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Statistical Treatment Choice: An Application to Active Labour Market Programmes

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  • Markus Frölich

Abstract

Choosing among a number of available treatments the most suitable for a given subject is an issue of everyday concern. A physician has to choose an appropriate drug treatment or medical treatment for a given patient, based on a number of observed covariates X and prior experience. A case worker in an unemployment office has to choose among a variety of available active labour market programmes for unemployed job seekers. In this paper, two methodological advancements are developed: First, this methodology permits to combine a data set on previously treated individuals with a data set on new clients when the regressors available in these two data sets do not coincide. It thereby incorporates additional regressors on previously treated that are not available for the current clients. Such a situation often arises due to cost considerations, data confidentiality reasons or time delays in data availability. Second, statistical inference on the recommended treatment choice is analyzed and conveyed to the agent, physician or case worker in a comprehensible and transparent way. The implementation of this methodology in a pilot study in Switzerland for choosing among active labour market programmes (ALMP) for unemployed job seekers is described.

Suggested Citation

  • Markus Frölich, 2006. "Statistical Treatment Choice: An Application to Active Labour Market Programmes," University of St. Gallen Department of Economics working paper series 2006 2006-14, Department of Economics, University of St. Gallen.
    • Handle: RePEc:usg:dp2006:2006-14
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    1. repec:ces:ifodic:v:4:y:2006:i:2:p:14567510 is not listed on IDEAS
    2. Staghøj, Jonas & Svarer, Michael & Rosholm, Michael, 2007. "A Statistical Programme Assignment Model," IZA Discussion Papers 3165, Institute of Labor Economics (IZA).
    3. Stefanie Behncke & Markus Frölich & Michael Lechner, 2006. "Statistical Assistance for Programme Selection - For a Better Targeting of Active Labour Market Policies in Switzerland," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 4(02), pages 61-68, July.
    4. Stefanie Behncke & Markus Frölich & Michael Lechner, 2009. "Targeting Labour Market Programmes - Results from a Randomized Experiment," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 145(III), pages 221-268, September.
    5. Andersen, Signe Hald, 2011. "Exiting unemployment: How do program effects depend on individual coping strategies?," Journal of Economic Psychology, Elsevier, vol. 32(2), pages 248-258, March.
    6. Stefanie Behncke & Markus Frölich & Michael Lechner, 2006. "Aktive Arbeitsmarktpolitik in Deutschland und der Schweiz: eine Gegenüberstellung," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 75(3), pages 118-154.
    7. Stefanie Behncke & Markus Frölich & Michael Lechner, 2006. "Statistical Assistance for Programme Selection - For a Better Targeting of Active Labour Market Policies in Switzerland," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 4(2), pages 61-68, 07.

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    More about this item

    Keywords

    Statistical treatment rules; active labour market policies;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy

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