Class size reduction mandates are frequent and invariably justified by studies reporting positive effects on student achievement. Yet other studies report no effects, and the literature as a whole awaits correction for potential publication bias. Moreover, if identification drives results systematically, the relevance of individual studies will vary. We build a sample of 1,767 estimates collected from 62 studies and for each estimate codify 42 factors reflecting estimation context. We employ recently developed nonlinear techniques for publication bias correction and Bayesian model averaging techniques that address model uncertainty. The results suggest publication bias among studies featured in top five economics journals, but not elsewhere. The implied class size effect is zero for all identification approaches except Tennessee's Student/Teacher Achievement Ratio project. The effect remains zero for disadvantaged students and across subjects, school types, and countries.

A key parameter in the analysis of wage inequality is the elasticity of substitution between skilled and unskilled labor. We show that the empirical literature is consistent with both publication and attenuation bias in the estimated inverse elasticities. Publication bias, which exaggerates the mean reported inverse elasticity, dominates and results in corrected inverse elasticities closer to zero than the typically published estimates. The implied mean elasticity is 4, with a lower bound of 2. Elasticities are smaller for developing countries. To derive these results, we use nonlinear tests for publication bias and model averaging techniques that account for model uncertainty.