Data and Code for: "Belief Elicitation When More Than Money Matters: Controlling for Control"

Principal Investigator(s): View help for Principal Investigator(s) Jean-Pierre Benoît, London Business School; Juan Dubra, Universidad de Montevideo; Giorgia Romagnoli, University of Amsterdam

Version: View help for Version V1

Name	File Type	Size	Last Modified
overconfidenceBDM			10/27/2020 10:34:PM

Project Description

Summary: Incentive compatible mechanisms for eliciting beliefs typically presume that the
utility of money is state independent or that money is the only argument in utility
functions. However, subjects may have non-monetary objectives that confound these
mechanisms. In particular, psychologists have argued that people favour bets where
their ability is involved over equivalent random bets, a so-called preference for control.
We propose a new belief elicitation method that mitigates the control preference. Using
this method, we determine that under the ostensibly incentive compatible matching
probabilities method, subjects report self-beliefs 18% higher than their true beliefs in
order to increase control. Non-monetary objectives account for at least 68% of what
would normally be measured as overconfidence. We also find that control manifests
itself only as a desire for betting on doing well; betting on doing badly is perceived
as a negative. Our mechanism can be used to yield better measurements of beliefs in
contexts beyond the study of overconfidence.

Scope of Project

Subject Terms: Beliefs

JEL Classification:
      C91 Design of Experiments: Laboratory, Individual
      D01 Microeconomic Behavior: Underlying Principles
      D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

Geographic Coverage: Amsterdam (The Netherlands), Munich (Germany)

Universe:

- Students at the University of Amsterdam (for both the Fall 2016 and the Spring 2020 dataset) belonging to the subject pool of the CREED Lab.

- Students at the Ludwig-Maximilians University in Munich (for the Spring 2020 dataset) belonging to the subject pool of the MELESSA Lab.

Data Type(s): experimental data

Methodology

Response Rate:

For data collected in Fall 2016, the completion rate was 100%: The totality of participants who showed up in the Lab completed the experiment.

For data collected in Spring 2020, the completion rate was 98.6%: 9 subjects (over 619 subjects in total) started but did not complete the experiment.

Sampling:

The sampling followed the standard protocol for experimental studies conducted with a population of university students:

- Participants belong to a database (i.e., subject-pool) of active students interested in participating in experiments.

- Invitations indicating the time and date of the session were sent to the database and students could sign up for the sessions until seats were filled.

- Only students who signed-up could take part in the study at the selected time.

Data Source: Original Experimental data.

Collection Mode(s): computer-assisted personal interview (CAPI); on-site questionnaire

Scales: No scales were used

Weights:
No weighting
was used

Unit(s) of Observation: Individuals

Related Publications

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Published Versions

V1 [2022-07-19]

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