Mobilizing FDI in natural resources in the post-COP28 era: Spatial drivers, natural capital, and sustainability dynamics

Abstract

This study examines the dynamic determinants of resource-related Foreign Direct Investment (FDI) using a panel dataset spanning from 2000 to 2022. By employing an Error Correction Model with Spatial Autoregression (ECM-SAR) and a Smooth Transition Autoregressive (STAR) model, we explore both the short-run and long-run drivers of resource FDI while accounting for spatial dependencies and nonlinear threshold effects. The results confirm the significant role of market size, human capital, and economic prosperity in attracting resource-related FDI, while excessive government intervention and stringent environmental policies exert a deterrent effect. Our findings reveal strong persistence in resource FDI flows, with past investment decisions heavily influencing current inflows. Population size and human capital emerge as robust determinants, reinforcing the importance of labor market dynamics in investment decisions. The analysis also uncovers spatial dependencies, indicating that FDI in one country is influenced by investments in neighboring regions. Furthermore, the STAR model highlights nonlinearities in FDI determinants, suggesting that threshold effects shape investment behavior, particularly concerning government intervention and resource dependence. The policy implications emphasize the need for balanced regulatory frameworks that encourage investment while maintaining sustainable environmental and economic policies.