Statistical uncertainty in the ranking of journals and universities - Magne Mogstad; Joseph P. Romano; Azeem M. Shaikh; Daniel Wilhelm (Centre for Microdata Methods and Practice (cemmap), 2022)
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. The purpose of this paper is to review the approach to the construction of such confidence sets by Mogstad et al. (2020) and then apply their methods to rankings of economics journals and universities by impact factors.
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