Labor Demand for Workers with a Criminal Conviction
Last registered on March 20, 2020


Trial Information
General Information
Labor Demand for Workers with a Criminal Conviction
Initial registration date
December 23, 2019
Last updated
March 20, 2020 5:38 PM EDT
Primary Investigator
Other Primary Investigator(s)
PI Affiliation
Rotman School of Management, University of Toronto
PI Affiliation
Harvard Business School
Additional Trial Information
In development
Start date
End date
Secondary IDs
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
Cullen, Zoë, Will Dobbie and Mitchell Hoffman. 2020. "Labor Demand for Workers with a Criminal Conviction." AEA RCT Registry. March 20.
Sponsors & Partners

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Experimental Details
Intervention Start Date
Intervention End Date
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
Not available
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?
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)
IRB Name
Harvard University-Area Committee on the Use of Human Subjects
IRB Approval Date
IRB Approval Number
Analysis Plan

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