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Selection in the Lab: A Network Approach

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  • A. Alekseev
  • Mikhail Freer

Abstract

We study the selection problem in economic experiments by focusing on its dynamic and network aspects. We develop a dynamic network model of student participation in a subject pool, which assumes that students' participation is driven by the two channels: the direct channel of recruitment and the indirect channel of student interaction. Using rich recruitment data from a large public university, we find that the patterns of participation and biases are consistent with the model. We also find evidence of both short- and long-run selection biases between males and females, as well as between cohorts of students. Males tend to have higher participation rates than females, and participation rates tend to decrease with a cohort's age. Our empirical findings confirm that dynamic and peer effects play an important role in shaping the selection problem. Our model allows us to reconcile some of the mixed results in previous studies.

Suggested Citation

  • A. Alekseev & Mikhail Freer, 2018. "Selection in the Lab: A Network Approach," Working Papers ECARES 2018-32, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:eca:wpaper:2013/278180
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    References listed on IDEAS

    as
    1. Jackson, Matthew O. & Lã“Pez-Pintado, Dunia, 2013. "Diffusion and contagion in networks with heterogeneous agents and homophily," Network Science, Cambridge University Press, vol. 1(1), pages 49-67, April.
    2. Slonim, Robert & Wang, Carmen & Garbarino, Ellen & Merrett, Danielle, 2012. "Opting-In: Participation Biases in the Lab," IZA Discussion Papers 6865, Institute of Labor Economics (IZA).
    3. Blair Cleave & Nikos Nikiforakis & Robert Slonim, 2013. "Is there selection bias in laboratory experiments? The case of social and risk preferences," Experimental Economics, Springer;Economic Science Association, vol. 16(3), pages 372-382, September.
    4. Alexander W. Cappelen & Knut Nygaard & Erik Ø. Sørensen & Bertil Tungodden, 2015. "Social Preferences in the Lab: A Comparison of Students and a Representative Population," Scandinavian Journal of Economics, Wiley Blackwell, vol. 117(4), pages 1306-1326, October.
    5. Michal Krawczyk, 2011. "What brings your subjects to the lab? A field experiment," Experimental Economics, Springer;Economic Science Association, vol. 14(4), pages 482-489, November.
    6. Armin Falk & Stephan Meier & Christian Zehnder, 2013. "Do Lab Experiments Misrepresent Social Preferences? The Case Of Self-Selected Student Samples," Journal of the European Economic Association, European Economic Association, vol. 11(4), pages 839-852, August.
    7. Steven D. Levitt & John A. List, 2007. "What Do Laboratory Experiments Measuring Social Preferences Reveal About the Real World?," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 153-174, Spring.
    8. Slonim, Robert & Wang, Carmen & Garbarino, Ellen & Merrett, Danielle, 2013. "Opting-in: Participation bias in economic experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 90(C), pages 43-70.
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    More about this item

    Keywords

    peer effects; experimental economics; selection problem; laboratory experiments; external validity; networks; diffusion;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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