Legislative Bargaining with Private Information

Last registered on August 18, 2022


Trial Information

General Information

Legislative Bargaining with Private Information
Initial registration date
July 13, 2022

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
August 18, 2022, 3:13 PM EDT

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



Primary Investigator

Heidelberg University

Other Primary Investigator(s)

PI Affiliation
Heidelberg University

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
We conduct a three person legislative bargaining experiment in the lab. The main treatment variable is the decision rule (unanimity vs. majority rule). The game involves a probability of "breakdown" following failure of a proposal. In case of breakdown, players receive exogenously fixed breakdown values. These breakdown values are private information in some of the experimental periods. Our main hypothesis is that subjects are more likely to vote "no" (on comparable proposals) and to claim (via free form messages) that they have a high breakdown value under unanimity rule than under majority rule, resulting in lower agreement rates.
External Link(s)

Registration Citation

Piazolo, David and Christoph Vanberg. 2022. "Legislative Bargaining with Private Information." AEA RCT Registry. August 18. https://doi.org/10.1257/rct.9732-1.0
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Experimental Details


See abstract
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Types of proposals made for given parameters (rule, breakdown values, breakdown probability)
Frequency of yes/no votes given (types of) proposals and parameters.
Frequency of agreement given parameters.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The game involves a fixed proposer and two responders. The proposer has two chances to make a proposal, with a probability of breakdown following failure the first proposal and certain breakdown following failure of the second. Breakdown values are randomly assigned (high or low) independently in each round. The continuation probability is varied between sessions. Subjects play 10 Rounds of complete and 10 rounds of private information regarding the breakdown values (order varied between sessions). When voting on the first proposal, voters can optionally send a message that is displayed to all participants together with voting results.
Experimental Design Details
The group bargains over the division of 100 Points worth a total of 20 EUR. The game is repeated 20 times with random rematching. 10 games are played under complete information (breakdown values commonly known), 10 under private information (breakdown values known only privately). Three rounds are randomly chosen for payment.
Responder disagreement values are equal to either 10 or 45 points with equal probability. Proposer breakdown value is zero (always commonly known). The game lasts for at most two periods. If the first proposal fails, breakdown occurs with probability 1/6 or 5/6 (a treatment parameter, between subjects). If the second proposal fails, breakdown is certain. In addition to the the proposer subjects' proposal, a computer generated proposal is presented for a vote in round 1. Following voting on both proposals, one is randomly chosen to count. This is to observe voting on five specific proposals that we introduce exogenously:

Three (pairs of) proposals where a one subject (e.g. B) should expect to be pivotal:
Unanimity: (44,10,46), (34,20,46), (24,30,46)
Majority: (90,10,0), (80,20,0), (70,30,0)
These proposals come in "pairs" where subject B is offered the same amounts, respectively, under both rules. In every case, subject B should expect to be pivotal: Under unanimity, because the other is offered 46 and should therefore vote "yes", under majority, because the other is offered 0 and should therefore vote "no". We intend to compare acceptance rates by B between rules within these pairs.
The main prediction is that B is less likely to vote "yes" on these proposals under unanimity rule. For example: Both "types" (10 and 45) should vote "no" on (44,10,46) given unanimity rule. Under majority rule, both types should vote "yes" on (90,10,0) when the continuation probability is 5/6 and (only) low types (10) should vote "yes" when the continuation probability is 1/6.

One proposal (same under both rules) which should fail under unanimity rule and pass under majority rule:

One proposal (same under both rules) corresponding to a "fair" split:
Under unanimity, responders vote "no" unless breakdown value = 10 and continuation probability = 1/6
Under majority, responders vote "yes" unless breakdown value = 45 and continuation probability = 1/6

These and similar predictions come from our theoretical analysis. (Bayesian equilibrium in sequentially weakly undominated strategies.)

In addition to these Hypotheses we intend to investigate voting behavior on proposals that arise endogenously. Overall, the method will be to compare the frequency of "yes" votes between rules while controlling for parameters and the likelihood of being pivotal.
Randomization Method
All game parameters and the matching scheme are randomised using a computer ex ante and fixed for all sessions.
The incidence of breakdown following period 1 proposals is randomised "live" during sessions (computer).
The assignment of subjects to treatments is randomised by drawing cards for seat allocation in the laboratory.
Randomization Unit
Individual subjects.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
12 Sessions, each with two matching groups of size 9, for a total of 216 subjects.
6 Sessions involving continuation probability 1/6
6 Sessions involving continuation probability 5/6
Each session one matching group unanimity, one majority
Sample size: planned number of observations
See above
Sample size (or number of clusters) by treatment arms
See above
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
IRB of the Faculty of Economics and Social Sciences at Heidelberg University
IRB Approval Date
IRB Approval Number


Post Trial Information

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

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Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials