A Bias of Screening

David Lagziel, Ehud Lehrer

Research output: Contribution to journalArticlepeer-review


This paper deals with the issue of screening. It focuses on a decision maker who, based on noisy unbiased assessments, screens elements from a general set. Our analysis shows that stricter screening not only reduces the number of accepted elements, but possibly reduces their average expected value. We provide a characterization for optimal threshold strategies for screening and also derive implications to cases where such screening strategies are suboptimal. We further provide various applications of our results to credit ratings, auctions, general trade, the Peter Principle, and affirmative action.
Original languageEnglish GB
Pages (from-to)343-356
Number of pages14
JournalAmerican Economic Review: Insights
Issue number3
StatePublished - 1 Dec 2019


  • Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
  • Auctions
  • Trade: General
  • Investment Banking; Venture Capital; Brokerage; Ratings and Ratings Agencies
  • Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination


Dive into the research topics of 'A Bias of Screening'. Together they form a unique fingerprint.

Cite this