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Linear Relationship between CO2 Emissions and Economic Variables: Evidence from a Developed Country and a Developing Country

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  • Lazim Abdullah

Abstract

Multiple linear regressions (MLR) analyses have been used to explain various linear relationships between CO2 emissions and economic variables. Previous research have suggested that predictors of CO2 emissions can be vary depending on economic development of a country and also region where a country is located. This paper investigates the linear relationships between CO2 emissions and its related economic variables using MLR analyses for the UK and Malaysia. Differently from the typical MLR analyses which directly identify the most prevalent predictors, these analysis includes F- test to check linearity property of the relationships, regression equations and also error analysis to validate the robustness of the multiple linear regressions as predictive tool. It is shown that the linear relationships of the UK data outperformed the linear relationship of Malaysian data where agriculture and transport are the most effective predictors for the UK and Malaysia data respectively. The most effective predictor from the linear relationship would provide valuable information for policy holders and environmental management authority on potential causes of CO2 emissions.

Suggested Citation

  • Lazim Abdullah, 2015. "Linear Relationship between CO2 Emissions and Economic Variables: Evidence from a Developed Country and a Developing Country," Journal of Sustainable Development, Canadian Center of Science and Education, vol. 8(2), pages 1-66, February.
  • Handle: RePEc:ibn:jsd123:v:8:y:2015:i:2:p:66
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    References listed on IDEAS

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    1. Ang, James B., 2009. "CO2 emissions, research and technology transfer in China," Ecological Economics, Elsevier, vol. 68(10), pages 2658-2665, August.
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    Cited by:

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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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