Selection Neglect and Inaccurate Statistical Discrimination

Last registered on October 16, 2026

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Pre-Trial

Trial Information

General Information

Title

Selection Neglect and Inaccurate Statistical Discrimination

RCT ID

AEARCTR-0019920

Initial registration date

October 09, 2026

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

October 16, 2026, 2:12 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Name

Lingbo Huang

Affiliation

Shandong University

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

In development

Start date

2026-10-12

End date

2026-11-12

Keywords

Behavior, Lab

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Do decision-makers account for how people select into opportunities when evaluating members of different groups? In hiring, employers observe applicants rather than everyone who could have applied. Workers may apply based on private information about their suitability for a job. When this selection differs across groups, applying can reveal different information about an applicant’s likely productivity. This study asks whether employers overlook that information and consequently misjudge productivity differences between groups of applicants. It examines how these beliefs affect wage offers and whether making the implications of selection explicit improves judgments and decisions.

External Link(s)

Registration Citation

Citation

Huang, Lingbo. 2026. "Selection Neglect and Inaccurate Statistical Discrimination." AEA RCT Registry. October 16. https://doi.org/10.1257/rct.19920-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Employers (subjects) evaluate computerized job applicants from two color groups, making wage offers and reporting productivity beliefs. Six treatment arms vary the information employers receive about how workers select into the applicant pool: (1) Hidden — employers are not told the group-specific application rules; (2) Rule — employers are taught the application rule; (3) Display — same information as Rule, plus each applicant card explicitly displays what the applicant's application status implies about their private signal; (4) Posterior — same information environment as Rule, plus each card displays the correct Bayesian posterior probability of high productivity; (5) Negative Rule — employers are taught that selective-group workers apply only after a low private signal; (6) Negative Display — same as Negative Rule, with the low-signal implication of application explicitly displayed on each card.

Intervention Start Date

2026-10-12

Intervention End Date

2026-11-12

Primary Outcomes

Primary Outcomes (end points)

Belief selection weight, Wage premium

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

Laboratory experiment in which subjects act as employers evaluating computerized job applicants from two color groups. In the selective-application group, workers apply only after receiving a private signal — a high signal in the four positive-selection treatments, a low signal in the two negative-selection treatments; in the broad-application group, application is unrelated to the signal — so applying reveals different information about likely productivity across groups. Subjects are randomly assigned to one of six between-subject treatments (Hidden, Rule, Display, Posterior, Negative Rule, Negative Display) that vary what employers are told about the application rule and what each applicant card displays, then make wage offers and report productivity beliefs for a series of applicant cards. 360 subjects total, 60 per treatment.

Experimental Design Details

Not available

Randomization Method

Randomization done by computer. Subjects are randomly assigned to one of six treatments with balanced assignment (60 subjects per treatment). A separately permuted list assigns which color (blue/orange) follows the selective-application rule, balanced across participants. Candidate order, productivity draws, and payment draws use separate recorded random draws.

Randomization Unit

Individual (subject).

Was the treatment clustered?