Accounting for Peer Effects in Treatment Response
AbstractWhen 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.
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Bibliographic InfoPaper provided by Aix-Marseille School of Economics, Marseille, France in its series AMSE Working Papers with number 1335.
Length: 47 pages
Date of creation: Jul 2014
Date of revision: Jul 2014
Education; social network; impact evaluation;
Find related papers by 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-07-15 (All new papers)
- NEP-GTH-2013-07-15 (Game Theory)
- NEP-HPE-2013-07-15 (History & Philosophy of Economics)
- NEP-MIC-2013-07-15 (Microeconomics)
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- Sergiu Hart & Andreu Mas-Colell, 1996.
"A simple adaptive procedure leading to correlated equilibrium,"
Economics Working Papers
200, Department of Economics and Business, Universitat Pompeu Fabra, revised Dec 1996.
- Sergiu Hart & Andreu Mas-Colell, 2000. "A Simple Adaptive Procedure Leading to Correlated Equilibrium," Econometrica, Econometric Society, vol. 68(5), pages 1127-1150, September.
- S. Hart & A. Mas-Collel, 2010. "A Simple Adaptive Procedure Leading to Correlated Equilibrium," Levine's Working Paper Archive 572, David K. Levine.
- Sergiu Hart & Andreu Mas-Colell, 1997. "A Simple Adaptive Procedure Leading to Correlated Equilibrium," Game Theory and Information 9703006, EconWPA, revised 24 Mar 1997.
- Drew Fudenberg & David K. Levine, 1998.
"The Theory of Learning in Games,"
MIT Press Books,
The MIT Press,
edition 1, volume 1, number 0262061945, December.
- Tilman B�rgers & Rajiv Sarin, .
"Learning Through Reinforcement and Replicator Dynamics,"
ELSE working papers
051, ESRC Centre on Economics Learning and Social Evolution.
- Borgers, Tilman & Sarin, Rajiv, 1997. "Learning Through Reinforcement and Replicator Dynamics," Journal of Economic Theory, Elsevier, vol. 77(1), pages 1-14, November.
- T. Borgers & R. Sarin, 2010. "Learning Through Reinforcement and Replicator Dynamics," Levine's Working Paper Archive 380, David K. Levine.
- Fudenberg, D. & Kreps, D.M., 1992.
"Learning Mixed Equilibria,"
92-13, Massachusetts Institute of Technology (MIT), Department of Economics.
- Berger, Ulrich, 2005. "Fictitious play in 2 x n games," Journal of Economic Theory, Elsevier, vol. 120(2), pages 139-154, February.
- Ed Hopkins, 2002.
"Two Competing Models of How People Learn in Games,"
Econometric Society, vol. 70(6), pages 2141-2166, November.
- Ed Hopkins, 2001. "Two Competing Models of How People Learn in Games," Levine's Working Paper Archive 625018000000000226, David K. Levine.
- Ed Hopkins, 2004. "Two Competing Models of How People Learn in Games," ESE Discussion Papers 51, Edinburgh School of Economics, University of Edinburgh.
- Ed Hopkins, 2001. "Two Competing Models of How People Learn in Games," NajEcon Working Paper Reviews 625018000000000226, www.najecon.org.
- Ed Hopkins & Martin Posch, 2004.
"Attainability of Boundary Points under Reinforcement Learning,"
ESE Discussion Papers
79, Edinburgh School of Economics, University of Edinburgh.
- Hopkins, Ed & Posch, Martin, 2005. "Attainability of boundary points under reinforcement learning," Games and Economic Behavior, Elsevier, vol. 53(1), pages 110-125, October.
- Ed Hopkins & Martin Posch, 2003. "Attainability of Boundary Points under Reinforcement Learning," Levine's Working Paper Archive 506439000000000350, David K. Levine.
- Alan Beggs, 2002.
"On the Convergence of Reinforcement Learning,"
Economics Series Working Papers
96, University of Oxford, Department of Economics.
- Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-81, September.
- Monderer, Dov & Shapley, Lloyd S., 1996. "Fictitious Play Property for Games with Identical Interests," Journal of Economic Theory, Elsevier, vol. 68(1), pages 258-265, January.
- I. Gilboa & A. Matsui, 2010.
"Social Stability and Equilibrium,"
Levine's Working Paper Archive
534, David K. Levine.
- Martin Posch, 1997. "Cycling in a stochastic learning algorithm for normal form games," Journal of Evolutionary Economics, Springer, vol. 7(2), pages 193-207.
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