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Design of randomized experiments to measure social interaction effects

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  • Hirano, Keisuke
  • Hahn, Jinyong

Abstract

We consider randomized experiments with two levels of randomization for measuring social interaction effects. We examine how the randomization should be carried out to estimate the coefficients of interest most precisely.

Suggested Citation

  • Hirano, Keisuke & Hahn, Jinyong, 2010. "Design of randomized experiments to measure social interaction effects," Economics Letters, Elsevier, vol. 106(1), pages 51-53, January.
    • Handle: RePEc:eee:ecolet:v:106:y:2010:i:1:p:51-53
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    References listed on IDEAS

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    1. Brock, William A. & Durlauf, Steven N., 2001. "Interactions-based models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 54, pages 3297-3380, Elsevier.
    2. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    3. Esther Duflo & Emmanuel Saez, 2003. "The Role of Information and Social Interactions in Retirement Plan Decisions: Evidence from a Randomized Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(3), pages 815-842.
    4. Manuela Angelucci & Giacomo De Giorgi, 2009. "Indirect Effects of an Aid Program: How Do Cash Transfers Affect Ineligibles' Consumption?," American Economic Review, American Economic Association, vol. 99(1), pages 486-508, March.
    5. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    6. Graham, Bryan S. & Hahn, Jinyong, 2005. "Identification and estimation of the linear-in-means model of social interactions," Economics Letters, Elsevier, vol. 88(1), pages 1-6, July.
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    Cited by:

    1. Steven N. Durlauf & Yannis M. Ioannides, 2010. "Social Interactions," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 451-478, September.
    2. Dario Tortarolo & Guillermo Cruces & Gonzalo Vazquez-Bare, 2023. "Design of partial population experiments with an application to spillovers in tax compliance," IFS Working Papers W23/17, Institute for Fiscal Studies.
    3. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2014. "Designing Experiments to Measure Spillover Effects," PIER Working Paper Archive 14-032, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. M. Angelucci & V. Di Maro, 2016. "Programme evaluation and spillover effects," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 8(1), pages 22-43, March.
    5. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    6. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2017. "Optimal Design of Experiments in the Presence of Interference*, Second Version," PIER Working Paper Archive 16-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 30 Nov 2017.
    7. Braun, Martin & Verdier, Valentin, 2023. "Estimation of spillover effects with matched data or longitudinal network data," Journal of Econometrics, Elsevier, vol. 233(2), pages 689-714.
    8. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2015. "Designing Experiments to Measure Spillover Effects, Second Version," PIER Working Paper Archive 15-021, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Jun 2015.
    9. Michael P. Leung, 2020. "Treatment and Spillover Effects Under Network Interference," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 368-380, May.

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