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On the Generalizability of Experimental Results in Economics

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  • Omar Al-Ubaydli
  • John A. List

Abstract

Economists are increasingly turning to the experimental method as a means to estimate causal effects. By using randomization to identify key treatment effects, theories previously viewed as untestable are now scrutinized, efficacy of public policies are now more easily verified, and stakeholders can swiftly add empirical evidence to aid their decision-making. This study provides an overview of experimental methods in economics, with a special focus on developing an economic theory of generalizability. Given that field experiments are in their infancy, our secondary focus pertains to a discussion of the various parameters that they identify, and how they add to scientific knowledge. We conclude that until we conduct more field experiments that build a bridge between the lab and the naturally-occurring settings of interest we cannot begin to make strong conclusions empirically on the crucial question of generalizability from the lab to the field.

Suggested Citation

  • Omar Al-Ubaydli & John A. List, 2012. "On the Generalizability of Experimental Results in Economics," NBER Working Papers 17957, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:17957
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    Citations

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    Cited by:

    1. Francis Larson & John List & Robert Metcalfe, 2016. "Can Myopic Loss Aversion Explain the Equity Premium Puzzle? Evidence from a Natural Field Experiment with Professional Traders," Natural Field Experiments 00534, The Field Experiments Website.
    2. Omar Al-Ubaydli & John List, 2015. "Do Natural Field Experiments Afford Researchers More or Less Control than Laboratory Experiments? A Simple Model," Artefactual Field Experiments 00458, The Field Experiments Website.
    3. Beck, Adrian & Kerschbamer, Rudolf & Qiu, Jianying & Sutter, Matthias, 2014. "Car mechanics in the lab––Investigating the behavior of real experts on experimental markets for credence goods," Journal of Economic Behavior & Organization, Elsevier, vol. 108(C), pages 166-173.
    4. Decio Coviello & Andrea Guglielmo & Giancarlo Spagnolo, 2015. "The Effect of Discretion on Procurement Performance," CEIS Research Paper 361, Tor Vergata University, CEIS, revised 17 Nov 2015.
    5. Holmen, Martin & Kirchler, Michael & Kleinlercher, Daniel, 2014. "Do option-like incentives induce overvaluation? Evidence from experimental asset markets," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 179-194.
    6. Goeschl, Timo & Kettner, Sara Elisa & Lohse, Johannes & Schwieren, Christiane, 2015. "What do we learn from public good games about voluntary climate action? Evidence from an artefactual field experiment," Working Papers 0595, University of Heidelberg, Department of Economics.
    7. Michael L. Anderson & Fangwen Lu, 2017. "Learning to Manage and Managing to Learn: The Effects of Student Leadership Service," Management Science, INFORMS, vol. 63(10), pages 3246-3261, October.
    8. Omar Al-Ubaydli & John A. List, 2013. "On the Generalizability of Experimental Results in Economics: With a Response to Commentors," CESifo Working Paper Series 4543, CESifo.
    9. Matteo M. Galizzi & Daniel Navarro-Martinez, 2019. "On the External Validity of Social Preference Games: A Systematic Lab-Field Study," Management Science, INFORMS, vol. 65(3), pages 976-1002, March.
    10. Kendel, Adnane & Lazaric, Nathalie & Maréchal, Kevin, 2017. "What do people ‘learn by looking’ at direct feedback on their energy consumption? Results of a field study in Southern France," Energy Policy, Elsevier, vol. 108(C), pages 593-605.
    11. John A. List, 2014. "Using Field Experiments to Change the Template of How We Teach Economics," The Journal of Economic Education, Taylor & Francis Journals, vol. 45(2), pages 81-89, June.
    12. 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.
    13. Hunt Allcott & Richard L. Sweeney, 2017. "The Role of Sales Agents in Information Disclosure: Evidence from a Field Experiment," Management Science, INFORMS, vol. 63(1), pages 21-39, January.
    14. Michel André Maréchal & Christian Thöni, 2019. "Hidden Persuaders: Do Small Gifts Lubricate Business Negotiations?," Management Science, INFORMS, vol. 65(8), pages 3877-3888, August.
    15. 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).
    16. Omar Al-Ubaydli & John List, 2013. "On the Generalizability of Experimental Results in Economics: With A Response To Camerer," Artefactual Field Experiments j0001, The Field Experiments Website.
    17. Egebark, Johan & Ekström, Mathias, 2016. "Can indifference make the world greener?," Journal of Environmental Economics and Management, Elsevier, vol. 76(C), pages 1-13.
    18. Judd Kessler & Judd B. Kessler, 2013. "When will there be Gift Exchange? Addressing the Lab-Field Debate with Laboratory Gift Exchange Experiments," CESifo Working Paper Series 4161, CESifo.
    19. Omar Al-Ubaydli & John A. List & Danielle LoRe & Dana Suskind, 2017. "Scaling for Economists: Lessons from the Non-Adherence Problem in the Medical Literature," Journal of Economic Perspectives, American Economic Association, vol. 31(4), pages 125-144, Fall.
    20. Florian Englmaier & Andreas Roider & Uwe Sunde, 2017. "The Role of Communication of Performance Schemes: Evidence from a Field Experiment," Management Science, INFORMS, vol. 63(12), pages 4061-4080, December.
    21. Rodney J. Andrews & Trevon D. Logan & Michael J. Sinkey, 2012. "Identifying Confirmatory Bias in the Field: Evidence from a Poll of Experts," NBER Working Papers 18064, National Bureau of Economic Research, Inc.

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    More about this item

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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