PurposeMotivated by the conflicting evidence on the effect of financial development on environmental quality, this study investigates the moderating role of institutional quality in the link between financial development and environmental quality using a robust proxy in Malaysia from 1984 to 2017.Design/methodology/approachEcological footprint is used to measure environmental quality, while financial development is proxied using three measures (domestic credit provided by the private sector, domestic credit provided by the financial sector and domestic credit provided by the banking sector). An index of institutional quality is generated from voice and accountability, government effectiveness, regulatory quality, rule of law and control of corruption. Autoregressive Distributed Lag Bounds Test, Fully Modified Ordinary Least Square and Canonical Cointegrating Regression were used as the estimation techniques.FindingsThe results show that financial development, institutional quality, economic growth and foreign direct investment improve environmental quality in the short run, whereas trade openness and natural resources worsen it. In the long run, financial development, institutional quality, economic growth, trade openness and natural resources deteriorate the environment. Furthermore, findings from the interactive term suggest that institutions and financial development complement each other to affect the environment in the short run. However, institutions and financial development perform a substitutability role in influencing the environment in the long run.Practical implicationsThe outcome of this study suggests that there are time lags in the relationship between institutional quality, financial development and ecological footprint in Malaysia. Furthermore, the study offers important policy implications to policymakers in Malaysia and other developing countries on how to mitigate environmental degradation.Originality/valueThis study contributes to the body of knowledge on the moderating role of institutional quality in the relationship between financial development and ecological footprint in Malaysia. It examines the direct and indirect effects of financial development on environmental degradation through institutional quality, which have received less attention in the context of Malaysia. The findings from this study are robust to different proxies and estimation techniques.

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PurposeThis study investigates the effect of shadow economy on environmental pollution and the role of institutional quality in moderating the impact in African countries between 1991 and 2015.Design/methodology/approachThe study employs three pollutant variables namely: carbon dioxide emissions per capita, methane emission and nitrous oxide emission as robustness check. Also, battery of methodologies; ordinary least squares, fixed effects and system generalised method of moments are used to drive out the conclusions of this study.FindingsThe findings reveal that shadow economy and institutional quality contribute significantly to environmental pollution in Africa. Further, the interactive effect of shadow economy and institutional quality worsens environmental quality in the region. This reveals that weak institutional quality recorded in the region increases the level of shadow economy, thereby intensifying environmental pollution.Practical implicationsThe study concludes that weak institutional framework in the region reinforces shadow economy and environmental pollution. Hence, findings from this study can help policymakers in the region to better understand the role of institutional quality in reducing shadow economy and environmental pollution.Originality/valueThis study enriches one’s understanding on the role of institutional quality in the relationship between environmental quality and shadow economy in African context. It investigates the direct and indirect impact of institutions and shadow economy on environmental quality. The study also uses three different robust variables to measure environmental pollution (carbon dioxide (CO2) emissions per capita, methane emission and nitrous oxide emission) for sensitivity analysis.

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