As a Chinese scheme with the attribute of international public goods in the new era,whether the Belt and Road Initiative can solve the global peace deficit has attracted attention from all walks of life.Based on Uppsala Conflict Data from 2006 to 2019,this paper constructs a multiple period DID model to test the impact of the Belt and Road Initiative on internal conflicts in participating countries.The results show that the Belt and Road Initiative has effectively curbed the internal conflicts in participating countries,and with the extension of a country's participation time,this inhibitory effect increases marginally.The mechanism test shows that,on the one hand,the Belt and Road Initiative has significantly improved the employment,income distribution and other livelihood conditions of participating countries,thus increasing the opportunity cost of people's participation in conflict,easing the dissatisfaction of low-income groups,and promoting more stability of the domestic situation.On the other hand,the concept of"mutual consultation"advocated by the Belt and Road Initiative has been widely practiced and deeply internalized,significantly improving the level of consultative democracy in participating countries.As a result,social conflicts and differences can be effectively resolved,and the domestic political environment continues to improve,leading to a significant reduction in conflicts.In addition,the peace effect of the the Belt and Road Initiative shows great heterogeneity in the dimensions of conflict scale,cooperation content,economic development level of participating countries,and political relations between participating countries and the United States.The research results of this paper show that the Belt and Road Initiative,as a concrete practice platform for China's participation in global governance,has become a powerful driving force and a solid link for maintaining world peace and stability.
the Belt and Road Initiativedomestic conflictlivelihood statedeliberative democracymultiple period DID
NETL
NSTL
万方数据
