Interaction Economics: Instruments that Measure Social­ Computational Systems

Last registered on November 13, 2018
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Pre-Trial

Trial Information

General Information

Title
Interaction Economics: Instruments that Measure Social­ Computational Systems
RCT ID
AEARCTR-0003541
Initial registration date
November 07, 2018

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 13, 2018, 1:05 AM EST

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

Locations

Country
United States of America
Region

Primary Investigator

Name
Claus Portner
Affiliation
Seattle University
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
Completed
Start date
2014-03-18
End date
2014-11-25
Keywords
Firms & Productivity, Labor, Other
Additional Keywords
JEL code(s)
Secondary IDs
1110965
Abstract
The purpose of this research is to test a set of fundamental economic theories that previously has not been tested experimentally. The main question is the extent to which workers require additional compensation for performing work that is less appealing and, if so, how large this effect is. The research is conducted using the online labor market Amazon's Mechanical Turk. For each experiment, we offered a job on Mechanical Turk and randomly vary the pay offered and the job characteristics. We observe workers once they click on our offered job. Once workers click on the offered job, they are presented with a description of the job and the randomly allocated job characteristics. We then observe whether the worker decides to perform the job and, if so, how much work they do. Once the experiment is over we surveyed the workers to collect basic demographic information (no identifiable information was collected).
External Link(s)

Registration Citation

Citation
Portner, Claus. 2018. "Interaction Economics: Instruments that Measure Social­ Computational Systems." AEA RCT Registry. November 13. https://doi.org/10.1257/rct.3541-1.0
Former Citation
Portner, Claus. 2018. "Interaction Economics: Instruments that Measure Social­ Computational Systems." AEA RCT Registry. November 13. https://www.socialscienceregistry.org/trials/3541/history/37097
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
We ran experiments to test one of the oldest theories in economics—Adam Smith's theory of the Compensating Wage Differential. This theory has been influential since it was first proposed in the "Wealth of Nations." The theory has, however, never been validated by experimental data because the experiments required have been impractical. We demonstrate that we can measure four of the five dimensions of a job that Adam Smith defined in his theory:
1) Pleasantness of the work.
2) Amount of learning required to perform the job.
3) Probability of success in the job.
4) Constancy of employment available.
For each of these conditions, we designed experimental equivalents. We implemented this study with two different real­-world tasks that are commonly found in Internet labor markets, and for each, we have designed manipulations to all four of these dimensions.
Intervention Start Date
2014-03-18
Intervention End Date
2014-11-25

Primary Outcomes

Primary Outcomes (end points)
The decision whether to work or not on our job and how much work to do if working.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Once a worker clicks on our offered task, the worker will randomly be assigned to an experimental condition and a pay offered. Each experiment offers two or more conditions or treatments and a variety of levels of pay per task completed, and each worker will see one of these conditions and pay levels. We then observe whether the worker accepts the task with that condition and pay level, and, if so, how many tasks she performs. The number of tasks performed is the main outcome of interest. All information is gathered electronically by the system we have set up.
Experimental Design Details
Randomization Method
Randomization done by computer program
Randomization Unit
Individual worker
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
6,499 workers
Sample size (or number of clusters) by treatment arms
This was a factorial experiment, so there are no treatment arms per se.
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 Washington Human Subjects Division
IRB Approval Date
2013-08-21
IRB Approval Number
45700
IRB Name
SU Institutional Review Board
IRB Approval Date
2013-07-13
IRB Approval Number
N/A
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
November 25, 2014, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
November 25, 2014, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
6,499 workers
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
No
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials