Do the Long-term Unemployed Benefit from Automated Occupational Advice during Online Job Search?

• 成果类型: Article; Early Access
• 署名作者: Belot, Michele; Kircher, Philipp; Muller, Paul
• 署名单位: Cornell University; University of Edinburgh; Universite Catholique Louvain; Vrije Universiteit Amsterdam; Tinbergen Institute
• 刊物名称: ECONOMIC JOURNAL
• ISSN/ISSBN: 0013-0133
• DOI: 10.1093/ej/ueaf041
• 发表日期: 2025
• 关键词: market; seekers

摘要

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.