Title: Industrialisation and environmental quality in Africa: governance and industrial Kuznets curve perspective in quantile and threshold analysis

Authors: Richard Amankwa Fosu; Eric Boachie Yiadom; Evans Acheampong; Kwadwo Obeng

Addresses: Accounting Department, University of Professional Studies, P.O. Box LG 149, Legon –Accra, Ghana ' Banking and Finance Department, University of Professional Studies, P.O. Box LG 149, Legon, Accra, Ghana ' Banking and Finance Department, University of Professional Studies, P.O. Box LG 149, Legon, Accra, Ghana ' Accounting Department, University of Professional Studies, P.O. Box LG 149, Legon – Accra, Ghana

Abstract: The study employs a comprehensive empirical approach to analyse the intricate relationship between industrialisation, governance quality, and environmental sustainability in Africa. Through quantile regression and dynamic panel threshold analysis, three main objectives are pursued: assessing industrialisation's effect on environmental quality across quantiles, exploring governance quality's influence on this relationship, and investigating the presence of the industrialised environmental kuznet curve (IEKC). Findings reveal industrialisation's significant negative impact on environmental quality at lower quantiles, with a positive effect observed at higher quantiles, suggesting a threshold effect. Governance quality moderates this impact, particularly at lower quantiles, emphasising its pivotal role in promoting sustainable industrial development. Dynamic panel threshold regression identifies critical thresholds where industrialisation's environmental implications intensify, informing targeted policy interventions. Policy recommendations include fortifying environmental regulations, promoting sustainable industrial practices, enhancing governance capacity, and adopting integrated policy approaches to balance economic development and environmental conservation in Africa.

Keywords: industrialisation; environmental quality; governance quality; sustainability; quantile regression; dynamic panel threshold regression.

DOI: 10.1504/IJGE.2025.146430

International Journal of Green Economics, 2025 Vol.19 No.1, pp.21 - 43

Accepted: 30 Jul 2024
Published online: 29 May 2025 *

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