On Asymmetric Tournaments

Last registered on November 15, 2024

Pre-Trial

Trial Information

General Information

Title
On Asymmetric Tournaments
RCT ID
AEARCTR-0014254
Initial registration date
November 05, 2024

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
November 15, 2024, 1:33 PM EST

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

Locations

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Primary Investigator

Affiliation
University of Fribourg

Other Primary Investigator(s)

PI Affiliation
PI Affiliation

Additional Trial Information

Status
In development
Start date
2024-11-07
End date
2028-02-29
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We consider a Lazear-Rosen tournament model involving a tournament administrator (employer or principal) and two agents competing for the prize (the promotion), and test experimentally the principal's inferences and the agents' responses. Specifically, one agent has an exogenous advantage, which is known and observable to the principal. The principal's incentives are designed such that it's in their best interest to design a promotion rule that levels the playing field ex post. We will test whether i) the principals promote optimally and if not, ii) agents anticipate this distortion and adapt effort accordingly.
External Link(s)

Registration Citation

Citation
Gomez-Martinez, Francisco, Holger Herz and Christian Zihlmann. 2024. "On Asymmetric Tournaments." AEA RCT Registry. November 15. https://doi.org/10.1257/rct.14254-1.0
Experimental Details

Interventions

Intervention(s)
The interventions:
1) In Baseline, the agents are fully symmetric.
2) In Treatment, the agents are asymmetric.
Intervention Start Date
2024-11-07
Intervention End Date
2025-04-30

Primary Outcomes

Primary Outcomes (end points)
1) Principal's choice of the promotion rule, in which they decide how to assign the high prize as a function of the difference of the output of agents (scale: -100 to 100).
2) Beliefs of agents regarding principal's choice of the allocation rule (scale: -100 to 100)
3) Agent's effort provision (effort choice 0 to 100).

Primary Outcomes (explanation)
The outcomes are directly observable and will not be constructed.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)
The outcomes are directly observable and will not be constructed.

Experimental Design

Experimental Design
See below.
Experimental Design Details
Not available
Randomization Method
First, participants randomly draw a card that assigns them to their computer / cubicle. This determines whether they are a principal or agent, whether they are in baseline or treatment, and also in which matching group of 9 participants they are (cluster). In each round, a group of 1 principal and 2 agents will be formed randomly by the computer (repeated random re-matching). Finally, the agent's error term is randomly drawn by the computer in each round, too.
Randomization Unit
We will cluster error terms on matching group level, since there might be correlated error terms within matching group.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Matching groups of 9, which means 216/9=24 clusters (matching groups) on which the SE's will be clustered on.

Sample size: planned number of observations
216 participants, 72 agent type 1, 72 agent type 2, 72 principals.
Sample size (or number of clusters) by treatment arms
We will collect around 200 observations. Given that we have sessions of the size of 18 participants, this will be 216 participants in total. This yields 24 matching groups à 9 participants; and 72 prinicipals, 72 agents of type 1, and 72 agents of type 2.

There will be 2 treatments. Thus, 216/2=108 participants per treatment arm. Of those, in each treatment: 36 principals, 36 agents type 1, 36 agents type 2.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We will use the following paramaters for the calculation of the minimum detectable effect size ("MDES"): power=0.8; p-value (error probability) = 0.05. We will also conduct the analogous non-parametric tests for the tests described further below, but calculate the MDES for the parametric variant. All numbers reported below obtained from GPower. We will cluster on matching group level, but the power calculations do not take this into account given the lack of method to do so. *************************************************************** Hypothesis 1a: Principals (in treatment) fail to choose the optimal promotion rule by not accounting for the shock of the advantaged player appropriately. Test 1: Two-sided t test against the theoretical optimal value of the allocation rule correction of 16. MDES t: .48. MDES Wilcoxon-rank-sum: .49 Hypothesis 1b: Principals in treatment promote more (often) sub-optimally than principals in baseline. Test 1: Treatment group differences: Subtracting the actual chosen value of the promotion rule from the optimal value (the size of suboptimal delegation), the principals in the treatment group differ from baseline principals - panel regression on treatment dummy. MDES: 0.24 Test 2: Treatment group differences: Frequency (number of deviations from optimal value) of suboptimal delegation the actual chosen value of the promotion rule from the optimal value (the size of suboptimal delegation), the principals in the treatment group differ from baseline principals. Linear panel: MDES: 0.24. In addition, Panel regression: Poisson or Neg-Bin regression. Test 3: Types created according to the average value of deviation across the 20 periods. If someone chooses optimal allocation rule on average classified as rational, otherwise not. Two sample t test, Mann-Whitney-U, MDES: .67. In addition probit regression. *************************************************************** Hypothesis 2a: Agents anticipate that principals promotion rules will be biased. Test 1: Belief of agents. Two-sided t test against the theoretical optimal value of the allocation rule correction of 16. MDES t: .33. MDES Wilcoxon-rank-sum: .34 Hypothesis 2b: Agents in treatment believe the principal promotes more suboptimally than agents in baseline. Test 1: Treatment group differences: Subtracting the actual chosen value (belief) about the principals' promotion rule from the optimal non-biased value 16 (=agents' belief about the size of suboptimal delegation), the agents in the treatment group differ from baseline agents - panel regression on treatment dummy. MDES: 0.17 *************************************************************** Hypothesis 3: In light of distorted incentives, (treated) agents adjust their effort provision downwards accordingly. Test 1: Treatment differences in effort exerted. Panel regression of effort on treatment dummy: MDES: 0.17 t-test (two sample independent): MDES: .48 Test 2: Deviation from the NE effort if the principal would choose the optimal allocation rule. Deviation larger for the treatment group. Treatment differences in effort exerted from optimal effort given principal's optimal decision. Panel regression of effort on treatment dummy: MDES: 0.17 Test 3: Best-response effort given beliefs of agents about the principal's alloaction rule. We do not expect substiantial treatment differences here given that agent's correctly anticipate principal's distortion.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
IRB (SES) of the University of Fribourg
IRB Approval Date
2024-03-26
IRB Approval Number
No. 2024-03-01