Wavelet and Fourier augmented convergence analysis of methane emissions in more than two centuries: implications for environmental management in OECD countries

Abstract

Addressing the challenges posed by pollutants is necessary to achieve Sustainable Development Goal 13, which involves climate change mitigation and enhancement of environmental quality. The convergence analysis of a pollutant provides information that can be useful to how to handle that pollutant across countries or regions, and previous studies mainly focused on carbon emission. However, the second most significant greenhouse gas, methane emission, was mostly ignored. The primary objective of this research is to investigate whether stochastic convergence of methane emissions is valid in 37 OECD (Organisation for Economic Co-operation and Development) countries using a dataset of more than two centuries. The results obtained by using a set of traditional unit root tests and a newly proposed wavelet unit root test with a Fourier function provide overwhelming evidence for these countries' divergence of methane emissions. The policy implications resulting from the empirical findings for environmental management are discussed in the relevant sections of the paper.

Keywords: Environmental management; Fourier; Methane emissions; Stochastic convergence; Wavelet.