Sensitivity of matching-based program evaluations to the availability of control variables

Michael Lechner and Conny Wunsch

No 8294, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: Based on new, exceptionally informative and large German linked employer-employee administrative data, we investigate the question whether the omission of important control variables in matching estimation leads to biased impact estimates of typical active labour market programs for the unemployed. Such biases would lead to false policy conclusions about the cost-effectiveness of these expensive policies. Using newly developed Empirical Monte Carlo Study methods, we find that besides standard personal characteristics, information on individual health and firm characteris-tics of the last employer are particularly important for selection correction. Moreover, it is important to account for past performance on the labour market in a very detailed and flexible way. Information on job search behaviour, timing of unemployment and program start, as well as detailed regional characteristics are also relevant.

Keywords: Active labour market policies; Job search assistance; Matching estimation; Training (search for similar items in EconPapers)
JEL-codes: J68 (search for similar items in EconPapers)
Date: 2011-03
New Economics Papers: this item is included in nep-lab
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Citations: View citations in EconPapers (17)

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Related works:
Journal Article: Sensitivity of matching-based program evaluations to the availability of control variables (2013)
Working Paper: Sensitivity of Matching-Based Program Evaluations to the Availability of Control Variables (2011)
Working Paper: Sensitivity of Matching-Based Program Evaluations to the Availability of Control Variables (2011)
Working Paper: Sensitivity of matching-based program evaluations to the availability of control variables (2011)
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