Understanding State-Dependent Price Setting: Evidence from a Lab Experiment

Last registered on April 22, 2025
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Pre-Trial

Trial Information

General Information

Title
Understanding State-Dependent Price Setting: Evidence from a Lab Experiment
RCT ID
AEARCTR-0015767
Initial registration date
April 16, 2025

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
April 22, 2025, 9:54 AM EDT

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

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Primary Investigator

Name
Salle Isabelle
Affiliation
University of Ottawa and University of Amsterdam
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Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2025-04-15
End date
2026-04-30
Keywords
Behavior, Finance & Microfinance
Additional Keywords
Markets; Macroeconomics
JEL code(s)
D22; D43; E31; E70
Secondary IDs
EB-12945
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This individual decision-making experiment investigates how firms adjust their prices in response to cost-push shocks, such as tariffs or supply-chain disruptions. Recent inflation episodes have shown that firms change prices more frequently and by larger amounts when inflation is relatively high, but real-world data often lacks the availability and the clarity needed to study the pass-though between cost-push shocks and selling prices in detail. We design a lab experiment where participants act as firms: setting prices, forecasting future prices, and responding to shocks in a simulated market.
Participants face three types of shocks—sudden tariffs, large gradual supply shocks, and small ones— and the rest of the market is simulated with rational behavior. The experiment also tests how price-setting changes depending on the market structure (many firms vs. very few) and the type of price adjustment friction (either a cognitive or monetary menu costs). Subjects make decisions under time pressure and are paid based on profits and forecast accuracy. The design allows researchers to isolate how firms respond to different cost environments in a controlled, replicable way.
External Link(s)

Registration Citation

Citation
Isabelle, Salle. 2025. "Understanding State-Dependent Price Setting: Evidence from a Lab Experiment." AEA RCT Registry. April 22. https://doi.org/10.1257/rct.15767-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
This is an RCT with a 2-by-2 design where the treatment variables are the degree of market competition (two firms versus 100) and the nominal rigidities (a small cognitive cost or a monetary menu cost for changing the price). We randomly attribute individual participants to one of the four following treatments upon entry in the lab. Everything else (incentives, payoff, underlying model, interface) is kept the same across all treatments.
Intervention Start Date
2025-04-15
Intervention End Date
2025-09-30

Primary Outcomes

Primary Outcomes (end points)
Dynamics of individual mark-ups, frequency of price changes, sizes of price changes
Primary Outcomes (explanation)
The mark-ups are the difference between the prices set by the subjects and their unit costs (that we set exogenously).

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This is an RCT with a 2-by-2 design where the treatment variables are the degree of market competition (two firms versus 100) and the nominal rigidities (a small cognitive cost or a monetary menu cost for changing the price). We randomly attribute individual participants to one of the four following treatments upon entry in the lab.
Subjects then play multiple independent sequences of price-setting games where they will be successively confronted with a large and a small cost-push shock, a large demand shock and a Markov-process shock describing highly uncertain changes in their costs (the order of the four shocks is randomized for each subject). Only two sequences are drawn for payment, where their cumulative profits are paid out to the subjects, on top of a participation fee and the forecasting bonus points drawn out of sequence (participants also have to submit forecast of the market price). Most of the student-subjects are in the lab, but some will be online to replicate the conditions of the entrepreneur-subjects. Two treatments only out of the four will be reproduced with entrepreneurs (about 30 by treatment).
Experimental Design Details
Not available
Randomization Method
Randomization done by a computer.
Randomization Unit
individual lab subject
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
240 student-subjects (60 per treatment) and 60 entrepreneur-subjects, for a total of 300 subjects.
Sample size: planned number of observations
300 subjects
Sample size (or number of clusters) by treatment arms
90 for two treatments (monetary menu costs and duopoly and another one chosen to be reproduced with the entrepreneurs) and 60 in each of the two other treatments.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
alpha = 0.05, at 80% power: * for frequency of price changes, an average of 75% (+/-10%) versus 70% is detectable with n = 63. * for sizes of price changes and average mark-up sizes, an average of 10% (+/- 5) versus a 7.5% is detectable with n = 63.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Amsterdam, Faculty of Economics and Business Institutional Review Board
IRB Approval Date
2025-04-08
IRB Approval Number
EB-12945
Analysis Plan