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Two Selection Problems, One Bias Term: Experimental Sign-Up Is Treatment Choice in Disguise

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Listed:
  • John List

Abstract

Consider a referee report containing the sentence: "Assignment to treatment was voluntary, though the authors acknowledge this as a limitation in the conclusion." The Editor would summarily reject. Now replace "assignment to treatment" with "entry into the experimental sample," and the sentence describes the modal published experiment. This study shows that both biases are the same mathematical object. The bias from non-random sample entry is the sorting-on-gains term from the classic selection decomposition. Interestingly, they both admit an isomorphic Roy micro-foundation and inverse-Mills characterization. A simple calibration reveals that for the typical experiment, the observed bias can be large. One solution to this bias is to conduct a natural field experiment (NFE). When an NFE is not possible, three alternative reporting practices are offered.

Suggested Citation

  • John List, 2026. "Two Selection Problems, One Bias Term: Experimental Sign-Up Is Treatment Choice in Disguise," Natural Field Experiments 00837, The Field Experiments Website.
    • Handle: RePEc:feb:natura:00837
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    References listed on IDEAS

    as
    1. John A. List, 2026. "Make science more reliable: study people as they go about their lives," Nature, Nature, vol. 654(8120), pages 863-866, June.
    2. Omar Al-Ubaydli & John A. List & Dana L. Suskind, 2017. "What Can We Learn from Experiments? Understanding the Threats to the Scalability of Experimental Results," American Economic Review, American Economic Association, vol. 107(5), pages 282-286, May.
    3. 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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • 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
    • C99 - Mathematical and Quantitative Methods - - Design of Experiments - - - Other

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