M
Michael Lechner
Researcher at University of St. Gallen
Publications - 328
Citations - 12371
Michael Lechner is an academic researcher from University of St. Gallen. The author has contributed to research in topics: Matching (statistics) & Estimator. The author has an hindex of 48, co-authored 317 publications receiving 11516 citations. Previous affiliations of Michael Lechner include University of London & Stockholm School of Economics.
Papers
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Book
The Estimation of Causal Effects by Difference-in-Difference Methods
TL;DR: The authors presents a brief overview of the literature on the difference-in-difference estimation strategy and discusses major issues mainly using a treatment effect perspective that allows more general considerations than the classical regression formulation that still dominates the applied work.
Book ChapterDOI
Identification and estimation of causal effects of multiple treatments under the conditional independence assumption
TL;DR: In this paper, a matching estimator is proposed to identify causal effects when there are more than two types of mutually exclusive treatments, similar to the ones valid in the case of only two treatments.
Journal ArticleDOI
Program Heterogeneity and Propensity Score Matching: An Application to the Evaluation of Active Labor Market Policies
TL;DR: In this article, the authors address micro-econometric evaluation by matching methods when the programs under consideration are heterogeneous, assuming that selection into the different sub-programs and the potential outcomes are independent given observable characteristics, estimators based on different propensity scores are compared and applied to the analysis of active labor market policies in the Swiss region of Zurich.
Journal ArticleDOI
Long-run effects of public sector sponsored training in west germany
TL;DR: In this paper, the effects of different types of training programmes over a horizon of more than seven years were identified using bias corrected weighted multiple neighbors matching, and they found that all programmes have negative effects in the short run and positive effects over a four years.
Journal ArticleDOI
Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods
TL;DR: In this article, the authors show that the matching approach per se is no magic bullet solving all problems of evaluation studies, but that its success depends critically on the information available in the sample.