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Spatial dependencies and long-run dynamics of the Environmental Kuznets Curve in West Africa: an analysis of growth vs. emissions

Year: 2025

Type: article

Abstract: Validating the Environmental Kuznets Curve (EKC) hypothesis has been a core subject for decades. Still, its universality is contested in contemporary studies due to prior region-specific outcomes. Comprehensively estimating its applicability for West African countries, while addressing the gaps in prior studies, second-generation and non-spherical error methods, spatial approaches, and long-run estimators are applied to 3 decades’ worth of data. The findings reveal that (1) pertaining to environmental deterioration (EAI), West African countries fall within clusters of low-low, low-high, and high-low, with the presence of spatial dependencies. Thus, three types of spatial associations are discovered: low-low clusters (LL), where low-EAI countries are neighbours to other low-EAI countries; low-high outliers (LH), where a low-EAI country is surrounded by high-EAI neighbours; and high-low outliers (HL), where a high-EAI country is bordered by low-EAI countries. (2) Per capita GDP and its quadratic form locally have an inverse relationship with environmental degradation, but in the long run, have a positive correlation. (3) FDI’s impact supports the pollution halo hypothesis, while trade exacerbates emissions through emission-intensive goods and transportation-related emissions. (4) Industries affect environmental degradation in the long run negatively, whereas population density exhibits a similar effect locally, and its effects spill over to neighbouring countries. (5) The inverted U-shaped correlation does not hold for West African countries, insinuating that the EKC hypothesis is not universally applicable. Overall, recommendations based on the empirical outcomes are cited for policymakers, stakeholders, and future research.

Source: Frontiers in Environmental Science

DOI: 10.3389/fenvs.2025.1621251

Authors: Decai Tang, Valentina Boamah, Qiang Ding, Jiangang Bai

Institutions: Nanjing University of Information Science and Technology, Hengxing University, Nanjing University of Finance and Economics

Language: English

Topic: Energy, Environment, Economic Growth

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDG: Climate action

Open Access status: gold

Estimated APC paid: $3,801