Employer Preferences for Local vs. Non-Local Workers: A Resume Audit

We systematically vary the distance between a fictitious job applicant and the labor market the applicant searches for jobs in.

2022-07-25

2023-07-31

The primary outcome of interest is the job application outcome.

Generally, job application outcomes are the employer’s contacting the candidate for interview- a categorical variable we define with four categories. One implies the employer is keen to interview the candidate, two implies a callback with ambiguity such as a request for more information, zero implies no response or no contact of the candidate from the employer, and -1 implies the employer contacted the candidate to reject or decline their application. This variable is constructed by monitoring the candidates phone voicemail, text message, job posting site messaging inboxes, and email inboxes.

Secondary job application outcomes which we collect and may consider in our analysis includes duration to callback (a truncated time variable), means of contact (text message, voicemail message, direct message, or email), and strength of contact (neutral or strong). We also record whether the contact content acknowledges the applicants' location relative to the jobsite location or asks about whether they are moving or are willing to move.

The duration to callback is a truncated time variable constructed by counting the time between when the application was sent and when the employer replied (if they replied). The means of contact is how the employer/hiring manager contacted the fictitious candidate: text message, voicemail message, direct message, or email. Strength of contact (neutral or strong) is implied from text analysis of message content- for instance, messages which ask for a return call to set up an interview may be interpreted as neutral, whereas messages which offers the candidate the job or invites them to a training may be interpreted as strong. The location acknowledgement variable is a binary variable that takes the value of one when the contact content mentions or acknowledges the worker's location, asks whether or not they are moving, or asks if they are willing to move.

In this resume audit, we consider the effect of the distance between fictitious applicants and job opportunities on the likelihood the employer contacts the applicant back for an interview for the job.

To do this we randomly selected residential addresses in random mid-large US cities (more than 100,000 people) and then randomly select zip codes for the fictitious applicants to apply for jobs in within three distance categories- local/close, local/far commutes, and non-local/requires migration. Our resumes were randomly constructed using the text randomizer from Lahey and Beasley (2009) and our fictitious applicants include randomly selected names which are implied female and implied male from younger and middle aged birth generations in the USA. We consider several occupational titles/job titles and several US cities.

With the assistance of a team of research assistants, we apply to open job postings available on publically available job boards, recording the date, time, and the text from the job posting. We then will monitor the fictitious candidates' email inboxes, voicemail boxes, job site direct message chats, and text messages and record which employers contact them for an interview.

We seek to compare callback rates for candidates by distance, gender, gender and distance, career stage cohort, career stage cohort and gender, and, if possible, age cohort, gender, and distance.

Randomization occurs by a computer in several aspects of the project. For instance, we randomly select items for the fictitious worker resume construction employing the process/program developed by Lahey and Beasley 2009. Worker names, addresses (within random cities), and experience profiles were randomly selected. Then, when applying for jobs, we randomly select the zip codes to search for jobs in within each of the three distance criteria and randomly select which jobs to apply for on each of the job websites (position of the posting on the page).

Individual

No

1

10,000 job applications

1/3 of applications will be close, 1/3 will be middle distance, 1/3 far (migration category)

Unit: firm contact/callback incidence/percentage (15% on average in the pilot- conduct late summer, early Fall 2022); Pilot Sample Standard deviation: .12; Alpha=.05, two sided hypothesis tests, thus with probability .95 we don't reject the null when the null is true and with probability .05 we commit a type I error or a false positive and reject the null when the null is true; Power: 80%, so there is a 20% chance of a type II error- or failing to reject the false null hypothesis of no effect of distance; The Minimum detectable effect size with that sample is: .02 or 2 percentage points difference between close and far candidates, put another way we can detect a 13% reduction in firm contact rates with our proposed sample size.