Beyond Publication Bias



Abstract.  This review considers several meta-regression and graphical methods that can differentiate genuine empirical effect from publication bias. Publication selection exists when editors, reviewers, or researchers have a preference for statistically significant results. Because all areas of empirical research are susceptible to publication selection, any average or tally of significant/insignificant studies is likely to be biased and potentially misleading. Meta-regression analysis can see through the murk of random sampling error and selected misspecification bias to identify the underlying statistical structures that characterize genuine empirical effect. Meta-significance testing and precision-effect testing (PET) are offered as a means to identify empirical effect beyond publication bias and are applied to four areas of empirical economics research – minimum wage effects, union-productivity effects, price  elasticities, and tests of the natural rate hypothesis.