Less is more: Testing financial integration using identification-robust asset pricing models

Abstract

We revisit financial market integration and study the impact of multiple risk factors and model specification on inference. Our tests exploit a method correct in finite sample that jointly assesses coefficient significance and detects identification problems. Results on four countries show that multiple sources of risk in international asset pricing models lead to lack of identification and spurious inference. We find that domestic factor models are well identified which is not the case for global and international models. Nonetheless, domestic models do not provide a base for testing financial market integration. Given that constraint, the best-identified international model includes few factors and reveals that financial integration varies over time and across countries.