Renewable energy, carbon emissions, and economic growth in 24 Asian countries: evidence from panel cointegration analysis

Environ Sci Pollut Res Int. 2017 Nov;24(33):26006-26015. doi: 10.1007/s11356-017-0259-9. Epub 2017 Sep 23.

Abstract

This article aims to investigate the relationship among renewable energy consumption, carbon dioxide (CO2) emissions, and GDP using panel data for 24 Asian countries between 1990 and 2012. Panel cross-sectional dependence tests and unit root test, which considers cross-sectional dependence across countries, are used to ensure that the empirical results are correct. Using the panel cointegration model, the vector error correction model, and the Granger causality test, this paper finds that a long-run equilibrium exists among renewable energy consumption, carbon emission, and GDP. CO2 emissions have a positive effect on renewable energy consumption in the Philippines, Pakistan, China, Iraq, Yemen, and Saudi Arabia. A 1% increase in GDP will increase renewable energy by 0.64%. Renewable energy is significantly determined by GDP in India, Sri Lanka, the Philippines, Thailand, Turkey, Malaysia, Jordan, United Arab Emirates, Saudi Arabia, and Mongolia. A unidirectional causality runs from GDP to CO2 emissions, and two bidirectional causal relationships were found between CO2 emissions and renewable energy consumption and between renewable energy consumption and GDP. The findings can assist governments in curbing pollution from air pollutants, execute energy conservation policy, and reduce unnecessary wastage of energy.

Keywords: CO2 emissions; Granger causality test; Panel cointegration; Panel cross-sectional dependence; Renewable energy consumption.

MeSH terms

  • Asia
  • Carbon Dioxide / analysis*
  • Conservation of Energy Resources
  • Cross-Sectional Studies
  • Economic Development / statistics & numerical data*
  • Economic Development / trends
  • Environmental Pollution / prevention & control
  • Gross Domestic Product / statistics & numerical data
  • Gross Domestic Product / trends
  • Humans
  • Models, Statistical*
  • Renewable Energy / statistics & numerical data*

Substances

  • Carbon Dioxide