IDEAS home Printed from https://ideas.repec.org/p/aim/wpaimx/1435.html
   My bibliography  Save this paper

Accounting for Peer Effects in Treatment Response

Author

Listed:

Abstract

When one’s treatment status affects the outcomes of others, experimental data are not sufficient to identify a treatment causal impact. In order to account for peer effects in program response, we use a social network model. We estimate and validate the model on experimental data collected for the evaluation of a scholarship program in Colombia. By design, randomization is at the student-level. Friendship data reveals that treated and untreated students interact together. Besides providing evidence of peer effects in schooling, we find that ignoring peer effects would have led us to overstate the program actual impact.

Suggested Citation

  • Rokhaya Dieye & Habiba Djebbari & Felipe Barrera-Osorio, 2014. "Accounting for Peer Effects in Treatment Response," AMSE Working Papers 1435, Aix-Marseille School of Economics, France, revised Jul 2014.
    • Handle: RePEc:aim:wpaimx:1435
    as

    Download full text from publisher

    File URL: http://www.amse-aixmarseille.fr/sites/default/files/_dt/2012/wp_2014_-_nr_35.pdf#overlay-context=fr/recherche/documents-de-travail/accounting-peer-effects-treatment-response
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Paul Schultz, T., 2004. "School subsidies for the poor: evaluating the Mexican Progresa poverty program," Journal of Development Economics, Elsevier, vol. 74(1), pages 199-250, June.
    2. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," Review of Economic Studies, Oxford University Press, vol. 60(3), pages 531-542.
    3. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    4. Michael Kremer & Edward Miguel, 2007. "The Illusion of Sustainability," The Quarterly Journal of Economics, Oxford University Press, vol. 122(3), pages 1007-1065.
    5. Charles F. Manski, 2013. "Identification of treatment response with social interactions," Econometrics Journal, Royal Economic Society, vol. 16(1), pages 1-23, February.
    6. Kenneth I. Wolpin & Petra E. Todd, 2006. "Assessing the Impact of a School Subsidy Program in Mexico: Using a Social Experiment to Validate a Dynamic Behavioral Model of Child Schooling and Fertility," American Economic Review, American Economic Association, vol. 96(5), pages 1384-1417, December.
    7. Jeffrey Smith & Jeremy Lise & Shannon N. Seitz, 2003. "Equilibrium Policy Experiments And The Evaluation Of Social Programs," Working Paper 1012, Economics Department, Queen's University.
    8. Debopam Bhattacharya & Pascaline Dupas & Shin Kanaya, 2013. "Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets," CREATES Research Papers 2013-06, Department of Economics and Business Economics, Aarhus University.
    9. Lawrence F. Katz & Jeffrey R. Kling & Jeffrey B. Liebman, 2001. "Moving to Opportunity in Boston: Early Results of a Randomized Mobility Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 116(2), pages 607-654.
    10. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    11. Bramoullé, Yann & Djebbari, Habiba & Fortin, Bernard, 2009. "Identification of peer effects through social networks," Journal of Econometrics, Elsevier, vol. 150(1), pages 41-55, May.
    12. Liu, Xiaodong & Lee, Lung-fei, 2010. "GMM estimation of social interaction models with centrality," Journal of Econometrics, Elsevier, vol. 159(1), pages 99-115, November.
    13. Evans, William N & Oates, Wallace E & Schwab, Robert M, 1992. "Measuring Peer Group Effects: A Study of Teenage Behavior," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 966-991, October.
    14. Joshua Angrist & Eric Bettinger & Michael Kremer, 2006. "Long-Term Educational Consequences of Secondary School Vouchers: Evidence from Administrative Records in Colombia," American Economic Review, American Economic Association, vol. 96(3), pages 847-862, June.
    15. Roland Bénabou, 1996. "Inequality and Growth," NBER Chapters, in: NBER Macroeconomics Annual 1996, Volume 11, pages 11-92, National Bureau of Economic Research, Inc.
    16. Felipe Barrera-Osorio & Marianne Bertrand & Leigh L. Linden & Francisco Perez-Calle, 2011. "Improving the Design of Conditional Transfer Programs: Evidence from a Randomized Education Experiment in Colombia," American Economic Journal: Applied Economics, American Economic Association, vol. 3(2), pages 167-195, April.
    17. Antoni Calvó-Armengol & Eleonora Patacchini & Yves Zenou, 2009. "Peer Effects and Social Networks in Education," Review of Economic Studies, Oxford University Press, vol. 76(4), pages 1239-1267.
