Socio-economic Development and Carbon Productivity: A Panel Data Analysis of the World's Largest Carbon-Emitting Countries

Abstract

As global concerns about climate change intensify, assessing the environmental efficiency of production processes through carbon productivity has become increasingly important. This study examines the impact of socio-economic development on carbon productivity in the top 18 CO2-emitting countries, which contribute approximately 82% of global CO2 emissions, over the period 1990-2019. Using a class of econometric tests to address heterogeneity and cross-sectional dependence, we employ the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) model for final estimation, ensuring robustness with Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimations. The empirical findings reveal that GDP per capita, Trade, and FDI increase carbon productivity while energy consumption and urbanization curtail carbon productivity. The country-specific effects indicated that 83% of the sample countries exhibit positive relationships between socio-economic development and carbon productivity, suggesting that these nations can serve as models for effective low-carbon policies. Moreover, the results demonstrate bi-directional relationships for GDP per capita, FDI, and energy use with carbon productivity and uni-causal relationship for trade and urbanization. The study highlights the need for implementing stricter regulations to improve energy efficiency and promote the adoption of renewable energy sources such as wind, solar, hydro, and nuclear power. Additionally, countries should incentivize green technology investments through tax breaks and subsidies, enhance international trade agreements that support the exchange of clean technologies, and develop sustainable urban planning initiatives to mitigate the negative impact of urbanization on carbon productivity.

Keywords

Carbon productivity; Socio Economic development; World's largest carbon emitting countries; Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL)

Published in

Environmental Modeling and Assessment
2025, volume: 30, number: 1, pages: 37-52
Publisher: SPRINGER

SLU Authors

• Raza, Mohsin

  • Department of Economics, Swedish University of Agricultural Sciences
    
  • University of Bonn
  • Wageningen University

Global goals (SDG)

SDG7 Affordable and clean energy
SDG12 Responsible consumption and production
SDG13 Climate action

UKÄ Subject classification

Economics
Environmental Sciences

Publication identifier

• DOI: https://doi.org/10.1007/s10666-024-09992-8

Permanent link to this page (URI)

https://res.slu.se/id/publ/132681