Labor Demand for Workers with a Criminal Conviction

Last registered on October 12, 2022
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Pre-Trial

Trial Information

General Information

Title
Labor Demand for Workers with a Criminal Conviction
RCT ID
AEARCTR-0005200
Initial registration date
December 23, 2019

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
January 03, 2020, 4:37 PM EST

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

Last updated
October 12, 2022, 2:02 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country
United States of America
Region

Primary Investigator

Name
Will Dobbie
Affiliation
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Zoë Cullen
PI Affiliation
Harvard Business School
Contact Investigator
PI Name
Mitchell Hoffman
PI Affiliation
Rotman School of Management, University of Toronto
Contact Investigator

Additional Trial Information

Status
Completed
Start date
2019-11-01
End date
2022-10-01
Keywords
Crime, Violence, & Conflict, Firms & Productivity, Labor
Additional Keywords
Labor Demand, Labor Discrimination, Criminal Law, Field Experiments
JEL code(s)
C93; J23; J71; K14
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We employ a randomized discrete choice experiment on a large on-demand staffing platform to estimate the labor demand for workers with a past criminal conviction (WCCs) under different policies and market conditions. Employers using the platform will have the option to have WCCs assigned to their vacancies at a randomly chosen wage subsidy, both with and without the option of crime and safety insurance and increased performance screening, and under different hypothetical labor market conditions. Employer choices at different wage subsidies will yield willingness to pay (WTP) estimates for this population of jobseekers under different counterfactual policies. These estimates will also allow us to estimate a labor demand function.
External Link(s)

Registration Citation

Citation
Cullen, Zoë, Will Dobbie and Mitchell Hoffman. 2022. "Labor Demand for Workers with a Criminal Conviction." AEA RCT Registry. October 12. https://doi.org/10.1257/rct.5200-2.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2020-01-02
Intervention End Date
2020-10-01

Primary Outcomes

Primary Outcomes (end points)
Employers’ choices over whether to have workers with a criminal record assigned to their vacancies at randomly chosen wage subsidies.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will recruit participants through the online platform’s account managers.

In the survey experiment, we ask firms about their interest in hiring individuals with a criminal record. We cross randomize values of each of the following dimensions:

• Wage discount
• Level of commercial crime insurance
• Number of positive past performance scores on the platform
• Hypothetical local unemployment rate
• Years since the most recent criminal act

The survey is incentive-compatible because subjects are informed that choices will affect the workers assigned to their jobs.
Experimental Design Details
Randomization Method
The randomization will be conducted using a computer random number generator.
Randomization Unit
We will randomize at the level of the firm, where all managers from the same firm will be randomized into the same group.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
The survey will be administered to approximately 9,000 individuals at 7,600 firms. We will cluster at the firm level (where there are several managers from the same firm). Based on previous response rates to the online platform’s surveys, we expect between 760 and 2,000 firms to respond.
Sample size: planned number of observations
See above.
Sample size (or number of clusters) by treatment arms
We are cross randomizing all parameter values equally allocating firms to each value listed for each parameter.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Harvard University-Area Committee on the Use of Human Subjects
IRB Approval Date
2019-06-30
IRB Approval Number
IRB19-1079
Analysis Plan

Analysis Plan Documents

WCC_PAP_23Dec2019

MD5: 1203f84ce5f10eb36c3968d77760c530

SHA1: 9e704a18a2d2eb854ab93d25a57d5f60958fdfb0

Uploaded At: December 23, 2019

WCC_PAP_20Mar2020.pdf

MD5: da5c76ef50c1b7002a055adc265cab29

SHA1: bd30879cbfb0e0da8b00089c52c05ffd32ac472d

Uploaded At: March 20, 2020

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
April 11, 2020, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
April 11, 2020, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
913 businesses
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
1,095 hiring managers
Final Sample Size (or Number of Clusters) by Treatment Arms
234 managers asked questions about willingness to hire without wage subsidy, 204 asked questions about willingness to hire with 10% subsidy, 208 asked questions about willingness to hire with 25% subsidy, 215 asked questions about willingness to hire with 50% subsidy, and 234 asked questions about willingness to hire with 100% subsidy.
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Yes
Program Files URL
https://doi.org/10.7910/DVN/SDX3XM
Reports, Papers & Other Materials

Relevant Paper(s)

Abstract
We experimentally test several approaches to increasing the demand for workers with a criminal record on a nationwide staffing platform by addressing potential downside risk and productivity concerns. The staffing platform asked hiring managers to make a series of hypothetical hiring decisions that affected whether workers with a criminal record could accept their jobs in the future. We find that 39% of businesses in our sample are willing to work with individuals with a criminal record at baseline, which rises to over 50% when businesses are offered crime and safety insurance, a single performance review, or a limited background check covering just the past year. Wage subsidies can achieve similar increases but at a substantially higher cost. Based on our findings, the staffing platform relaxed the criminal background check requirement and offered crime and safety insurance to interested businesses.
Citation
Zoë Cullen, Will Dobbie, Mitchell Hoffman, Increasing the Demand for Workers with a Criminal Record, The Quarterly Journal of Economics, 2022;, qjac029, https://doi.org/10.1093/qje/qjac029
URL
https://doi.org/10.1093/qje/qjac029

Reports & Other Materials