By: Gene Yang ‘19

Reciprocity, the act of responding to kind actions with other kind actions, has been known to stabilize cooperation within populations and communities. When applied on a global scale, models of international cooperation have shown reciprocity to be a key factor in stabilization. However, empirical research to verify these models have so far been limited to small-scale studies involving two or three country pairs. The inability to detect large-scale reciprocity in the international system can be attributed to a statistical problem: it has been traditionally very hard to predict causality between dependent time series variables. In other words, because cooperation between one country and another might indirectly influence a third country, statistical tests that rely on variables being independent, such as the Granger causality test, do not produce accurate results.

However, a newly developed statistical test, called convergent cross mapping (CMM), has shown to reliably predict causality between dependent variables. Researchers from Massachusetts Institute of Technology used this new statistical test to study international reciprocity, and detected reciprocity between 47 pairs of countries. When these interactions were mapped to a network, the empirical data supported models of reciprocity. Reciprocating country pairs were more likely to exhibit stable cooperation regardless of recent—whether positive of negative—interaction, and less likely to engage in conflict. However, reciprocating countries were also more likely to reciprocate conflict. This study provides the strongest empirical evidence to date that policies of reciprocity can lead to interaction cooperation.

References

1. M. Frank, et al., Detecting reciprocity at a global scale. Science Advances 4 (2018). doi: 10.1126/sciadv.aao5348.
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