Evaluating the Sunk Cost Effect

Last registered on July 15, 2019
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Pre-Trial

Trial Information

General Information

Title
Evaluating the Sunk Cost Effect
RCT ID
AEARCTR-0004083
Initial registration date
July 04, 2019

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
July 08, 2019, 10:24 AM EDT

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

Last updated
July 15, 2019, 10:54 AM EDT

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

Locations

Country
United States of America
Region

Primary Investigator

Name
Daniel Sgroi
Affiliation
University of Warwick
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Other Primary Investigator(s)

PI Name
Anthony Tuckwell
PI Affiliation
University of Warwick
Contact Investigator
PI Name
David Ronayne
PI Affiliation
University of Oxford
Contact Investigator

Additional Trial Information

Status
In development
Start date
2019-07-19
End date
2020-07-19
Keywords
Other
Additional Keywords
sunk cost effect, sunk cost fallacy, cognitive ability, fluid intelligence, crystallised intelligence, reflective thinking, Raven's progressive matrices, international cognitive ability resource, cognitive reflection test, openness, Big Five Personality Inventory
JEL code(s)
D91, C91
Secondary IDs
Abstract
Experimental evidence is used to measure the sunk cost effect, and to evaluate the relationship between it and different measures of intelligence and reflective thinking, including fluid intelligence (Raven's progressive matrices), crystallised intelligence (International Cognitive Ability Resource: verbal reasoning item), the cognitive reflection test and openness from the Big Five Personality Inventory. In addition, the introduced experimental measure is used to validate an accessible scale-based (eighteen-item) measure for the sunk-cost effect based on self-reported choices in hypothetical scenarios.
External Link(s)

Registration Citation

Citation
Ronayne, David, Daniel Sgroi and Anthony Tuckwell. 2019. "Evaluating the Sunk Cost Effect." AEA RCT Registry. July 15. https://doi.org/10.1257/rct.4083-2.0
Former Citation
Ronayne, David, Daniel Sgroi and Anthony Tuckwell. 2019. "Evaluating the Sunk Cost Effect." AEA RCT Registry. July 15. https://www.socialscienceregistry.org/trials/4083/history/50052
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Subjects either complete the core "treatment" condition or one of two control conditions where there is no real-effort task (designed to control for the endowment effect and a general failure of individuals to maximize pecuniary outcomes, respectively).
Intervention Start Date
2019-07-19
Intervention End Date
2020-07-19

Primary Outcomes

Primary Outcomes (end points)
A binary variable equal to 1 if subjects stick with a lottery they earn via the real-effort task, or 0 if they switch to a dominant lottery.

We also collect information on different measures of intelligence (fluid and crystallised), reflective thinking, and openness, to correlate with the sunk-cost effect.

In addition, we aim to validate a scale-based measure for the sunk-cost effect based on self-reported choices in hypothetical scenarios.
Primary Outcomes (explanation)
To measure the sunk-cost effect, subjects are first asked to complete a task involving real effort (letter-counting) where their performance in the task determines whether or not they earn a lottery (which offers a positive amount of money in expectation). They are then presented with a choice to either keep the lottery they earned or to switch to a different lottery that (stochastically) dominates the one they earned. A maximizer of expected pecuniary outcomes would switch lotteries, but because of the effort sunk into the acquirement, some subjects may choose to keep the inferior (but earned) lottery.

Fluid intelligence (cognitive ability) is measured by subjects' (incentivized) answers to Raven's progressive matrices. Crystallised intelligence is measured by (incentivized) answers to the verbal reasoning item of the International Cognitive Ability Resource. The propensity for reflective thinking is captured by two measures: the Cognitive Reflection Test (incentivized); and the Openness scale from the Big Five Personality Inventory.

The scale-based measure of the sunk-cost effect is given by subjects' choices in a series of 18 hypothetical scenarios where they indicate on a 6-point Likert scale their preference between two hypothetical alternatives (where one corresponds to the sunk cost effect).

Secondary Outcomes

Secondary Outcomes (end points)
Age, gender, race, income, education, and political affiliation.

Additionally, two separate conditions account for the endowment effect and concerns that individuals may not maximize expected pecuniary payoffs. This allows us to see how much of any sunk-cost effect is due to these factors.
Secondary Outcomes (explanation)
To measure the role of the endowment effect in the lottery-choice, subjects are first told they have been endowed with the dominated lottery before being asked to make the choice between the dominant and dominated lottery. Concerns regarding whether subjects maximize expected pecuniary outcomes are assessed by giving subjects a straight choice between the two lotteries.

Experimental Design

Experimental Design
US subjects will be recruited online through Amazon's Mechanical Turk. The primary part of the design requires subjects to carry out a real-effort task. If they perform well enough, they earn a lottery. They are then presented with the choice between the lottery they earned and a dominant lottery. They exhibit the sunk-cost effect if they choose to stick with the earned (but dominated) lottery. Subjects then complete fluid and crystallised intelligence tests, a reflective thinking test, an 18-item scale that measures the sunk-cost effect via stated choices in hypothetical scenarios, and some intelligence, personality and demographic questions.
Experimental Design Details
Randomization Method
Randomization carried out by the software Qualtrics.
Randomization Unit
Randomization is at the individual level
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clustering.
Sample size: planned number of observations
530
Sample size (or number of clusters) by treatment arms
numbers are approximate
320: Main sunk-cost condition;
180: endowment effect control;
30: basic expected-pecuniary-payoff-maximizer check.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Given a 60/35/5% split between the conditions (as ordered above), and hypothesized effect sizes (the proportion who choose to keep the dominated lottery) of 0.2/0.1/0, n=506 subjects are required in total (two-sided tests for differences in proportions; 80% power; 5% significance) - 304/177/25 in each condition. Rounding up, we will gather 320/180/30, a total of n=530.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Oxford Economics Departmental Research Ethics Committee
IRB Approval Date
2019-04-12
IRB Approval Number
ECONCIA19-20-08
IRB Name
University of Warwick Humanities and Social Sciences Research Ethics Committee (HSSREC)
IRB Approval Date
2019-03-18
IRB Approval Number
HSS 83/18-19
Analysis Plan

Post-Trial

Post Trial Information

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials