AI Summary & Key Takeaways
AI InsightThe results emphasise the necessity of differentiated policy trajectories for converging and diverging countries.
📌 3 Key Takeaways
Abstract
This study analyzes the LCF convergence of the world’s ten largest polluters—Brazil, the United States, Germany, South Korea, India, China, Indonesia, Japan, Mexico, and France—using data for the period 1961–2024. The research goes beyond the static framework and the heterogeneous findings of the linear, structural-break, and nonlinear unit root tests. As an analytical contribution, it applies the Nahar–Inder (2002) methodology to the LCF literature for the first time. This approach models convergence towards the leading country (Brazil) as a dynamic polynomial function of time, thereby relaxing the restrictive assumption of stationarity. With the contribution of Bentzen and Tung (2021), changes in the speed of convergence (acceleration or deceleration) are also captured through secondderivative analysis. The findings stand in sharp contrast to those obtained from unit root tests: the Nahar–Inder methodology identifies strong convergence for seven countries (the United States, India, Japan, Indonesia, Germany, France, and South Korea), while China and Mexico exhibit divergence. This result indicates that economies appearing to be divergent under traditional tests (e.g., the U.S., Germany, France) are, in fact, dynamically converging. The results emphasise the necessity of differentiated policy trajectories for converging and diverging countries.