Beyond the Single Horizon: Ecological Footprint Convergence in the Big Ten Emerging Economies Using Discrete Wavelet Transform

This study investigates the ecological footprint (EF) convergence dynamics of the “Big Ten Emerging Economies” (BTEs) over the period 1967–2024. Employing the Maximum Overlap Discrete Wavelet Transform (MODWT) in conjunction with the Fourier KPSS (FKPSS) stationarity test, the analysis decomposes the EF series into short-, medium-, and long-term frequency components, allowing the stochastic convergence hypothesis to be examined separately across multiple time horizons. The empirical results reveal that convergence is largely absent in the original series, with stochastic convergence detected only for India, Indonesia, and Türkiye at the aggregate level. Once the series are decomposed, convergence becomes considerably more visible. In the short run, convergence is supported for Argentina, Indonesia, Mexico, Poland, and Türkiye. The medium run emerges as the most robust convergence horizon, with all ten economies exhibiting stochastic convergence—a result that becomes visible only after accounting for nonlinear structural breaks through the Fourier framework. In the long run, convergence is supported for Argentina, Brazil, China, Korea, Poland, and South Africa, while India, Indonesia, Mexico, and Türkiye exhibit persistent divergence. No single country maintains convergence consistently across all time horizons, underscoring the heterogeneous and frequency-dependent nature of EF dynamics in major emerging economies. The robustness analysis based on the Fourier ADF and standard ADF tests supports the primary findings. These results contribute to the EF convergence literature by demonstrating that environmental convergence is a multi-layered and frequency-dependent phenomenon, and offer empirical insights relevant to the design of long-run sustainability policies for emerging economies.