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Treatment Evaluation in the Case of Interactions within Markets

Author

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  • Ferracci, Marc

    () (CREST-INSEE)

  • Jolivet, Grégory

    () (University of Bristol)

  • van den Berg, Gerard J.

    () (University of Bristol)

Abstract

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

Suggested Citation

  • Ferracci, Marc & Jolivet, Grégory & van den Berg, Gerard J., 2010. "Treatment Evaluation in the Case of Interactions within Markets," IZA Discussion Papers 4700, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp4700
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    References listed on IDEAS

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    1. Pierre Cahuc & Bruno Crépon & Julien Guitard & Marc Gurgand, 2008. "Policy Evaluation in Equilibrium The Case of Job Searcg Counseling in France," Working Papers 2008-13, Center for Research in Economics and Statistics.
    2. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
    3. Bruno Crépon & Marc Ferracci & Grégory Jolivet & Gerard J. van den Berg, 2009. "Active Labor Market Policy Effects in a Dynamic Setting," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 595-605, 04-05.
    4. Bruno Crépon & Marc Ferracci & Denis Fougere, 2012. "Training the Unemployed in France: How Does it Affect Unemployment Duration and Recurrence?," Annals of Economics and Statistics, GENES, issue 107-108, pages 175-199.
    5. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
    6. Bhattacharya, Debopam & Dupas, Pascaline, 2012. "Inferring welfare maximizing treatment assignment under budget constraints," Journal of Econometrics, Elsevier, vol. 167(1), pages 168-196.
    7. Edward Miguel & Michael Kremer, 2004. "Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities," Econometrica, Econometric Society, vol. 72(1), pages 159-217, January.
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    Citations

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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. Landais, Camille & Michaillat, Pascal & Saez, Emmanuel, 2010. "Optimal Unemployment Insurance over the Business Cycle," CEPR Discussion Papers 8132, C.E.P.R. Discussion Papers.
    3. 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.
    4. Blasco, Sylvie & Pertold-Gebicka, Barbara, 2013. "Employment policies, hiring practices and firm performance," Labour Economics, Elsevier, vol. 25(C), pages 12-24.
    5. Peter Mueser & Marios Michaelides, 2015. "Are Reemployment Services Effective? Experimental Evidence from the Great Recession," Working Papers 18-04, Department of Economics, University of Missouri, revised Feb 2018.
    6. Gautier, Pieter A. & Muller, Paul & van der Klaauw, Bas & Rosholm, Michael & Svarer, Michael, 2012. "Estimating Equilibrium Effects of Job Search Assistance," IZA Discussion Papers 6748, Institute for the Study of Labor (IZA).
    7. 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.
    8. 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.
    9. 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, pages 839-867, August.
    10. 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.
    11. Andrew C. Johnston & Alexandre Mas, 2015. "Potential Unemployment Insurance Duration and Labor Supply: The Individual and Market-Level Response to a Benefit Cut," Working Papers 590, Princeton University, Department of Economics, Industrial Relations Section..

    More about this item

    Keywords

    treatment evaluation; equilibrium effects; matching estimators;

    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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