capital, while human capital causes renewable energy. Additionally, human capital, renewable energy, and economic growth are predictors of trade. The study therefore recommends South African policymakers to consider the importance of renewable energy, human capital development, and trade as a policy option to reduce ecological footprint and improve environmental quality.

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Data availability

The datasets generated and/or analyzed during the current study are available in the repositories:

- Ecological Footprint per capita is available at Global Footprint Network (GFN 2018)

- Renewable Energy per capita is available at International Energy Agency (IEA 2018)

- Human Capital Development is available at Penn World Table (PWT 9.1 2019)

- Trade and GDP per capita are available at World Development Indicators (World Bank 2018)

Change history

Notes

  1. Equation 1 presents a model with the level shifts. Equation 2 is a model with level shifts and trend. Equation 3 presents a model with regime shifts, while Equation 4 presents a model with a model with regime shifts and trend.

  2. “Trade flow is already in percentage. Generally, log of a variable measured in percentage is not preferred in empirical studies when other variables are in log levels” ( Balcilar et al. 2020).

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Contributions

Paul Terhemba Iorember: data curation, writing—original draft, and formal analysis. Ojonugwa Usman: conceptualization, formal analysis, investigation, and methodology. Gylych Jelilov: writing, original draft; writing—review and editing. Abdurrahman Işık: writing—review and editing, validation, visualization, and supervision. Bilal Celik: writing—original draft, supervision, validation, and visualization

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Correspondence to Ojonugwa Usman.

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The original article was revised: The correct 1st sentence of the Abstract is “Recent economic and environmental literature suggests that the current state of energy use in South Africa amidst rapid growing population is unsustainable.”.

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Iorember, P.T., Jelilov, G., Usman, O. et al. The influence of renewable energy use, human capital, and trade on environmental quality in South Africa: multiple structural breaks cointegration approach. Environ Sci Pollut Res 28, 13162–13174 (2021). https://doi.org/10.1007/s11356-020-11370-2

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