The Design of Recurrent Procurement Auctions

Last registered on March 13, 2025
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Pre-Trial

Trial Information

General Information

Title
The Design of Recurrent Procurement Auctions
RCT ID
AEARCTR-0012049
Initial registration date
October 16, 2023

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
October 17, 2023, 1:54 PM EDT

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

Last updated
March 13, 2025, 10:10 AM EDT

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

Locations

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Primary Investigator

Name
Carlos Vega
Affiliation
University of East Anglia, Philippine Competition Commission
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Other Primary Investigator(s)

PI Name
Sean Ennis
PI Affiliation
University of East Anglia, Centre for Competition Policy
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PI Name
Timothy Salmon
PI Affiliation
Southern Methodist University
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PI Name
Farasat Bokhari
PI Affiliation
Loughborough University
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Additional Trial Information

Status
In development
Start date
2023-10-18
End date
2026-12-31
Keywords
Behavior, Firms & Productivity
Additional Keywords
dynamic games, auctions, experiments, procurement, pricing, market structure
JEL code(s)
C73, C91, D44, H57, L11
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We look at the behavior of laboratory auction markets when a dynamic reserve price is imposed. When firms exit markets due to high costs, competition wavers and bidders bid less aggressively. Ensuing higher prices could conceivably be modulated by a reserve price mechanism that uses the lowest bid from the previous period. Using a controlled setting, we show how dynamics in reserve price setting influence bid shading and if the behavior of these markets are more consistent with standard predictions or with the focal point hypothesis.
External Link(s)

Registration Citation

Citation
Bokhari, Farasat et al. 2025. "The Design of Recurrent Procurement Auctions." AEA RCT Registry. March 13. https://doi.org/10.1257/rct.12049-2.0
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Experimental Details

Interventions

Intervention(s)
Our intervention in procurement auction markets involves settting a dynamic reserve price based on outcomes from a previous round. Specifically, we will use the winning bid in the previous period to set the maximum bid possible for bidders in the next round. Two variants will be investigated. The first involves a single auction market, and the second uses a multi market setting. In the first variant, a market's bid cap is determined by the winning bid in that market from the previous round, while the second variant uses another market's winning bid in the previous round.
Intervention Start Date
2023-10-18
Intervention End Date
2025-05-30

Primary Outcomes

Primary Outcomes (end points)
bidding behaviour (bids), auction price, entry (number of sellers), efficiency
Primary Outcomes (explanation)
Efficiency of auctions will be measured as the number of times that the object goes to the lowest cost bidder over the total number of auctions.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment requires four treatments using the low price sealed bid mechanism: one without a dynamic reserve price, one using a dynamic reserve price in a single market, the third using a dynamic reserve price with multiple markets, and the fourth without a bid cap splitting the award between the two lowest bidders.
Using a between-subjects design, each participant is exposed to only one of the three conditions and plays multi-round auctions.
In round 1 of each sequence, everyone is told their realized cost and everyone participates. In each subsequent round, participants are told their realized cost for that round and will be allowed to choose whether or not to participate in the auction for that round. If they choose not to participate in a round, they will not be able to participate for the remaining rounds in that sequence, but they will be able to rejoin in the subsequent sequence. After deciding to participate, the participants are informed of the number of competitors who are participating. Each competitor will have received a realized cost using the same method with all draws being independent.
Experimental Design Details
Not available
Randomization Method
randomization by a computer
Randomization Unit
group of students
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
96 groups
Sample size: planned number of observations
14,400 bids
Sample size (or number of clusters) by treatment arms
120 students each treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of East Anglia School of Economics Research (ECO S-REC)Ethics Subcommittee
IRB Approval Date
2023-10-12
IRB Approval Number
ETH2324-0065
IRB Name
University of East Anglia School of Economics Research (ECO S-REC)Ethics Subcommittee
IRB Approval Date
2023-10-16
IRB Approval Number
ETH2324-0451(amendments)
IRB Name
University of East Anglia School of Economics Research (ECO S-REC)Ethics Subcommittee
IRB Approval Date
2025-03-13
IRB Approval Number
ETH2425-1779
Analysis Plan