Does Economic Policy Uncertainty Matter for Environmental Degradation in Emerging Countries? Fresh Evidence from Fourier Bootstrap ARDL Estimation

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Abstract In recent years, economic policy uncertainty has initiated a new discussion in environmental economics on the main drivers of environmental degradation. The main goal is to determine whether economic policy uncertainty leads to environmental damage or contributes to environmental quality. For this purpose, researchers commonly employ panel data analyses based on group estimation and use carbon emissions as a proxy for environmental indicators. However, by doing so they overlook country-specific estimations as well as underrepresent the ecological balance. To overcome these shortcomings, in this paper we employ two new approaches. First, we apply novel Fourier bootstrap autoregressive distributed lag estimation, which is the stronger estimation procedure in time-series analysis, to detect individual outcomes. Second, we use the ecological footprint as a proxy for environmental degradation, which reflects the natural balance more holistically and comprehensively than pollution indicators. In this context, our paper examines the impact of economic policy uncertainty on ecological footprint by using some control variables, such as economic growth and energy consumption. Our sample consists of seven emerging countries from 1965 to 2022. Fourier ARDL test results reveal a strong long-run relationship between ecological footprint and economic policy uncertainty, economic growth, and energy consumption for four emerging countries: India, Indonesia, Russia, and Türkiye. The estimations reveal that economic policy uncertainty in these countries contributes to environmental quality in the long run. In this context, it is important for policymakers to implement environmentally friendly growth strategies far from any uncertainty for the sake of sustainable economic development.