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Articles

The impact of income inequality and economic complexity on ecological footprint: an analysis covering a long-time span

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Pages 133-153 | Received 26 Dec 2020, Accepted 11 May 2021, Published online: 19 May 2021
 

ABSTRACT

Income inequality and economic complexity impacts on ecological footprint were researched for a panel of twenty-five countries, from 1970 to 2016, using the panel quantile regression approach. Results support that the economic complexity index in the 10th and 25th quantiles and pooled OLS regression positively affects ecological footprint, but not in the 75th and 90th quantiles. Gross Domestic Product in the 10th, 25th, 50th, 75th, and 90th quantiles have a positive effect on ecological footprint. Consumption of fossil fuels and population growth positively affects the ecological footprint in 10th, 25th, 50th, 75th, and 90th quantiles and the pooled OLS. Income inequality in the 10th, 25th, and 50th quantiles and the OLS model regression positively affect ecological footprint. Economic openness in 10th, 25th, 50th, 75th, and 90th quantiles and the pooled OLS negatively affect ecological footprint. Policymakers should promote policies to (i) encourage investment in green energy technologies and implement upgraded energy and environmental laws; (ii) diversify exports and sophisticate products in countries with a high ecological footprint; (iii) depth of human development to control for the population growth and stimulate the economic complexity; (vi) negotiate international trade agreements to open the economy; (v) implement measures to curb income inequality.

Acknowledgements

CeBER R&D unit funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., project UIDB/05037/2020. Emad Kazemzadeh thanks the Faculty of Economics of the University of Coimbra for the host and resources for carrying out this research.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Research supported by: CeBER, R&D unit funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., project UIDB/05037/2020.

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