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Star Wars at Central Banks

Author

Listed:
  • Joel Bank
  • Hamish Fitchett
  • Adam Gorajek
  • Benjamin A. Malin
  • Andrew Staib
Abstract
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.

Suggested Citation

  • Joel Bank & Hamish Fitchett & Adam Gorajek & Benjamin A. Malin & Andrew Staib, 2021. "Star Wars at Central Banks," Staff Report 620, Federal Reserve Bank of Minneapolis.
    • Handle: RePEc:fip:fedmsr:89864
    DOI: 10.21034/sr.620
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    References listed on IDEAS

    as
    1. Abel Brodeur & Nikolai Cook & Anthony Heyes, 2020. "Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics," American Economic Review, American Economic Association, vol. 110(11), pages 3634-3660, November.
    2. Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2016. "Star Wars: The Empirics Strike Back," American Economic Journal: Applied Economics, American Economic Association, vol. 8(1), pages 1-32, January.
    3. Burlig, Fiona, 2018. "Improving transparency in observational social science research: A pre-analysis plan approach," Economics Letters, Elsevier, vol. 168(C), pages 56-60.
    4. Andrew Gelman & Guido Imbens, 2013. "Why ask Why? Forward Causal Inference and Reverse Causal Questions," NBER Working Papers 19614, National Bureau of Economic Research, Inc.
    5. Leeb, Hannes & Pötscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(1), pages 21-59, February.
    6. Brian Fabo & Martina Jancokova & Elisabeth Kempf & Lubos Pastor, 2020. "Fifty Shades of QE: Conflicts of Interest in Economic Research," Working Papers 2020-128, Becker Friedman Institute for Research In Economics.
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    Cited by:

    1. Jakub Rybacki & Dobromił Serwa, 2021. "What Makes a Successful Scientist in a Central Bank? Evidence From the RePEc Database," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(3), pages 331-357, September.

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    More about this item

    Keywords

    Researcher bias; Central banks;

    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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