Preprint Article Version 1 NOT YET PEER-REVIEWED

The Impact of Energy, Agriculture, Macroeconomic and Human-Induced Indicators on Environmental Pollution from 1971 to 2011

  1. Middle East Technical University, Northern Cyprus Campus, Mersin 10, Turkey
Version 1 : Received: 25 September 2016 / Approved: 26 September 2016 / Online: 26 September 2016 (12:09:01 CEST)

How to cite: Asumadu-Sarkodie, S.; Owusu, P. The Impact of Energy, Agriculture, Macroeconomic and Human-Induced Indicators on Environmental Pollution from 1971 to 2011. Preprints 2016, 2016090095 (doi: 10.20944/preprints201609.0095.v1). Asumadu-Sarkodie, S.; Owusu, P. The Impact of Energy, Agriculture, Macroeconomic and Human-Induced Indicators on Environmental Pollution from 1971 to 2011. Preprints 2016, 2016090095 (doi: 10.20944/preprints201609.0095.v1).

Abstract

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 human-induced 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%, thus supports the environmental Kuznets curve hypothesis that an increase in a country’s economic growth leads to a reduction in environmental pollution. An 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.

Subject Areas

SIMPLS; energy economics; econometrics; carbon dioxide emissions; Ghana

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