We investigate the credibility of central bank research by searching for traces of researcher bias, which is a tendency to use undisclosed analytical procedures that raise measured levels of statistical significance (stars) in artificial ways. To conduct our search, we compile a new dataset and borrow 2 bias-detection methods from the literature: the p-curve and z-curve. The results are mixed. The p-curve shows no traces of researcher bias but has a high propensity to produce false negatives. The z-curve shows some traces of researcher bias but requires strong assumptions. We examine those assumptions and challenge their merit. At this point, all that is clear is that central banks produce results with patterns different from those in top economic journals, there being less bunching around the 5 per cent threshold of statistical significance.
Related Staff Report 621: Online Appendix for Star Wars at Central Banks, https://doi.org/10.21034/sr.621.
[Supplemental data and code for replication.](https://researchdatabase.minneapolisfed.org/concern/datasets/n870zr01k)