Assessing the impact of FDI on PM2.5 concentrations: A nonlinear panel data analysis for emerging economies

Abstract

While emerging markets have obtained powerful growth for foreign direct investment (FDI) inflows, they are facing severe smog pollution, and this contradiction has become increasingly prominent since the financial crisis. Assessing the influence of FDI on pollutant emissions is of great significance for determining how to attract FDI to promote environmental sustainability. The present study simultaneously investigates the direct and indirect effects of FDI on PM2.5 contamination for emerging countries spanning the period 2010–2016. Due to the features of the nonlinear analysis, a generalized panel smooth transition regression (GPSTR) model was introduced, and cross-sectional dependence, heterogeneity, nonlinear unit root, nonlinear cointegration tests and non-parametric kernel density estimation were applied to achieve this goal. The results reveal that FDI directly contributes to decreasing PM2.5, but indirectly has on increasing PM2.5 emissions. The total effect of FDI on PM2.5 concentrations is proven to be negative, which confirms the pollution halo hypothesis. Moreover, the connection between FDI inflows and PM2.5 emissions displays a threshold and dynamic characteristic and is “S-shaped”. At lower levels of FDI, the inflows of FDI exert a positive effect on reducing PM2.5 concentrations, whereas when FDI exceeds the threshold of 23.2981, such influence is gradually weakened with an increase in its own accumulation. The study provides new assessments on FDI's contribution to pollutant emissions and evidence for environmental sustainability in the post-financial crisis era.