The heterogeneous impacts of climate finance on environmental sustainability and social welfare in developing countries

Abstract

Purpose

Due to their limited capacity for adaptation and dependence on natural resources for economic growth, developing countries (DCs) tend to be more prone to climate change. It is argued that climate finance (CF) is a significant financial innovation to mitigate the negative effects of climate variation. However, the heterogeneous impacts of CF on environmental sustainability (ES) and social welfare (SW) have been masked. Thus, this study aims to investigate the heterogeneous effects of CF on ES and SW in 80 CF receipt DCs from 2002 to 2018. This study also aims to investigate the effects of CF on ES and SW based on population size, income heterogeneity and the type of CF.

Design/methodology/approach

The method of moments quantile regression (MMQR) with fixed effects is utilized. Alternatively, the fully modified least square (FMOLS) and dynamic least square (DOLS) estimators are used for the robustness test.

Findings

The findings revealed that DCs with the lowest and middle quantiles of EF, carbon dioxide (CO₂) emissions and human development exhibit large beneficial impacts of CF on ES and SW. In contrast, the positive effects of CF on ES breakdown for countries with the largest distributions of EF and CO₂ emissions. Besides, the impacts of CF on ES and SW depend on income heterogeneity, population size and the type of CF.

Practical implications

This study calls for a framework to integrate CF into all economic development decisions to strengthen climate-resilient SW and ES in DCs.

Originality/value

To the best of the authors’ knowledge, this is the first study to investigate the effects of CF on ES and SW in a wide range of DCs. Thus, it complements existing related literature focusing on the effects of CF on ES and SW.

Citation

Gong, X., Borojo, D.G. and Yushi, J. (2023), "The heterogeneous impacts of climate finance on environmental sustainability and social welfare in developing countries", Kybernetes, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-05-2023-0839