Mapapu, Babalwa and Phiri, Andrew (2017): Carbon emissions and economic growth in South Africa: A quantile regression approach.
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Abstract
Of recent carbon emissions have become an increasing concern for economies worldwide. In this study we investigate the relationship between carbon emissions and economic growth for the South African economy, one of the largest emitters of carbon dioxide worldwide. We employ the quantile regression methodology which is applied to annual data covering a period of 1970 to 2014. Our empirical results indicate that very low levels of carbon emissions are most beneficial towards economic growth. Our results thus encourage policymakers to continue to embark on energy efficiency programmes which specifically target lower levels of carbon pollution.
Item Type: | MPRA Paper |
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Original Title: | Carbon emissions and economic growth in South Africa: A quantile regression approach |
Language: | English |
Keywords: | Carbon Emissions; Economic growth; Environmental Kuznets curve; South Africa; Quantile regressions |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q43 - Energy and the Macroeconomy Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q56 - Environment and Development ; Environment and Trade ; Sustainability ; Environmental Accounts and Accounting ; Environmental Equity ; Population Growth |
Item ID: | 81801 |
Depositing User: | Dr. Andrew Phiri |
Date Deposited: | 08 Oct 2017 15:34 |
Last Modified: | 27 Sep 2019 10:24 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/81801 |