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Identification of treatment response with social interactions

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  • Charles F. Manski

    () (Institute for Fiscal Studies and Northwestern University)

Abstract

This paper develops a formal language for study of treatment response with social interactions, and uses it to obtain new findings on identification of potential outcome distributions. Defining a person's treatment response to be a function of the entire vector of treatments received by the population, I study identification when shape restrictions and distributional assumptions are placed on response functions. An early key result is that the traditional assumption of individualistic treatment response (ITR) is a polar case within the broad class of constant treatment response (CTR) assumptions, the other pole being unrestricted interactions. Important non-polar cases are interactions within reference groups and distributional interactions. I show that established findings on identification under assumption ITR extend to assumption CTR. These include identification with assumption CTR alone and when this shape restriction is strengthened to semi-monotone response. I next study distributional assumptions using instrumental variables. Findings obtained previously under assumption ITR extend when assumptions of statistical independence (SI) are posed in settings with social interactions. However, I find that random assignment of realized treatments generically has no identifying power when some persons are leaders who may affect outcomes throughout the population. Finally, I consider use of models of endogenous social interactions to derive restrictions on response functions. I emphasize that identification of potential outcome distributions differs from the longstanding econometric concern with identification of structural functions. This paper is a revised version of CWP01/10

Suggested Citation

  • Charles F. Manski, 2010. "Identification of treatment response with social interactions," CeMMAP working papers CWP01/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:01/10
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    File URL: http://cemmap.ifs.org.uk/wps/cwp0110-2.pdf
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    Cited by:

    1. Di Gennaro, Daniele & Pellegrini, Guido, 2016. "Evaluating direct and indirect treatment effects in Italian R&D expenditures," MPRA Paper 76467, University Library of Munich, Germany, revised 28 Jan 2017.
    2. Rokhaya Dieye & Habiba Djebbari & Felipe Barrera-Osorio, 2014. "Accounting for Peer Effects in Treatment Response," AMSE Working Papers 1435, Aix-Marseille School of Economics, Marseille, France, revised Jul 2014.
    3. Edoardo Rainone, 2015. "Testing information diffusion in the decentralized unsecured market for euro funds," Temi di discussione (Economic working papers) 1022, Bank of Italy, Economic Research and International Relations Area.
    4. Gibbons, Steve & Overman, Henry G. & Patacchini, Eleonora, 2015. "Spatial Methods," Handbook of Regional and Urban Economics, Elsevier.
    5. Giovanni Cerulli, 2014. "ntreatreg: A Stata module for estimation of treatment effects in the presence of neighborhood interactions," Italian Stata Users' Group Meetings 2014 06, Stata Users Group.
    6. Clarke, Damian, 2017. "Estimating Difference-in-Differences in the Presence of Spillovers," MPRA Paper 81604, University Library of Munich, Germany.
    7. Delgado, Michael S. & Florax, Raymond J.G.M., 2015. "Difference-in-differences techniques for spatial data: Local autocorrelation and spatial interaction," Economics Letters, Elsevier, vol. 137(C), pages 123-126.
    8. Boucher, Vincent & Fortin, Bernard, 2015. "Some Challenges in the Empirics of the Effects of Networks," IZA Discussion Papers 8896, Institute for the Study of Labor (IZA).
    9. Kobayashi, Mimako & Melkonyan, Tigran A., 2011. "Strategic Incentives in Biosecurity Actions: Theoretical and Empirical Analyses," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 36(2), August.
    10. Roberto Gabriele & Enrico Tundis, 2015. "the effect of longitudinal multiple subsidies on firm performance in the presence of neighbour interactions," ERSA conference papers ersa15p1368, European Regional Science Association.
    11. Mathias Lundin & Maria Karlsson, 2014. "Estimation of causal effects in observational studies with interference between units," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 417-433, August.
    12. Lafférs, Lukáš, 2013. "A note on bounding average treatment effects," Economics Letters, Elsevier, vol. 120(3), pages 424-428.
    13. Giovanni Cerulli, 2014. "Identification and Estimation of Treatment Effects in the Presence of Neighbourhood Interactions," CERIS Working Paper 201404, Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY -NOW- Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY.
    14. Noll, Daniel & Dawes, Colleen & Rai, Varun, 2014. "Solar Community Organizations and active peer effects in the adoption of residential PV," Energy Policy, Elsevier, vol. 67(C), pages 330-343.
    15. Xi Song, 2016. "Diverging Mobility Trajectories: Grandparent Effects on Educational Attainment in One- and Two-Parent Families in the United States," Demography, Springer;Population Association of America (PAA), vol. 53(6), pages 1905-1932, December.
    16. Charles F. Manski, 2014. "Vaccine Approvals and Mandates Under Uncertainty: Some Simple Analytics," NBER Working Papers 20432, National Bureau of Economic Research, Inc.
    17. Daniele Di Gennaro & Guido Pellegrini, 2016. "Policy Evaluation In Presence Of Interferences: A Spatial Multilevel Did Approach," Working Papers 0416, CREI Università degli Studi Roma Tre, revised 2016.
    18. Girma, Sourafel & Gong, Yundan & Görg, Holger & Lancheros, Sandra, 2015. "Estimating direct and indirect effects of foreign direct investment on firm productivity in the presence of interactions between firms," Journal of International Economics, Elsevier, vol. 95(1), pages 157-169.
    19. Arun Advani & Bansi Malde, 2014. "Empirical methods for networks data: social effects, network formation and measurement error," IFS Working Papers W14/34, Institute for Fiscal Studies.
    20. Giovanni Cerulli & Roberto Gabriele & Enrico Tundis, 2014. "Evaluating locally-based policies in the presence of neighbourhood effects: The case of touristic accommodation in the Garda district of Trentino," ERSA conference papers ersa14p715, European Regional Science Association.
    21. Hidano, Noboru & Hoshino, Tadao & Sugiura, Ayako, 2015. "The effect of seismic hazard risk information on property prices: Evidence from a spatial regression discontinuity design," Regional Science and Urban Economics, Elsevier, vol. 53(C), pages 113-122.
    22. Kline, Brendan, 2015. "Identification of complete information games," Journal of Econometrics, Elsevier, vol. 189(1), pages 117-131.

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