Data · dataset · 2024
Replication Data for "Do employers care about past mobility? A field experiment examining hiring preferences in technology and non-technology jobs"
Listed in Borealis
This dataset provides the data and scripts necessary to replicate the figures and tables for the paper “Do employers care about past mobility?
Description
A field experiment examining hiring preferences in technology and non-technology jobs” by Matissa Hollister, Nicole Denier, and Xavier St-Denis. The Master do-file runs the data analysis and calls the other do-files.
After the Master file is run, the figures can be created in R by running the R scripts. Paper
Read the rest (4 more)
Abstract
Research in previous decades found that employers imposed penalties on job applicants with a past history of frequent moves across employers, and yet mobility across employers is more common in today’s economy and perhaps even a valuable career strategy. While popular discourse and some academic literature has portrayed highly mobile careers as widespread and broadly accepted, other studies have suggested that such careers may only thrive in specific pockets of the labor market, particularly high-technology jobs.
We conducted a field experiment in the United States to assess employer responses to resumes with three levels of past mobility. We found significant variation in employer mobility preferences, with jobs in human resources, financial reporting, marketing, and IT penalizing high-mobility applicants. In contrast, very stable work histories were penalized when hiring software testers.
Counter to expectations, high-technology employers did not broadly embrace mobility. These findings suggest that employers follow occupation-specific mobility expectations, and as a consequence must balance competing mobility orientations within their workforce. Workers, meanwhile, must face the challenges of navigating a precarious labor market while also being mindful of the impact that their cumulative mobility may have on future job opportunities.
Links
Where it is published
- Dataverse dataset page borealisdata.ca/dataset.xhtml?persistentId=doi%3A10.5683%2FSP3%2F6U8BKC ↗
landing page · from borealisdata ca
- DOI doi.org/10.5683/sp3/6u8bkc ↗
DOI / persistent id · from borealisdata ca
Catalogue records · 1
- Dataverse API borealisdata.ca/api/datasets/:persistentId/?persistentId=doi%3A10.5683%2FSP3%2… ↗
metadata API · from borealisdata ca
Topics
- Stated by source
- Business and Management · Social Sciences
- From keywords
- Economics & Finance · Social Science
- Inferred from text
- Econometrics 74%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Borealis | doi:10.5683/SP3/6U8BKC | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3802 | enrichment · borealisdata ca | taxonomy-embedding@1.1.0 | title+keywords+description (74%) |
| concepts[field].dataverse_subject:business-and-management | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].dataverse_subject:social-sciences | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| created_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| description | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /description |
| publication_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| title | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /name |
| updated_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| version_label | source · borealisdata ca | connector:borealisdata_ca@1.0.0 |