Truth and Robustness in Cross-Country Law and Finance Regressions: A Bayesian Analysis of Empirical 'Law Matters' Thesis

Abstract

This paper applies a Bayesian model averaging algorithm to systematically evaluate the “law matters” literature and finds that the positive cross-country relationship between anti-self-dealing rules and stock market development proposed by Djankov, La Porta, Lopez-de-Silanes, and Sheifer (2008, Journal of Financial Economics 88: 430-465) is fragile. In contrast, proxies for information disclosure, political power of incumbents and economic development are found to have strong predictive power for stock market outcome variables. Finally, variant sets of variables are shown to predict stock market development, which rejects the “one-size-fits-all” specification employed in previous macro law and finance studies.

Keywords: Anti-self-dealing rules; Bayesian model averaging; Law and finance; Model uncertainty; Stock market development

JEL Classification: G38; K22; C11