|
Field
Abstract
|
Before
The goal of our study is to causally estimate of the effects of noncompetes themselves on the employment outcomes of workers. To do this, we propose to run a large field experiment in which we occupy the role of the employer. As the employer we can randomly assign noncompetes (and various other treatment arms) and examine how the assignment of noncompetes affects individual willingness to accept a job offer. We can also examine subsequent employment outcomes for the workers, and even directly test the worker’s willingness to violate the noncompete by working with a second employer seeking to hire the workers.
|
After
The goal of our study is to causally estimate of the effects of noncompetes themselves on the employment outcomes of workers. To do this, we propose to run a large field experiment in which we occupy the role of the employer. As the employer we can randomly assign noncompetes and their salience, as well as wage offers, to examine how the assignment of noncompetes affects individual willingness to accept a job offer. We can also examine subsequent employment outcomes for the workers, and even directly test the worker’s willingness to violate the noncompete by working with a second employer seeking to hire the workers.
|
|
Field
Trial Start Date
|
Before
March 01, 2021
|
After
May 23, 2023
|
|
Field
Trial End Date
|
Before
June 01, 2022
|
After
November 01, 2023
|
|
Field
Last Published
|
Before
January 04, 2021 09:10 AM
|
After
May 22, 2023 10:02 PM
|
|
Field
Intervention (Public)
|
Before
We propose hiring professional HR workers, who will be tasked with reviewing and screening resumes. For HR workers who respond to our job ad, our experimental design involves two dimensions of randomization. Our first randomization relates to the job offer. The second randomization occurs after the worker has completed their work and we post reviews of the worker and job. We describe these more in the hidden fields in order to keep the interventions private from potential subjects.
|
After
We propose hiring professional HR workers, who will be tasked with reviewing and screening resumes. For HR workers who respond to our job ad, our experimental design involves three dimensions of randomization. In the job offer we will randomly assign the use of a noncompete, the salience of the noncompete, and wages. We describe these more in the hidden fields in order to keep the interventions private from potential subjects.
|
|
Field
Intervention Start Date
|
Before
March 01, 2021
|
After
May 23, 2023
|
|
Field
Intervention End Date
|
Before
June 01, 2021
|
After
November 01, 2023
|
|
Field
Primary Outcomes (End Points)
|
Before
The outcomes we aim to measure from the first randomization are below:
--Job Acceptance and Wages: We then measure who accepts the job offer. For workers who reject the initial offer, we engage in a standard negotiation procedure, probing the worker's willingness to accept higher wages in return for signing the noncompete. This randomization permits us to infer the effects of noncompete agreements on the composition of hired workers, the job acceptance rate, the salary demands and bargaining patterns of workers, and the length of employer search.
-- Performance. For workers who accept the job, we will send recruiting work and instructions to review sixteen resumes or job applications. We will measure who complies with these instructions for all workers as a measure of their quality.
The outcomes we aim to measure from the first and second randomization are below:
-Other Employment Experiences and Earnings: During the prohibited noncompete period (6 months), we will also gather information from the platform on other work that the worker has completed (i.e., number of other employers) and their cumulative earnings. We will supplement this information with any new information on their LinkedIn profile related to employment.
-Testing Willingness to Violate the Noncompete: During the prohibited noncompete period (6 months), we will assume the role of a poaching firm and reach out to the workers we hired previously. We will make them a job offer to measure if (a) those bound by noncompetes are less willing to accept our offer, and (b) whether they require higher wages to violate the provision.
|
After
The outcomes we aim to measure from the first randomization are below:
--Job Acceptance and Wages: We then measure who accepts the job offer. The randomization permits us to infer the effects of noncompete agreements on the composition of hired workers, the job acceptance rate, compensating differentials for noncompetes, and the length of employer search.
-- Performance. For workers who accept the job, we will send recruiting work and instructions to review sixteen resumes or job applications. We will measure who complies with these instructions for all workers as a measure of their quality. Exploiting the salience intervention allows us to address selection into second-stage performance.
Other outcomes we aim to measure are below:
-Other Employment Experiences and Earnings: During the prohibited noncompete period (6 months), we will also gather information from the platform on other work that the worker has completed (i.e., number of other employers) and their cumulative earnings. We will supplement this information with any new information on their LinkedIn profile related to employment.
-Testing Willingness to Violate the Noncompete: During the prohibited noncompete period (6 months), we will assume the role of a poaching firm and reach out to the workers we hired previously. We will make them a job offer to measure if (a) those bound by noncompetes are less willing to accept our offer, and (b) whether they require higher wages to violate the provision.
|
|
Field
Experimental Design (Public)
|
Before
For HR workers who respond to our job ad, our experimental design involves two dimensions of randomization. Our first randomization relates to the job offer. The second randomization occurs after the worker has completed their work and we post reviews of the worker and job. We describe these more in the hidden fields in order to keep the interventions private from potential subjects.
|
After
For HR workers who respond to our job ad, our experimental design involves three dimensions of randomization related to the job offer. We describe these more in the hidden fields in order to keep the interventions private from potential subjects.
|
|
Field
Planned Number of Clusters
|
Before
We expect to make about 2080 job offers. This is a high number in case they are declined.
|
After
We expect to hire approximately 2080 workers. Anticipating a 20-25% acceptance rate, this is approximately 8-10k workers in the initial outreach.
|
|
Field
Planned Number of Observations
|
Before
2080 job offers to 2080 individuals.
|
After
It depends on the stage of the survey. At the outset, we hope to hire 2080 individuals, out of approximately 10k job offers.
|
|
Field
Sample size (or number of clusters) by treatment arms
|
Before
240 offers to 240 individuals in each of the 2 control conditions without noncompetes.
