Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/37434
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dc.contributor.authorLechner, Michaelen_US
dc.contributor.authorWunsch, Connyen_US
dc.date.accessioned2010-08-11T09:04:55Z-
dc.date.available2010-08-11T09:04:55Z-
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/10419/37434-
dc.description.abstractBased on a new, exceptionally informative and large German linked employer-employee administrative dataset, we investigate the question whether the omission of important control variables in matching estimation leads to biased impact estimates of typical active labour market programmes for the unemployed. Such biases would lead to false policy conclusions about the effectiveness of these expensive policies. Based on our preliminary findings, it seems that controlling for standard demographic variables removes already a substantial part of the potential selection bias.en_US
dc.language.isoengen_US
dc.publisher|aVerein für Socialpolitik |cFrankfurt a. M.en_US
dc.relation.ispartofseries|aBeiträge zur Jahrestagung des Vereins für Socialpolitik 2010: Ökonomie der Familie - Session: Evaluation Econometrics |xA6-V1en_US
dc.subject.jelJ68en_US
dc.subject.jelJ64en_US
dc.subject.jelJ69en_US
dc.subject.ddc330en_US
dc.subject.keywordTrainingen_US
dc.subject.keywordjob search assistanceen_US
dc.subject.keywordmatching estimationen_US
dc.subject.keywordactive labour market policiesen_US
dc.titleWhich control variables do we really need for matching based evaluations of labour market programmes?en_US
dc.typeConference Paperen_US
dc.identifier.ppn654902992-
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-

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