The impact of energy, agriculture, macroeconomic and human-induced indicators on environmental pollution: evidence from Ghana

Asumadu-Sarkodie S., Owusu P. A.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, cilt.24, sa.7, ss.6622-6633, 2017 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 24 Sayı: 7
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1007/s11356-016-8321-6
  • Dergi Adı: ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.6622-6633
  • Anahtar Kelimeler: SIMPLS, Energy economics, Econometrics, Carbon dioxide emissions, Ghana, CARBON-DIOXIDE EMISSIONS, PARTIAL LEAST-SQUARES, ECONOMIC-GROWTH, CAUSALITY ANALYSIS, FINANCIAL DEVELOPMENT, KUZNETS CURVE, CO2 EMISSIONS, CONSUMPTION, COINTEGRATION, NEXUS
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

In this study, the impact of energy, agriculture, macroeconomic and human-induced indicators on environmental pollution from 1971 to 2011 is investigated using the statistically inspired modification of partial least squares (SIMPLS) regression model. There was evidence of a linear relationship between energy, agriculture, macroeconomic and humaninduced indicators and carbon dioxide emissions. Evidence from the SIMPLS regression shows that a 1% increase in crop production index will reduce carbon dioxide emissions by 0.71%. Economic growth increased by 1% will reduce carbon dioxide emissions by 0.46%, which means that an increase in Ghana's economic growth may lead to a reduction in environmental pollution. The increase in electricity production from hydroelectric sources by 1% will reduce carbon dioxide emissions by 0.30%; thus, increasing renewable energy sources in Ghana's energy portfolio will help mitigate carbon dioxide emissions. Increasing enteric emissions by 1% will increase carbon dioxide emissions by 4.22%, and a 1% increase in the nitrogen content of manure management will increase carbon dioxide emissions by 6.69%. The SIMPLS regression forecasting exhibited a 5% MAPE from the prediction of carbon dioxide emissions.