Abstract

The one belt one road initiative, spearheaded by China, stands as a monumental foreign policy endeavour designed to strengthen ties with 146 nations. The construction projects within this initiative wield a substantial influence on the economic landscapes of participating countries, significantly affecting financial stability, infrastructure investments, and fiscal expansion. Studies utilizing CO2 emissions as a function of financial data (FD), Foreign Direct Investment (FDI), Gross Domestic Product (GDP), squared Gross Domestic Product (GDP2), economic indicators (EC), and trade-related factors (TR) have demonstrated a statistically positive relationship between these variables. The study spans from 2014 to 2021, employing panel data regression techniques to analyze the impact of the One Belt One Road initiative on participating countries' economic landscapes. Utilizing dynamic seemingly unrelated regression (DSUR) panel estimation, the study assesses the initiative's impact on macroeconomic factors such as GDP, FDI, EPI, trade, and FDPS. Statistical significance tests, including p-values and F-statistics, are employed to gauge the significance of the relationship between these factors and the initiative. Null hypothesis testing is utilized to determine whether a variable Granger causes another variable, providing further insights into causal relationships. R2 values are employed to quantify the proportion of variance in the dependent variable attributable to the independent factors. These statistical methodologies offer a robust and empirical approach to comprehending the one belt one road initiative's profound impact on the economic landscapes of participating nations.

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