Risk Attitudes, Randomization to Treatment, and Self-Selection Into Experiments

Glenn W. Harrison, Morten Lau, E. Elisabet Rutström

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Randomization to treatment is fundamental to statistical control in the design of experiments. However randomization implies some uncertainty about treatment condition, and individuals differ in their preferences towards taking on risk. Since human subjects often volunteer for experiments or are allowed to drop out of the experiment at any time if they want to, it is possible that the sample observed in an experiment might be biased because of the risk of randomization. On the other hand, the widespread use of a guaranteed show-up fee that is non-stochastic may generate sample selection biases of the opposite direction, encouraging more risk averse samples into experiments. We directly test these hypotheses that risk attitudes play a role in sample selection. Our results suggest that randomization bias does affect the overall level of risk aversion in the sample we observe, but that it does not affect the demographic mix of risk attitudes in the sample. We show that the common use of non-stochastic show-up fees can generate samples that are more risk averse than would otherwise have been observed
Original languageEnglish
JournalJournal of Economic Behavior & Organization
Volume70
Issue number3
Pages (from-to)498-507
ISSN0167-2681
DOIs
Publication statusPublished - Jun 2009
Externally publishedYes

Keywords

  • Risk Aversion
  • Randomization
  • Sample Selection
  • Experiments

Cite this

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abstract = "Randomization to treatment is fundamental to statistical control in the design of experiments. However randomization implies some uncertainty about treatment condition, and individuals differ in their preferences towards taking on risk. Since human subjects often volunteer for experiments or are allowed to drop out of the experiment at any time if they want to, it is possible that the sample observed in an experiment might be biased because of the risk of randomization. On the other hand, the widespread use of a guaranteed show-up fee that is non-stochastic may generate sample selection biases of the opposite direction, encouraging more risk averse samples into experiments. We directly test these hypotheses that risk attitudes play a role in sample selection. Our results suggest that randomization bias does affect the overall level of risk aversion in the sample we observe, but that it does not affect the demographic mix of risk attitudes in the sample. We show that the common use of non-stochastic show-up fees can generate samples that are more risk averse than would otherwise have been observed",
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Risk Attitudes, Randomization to Treatment, and Self-Selection Into Experiments. / Harrison, Glenn W.; Lau, Morten; Rutström, E. Elisabet.

In: Journal of Economic Behavior & Organization, Vol. 70, No. 3, 06.2009, p. 498-507.

Research output: Contribution to journalJournal articleResearchpeer-review

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AU - Harrison, Glenn W.

AU - Lau, Morten

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AB - Randomization to treatment is fundamental to statistical control in the design of experiments. However randomization implies some uncertainty about treatment condition, and individuals differ in their preferences towards taking on risk. Since human subjects often volunteer for experiments or are allowed to drop out of the experiment at any time if they want to, it is possible that the sample observed in an experiment might be biased because of the risk of randomization. On the other hand, the widespread use of a guaranteed show-up fee that is non-stochastic may generate sample selection biases of the opposite direction, encouraging more risk averse samples into experiments. We directly test these hypotheses that risk attitudes play a role in sample selection. Our results suggest that randomization bias does affect the overall level of risk aversion in the sample we observe, but that it does not affect the demographic mix of risk attitudes in the sample. We show that the common use of non-stochastic show-up fees can generate samples that are more risk averse than would otherwise have been observed

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