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early Identification of Long Term Unemployed

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  • Clive Payne and Joan Payne

Abstract

The paper describes a fesibility study carried out for the Employment Service and the Department for Education and Employment in Britain to identify those individuals who, when first registering as umemployed, are likely to be at high rish of becoming long-term unemployed. A simple preidction scheme is developed that can be easily administered by officials who deal with unemployment registration. The scheme is based on a logistic model for the odds of long-term employment which is clibrated and cross-validated on the ntional cohort study containing data on employment histories. The paper concludes with discussion of the effects of the decision rules that are chosen and of the prediction errors that arise when the prediction scheme is applied in pratice.

Suggested Citation

  • Clive Payne and Joan Payne, 2000. "early Identification of Long Term Unemployed," PSI Research Discussion Series 4, Policy Studies Institute, UK.
    • Handle: RePEc:psi:resdis:4
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    File URL: http://www.psi.org.uk/publications/Research%20Discussion%20Series/pdffiles/Research_Discussion_Paper_4.pdf
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    Cited by:

    1. Sidelmann, Peter & Bason, Christian & Köllner, Angela, 2001. "Früherkennung von Personen mit hohem Arbeitslosigkeitsrisiko : Ergebnisse einer EU-Studie (Early recognition of people with a high risk of unemployment : results of an EU study)," Mitteilungen aus der Arbeitsmarkt- und Berufsforschung, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 34(4), pages 554-566.
    2. Hock-Eam Lim, 2010. "Predicting Low Employability Graduates: The Case Of Universiti Utara Malaysia," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 55(03), pages 523-535.
    3. Sidelmann, Peter & Bason, Christian & Köllner, Angela, 2001. "Früherkennung von Personen mit hohem Arbeitslosigkeitsrisiko : Ergebnisse einer EU-Studie (Early recognition of people with a high risk of unemployment : results of an EU study)," Mitteilungen aus der Arbeitsmarkt- und Berufsforschung, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 34(4), pages 554-566.
    4. Rosna Awang-Hashim & Hock Eam Lim & Bidin Yatim & Tengku Faekah Tengku Ariffin & Ainol Madziah Zubairi & Haniza Yon & Omar Osman, 2015. "Estimating A Prediction Model For The Early Identification Of Low Employability Graduates In Malaysia," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 60(04), pages 1-22.

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