Simple Elicitation of Risk Attitudes, SERA

Last registered on August 04, 2020


Trial Information

General Information

Simple Elicitation of Risk Attitudes, SERA
Initial registration date
May 01, 2020

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
May 01, 2020, 3:32 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
August 04, 2020, 6:30 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.



Primary Investigator

University of Melbourne

Other Primary Investigator(s)

Additional Trial Information

Start date
End date
Secondary IDs
Attitudes toward risk are one of the primitive concepts in economics. Moreover, measuring risk preferences is critical for economic analysis and policy prescriptions alike. Therefore, it is only natural that economists have developed a variety of experimental methodologies. However, “risk elicitation is a risky business” (Friedman et al., 2014) with some of the current established methods being hard to understand for participants, difficulty to implement, or not able to capture attitudes well enough. In this study we propose an improved, simple but effective method to elicit on-line individuals’ attitudes toward risk, SERA. This new method sits between a fixed design (i.e., Multiple Price List, Holt & Laury, 2002) and a dynamically optimal design (i.e., BOARD, Wang, Filiba, & Camerer 2019) using an adaptive three questions procedure. Hence, it strikes a compromise among quality of the data, simplicity of implementation (for experimenters), and easiness to understand (for participants).
In an empirical validation we perform a within-subjects comparison of SERA with the most commonly used risk elicitation procedures (the MPL and the investment task) using as a metric of judgement the proportion of out-of-sample correctly predicted choices.
External Link(s)

Registration Citation

Garagnani, Michele. 2020. "Simple Elicitation of Risk Attitudes, SERA." AEA RCT Registry. August 04.
Experimental Details


SERA, a new method to elicit attitudes toward risk, is compared to established alterantive methods.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Proportion of correctly predicted choices out-of-sample across 3 different elicitation methods (SERA, MPL, investment task).
Primary Outcomes (explanation)
Proportion of correctly predicted choices (0,1) over 32 binary lottery choices.

Secondary Outcomes

Secondary Outcomes (end points)
Gender differences in risk attitudes.
Correlation between the estimated risk attitudes across the 3 eliciation methods.
Robustness of SERA to a within-subject repetition with re-scaled values.
Secondary Outcomes (explanation)
Gender differences in risk attitudes as evaluated across the 3 elicitation methods will be studied in an explorative way.

Experimental Design

Experimental Design
Within-subjects comparison of different risk-elicitation methods (SERA, MPL, investment task, qualitative risk assessment).
Experimental Design Details
All subjects will be presented with the same list of tasks and in the same order. Specifically, SERA, MPL, investment task, 32 binary-choice lotteries, 4 binary-choice lotteries involving a dominance relation, SERA with re-scaled values, gender question, qualitative risk assessment, attention checks.
Randomization Method
The order of the 36 lotteries is randomized and fixed to be the same for each participant.
One out of all decision situations will be randomily used to determine the earnings of subjects.
Randomization Unit
Individuals are the independent level of analysis in this study.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
N=400 is the desired sample size. Subjects will be recrited until the desired size is reached. However, because the experiment is performed on-line, more subjects will be invited to participate in the experiment. Subjects exceeding the desired sample will be included in the analysed sample.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
N=400 based on a power analysis for detecting a small effect size according to a test of proportions with multiple testing correction (SERA vs. MPL; SERA vs. Investment task) and in order to obtain a power of at least 0.8.

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Intervention Completion Date
May 15, 2020, 12:00 +00:00
Data Collection Complete
Data Collection Completion Date
May 15, 2020, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials