Re-visiting resource curse hypothesis in China through the lens of human capital and globalization

The resource curse hypothesis has recently become an important research topic in environmental economics. However, there still needs to be consensus in the literature on whether natural resource rents (NRRs) support economic growth. Previous studies on China have mainly analyzed the resource curse hypothesis based on local or regional data. However, this study examines the issue based on national-level data using globalization and human capital as control variables. The dynamic Auto-Regressive Distributive Lag (DARDL) Simulations and the Kernel-based Regularized Least Squares (KRLS) techniques are employed for policy formulation for 1980–2019. The empirical assessments indicate that NRRs escalate economic growth, i.e., China's resource curse hypothesis is invalid. Further, empirical outcomes reveal that human capital and globalization encourage China's economic growth. The KRLS, a machine learning algorithm, also supports the findings of the DARDL approach. Finally, based on the empirical outcomes, several policy recommendations can be developed, such as more investment in the education sector and the use of NRRs for productive sectors of the economy.