Using Quantile Regression to Analyze the Relationship between Socioeconomic Indicators and Carbon Dioxide Emissions in G20 Countries

Abdulaziz A Alotaibi,Naif Alajlan

doi:10.3390/su13137011

Abdulaziz A Alotaibi, Naif Alajlan

Open Access

https://doi.org/10.3390/su13137011

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Abstract

Numerous studies addressed the impacts of social development and economic growth on the environment. This paper presents a study about the inclusive impact of social and economic factors on the environment by analyzing the association between carbon dioxide (CO2) emissions and two socioeconomic indicators, namely, Human Development Index (HDI) and Legatum Prosperity Index (LPI), under the Environmental Kuznets Curve (EKC) framework. To this end, we developed a two-stage methodology. At first, a multivariate model was constructed that accurately explains CO2 emissions by selecting the appropriate set of control variables based on model quality statistics. The control variables include GDP per capita, urbanization, fossil fuel consumption, and trade openness. Then, quantile regression was used to empirically analyze the inclusive relationship between CO2 emissions and the socioeconomic indicators, which revealed many interesting results. First, decreasing CO2 emissions was coupled with inclusive socioeconomic development. Both LPI and HDI had a negative marginal relationship with CO2 emissions at quantiles from 0.2 to 1. Second, the EKC hypothesis was valid for G20 countries during the study period with an inflection point around quantile 0.15. Third, the fossil fuel consumption had a significant positive relation with CO2 emissions, whereas urbanization and trade openness had a negative relation during the study period. Finally, this study empirically indicates that effective policies and policy coordination on broad social, living, and economic dimensions can lead to reductions in CO2 emissions while preserving inclusive growth.

Highlights

Public Administration Department, College of Business Administration, King Saud University, Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia
(ii) We modelled the per capita CO2 emissions using two socioeconomic indicators and four well-studied control variables, i.e., per capita gross domestic product (GDP), fossil fuel consumption, urbanization, and trade openness. (iii) We empirically tested the Environmental Kuznets Curve (EKC) hypothesis. (iv) We applied the most recent data for all G20 countries, which widely represent the world and include a period after the Paris climate change agreement [3]
This subsection provides discussion about the results of this paper and comparison with similar works in the literature. For both Legatum Prosperity Index (LPI) and Human Development Index (HDI), there was a negative marginal relationship with CO2 emissions at quantiles larger than 0.2, with this relation becoming more significant as the quantile increases

Summary

Introduction

Public Administration Department, College of Business Administration, King Saud University, Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia. This paper presents a study about the inclusive impact of social and economic factors on the environment by analyzing the association between carbon dioxide (CO2 ) emissions and two socioeconomic indicators, namely, Human Development Index (HDI) and Legatum Prosperity. Index (LPI), under the Environmental Kuznets Curve (EKC) framework. To this end, we developed a two-stage methodology. Decreasing CO2 emissions was coupled with inclusive socioeconomic development. Both LPI and HDI had a negative marginal relationship with CO2 emissions at quantiles from 0.2 to 1. The fossil fuel consumption had a significant positive relation with CO2 emissions, whereas urbanization and trade openness had a negative relation during the study period

Methods

Results

Conclusion