Code for: Search, Screening and Sorting

Principal Investigator(s): View help for Principal Investigator(s) Xiaoming Cai, Peking University; Pieter Gautier, VU University Amsterdam; Ronald Wolthoff, University of Toronto

Version: View help for Version V1

Name	File Type	Size	Last Modified
Calib.m	text/x-matlab	4.2 KB	03/29/2024 08:30:AM
FirmAlloc.m	text/x-objcsrc	595 bytes	07/28/2023 06:50:PM
NumericalProcedure.pdf	application/pdf	91.4 KB	04/01/2024 06:20:PM
R.m	text/x-matlab	266 bytes	07/28/2023 01:53:AM
S2firms.m	text/x-matlab	574 bytes	09/07/2023 10:36:PM
S2firmsOpt.m	text/x-matlab	285 bytes	07/29/2023 12:59:AM
S2firmsOptW1.m	text/x-matlab	221 bytes	07/28/2023 06:46:PM
S2firmsV.m	text/x-matlab	644 bytes	07/31/2023 07:15:PM
Smax.m	text/x-matlab	253 bytes	07/28/2023 10:14:PM
Sone.m	text/x-matlab	182 bytes	07/28/2023 02:06:AM

Project Description

Summary: We examine how search frictions impact labor market sorting by constructing a model consistent with recent evidence that employers collect a pool of applicants before interviewing a subset. We derive the necessary and sufficient conditions for sorting in both applications and matches. Positive sorting is obtained when production complementarities outweigh a force against sorting measured by a (novel) quality-quantity elasticity. Interestingly, the production complementarities needed for positive sorting depend on the population fraction of high-type workers and can be increasing in the number of inter-views. Our model shows how policies like Ban the Box can backfire because when attractive firms can no longer perfectly screen certain workers, they may discourage them from applying.

Scope of Project

Subject Terms: labor markets; employment; social reintegration

JEL Classification:
      D82 Asymmetric and Private Information; Mechanism Design
      D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      E24 Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

Geographic Coverage: United States

Universe: US labor force

Data Type(s): program source code

Methodology

Unit(s) of Observation: individuals

Related Publications

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Published Versions

V1 [2025-06-06]

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Dublin Core

DDI 2.5

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