Beyond Publication Bias

Abstract

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.