    18. Emily Oster & Rebecca Thornton, 2011. "Menstruation, Sanitary Products, and School Attendance: Evidence from a Randomized Evaluation," American Economic Journal: Applied Economics, American Economic Association, vol. 3(1), pages 91-100, January.
    19. Comola, Margherita & Prina, Silvia, 2014. "Do Interventions Change the Network? A Panel Peer-Effect Model Accounting for Endogenous Network Changes," IZA Discussion Papers 8641, Institute of Labor Economics (IZA).
    20. Tomas Philipson, 1999. "External Treatment Effects and Program Implementation Bias," Working Papers 9929, Harris School of Public Policy Studies, University of Chicago.
    21. 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.
    22. Xu Lin, 2010. "Identifying Peer Effects in Student Academic Achievement by Spatial Autoregressive Models with Group Unobservables," Journal of Labor Economics, University of Chicago Press, vol. 28(4), pages 825-860, October.
    23. Giacomo De Giorgi & Michele Pellizzari & Silvia Redaelli, 2010. "Identification of Social Interactions through Partially Overlapping Peer Groups," American Economic Journal: Applied Economics, American Economic Association, vol. 2(2), pages 241-275, April.
    24. Lung-fei Lee & Xiaodong Liu & Xu Lin, 2010. "Specification and estimation of social interaction models with network structures," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 145-176, July.
    25. Michael Kremer & Alaka Holla, 2009. "Improving Education in the Developing World: What Have We Learned from Randomized Evaluations?," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 513-545, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nakano, Yuko & Tsusaka, Takuji W. & Aida, Takeshi & Pede, Valerien O., 2018. "Is farmer-to-farmer extension effective? The impact of training on technology adoption and rice farming productivity in Tanzania," World Development, Elsevier, vol. 105(C), pages 336-351.
    2. Felipe Barrera-Osorio & Leigh L. Linden & Juan E. Saavedra, 2019. "Medium- and Long-Term Educational Consequences of Alternative Conditional Cash Transfer Designs: Experimental Evidence from Colombia," American Economic Journal: Applied Economics, American Economic Association, vol. 11(3), pages 54-91, July.
    3. Izaguirre, Alejandro & Di Capua, Laura, 2020. "Exploring peer effects in education in Latin America and the Caribbean," Research in Economics, Elsevier, vol. 74(1), pages 73-86.
    4. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2019. "Peer Effects in Networks: a Survey," Working Papers halshs-02440709, HAL.
    5. Michael P. Leung, 2019. "Causal Inference Under Approximate Neighborhood Interference," Papers 1911.07085, arXiv.org, revised Nov 2020.
    6. Boucher, Vincent & Fortin, Bernard, 2015. "Some Challenges in the Empirics of the Effects of Networks," IZA Discussion Papers 8896, Institute of Labor Economics (IZA).
    7. Maria Marchenko, 2019. "Dealing with Endogenous Shocks in Dynamic Friendship Network," Department of Economics Working Papers wuwp291, Vienna University of Economics and Business, Department of Economics.
    8. Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers CWP52/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Belhaj, Mohamed & Deroïan, Frédéric, 2019. "Group targeting under networked synergies," Games and Economic Behavior, Elsevier, vol. 118(C), pages 29-46.
    10. Arun Advani & Bansi Malde, 2018. "Methods to identify linear network models: a review," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-16, December.
    11. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Nov 2020.
    12. Philip Babcock & Kelly Bedard & Stefanie Fischer & John Hartman, 2019. "Coordination and Contagion: Individual Connections and Peer Mechanisms in a Randomized Field Experiment," Working Papers 1904, California Polytechnic State University, Department of Economics.

    More about this item

    Keywords

    Education; social network; impact evaluation;

    JEL classification:

    • 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
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • I22 - Health, Education, and Welfare - - Education - - - Educational Finance; Financial Aid

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aim:wpaimx:1435. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Gregory Cornu). General contact details of provider: http://edirc.repec.org/data/amseafr.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.