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How a novel mechanism for product testing organizations improves markets with asymmetric information
Last registered on October 30, 2020

Pre-Trial

Trial Information
General Information
Title
How a novel mechanism for product testing organizations improves markets with asymmetric information
RCT ID
AEARCTR-0006685
Initial registration date
Not yet registered
Last updated
October 30, 2020 9:05 AM EDT
Location(s)
Region
Primary Investigator
Affiliation
University of Michigan
Other Primary Investigator(s)
Additional Trial Information
Status
On going
Start date
2017-01-10
End date
2020-11-24
Secondary IDs
Abstract
Sellers are often better informed about product quality than buyers. Product testing organizations like Consumer Reports (US) or Stiftung Warentest (Germany) can reduce this asymmetry by providing credible information. Due to limited capacities, however, the sample of tested product models – often bestsellers – may lead to suboptimal information. We propose a novel mechanism, and develop a game to derive testable predictions. We show theoretically that a unique Nash equilibrium exists in which our mechanism leads to optimal information, thus to the consumer surplus of a world of complete information, while selecting bestsellers does not. Subsequently, we confirm experimentally that our new mechanism increases consumer surplus.
External Link(s)
Registration Citation
Citation
Vollstaedt, Ulrike. 2020. "How a novel mechanism for product testing organizations improves markets with asymmetric information." AEA RCT Registry. October 30. https://doi.org/10.1257/rct.6685-1.0.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2017-01-10
Intervention End Date
2018-12-14
Primary Outcomes
Primary Outcomes (end points)
consumer surplus
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We design four experimental treatments. The first two represent currently used product model selection mechanisms (called BESTSELLERS), the latter two represent our new product model selection mechanism (called SELLERS APPLY).

Experimental Design Details
BESTSELLERS-WORST CASE: To model a scenario in which the market functions extremely poorly, we include the worst-case-scenario regarding the bestselling product models, i.e., the bestsellers are chosen to be the product models farthest away from the globally non-dominated ones. BESTSELLERS-RANDOM: We add an intermediate scenario regarding the bestselling product models. More specifically, bestsellers are chosen randomly among all product models. We include this treatment to investigate whether our new mechanisms outperforms chance. SELLERS APPLY-LYING POSS: We include this treatment to provide sellers with the option of stating false qualities towards the product testing organization when applying to be tested, thus the name LYING POSS(ible). SELLERS APPLY-TRUTH: We include this treatment to investigate an ideal setting for our new mechanism in which sellers can apply to be tested while technically not being able to state false qualities towards the product testing organization.
Randomization Method
randomization done by a computer
Randomization Unit
experimental session as one level of randomization (regarding which treatment), individual as a second level of randomization (regarding whether an a person participates as a seller or buyer, and with which ID)
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
25 experimental sessions
Sample size: planned number of observations
575 participants
Sample size (or number of clusters) by treatment arms
Bestsellers-WorstCase: 5 experimental sessions, Bestsellers-Random: 5 experimental sessions, SellersApply-LyingPoss: 5 experimental sessions, SellersApply-Truth: 10 experimental sessions

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
Intervention
Is the intervention completed?
No
Is 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