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Modeling CO2 emissions in South Africa: empirical evidence from ARDL based bounds and wavelet coherence techniques.

Tomiwa Sunday AdebayoJamiu Adetola Odugbesan
Published in: Environmental science and pollution research international (2020)
The theme of this paper is to explore the interconnection between financial development, real growth, and urbanization and CO2 emissions using South Africa. The study used a recent econometric technique to investigate this relationship. The data used in this study cover period between 1971 and 2016. No previous research has utilized the wavelet coherence method to collect information on the correlation and causal interaction between these economic indicators at various frequencies and timeframes in the case of South Africa. The research objectives were to fix the questions: (i) if there is a stable long-run relationship among the indicators under consideration? (ii) Does financial development, economic growth, and urbanization affect CO2 emissions? (iii) How are the indicators related, at different frequencies and various periods? The outcomes affirm that (i) financial development impacts CO2 emissions positively. (ii) The linkage between urbanization and CO2 emissions is negative. (iii) Positive interaction between real growth and CO2. The results of the wavelet coherence approach support the ARDL long-term estimate. Based on these results, recommendations have been made.
Keyphrases
  • south africa
  • life cycle
  • municipal solid waste
  • hiv positive
  • convolutional neural network
  • healthcare
  • genome wide
  • machine learning
  • electronic health record
  • metabolic syndrome
  • health information