Transport infrastructure connectivity and conflict resolution: a machine learning analysis

被引:110
作者
Luo, Ji [1 ]
Wang, Guijun [2 ]
Li, Guangqin [3 ]
Pesce, Greta [4 ]
机构
[1] Tsinghua Univ, Sch Publ Policy & Management, Beijing, Peoples R China
[2] Peking Univ, Sch Econ, Beijing, Peoples R China
[3] Anhui Univ Finance & Econ, Sch Int Trade & Econ, Bengbu, Peoples R China
[4] Shanghai Jiao Tong Univ, Sch Int & Publ Affairs, Shanghai, Peoples R China
关键词
Transport infrastructure connectivity; Conflict resolution; Difference-in-differences model; Machine learning; WOMENS WORK; TERRORISM; INVESTMENT; PARTICIPATION; QUALITY;
D O I
10.1007/s00521-021-06015-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Transport infrastructure connectivity (TIC) has strong endogeneity issues, making it difficult to directly assess its impact on local conflict resolution. This study presents new evidence of the effects of TIC on conflict resolution by conducting a natural experiment and applying machine learning methods to overcome the endogeneity issue. Based on global conflict data from 2010 to 2017, the empirical results show the following: (1) TIC can significantly improve countries' global ranking for conflict resolution; in particular, the marginal benefit of developed countries is greater than that of developing countries. (2) The mechanism behind this effect is the promotion of trade facilitation, a more balanced employment ratio across genders, and improved income levels through TIC, which further enhances the conflict governance capacity of countries. In light of the findings, policy-makers should consider the opportunity to combine TIC with greater security for the realization of economic and social benefits, taking into account the significant opportunities for developing countries and the importance of balance across genders and income levels.
引用
收藏
页码:6585 / 6601
页数:17
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