x

Please fill out this short user survey of only 3 questions in order to help us improve the site. We appreciate your feedback!
Effort and Risk Taking under Performance Thresholds
Last registered on April 13, 2021

Pre-Trial

Trial Information
General Information
Title
Effort and Risk Taking under Performance Thresholds
RCT ID
AEARCTR-0007536
Initial registration date
April 12, 2021
Last updated
April 13, 2021 11:34 AM EDT
Location(s)

This section is unavailable to the public. Use the button below to request access to this information.

Request Information
Primary Investigator
Affiliation
Uni Essex
Other Primary Investigator(s)
PI Affiliation
London School of Economics
PI Affiliation
University of Leicester
PI Affiliation
University of Copenhagen
Additional Trial Information
Status
In development
Start date
2021-04-13
End date
2021-12-13
Secondary IDs
Abstract
We study the effect of performance thresholds on effort and risk-taking in economic decisions. Using a theoretical model, we show that if action is required to meet the threshold, then effort unambiguously increases. The effect of the threshold on risk taking is ambiguous: risk taking increases for thresholds of intermediate levels and decreases otherwise. Our experiment tests whether effort and risk-taking are affected by thresholds of different difficulty. It then studies whether these effects are in line with the model.
External Link(s)
Registration Citation
Citation
Campos Mercade, Pol et al. 2021. "Effort and Risk Taking under Performance Thresholds." AEA RCT Registry. April 13. https://doi.org/10.1257/rct.7536-1.0.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2021-04-13
Intervention End Date
2021-06-13
Primary Outcomes
Primary Outcomes (end points)
The change in effort and risk taking behaviour after the introduction of the threshold.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
N/A
Experimental Design Details
Not available
Randomization Method
The design is within subjects. The order of tasks is randomized by the software (Qualtrics).
Randomization Unit
Subjects
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
Subjects
Sample size: planned number of observations
At least 500 subjects and up to the number that ensures 200 Round 1 choices between 40 and 80 (see below).
Sample size (or number of clusters) by treatment arms
500+ subjects, within subject treatment variation. Each subject answers 6 questions with high thresholds and 6 with low thresholds, implying 3000+ (non-independent) observations of high thresholds and 3000+ (non-independent) observations of low thresholds.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Main test: We are interested in testing whether different thresholds trigger different effort provision and risk taking. To do so, for the main test we define two kinds of threshold for each participant, based on the participant’s baseline effort provision: low thresholds and high thresholds. We will restrict the analysis to people who in Round 1 provided effort between 40 and 80. For this subsample, we will define: - Low threshold: The thresholds of 20 and 40 tasks. - High threshold: The thresholds of 80 and 100 tasks. Test 1: We regress \Delta Effort, defined as the difference between effort choices in Rounds 9-20 and corresponding choices in Rounds 6-8, on dummy variables indicating whether the threshold is low or high. Controls will be gender, age, social class, ethnicity, and education. Standard errors will be clustered at the participant level. Test 2: We regress \Delta Risk, defined as the difference between risk choices in Rounds 9-20 and corresponding choices in Rounds 6-8, on dummy variables indicating whether the threshold is low or high. Controls will be gender, age, social class, ethnicity, and education. Standard errors will be clustered at the participant level. We performed a power analysis using a pilot with 34 participants. To do so, we performed simulations in which we bootstrapped the sample and assigned treatments (thresholds) randomly (code available upon request). We conclude that with a sample of 500 participants, we expect around 200 participants with Round 1 choices between 40 and 80 and in this case we have 80% power to detect at the 5% level an effect of high thresholds on effort of 2.5 tasks and on risk of 7 percentage points. Secondary tests: To more closely test the model, we will define four types of thresholds: - the low threshold to be the highest threshold weakly below the participant’s effort choice in the corresponding Round 6-8, - the high threshold to be the lowest threshold strictly above the participant’s effort choice in the corresponding Round 6-8, - the very high threshold to be any threshold at least 21 units but less than 40 units above the participant’s effort choice in the corresponding Round 6-8 and - the extremely high threshold to be any threshold at least 41 units above the participant’s effort choice in the corresponding Round 6-8. Note that any of these might be missing for some participants. Note also that we do not define very low and extremely low thresholds as we do not expect behavioural differences between those types of thresholds. We will run the same regressions as defined above using these four thresholds and study to what extent they are in line with the model. Tertiary tests: - We are interested in exploring heterogeneity by other background variables, and in particular gender. - We are interested in comparing effort choices in R2-5 with R1 depending on the difficulty of the threshold.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Ethics Sub Committee 3 University of Essex
IRB Approval Date
2021-01-28
IRB Approval Number
ETH2021-0870