4.6 Article

Financial Risk and Environmental Sustainability in Poland: Evidence from Novel Fourier-Based Estimators

Journal

SUSTAINABILITY
Volume 15, Issue 7, Pages -

Publisher

MDPI
DOI: 10.3390/su15075801

Keywords

financial risk; environment; sustainability; Fourier-based estimators; Poland

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This study uses Fourier-based ARDL and Fourier Toda Yamamoto causality methods to examine the impact of financial risk on environmental sustainability in Poland. The results show that renewable energy consumption and financial risk contribute to reducing environmental degradation, while primary energy consumption and economic growth have detrimental effects. Furthermore, the analysis of causality direction indicates that financial risk and renewable energy consumption have a one-way causal effect on environmental degradation.
Using Fourier-based ARDL and Fourier Toda Yamamoto causality methods, this study aims to detect the impact of financial risk on environmental sustainability in Poland while controlling economic growth, primary energy consumption, and renewable energy consumption from 1990Q1 to 2019Q4. The outcomes of the Fourier ADL cointegration test indicate all variables are cointegrated. Additionally, the Fourier ARDL long-form estimates indicate both renewable energy consumption and financial risk contribute to reducing environmental degradation in Poland. However, the Fourier ARDL long-form estimates show that both primary energy consumption and economic growth have detrimental impacts on the economy's level of environmental degradation. Analysis of causality direction with the Fourier Toda Yamamoto causality test indicates both financial risk and renewable energy consumption for the period had a one direction causal effect on environmental degradation. For policy insight, the government could support environmental policies requiring companies to factor climate-related risks into their supervision and financial stability monitoring. The Polish government requires financial institutions to prioritize climate risk scenarios in stress testing to control catastrophic weather-related losses.

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