Role of education and natural resources in achieving green economic growth in China: A wavelet quantile correlation approach

Abstract

AbstractClimate change has emerged as a major threat for developed as well as emerging nations. In order to effectively address this matter, it is imperative to undertake a transition towards a sustainable and environment‐friendly economic model. From an economic standpoint, it is worth noting that green economic growth serves as a mechanism to enhance income levels while preserving the integrity of the environment. Therefore, there is a significant interest among researchers and policymakers to identify the determinants of green growth (GG), with the aim of formulating effective policies to promote sustainable development. In light of this, we probe the impact of education and natural resources on GG in China. The novel augmented autoregressive distributed lag approach reports the long‐run co‐movement between education, natural resources, and GG. Moreover, the results derived from the novel wavelet quantile correlation method indicate that education positively affects GG in both the short‐ and long‐term, across different quantiles. However, in the medium‐term, the impact of education on GG is negative. In both the short‐ and long‐term, natural resources hinder GG, thus providing support for the natural resource curse theory. We present policy recommendations aimed at fostering GG in the Chinese economy. For example, there should be a substantial increase in investment in education to boost GG. Next, access to education is inevitable to attain higher GG; therefore, quality education should be provided at a lower cost.