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Non-traditional work arrangements: stepping stones or dead ends?
Last registered on March 16, 2018


Trial Information
General Information
Non-traditional work arrangements: stepping stones or dead ends?
Initial registration date
March 16, 2018
Last updated
March 16, 2018 11:53 AM EDT
Primary Investigator
Institute for labor market and education policy evaluation
Other Primary Investigator(s)
PI Affiliation
Institute for labor market and education policy evaluation
Additional Trial Information
In development
Start date
End date
Secondary IDs
The aim of the study is to examine whether work-experience from the non-traditional labor market (or the gig economy) is valuable in terms of finding employment in the regular labor market. We intend to study this question through a correspondence study conducted in the Swedish labor market, where we send out fictitious applications to companies with open vacancies in entry-level jobs. By randomly changing the job seekers' labor market experience we can compare the number of positive responses from employers for applicants with (i) experience from a job in the non-traditional labor market (the so-called gig-economy) (ii) experience from a (similar) job in the traditional labor market (iii) no labor market experience. This method has been successfully used to study, among other things, the effect of long-term unemployment and ethnic hiring discrimination.
External Link(s)
Registration Citation
Adermon, Adrian and Lena Hensvik. 2018. "Non-traditional work arrangements: stepping stones or dead ends?." AEA RCT Registry. March 16. https://doi.org/10.1257/rct.2766-1.0.
Former Citation
Adermon, Adrian, Lena Hensvik and Lena Hensvik. 2018. "Non-traditional work arrangements: stepping stones or dead ends?." AEA RCT Registry. March 16. http://www.socialscienceregistry.org/trials/2766/history/26764.
Experimental Details
To examine our main hypothesis, the impact of non-traditional work experience, we will send fictious job applications to employers who are looking to hire at the Swedish job board Platsbanken. We randomly assign the fictitious job applicants into 8-15 months of (i) non-traditional work experience in the gig-economy (treatment) (ii) traditional work experience (control I) or (iii) unemployment (control II). We would like the job tasks in the treatment group (i.e. in the non-traditional job) to appear as similar as possible to the job-tasks in the traditional job. Therefore, we will compare a gig-job where the task is to deliver food from restaurants to customers to a traditional job of delivering mail. In addition, we randomly assign applicants to one of four identities, where two have an Arabic-sounding name and two have a Swedish-sounding name. The names are selected based on official statistics over the most popular names in Sweden.

Since we are interested in the value of non-traditional work experience for entry into the traditional labor market, the job applications will be designed for young workers who search for a job approximately a year upon high school graduation. All four fictitious applicants are male and born in 1998. The reason for focusing on males is that these comprise the majority of the workers in the gig-economy. To get a reasonably high callback rate, the applications will be designed to signal a relatively well-qualified applicant (for it's age). To this aim, place of residence and high school will be chosen to signal a middle-class applicant with a completed high school degree from a vocational track aimed for the service sector. In addition, we state in the resume that the applicant has a drivers license. In the resumes we also include 12 weeks of job training in a traditional job, which is the mandated amount of job training in vocational high school tracks.

To achieve the desired sample size we send three applications to each posted vacancy in the sampling frame. To this end, we generate four applicant identities, which each comprise a name, an email address, and a phone number. The applications will be submitted with a lag of one day between them.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
The main variable of interest is an indicator taking the value one if the fictitious job applicant receives a call-back from the employer.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The correspondence study will be conducted in the three largest cities of Sweden: Stockholm, Goteborg and Malmo. The reason for focusing on these regional labor markets is that gig-economy jobs are represented there. The population consists of all employers that post vacancies at Sweden's largest job board Platsbanken in the geographic regions during the study period. We restrict the population to employers posting low-skilled jobs, i.e. jobs without requirements of previous experience or post-secondary education. The restriction of the target population to employers with low-skilled vacancies is motivated by our research question, namely if non-traditional jobs can serve as a stepping stone to entry-level jobs in the traditional labor market. We restrict the sample to employers who have included an email- address in the job ad. If the employer has its own application procedure on their external webpage, we will not include this vacancy in the sampling frame.
Experimental Design Details
Randomization Method
We will send three unique fictitious applications to each posted vacancy in the sample. For each application we will randomize (without replacement) fictious applicants into : (i) treatment or one of the two controls (see above under intervention), and (ii) one of four applicant identities. Randomization will be performed by a computer program.
Randomization Unit
Since each vacancy receives all three versions of the main treatment (labor market history), this treatment is stratified on the vacancy level. The secondary treatment, Swedish- or Arabic-sounding name, is also stratified on the vacancy level, since each vacancy will receive at least one application with each treatment.
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
2,700 vacancies
Sample size: planned number of observations
8,000 applications
Sample size (or number of clusters) by treatment arms
2,700 applications randomized into non-traditional work experience, 2,700 applications randomized into traditional work experience and 2,700 applications randomized into unemployment. About 4,000 applications randomized into Swedish-sounding names and 4,000 applications randomized into Arabic-sounding names.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We estimate that we need to send about 8,000 applications. This number is based on the assumption that the call-back rate is 20 percent in the control group (based on results in results Eriksson and Roth (2014)) and that we want to be able to detect effect sizes of at least 2 percentage points with 80 percent statistical strength in hypotest testing with a critical limit of five percent. See the Analysis Plan for details about the power calculations.
IRB Name
Regionala Etikprövningsnämnden i Uppsala
IRB Approval Date
IRB Approval Number
Analysis Plan

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