The influence of FDI on GHG emissions in BRI countries using spatial econometric analysis strategy: the significance of biomass energy consumption.

Indeed, the Belt and Road Initiative (BRI) plays an increasingly important role in global economic and climate change mitigation. However, scientists have insufficient attention to the issues related to the elements that contribute to justifying these impacts and bolstering its response in BRI nations. Accordingly, the existent study executed an in-depth examination of the spatial direct and spillover effects of foreign direct investment inflows (FDI) and biomass energy consumption (BEC) on greenhouse gas emissions (GHG) for 57 BRI countries (1992-2012). We applied the spatial lag model (SLM), the spatial error model (SEM), and the spatial Durbin model (SDM) with five different weights matrices to verify the existence of the pollution haven hypothesis (PHH), the pollution halo hypothesis (P-HH), and the N-shaped environmental Kuznets curve (EKC). We linked the study results with the implementation level of the sustainable Development Goals (SDGs). The findings of local Moran's I (LMI) and Lagrange Multiplier (LM) tests confirm the existence of spatial autocorrelation (SAR). The empirical results revealed that FDI has a positive direct and spillover influence on GHG emissions, which supports the presence of PHH. Also, the nexus between economic growth and GHG emission is an N-shaped curve. The results revered that BEC has a negative sign for direct and spillover effects. In contrast to BEC, Fossil Fuel Energy Consumption (FFEC) and population positively sign for direct and indirect impact. Some policy proposals and future research directions are discussed for BRI countries.

Asymmetric impacts of disaggregated energy consumption and oil price fluctuations on the MENA net oil-exporting and importing economies.

This paper asymmetrically analyzes the impact of energy consumption and oil price fluctuations on the economic growth of the MENA net oil-exporting and importing nations from 1990 to 2019 using panel nonlinear autoregressive distributed lag (PNARDL) model developed by (Salisu and Isah, Econ Model 66:258-271, 2017). The findings revealed that for the net-oil exporting countries, the impact of nonrenewable energy on economic growth is nonlinear in both terms, where in the both terms, high consumption of nonrenewable energy is influencing economic growth and its low consumption is limiting it. Furthermore, the impact of renewable energy is linear and it is influencing and limiting economic growth in both terms respectively. Moreover, the impact of oil price fluctuations on economic growth is linear in the long run and nonlinear in the short run, where in the long run, increase in it is not influencing economic growth but in the short run, while its decrease has no effect. For the net-oil importing countries, the impact of nonrenewable energy on economic growth is nonlinear in both terms, where in the long run, high consumption of nonrenewable energy is influencing economic growth but in the short run, it is discouraging it; however, in both terms, low consumption of nonrenewable energy has no effect. In addition, in the long run, the impact of renewable energy is nonlinear but linear in the short run; however, none of its impacts is significant in both terms. Also, the impact of oil price fluctuations on economic growth is linear in both terms and in the both terms, it is influencing economic growth. Nonetheless, for all the variables, the impacts are higher in the net-oil exporting countries. Policy recommendations were provided.