400 offers to 400 individuals in each of the 4 treatment conditions with noncompetes.
|
After
In the second stage, we expect to have:
240 individuals in each of the 2 control conditions without noncompetes.
400 individuals in each of the 4 treatment conditions with noncompetes.
|
|
Field
Power calculation: Minimum Detectable Effect Size for Main Outcomes
|
Before
The power calculations are complicated by the fact that the first stage outcomes and second stage outcomes are linked. In the first stage we examine who accepts the job offer, and in the second stage we examine the effect of noncompetes among those who have accepted the job offer. If noncompetes make it exceedingly unlikely to accept a job offer, our treatment alone will affect our power in the second stage. Accordingly, our power calculations were done via backward induction from the second stage to the first stage.
We do not have precise information on several key variables to perform a power analysis for all of them. But based on prior experience and research we expect a 25% job acceptance rate in the first stage in the control group and a 15% job acceptance rate in the treatment groups. For the second stage, we expect a 70% job acceptance rate for the control groups and a 35% acceptance rate for the treatment groups. The upper envelope of our power calculations imply that we need to solicit approximately 400 individuals in each of our four treatment cells, and 240 individuals in the control cells to have power of at least 80% in both stages.
|
After
The power calculations are complicated by the fact that the first stage outcomes and second stage outcomes are linked. In the first stage we examine who accepts the job offer, and in the second stage we examine the effect of noncompetes among those who have accepted the job offer. If noncompetes make it exceedingly unlikely to accept a job offer, our treatment alone will affect our power in the second stage. Accordingly, our power calculations were done via backward induction from the second stage to the first stage.
We do not have precise information on several key variables to perform a power analysis for all of them. But based on prior experience and research we expect a 25% job acceptance rate in the first stage in the control group and a 15% job acceptance rate in the treatment groups. For the second stage, we expect a 70% job acceptance rate for the control groups and a 35% acceptance rate for the treatment groups. The upper envelope of our power calculations imply that we need to hire approximately 400 individuals in each of our four treatment cells, and 240 individuals in the control cells to have power of at least 80% in both stages.
|
|
Field
Keyword(s)
|
Before
Firms And Productivity, Labor, Other
|
After
Firms And Productivity, Labor, Other
|
|
Field
Intervention (Hidden)
|
Before
We propose hiring professional HR workers, who will be tasked with reviewing and screening resumes. For HR workers who respond to our job ad, our experimental design involves two dimensions of randomization. For each randomization, we describe the treatment and the outcomes we seek to link to the randomized treatment.
Our first randomization relates to the job offer. For all workers in our study, we would propose hiring them at the posted hourly rate on their online recruiter profile to complete a fixed set of resume-screening tasks. This offer would contain one of three randomized conditions (two treatment conditions and one control):
-Offer Control: We offer the worker an employment contract including a nondisclosure agreement (NDA). No noncompete agreement would be included.
-Offer Treatment 1 ("Full Transparency"): The worker receives an employment contract including an NDA and (separately) a clearly labeled noncompete agreement in a second document. We refer to this as our "full transparency" condition because it requires the worker to sign the employment contract and noncompete agreement separately.
-Offer Treatment 2 ("Hidden Noncompete"): The worker receives an employment contract that contains (in one document) both the NDA and the noncompete provisions. This is less transparent treatment as the noncompete is hidden inside a larger contract, requiring the worker to notice it.
The second randomization occurs after the worker has completed their work. At this time, our recruiting platform will ask us to leave a public review of each worker. We will leave a review for all workers. Our publicly-facing reviews will contain one of two random treatments.
-Review Treatment A: One group will receive a review that says nothing about noncompete agreements.
-Review Treatment B: The second group will receive a review that explicitly states the worker's noncompete status. If the worker has signed a noncompete with us, we will state this (and include the expiration date). If the worker has not signed a non-compete agreement, we will state this.
|
After
We propose hiring professional HR workers, who will be tasked with reviewing and screening resumes. For HR workers who respond to our job ad, our experimental design involves three dimensions of randomization. For each randomization, we describe the treatment and the outcomes we seek to link to the randomized treatment.
Our first randomization relates to the use of a noncompete in the job offer. The second randomization is how salient the noncompete is in the onboarding materials. And the third randomization is the wage offer. We describe the six treatment and control groups below.
1. No Noncompete, Low Wage: We offer the worker an employment contract including a nondisclosure agreement (NDA). No noncompete agreement would be included. The offered wage would be the 25th percentile of the wage distribution, which is approximately $20/hr.
2. No Noncompete, High Wage: Same as condition 1, except the offered waged is the 75th percentile of the wage distribution, approximately $40/hr.
3. Noncompete, Full Transparency, Low Wage: The worker receives an employment contract including an NDA and (separately) a clearly labeled noncompete agreement in a standalone document. The offered wage will be the 25th percentile of the wage distribution (~$20/hr). This condition includes mentioning the noncompete in the initial job post. We refer to this as our "full transparency" condition because there is no way the worker can sign the employment agreement without seeing the noncompete.
4. Noncompete, Full Transparency, High Wage: Same as 3, but with the high wage (~75th percentile of wage distribution, $40/hr).
5. Noncompete, Low Transparency, Low Wage: Same as 2, except the worker receives an employment contract that contains (in one document) both the NDA and the noncompete provisions. This is less transparent treatment as the noncompete is inside a larger contract, requiring the worker to notice it. The worker does not need to sign the noncompete separately.
6. Noncompete, Low Transparency, High Wage: Same as 5, except for the high wage.
|
|
Field
Building on Existing Work
|
Before
|
After
No
|