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Representative Evidence on Exchange Asymmetries

Last registered on March 22, 2019

Pre-Trial

Trial Information

General Information

Title
Representative Evidence on Exchange Asymmetries
RCT ID
AEARCTR-0003992
Initial registration date
March 08, 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
March 22, 2019, 12:41 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
University of Heidelberg

Other Primary Investigator(s)

PI Affiliation
WZB Berlin

Additional Trial Information

Status
On going
Start date
2018-09-01
End date
2021-03-08
Secondary IDs
Abstract
The endowment effect describes the tendency of individuals to place greater value on objects they own than on the same or a similar object they do not own. This drives a wedge between the willingness to pay and willingness to accept for an object, or leads individuals to trade a randomly assigned object significantly less often than predicted by standard theory, resulting in an exchange asymmetry. In this project, we investigate the prevalence of exchange asymmetries in the general population and test a leading theoretical explanation.
External Link(s)

Registration Citation

Citation
Fehr, Dietmar and Dorothea Kuebler. 2019. "Representative Evidence on Exchange Asymmetries." AEA RCT Registry. March 22. https://doi.org/10.1257/rct.3992-1.0
Former Citation
Fehr, Dietmar and Dorothea Kuebler. 2019. "Representative Evidence on Exchange Asymmetries." AEA RCT Registry. March 22. https://www.socialscienceregistry.org/trials/3992/history/43881
Experimental Details

Interventions

Intervention(s)
We implement our study in the SOEP Innovation Sample (SOEP IS, Richter and Schupp, 2015). The SOEP IS is a representative longitudinal survey of German households. Participating households receive monetary incentives for completing the surveys and, in addition, receive a small item in the beginning of a survey as appreciation for the time (household gift). We use this unique feature of the survey for our experiment and implement a modified version of the exchange paradigm introduced by Knetsch (1989).
Intervention Start Date
2018-09-01
Intervention End Date
2019-04-15

Primary Outcomes

Primary Outcomes (end points)
(i) the share of respondents who keep their assigned item and
(ii) the total trading rates.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Loss aversion
Secondary Outcomes (explanation)
We measure loss aversion with two hypothetical choice lists. Specifically, we elicit respondents’ loss aversion with two separate questions before and after the trading possibility. The first question consists of six hypothetical lotteries that involve an equal chance of a gain or a loss. For each lottery, respondents have to indicate whether they would accept or reject the lottery. The number of rejected lotteries is an indicator for individuals’ loss aversion. We ask this question before the trading possibility in the household survey. After the trading possibility and as part of the personal questionnaire, we use two additional questions to measure loss aversion. That is, we elicit the hypothetical minimum gain X to accept a fair gamble where a respondent has an equal chance to hypothetically win X or lose 25 Euro in one question and win X or lose 100 Euro in the other.

Experimental Design

Experimental Design
Our design is based on the exchange paradigm introduced by Knetsch (1989). That is, we randomly endow households with one of two equally valued items. At the end of the household survey, interviewers offer respondents the opportunity to trade the endowed item for the alternative item. After completing trades (if any), the interviewers continue with personal questionnaires for all household members.
Experimental Design Details
Our design is based on the exchange paradigm introduced by Knetsch (1989). That is, we randomly endow households with one of two equally valued items. The items were a microfiber towel and a notebook with a pen. Both items are worth about 5 euro. At the end of the household survey, interviewers offer respondents the opportunity to trade the endowed item for the alternative item. After completing trades (if any), the interviewers continue with personal questionnaires for all household members.

We randomize respondents – typically the head of household or person with most knowledge about household topics – into three treatments. In about 10 percent of the total sample, respondents simply have a choice between the two items, and there is be no opportunity to trade the item at the end (“choice condition”). In about 45% of the sample, we implement the “baseline condition”. That is, half of the respondents receive the towel as a present (“group A” and “item A”) and the other half of the respondents receive the notebook (“group B” and “item B”). More specifically, the survey software randomizes the two items in the beginning of the interview, interviewers show both items and assign the item as indicated by the survey software. At the end of the household survey, respondents can trade their assigned item with the other item. In the remaining 45% of the sample, we follow the same procedure as in the “baseline condition”, but inform respondents immediately after assigning items that they have the possibility to exchange their endowed item with the alternative item at the end of the survey (“expectations condition”).
Randomization Method
Randomization through survey software
Randomization Unit
First we randomize households to one of the three conditions described above and then we randomize the assignment of the two items.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
about 3,300
Sample size: planned number of observations
about 3,300. The exact number depends on panel stability.
Sample size (or number of clusters) by treatment arms
10% of the total sample participate in the choice condition
45% in the treatment without information about the trading possibility (baseline condition)
45% in the treatment with information about the trading possibility (expectation condition)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number

Post-Trial

Post Trial Information

Study Withdrawal

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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