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Evaluation of education and training impacts for the unemployed: Challenges of new data

Augusto Cerqua (), Peter Urwin, Dave Thomson and David Bibby

Labour Economics, 2020, vol. 67, issue C

Abstract: This study utilises an exceptionally rich English administrative dataset, to estimate employment impacts from training voluntarily initiated by unemployed individuals. A Coarsened Exact Matching approach is adopted, in a dynamic evaluation framework, to estimate impacts up to 5 years from training start. We identify economically and statistically significant impacts, estimated separately for (i) all training starters, (ii) the partially, and (iii) fully treated. Investigation of possible endogenous selection into partial/full treatment, using distance to training provider as an instrumental variable, suggests inclusion of extensive employment and learning histories in a matching framework, justifies invocation of the conditional independence assumption for comparisons of full/partial treatment. The partially treated secure a return that is, on average, 2 percentage points lower than full treatment. Thus, an `intention to treat' approach would not alter conclusions on the efficacy of training; but using the partially treated to estimate counterfactual outcomes risks understating returns.

Keywords: Active labour market programme; Full and partial treatment; Endogenous selection (search for similar items in EconPapers)
JEL-codes: I21 I26 I38 J64 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:labeco:v:67:y:2020:i:c:s0927537120301111

DOI: 10.1016/j.labeco.2020.101907

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