Statistical profiling in public employment services
Profiling tools help to deliver employment services more efficiently. They can ensure that more costly, intensive services are targeted at jobseekers most at risk of becoming long term unemployed. Moreover, the detailed information on the employment barriers facing jobseekers obtained through the profiling process can be used to tailor services more closely to their individual needs. While other forms of profiling exist, the focus is on statistical profiling, which makes use of statistical models to predict jobseekers’ likelihood of becoming long-term unemployed. An overview on profiling tools currently used throughout the OECD is presented, considerations for the development of such tools, and some insights into the latest developments such as using “click data” on job searches and advanced machine learning techniques. Also discussed are the limitations of statistical profiling tools and options for policymakers on how to address those in the development and implementation of statistical profiling tools.
|Year of publication||Feb, 2019|
|Publisher||Organisation for Economic Cooperation and Development (OECD), Paris|
|Website / Document||Visit|
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