Skip to search boxSkip to navigationSkip to main content

Economic Complexity, Economic Growth, and CO2 Emissions: A Panel Data Analysis

*Corresponding author for this work
  • Universidad Santo Tomás, Bogota
    ,
  • Colegio de Estudios Superiores de Administración
Research Output:
Contribution to journal
Article
Peer-review

Sustainable Development Goals

  • SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

Publication metrics

Metrics

SciVal
Citations
9
Scopus
Citations
SciVal
FWCI
0.66
SciVal
Author count
2
SciVal
Paper percentile
60

PlumX, opens in new tab

Captures
31
Citations
14

Abstract

Reducing global warming effects without jeopardizing economic prosperity demands the analysis of the link between these factors. Environmental degradation and economic growth are thought to be related in a non-linear manner, following an inverted-U pattern called the ‘Environmental Kuznets Curve’ (EKC). Despite the many studies seeking empirical support for this relationship, the literature does not provide conclusive findings. By presenting the Economic Complexity Index (ECI) as an explanatory variable, this paper aims at providing a comprehensive analysis of EKC from 86 countries with different development levels, covering the period between 1971 and 2014. Different statistical estimation techniques were used, including an Adaptive Neuro-Fuzzy Inference System (ANFIS) model, dynamic panel data techniques, and the Sasabuchi–Lind–Mehlum (SLM) test.
The results show no clear evidence supporting the idea of EKC, neither for production volumes nor for production sophistication, as captured by ECI. Nonetheless, when ECI increases, pollution levels drop monotonously only for developed countries.

Publication Information

Output type

Research Output:
Contribution to journal
Article
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 411-433 (23 pages)

Journal (Volume, Issue Number)

International Economic Journal (Volume 35, Issue 4)

Publication milestones

  • Published - 02/10/2021

Publication status

Published - 02/10/2021

ISSN

1016-8737

Publication IDs

  • ORCID: /0000-0002-0301-5641/work/99773955
  • Scopus: 85114813908