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Treatment Evaluation in the Case of Interaction Within Markets

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  • Marc FERRACCI

    (Crest)

  • Grégory JOLIVET

    (Crest)

  • Gerard J van den Berg

    (Crest)

Abstract

We extend the standard evaluation framework to allow for interactions betweenindividuals within segmented markets. An individual's outcome depends not only onthe assigned treatment status but also on (features of) the distribution of the assignedtreatments in his market. To evaluate how the distribution of treatments within amarket causally affects the average effect within the market, averaged over the fullpopulation, we develop an identification and estimation method in two steps. The firstone focuses on the distribution of the treatment within markets and betweenindividuals and the second step addresses the distribution of the treatment betweenmarkets. We apply our method to data on training programs for unemployed workersin France. We use a rich administrative register of unemployment and training spellsas well as the information on local labor demand that is used by unemploymentagencies to allocate training programs. The results show that the average treatmenteffect on the employment rate causally decreases with respect to the proportion oftreated in the market. Our analysis accounts for unobserved heterogeneity betweenmarkets (using the longitudinal dimension of the data) and, in a robustness check,between individuals.

Suggested Citation

  • Marc FERRACCI & Grégory JOLIVET & Gerard J van den Berg, 2009. "Treatment Evaluation in the Case of Interaction Within Markets," Working Papers 2009-22, Center for Research in Economics and Statistics.
  • Handle: RePEc:crs:wpaper:2009-22
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    References listed on IDEAS

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    Cited by:

    1. Huber, Martin & Steinmayr, Andreas, 2017. "A Framework for Separating Individual Treatment Effects From Spillover, Interaction, and General Equilibrium Effects," Rationality and Competition Discussion Paper Series 21, CRC TRR 190 Rationality and Competition.
    2. Goulas, Eleftherios & Zervoyianni, Athina, 2018. "Active labour-market policies and output growth: Is there a causal relationship?," Economic Modelling, Elsevier, vol. 73(C), pages 1-14.
    3. Marios Michaelides & Peter Mueser, 2018. "Are Reemployment Services Effective? Experimental Evidence from the Great Recession," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 37(3), pages 546-570, June.
    4. Rothstein, J & von Wachter, T, 2016. "Social Experiments in the Labor Market," Department of Economics, Working Paper Series qt7957p9g6, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    5. Bruno Crépon & Esther Duflo & Marc Gurgand & Roland Rathelot & Philippe Zamora, 2013. "Do Labor Market Policies have Displacement Effects? Evidence from a Clustered Randomized Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 128(2), pages 531-580.
    6. Rafael Lalive & Camille Landais & Josef Zweimüller, 2015. "Market Externalities of Large Unemployment Insurance Extension Programs," American Economic Review, American Economic Association, vol. 105(12), pages 3564-3596, December.
    7. Pieter Gautier & Paul Muller & Bas van der Klaauw & Michael Rosholm & Michael Svarer, 2018. "Estimating Equilibrium Effects of Job Search Assistance," Journal of Labor Economics, University of Chicago Press, vol. 36(4), pages 1073-1125.
    8. Ronald Wolthoff, 2014. "It'S About Time: Implications Of The Period Length In An Equilibrium Search Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 839-867, August.
    9. Jesse Rothstein & Till von Wachter, 2016. "Social Experiments in the Labor Market," NBER Working Papers 22585, National Bureau of Economic Research, Inc.
    10. Landais, Camille & Michaillat, Pascal & Saez, Emmanuel, 2010. "Optimal unemployment insurance over the business cycle," LSE Research Online Documents on Economics 35596, London School of Economics and Political Science, LSE Library.
    11. Bruno Crepon & Marc Ferracci & Grégory Jolivet & Gerard Van Den Berg, 2010. "Analyzing the Anticipation of Treatments with Data on Notification Dates," Working Papers 2010-41, Center for Research in Economics and Statistics.
    12. Marco Caliendo & Steffen Künn, 2015. "Getting back into the labor market: the effects of start-up subsidies for unemployed females," Journal of Population Economics, Springer;European Society for Population Economics, vol. 28(4), pages 1005-1043, October.
    13. Rothstein, Jesse & von Wachter, Till, 2016. "Social Experiments in the Labor Market," Department of Economics, Working Paper Series qt6605k20b, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    14. Andrew C. Johnston & Alexandre Mas, 2018. "Potential Unemployment Insurance Duration and Labor Supply: The Individual and Market-Level Response to a Benefit Cut," Journal of Political Economy, University of Chicago Press, vol. 126(6), pages 2480-2522.
    15. Blasco, Sylvie & Pertold-Gebicka, Barbara, 2013. "Employment policies, hiring practices and firm performance," Labour Economics, Elsevier, vol. 25(C), pages 12-24.
    16. Dayanand S. Manoli & Marios Michaelides & Ankur Patel, 2018. "Long-Term Effects of Job-Search Assistance: Experimental Evidence Using Administrative Tax Data," NBER Working Papers 24422, National Bureau of Economic Research, Inc.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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