This study investigates the small-sample performance of meta-regression methods for detecting and estimating genuine empirical effects in research literatures tainted by publication selection. Publication selection exists when editors, reviewers or researchers have a preference for statistically significant results. Meta-regression methods are found to be robust against publication selection. Even if a literature is dominated by large and unknown misspecification biases, precision-effect testing and joint precision-effect and meta-significance testing can provide viable strategies for detecting genuine empirical effects. Publication biases are greatly reduced by combining two biased estimates, the estimated meta-regression coefficient on precision (1/"Se") and the unadjusted-average effect. Copyright 2008 Blackwell Publishing Ltd and the Department of Economics, University of Oxford.

Abstract. Meta-regression analysis (MRA) can provide objective and comprehensive summaries of economics research. Their use has grown rapidly over the last few decades. To improve transparency and to raise the quality of MRA, the meta-analysis of economics research-network (MAER-Net) has created the below reporting guidelines. Future meta-analyses in economics will be expected to follow these guidelines or give valid reasons why a meta-analysis must deviate from them.

Pedagogically, literature reviews are instrumental. They summarize the large literature written on a particular topic, give coherence to the complex, often disparate, views expressed about an issue, and serve as a springboard for new ideas. However, literature surveys rarely establish anything approximating unanimous consensus. Ironically, this is just as true for the empirical economic literature. To harmonize this dissonance, we offer a quantitative methodology for reviewing the empirical economic literature. Meta-regression analysis (MRA) is the regression analysis of regression analyses. MRA tends to objectify the review process. It studies the processes that produce empirical economic results as though they were any other social scientific phenomenon. MRA provides a framework for replication and offers a sensitivity analysis for model specification. In this brief essay, we propose a new method of reviewing economic literature, MRA, and discuss its potential.

Pedagogically, literature reviews are instrumental. They summarize the large literature written on a particular topic, give coherence to the complex, often disparate, views expressed about an issue, and serve as a springboard for new ideas. However, literature surveys rarely establish anything approximating unanimous consensus. Ironically, this is just as true for the empirical economic literature. To harmonize this dissonance, we offer a quantitative methodology for reviewing the empirical economic literature. Meta-regression analysis (MRA) is the regression analysis of regression analyses. MRA tends to objectify the review process. It studies the processes that produce empirical economic results as though they were any other social scientific phenomenon. MRA provides a framework for replication and offers a sensitivity analysis for model specification. In this brief essay, we propose a new method of reviewing economic literature, MRA, and discuss its potential.Empirical results reported in economic journals are selected from a large set of estimated models. Journals, through their editorial policies, engage in some selection, which in turn stimulates extensive model searching and prescreening by prospective authors. Since this process is well known to professional readers, the reported results are widely regarded to overstate the precision of the estimates, and probably to distort them as well. As a consequence, statistical analyses are either greatly discounted or completely ignored (Leamer and Leonard, 1983, p. 306).

The magnitude of the value of a statistical life (VSL) is critical to the evaluation of many health and safety initiatives. To date, the large and rigorous VSL research literature has not explicitly accommodated publication selectivity bias (i.e., the reduced probability that insignificant or negative VSL values are reported). This study demonstrates that doing so is essential. For studies that employ hedonic wage equations to estimate VSL, correction for selection bias reduces the average value of a statistical life by 70-80%. Our meta-regression analysis also identifies several sources for the wide heterogeneity found among reported VSL estimates.