Does automatic recommendations lead to better matching between job seekers and employers?

Understanding the search process of job seekers and employers is at the heart of labor economic research and policy. Still our understanding of the nature and consequences of job search is inadequate, mainly due to lack of data. Our project proposes to provide new empirical evidence on the search strategies of both job seekers and of recruiters in the Swedish labor market. This evidence will enhance our understanding of the information asymmetries at the root of search frictions.
We will leverage the opportunity offered by online job boards, which record search activities in detail. We will analyze matched online search activity data with administrative data from unemployment-employment registers. This will enable us to jointly observe search activity and core economic outcomes (wage, job duration) on large samples.
We will evaluate the impact of recommending new matches to job seekers and recruiters, using randomized controlled trials. This will allow us to test for the extent of geographical and skill mismatch in the labor market. We will also learn whether targeted information can be used to improve the matching efficiency.
Our results will guide policy-makers who design job boards and the unemployment insurance system. While online job portals have flourished in the recent years, we still know very little about the impact on unemployment duration and the quality of employment. This project will shed light on the most important information frictions and test improvements. We hope that our research will help to reduce frictional unemployment and to increase productivity through a reduction of mismatch in the labor market.