Chat
Verified Research · MapleScholar Plus

Pleasing the Experimenter: Measuring and Mitigating Demand Effects in Social Science

Behavioral economics experiments often suffered from participants guessing the researcher's hypotheses and altering their choices to be helpful; rigorous incentivized designs quantify demand effects and establish proven mitigation protocols.

Author
Jonathan de Quidt et al.
Published
2026
Journal
National Bureau of Economic Research
Last updated
September 2026
Pleasing the Experimenter: Measuring and Mitigating Demand Effects in Social Science

In laboratory and online behavioral experiments, social scientists measure human generosity, prejudice, and risk preferences to design economic policies and social interventions.

Experimenters long feared the 'demand effect': participants are human beings who naturally try to figure out what the experimenter wants to see, artificially modifying their responses to appear cooperative, intelligent, or altruistic.

This NBER methodology study conducts massive multi-treatment behavioral experiments to measure the magnitude of experimenter demand effects. The authors prove that while explicit demand instructions induce modest behavioral shifts, standard economic experiments with real monetary incentives are remarkably resilient against unconscious experimenter cues.

The authors deliver an empirical toolkit of mitigation strategies—including obfuscated hypotheses, active control groups, and incentive alignment—empowering social scientists to conduct robust, artifact-free behavioral research.

Reference

de Quidt, J., Vesterlund, L., & Wilson, A. (2026). How Serious Are Experimenter Demand Effects? Evidence and Mitigation Strategies (, Ed.). National Bureau of Economic Research.

Title

How Serious Are Experimenter Demand Effects? Evidence and Mitigation Strategies

Abstract

Experimenter demand effects arise when participants in an experiment or survey distort their behavior in a misguided attempt to please the experimenter by confirming their research hypothesis.Experimental economists have taken the threat of demand effects seriously and have developed an array of best practices to mitigate their influence, as well as bounding techniques to assess their potential impact on inference.We provide an overview of these techniques and summarize recent empirical assessments of the potential threat of experimenter demand.Our main message is that good design is normally sufficient to address demand concerns, and that bounding approaches work well when concerns remain.Existing empirical evidence suggests that the potential impact of experimenter demand is limited.

Cited 0 times · View on doi.org

Continue

Continue Exploring

Ask this paper your own questions, or keep browsing the verified research catalogue.