Do the Long-term Unemployed Benefit from Automated Occupational Advice during Online Job Search
Bibliographic Data
| ID | 9705049 |
|---|---|
| Authors | Michèle Belot (0000-0002-6953-1200, Cornell University), Philipp Kircher (Cornell University), Paul Müller (0000-0002-5734-3130, VU Amsterdam & Tinbergen Institute) |
| Year | 2025 |
| Publication date | 2025-05-30 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The Economic Journal (JOURNAL) |
| Journal identifiers | ISSN: 0013-0133 • E-ISSN: 1468-0297 |
| Publisher | Oxford University Press (PUBLISHER • GB) |
| DOI | 10.1093/ej/ueaf041 |
| OpenAlex | W4410888423 |
| Language | EN |
| References cited | 17 |
In a randomised field experiment, we provide suggestions about suitable occupations to long-term unemployed job seekers. The suggestions are automatically generated, integrated in an online job search platform and fed into actual search queries. Effects on ‘reaching a cumulative earnings threshold’ and ‘finding a stable job’ are positive, large and are more pronounced for those who are longer unemployed. Treated individuals include more occupations in their search and find more jobs in recommended occupations
Advice (programming · Business · Economic growth · Economics · Labour economics · Term (time · Unemployment · Computer Science · COVID-19 Pandemic Impacts · Digital Economy and Work Transformation · Employment and Welfare Studies
| Citation velocity | historical |
|---|---|
| Highly cited | No |