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Combining Matching and Nonparametric Instrumental Variable Estimation: Theory and An Application to the Evaluation of Active Labour Market Policies

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  • Markus Frölich
  • Michael Lechner

Abstract

We show how instrumental variable and matching estimators can be combined in order to identify a broader array of treatment effects. Instrumental variable (IV) estimators are known to estimate effects only for the compliers, representing a subset of the entire population. By combining IV with matching, we can estimate the treatment effects for the always‐ and never‐takers as well. Since in many cases these groups are the (endogenous) outcome of some assignment process, such estimates also help in judging the implications of such a selection process. In our application to the effects of participation in active labour market programmes in Switzerland, we find large and lasting positive employment effects for the compliers, whereas the effects for the always‐ and never‐participants are small. In addition, the compliers have worse employment outcomes without treatment than those who participate in the programme with or without the intervention under investigation. This suggests that the earlier assignment policy of the caseworkers was inefficient in that the always‐participants were neither those unemployed who would experience the highest expected treatment effects nor those unemployed who had the largest need for assistance. Copyright © 2014 John Wiley & Sons, Ltd.

Suggested Citation

  • Markus Frölich & Michael Lechner, 2015. "Combining Matching and Nonparametric Instrumental Variable Estimation: Theory and An Application to the Evaluation of Active Labour Market Policies," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 718-738, August.
    • Handle: RePEc:wly:japmet:v:30:y:2015:i:5:p:718-738
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    Cited by:

    1. Hünermund, Paul & Czarnitzki, Dirk, 2019. "Estimating the causal effect of R&D subsidies in a pan-European program," Research Policy, Elsevier, vol. 48(1), pages 115-124.
    2. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    3. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    4. Jing You & Miguel Niño‐Zarazúa, 2019. "The Intergenerational Impact of China's New Rural Pension Scheme," Population and Development Review, The Population Council, Inc., vol. 45(S1), pages 47-95, December.
    5. Fabrice Gilles & Yannick L’Horty & Ferhat Mihoubi & Xi Yang, 2018. "Evaluating the impact of firm tax credits. Results from the French natural experiment CICE," TEPP Working Paper 2018-05, TEPP.
    6. Rotar Laura Južnik, 2018. "The Effects of Expenditures for Labour Market Policy on Unemployment Rate," Business Systems Research, Sciendo, vol. 9(1), pages 55-64, March.
    7. Jing You & Miguel Niño-Zarazúa, 2017. "Smoothing or strengthening the ‘Great Gatsby Curve’? The intergenerational impact of China’s New Rural Pension Scheme," WIDER Working Paper Series 199, World Institute for Development Economic Research (UNU-WIDER).
    8. Jing You & Miguel Niño-Zarazúa, 2017. "Smoothing or strengthening the 'Great Gatsby curve'?: The intergenerational impact of China's New Rural Pension Scheme," WIDER Working Paper Series wp-2017-199, World Institute for Development Economic Research (UNU-WIDER).

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