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Incorporating Forests, Agriculture, and Energy Consumption in the Framework of the Environmental Kuznets Curve: A Dynamic Panel Data Approach

1
Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695, USA
2
Department of Natural Resource Ecology and Management, Oklahoma State University, Stillwater, OK 74078, USA
3
Institute for Life Sciences and the Environment (ILSE), University of Southern Queensland, Toowoomba 4350, Australia
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(9), 2688; https://doi.org/10.3390/su11092688
Received: 13 April 2019 / Revised: 5 May 2019 / Accepted: 7 May 2019 / Published: 11 May 2019
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Abstract

Based on country-specific panel data from 1990–2014 for 86 different countries, we quantify the effects of forests and agricultural land in CO2 emissions, using the framework of the Environmental Kuznets Curve (EKC). The results from the dynamic panel data method reveal that forests are an important determinant in reducing CO2 emissions globally, but the effects vary by region. All else constant, we estimate a 0.11% decline in CO2 emissions per 1% increase in the forest area globally. However, the agricultural sector is found to be a true CO2 emitter. Our study provides additional empirical evidence for the roles of forests in regulating atmospheric CO2, further reinforcing the importance of forests in global climate change policies. View Full-Text
Keywords: dynamic panel data model; Environmental Kuznets Curve; CO2 emissions; economic growth; endogeneity dynamic panel data model; Environmental Kuznets Curve; CO2 emissions; economic growth; endogeneity
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Parajuli, R.; Joshi, O.; Maraseni, T. Incorporating Forests, Agriculture, and Energy Consumption in the Framework of the Environmental Kuznets Curve: A Dynamic Panel Data Approach. Sustainability 2019, 11, 2688.

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