A content analysis of 2 years of Psychological Science articles reveals inconsistencies in how researchers make inferences about indirect effects when conducting a statistical mediation analysis. In this study, we examined the frequency with which popularly used tests disagree, whether the method an investigator uses makes a difference in the conclusion he or she will reach, and whether there is a most trustworthy test that can be recommended to balance practical and performance considerations. We found that tests agree much more frequently than they disagree, but disagreements are more common when an indirect effect exists than when it does not. We recommend the bias-corrected bootstrap confidence interval as the most trustworthy test if power is of utmost concern, although it can be slightly liberal in some circumstances. Investigators concerned about Type I errors should choose the Monte Carlo confidence interval or the distribution-of-the-product approach, which rarely disagree. The percentile bootstrap confidence interval is a good compromise test.

This study examines associations between measures of stock exchange disclosure and market development at 50 of the member stock exchanges of the World Federation of Exchanges. We focus on stock exchange disclosure systems (rather than actual company disclosures) because this approach links stock exchange policy with desired outcomes related to market development (such as liquidity, trading activity, and market size relative to gross domestic product). We find strong support for the hypothesis that the strength of the disclosure system (disclosure rules, monitoring, and enforcement) is positively associated with market development, after controlling for legal system, legal protection of investors, market size, and several other potentially relevant explanatory variables.