Abstract
AbstractWe assess the impact of mandating data-sharing in economics journals on two dimensions of research credibility: statistical significance and excess statistical significance (ESS). ESS is a necessary condition for publication selection bias. Quasi-experimental difference-in-differences analysis of 20,121 estimates published in 24 general interest and leading field journals shows that data-sharing policies have reduced reported statistical significance and the associated t-values. The magnitude of this reduction is large and of practical significance. We also find suggestive evidence that mandatory data-sharing reduces ESS and hence decreases publication bias.
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