Statistical Uncertainty in the Ranking of Journals and Universities

Magne Mogstad, Joseph P. Romano, Azeem Shaikh and Daniel Wilhelm

No 29768, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: A0 C12 (search for similar items in EconPapers)
Date: 2022-02
New Economics Papers: this item is included in nep-ban, nep-ecm, nep-ore and nep-sog
Note: LS TWP
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Citations: View citations in EconPapers (1)

Published as Magne Mogstad & Joseph Romano & Azeem Shaikh & Daniel Wilhelm, 2022. "Statistical Uncertainty in the Ranking of Journals and Universities," AEA Papers and Proceedings, vol 112, pages 630-634.

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