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Conducting interactive experiments online

Author

Listed:
  • Antonio A. Arechar

    (Department of Psychology, Yale University,)

  • Simon Gaechter

    (School of Economics, University of Nottingham)

  • Lucas Molleman

    (School of Economics, University of Nottingham; Max Planck Institute for Human Development)

Abstract

Online labor markets provide new opportunities for behavioral research, but conducting economic experiments online raises important methodological challenges. This particularly holds for interactive designs. In this paper, we provide a methodological discussion of the similarities and differences between interactive experiments conducted in the laboratory and online. To this end, we conduct a repeated public goods experiment with and without punishment using samples from the laboratory and the online platform Amazon Mechanical Turk. We chose to replicate this experiment because it is long and logistically complex. It therefore provides a good case study for discussing the methodological and practical challenges of online interactive experimentation. We find that basic behavioral patterns of cooperation and punishment in the laboratory are replicable online. The most important challenge of online interactive experiments is participant dropout. We discuss measures for reducing dropout and show that, for our case study, dropouts are exogenous to the experiment. We conclude that data quality for interactive experiments via the Internet is adequate and reliable, making online interactive experimentation a valuable complement to laboratory studies.

Suggested Citation

  • Antonio A. Arechar & Simon Gaechter & Lucas Molleman, 2017. "Conducting interactive experiments online," Discussion Papers 2017-02, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    • Handle: RePEc:not:notcdx:2017-02
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    More about this item

    Keywords

    Experimental methodology; Behavioral research; Internet experiments; Amazon Mechanical Turk; Public goods game; Punishment;
    All these keywords.

    JEL classification:

    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations

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