Valentine Njike, University at Albany School of Public Health

The purpose of this presentation is to investigate possible methods of identifying unemployment insurance beneficiaries who are dislocated workers in order to target timely, more intensive services to these beneficiaries. There will be a discussion of statistical tools developed to separate those beneficiaries at risk (i.e., dislocated workers or people most likely to exhaust their benefits) from the beneficiaries who are more likely to become re-employed shortly. Among these tools is risk assessment. Risk assessment is a technique used with administrative data on beneficiaries to find a combination of primarily categorical parameters (profiles) that will flag those individuals more likely to exhaust benefits (26 weeks of benefits is the maximum in New York State). Algorithms to identify the combination of variables that is most effective in separating the at- risk group from the group not at risk will be discussed.