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Statistical Uncertainty in the Ranking of Journals and Universities

Author

Listed:
  • Magne Mogstad
  • Joseph P. Romano
  • Azeem Shaikh
  • Daniel Wilhelm

Abstract

Economists are obsessed with rankings of institutions, journals, or scholars according to the value of some feature of interest. These rankings are invariably computed using estimates rather than the true values of such features. As a result, there may be considerable uncertainty concerning the ranks. In this paper, we consider the problem of accounting for such uncertainty by constructing confidence sets for the ranks. We consider both the problem of constructing marginal confidence sets for the rank of, say, a particular journal as well as simultaneous confidence sets for the ranks of all journals. We apply these confidence sets to draw inferences about uncertainty in the ranking of economics journals and universities by impact factors.

Suggested Citation

  • Magne Mogstad & Joseph P. Romano & Azeem Shaikh & Daniel Wilhelm, 2022. "Statistical Uncertainty in the Ranking of Journals and Universities," NBER Working Papers 29768, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29768
    Note: LS TWP
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    Cited by:

    1. Johannes König & David I. Stern & Richard S.J. Tol, 2022. "Confidence Intervals for Recursive Journal Impact Factors," Tinbergen Institute Discussion Papers 22-038/III, Tinbergen Institute.
    2. Charemza, Wojciech & Lewandowski, Michał & Woźny, Łukasz, 2024. "On journal rankings and researchers' abilities," Journal of Informetrics, Elsevier, vol. 18(3).
    3. Fulya Y. Ersoy & Jennifer Pate, 2023. "Invisible hurdles: Gender and institutional differences in the evaluation of economics papers," Economic Inquiry, Western Economic Association International, vol. 61(4), pages 777-797, October.

    More about this item

    JEL classification:

    • A0 - General Economics and Teaching - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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