How often should we believe positive results? EconomicsSSMART
Eva Vivalt Aidan Coville
High false positive and false negative reporting probabilities (FPRP and FNRP) reduce the veracity of the available research in a particular field, undermining the value of evidence to inform policy. However, we rarely have good estimates of false positive and false negative rates since both the prior and study power are required for their calculation, and these are not typically available or directly knowable without making ad hoc assumptions. We will leverage on AidGrade’s dataset of 647 impact evaluations in development economics and complement this by gathering estimates of priors and reasonable minimum detectable effects of various intervention-outcome combinations from policymakers, development practitioners and researchers in order to generate estimates of the FPRP and FNRP rates in development economics.