Measuring and Bounding Experimenter Demand
Jonathan de Quidt, Johannes Haushofer, Christopher Roth
American Economic Review · 2018 · Volume 108 · Issue 11
Abstract
We propose a technique for assessing robustness to demand effects of findings from experiments and surveys. The core idea is that by deliberately inducing demand in a structured way we can bound its influence. We present a model in which participants respond to their beliefs about the researcher's objectives. Bounds are obtained by manipulating those beliefs with "demand treatments." We apply the method to 11 classic tasks, and estimate bounds averaging 0.13 standard deviations, suggesting that typical demand effects are probably modest. We also show how to compute demand-robust treatment effects and how to structurally estimate the model.
Keywords
Survey Methods, Sampling Methods, Design of Experiments: General, Search, Learning, Information and Knowledge, Communication, Belief, Unawareness, Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
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