Understanding complex dependence requires a network approach. Traditional theories focusing on firm-, industry-, country- or dyad-level factors fail to capture today's fragmented global economy. This new perspective highlights reciprocal and transitive relationships among cross-border investment flows.

Our study utilizes exponential random graph models (ERGM) for weighted networks. We analyze FDI data across multiple countries, testing hypotheses about reciprocity and transitivity in international investment relationships.

🔍 Key Findings:

• Strong evidence of reciprocity exists between investing nations
• Transitivity patterns show how investments form interconnected chains
• Established covariates still influence network formation but within the complex structure

🌍 Political Economy Implications:

This research demonstrates that FDI networks behave systematically. The findings revise conventional understanding and provide insights into global production dynamics.

📈 Methodological Contribution:

We offer a novel application of ERGMs to count-weighted international economic data, advancing political science analysis of globalization processes.