Do BRI policy and institutional quality influence economic growth and environmental quality? An empirical analysis from South Asian countries affiliated with the Belt and Road Initiative.

The effect of quality institutions on growth-environmental nexus is a generally ignored topic, especially in South Asia economies affiliated with the belt and road initiatives (BRIs). To fill this gap, we have examined the effect of BRI policy, economic freedom (EF), and institutional quality (IQ) on growth-environmental nexus in the South Asian region from 1984 to 2019. We have used CO emission as a proxy for the environment in this study. To prevent variable bias, we also included energy consumption (EN) and trade openness (TO) as key factors in the model. To solve the problem of cross-sectional dependence, we have used the second-generational unit root test. The results of unit root tests indicate that the variable IQ is stationary at the level and other variables are stationary at the first difference. Furthermore, all of the variables are cointegrated, according to the panel cointegration test. Thus, we have used the panel autoregressive distributed lag (ARDL) method to estimate the long-run (LR) and short-run (SR) impact of response factors on economic growth. Furthermore, this research utilized the Granger causality test among the selected variables to inquire into the causalities. The basic findings are as follows: (i) A significantly positive interaction variable (COIQ) among CO and IQ suggests that effective and fair political institutions are critical for increasing economic development and decreasing CO emissions simultaneously. (ii) Economic growth is invigorated by energy consumption, trade, economic freedom, and institutional quality. (iii) Since 2013, more significant economic growth has been stimulated by BRI policy in BRI-associated countries; thus, both the SR and LR results are significantly positive. Hence, it is essential to improve the quality of institutions to reduce carbon emissions during economic growth.