Inference for Ranks with Applications to Mobility across Neighborhoods and Academic Achievement across Countries
Magne Mogstad,
Joseph Romano (),
Azeem Shaikh and
Daniel Wilhelm
Additional contact information
Joseph Romano: Stanford University
No 2020-16, Working Papers from Becker Friedman Institute for Research In Economics
Abstract:
It is often desired to rank different populations according to the value of some feature of each population. For example, it may be desired to rank neighborhoods according to some measure of intergenerational mobility or countries according to some measure of academic achievement. These rankings are invariably computed using estimates rather than the true values of these features. As a result, there may be considerable uncertainty concerning the rank of each population. In this paper, we consider the problem of accounting for such uncertainty by constructing confidence sets for the rank of each population. We consider both the problem of constructing marginal confidence sets for the rank of a particular population as well as simultaneous confidence sets for the ranks of all populations. We show how to construct such confidence sets under weak assumptions. An important feature of all of our constructions is that they remain computationally feasible even when the number of populations is very large. We apply our theoretical results to re-examine the rankings of both neighborhoods in the United States in terms of intergenerational mobility and developed countries in terms of academic achievement. The conclusions about which countries do best and worst at reading, math, and science are fairly robust to accounting for uncertainty. By comparison, several celebrated findings about intergenerational mobility in the United states are not robust to taking uncertainty into account.
Keywords: Condence sets; Directional errors; Familywise error rate; Intergenerational mobility; Multiple testing; PISA; Ranks (search for similar items in EconPapers)
JEL-codes: C12 C14 D31 I20 J62 (search for similar items in EconPapers)
Pages: 80 pages
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)
Downloads: (external link)
https://repec.bfi.uchicago.edu/RePEc/pdfs/BFI_WP_202016.pdf (application/pdf)
Related works:
Journal Article: Inference for Ranks with Applications to Mobility across Neighbourhoods and Academic Achievement across Countries (2024) 
Working Paper: Inference for ranks with applications to mobility across neighborhoods and academic achievement across countries (2023) 
Working Paper: Inference for ranks with applications to mobility across neighborhoods and academic achievement across countries (2021) 
Working Paper: Inference for Ranks with Applications to Mobility across Neighborhoods and Academic Achievement across Countries (2020) 
Working Paper: Inference for ranks with applications to mobility across neighborhoods and academic achievement across countries (2020) 
Working Paper: Inference for Ranks with Applications to Mobility across Neighborhoods and Academic Achievement across Countries (2020) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bfi:wpaper:2020-16
Access Statistics for this paper
More papers in Working Papers from Becker Friedman Institute for Research In Economics Contact information at EDIRC.
Bibliographic data for series maintained by Toni Shears ( this e-mail address is bad, please contact ).