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The Efficiency Impact of Regulatory Uncertainty: An Experimental Study
Last registered on January 29, 2018

Pre-Trial

Trial Information
General Information
Title
The Efficiency Impact of Regulatory Uncertainty: An Experimental Study
RCT ID
AEARCTR-0002675
Initial registration date
January 29, 2018
Last updated
January 29, 2018 6:15 PM EST
Location(s)
Region
Primary Investigator
Affiliation
College of Charleston
Other Primary Investigator(s)
PI Affiliation
The Citadel
Additional Trial Information
Status
In development
Start date
2018-01-29
End date
2018-12-31
Secondary IDs
Abstract
We design an experiment to examine the impact of regulatory uncertainty on efficiency. We use a double-auction design as a baseline and then examine two regulatory regimes: a known tax and an unknown, retroactively applied tax. That is, in the second regime participants are told there is the possibility that a tax will be imposed on any transactions made, but subjects do not find out if the tax will be imposed until after the double auction is completed. We compare the efficiency of the market with the known tax to that of the market with the unknown tax. We have two primary competing hypotheses: 1) the lost efficiency with the unknown tax will be less than with the known tax or 2) the lost efficiency with the unknown tax will be more that with the know tax.
External Link(s)
Registration Citation
Citation
Blackwell, Calvin and Russell Sobel. 2018. "The Efficiency Impact of Regulatory Uncertainty: An Experimental Study." AEA RCT Registry. January 29. https://doi.org/10.1257/rct.2675-1.0.
Former Citation
Blackwell, Calvin, Calvin Blackwell and Russell Sobel. 2018. "The Efficiency Impact of Regulatory Uncertainty: An Experimental Study." AEA RCT Registry. January 29. http://www.socialscienceregistry.org/trials/2675/history/25363.
Experimental Details
Interventions
Intervention(s)
We design an experiment to examine the impact of regulatory uncertainty on efficiency. We use a double-auction design as a baseline and then examine two regulatory regimes: a known tax and an unknown, retroactively applied tax. That is, in the second regime participants are told there is the possibility that a tax will be imposed on any transactions made, but subjects do not find out if the tax will be imposed until after the double auction is completed. We compare the efficiency of the market with the known tax to that of the market with the unknown tax. The unknown tax treatment will have two sub-treatments: a regime in which participants are told the probability that the tax will be imposed, and a regime in which the participants are merely told that the tax could occur, but are not given a precise probability. In both sub-treatments the actual probability of the tax being imposed will be 0.5.
Intervention Start Date
2018-01-29
Intervention End Date
2018-12-31
Primary Outcomes
Primary Outcomes (end points)
We will measure the economic surplus generated under each treatment. The ratio of actual surplus to potential surplus generated will be used as our measure of efficiency. We will compare efficiency under each treatment.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We design an experiment to examine the impact of regulatory uncertainty on efficiency. We use a double-auction design as a baseline and then examine two regulatory regimes: a known tax and an unknown, retroactively applied tax. That is, in the second regime participants are told there is the possibility that a tax will be imposed on any transactions made, but subjects do not find out if the tax will be imposed until after the double auction is completed. We compare the efficiency of the market with the known tax to that of the market with the unknown tax. The unknown tax treatment will have two sub-treatments: a regime in which participants are told the probability that the tax will be imposed, and a regime in which the participants are merely told that the tax could occur, but are not given a precise probability. In both sub-treatments the actual probability of the tax being imposed will be 0.5.
Experimental Design Details
Randomization Method
Coin flip
Randomization Unit
Individual level randomization. Participants are randomly assigned to a treatment.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
Experimental sessions will be run with 10 or 20 participants at a time. We plan to start with 4 sessions.
Sample size: planned number of observations
Initial set of sessions will include 60 participants.
Sample size (or number of clusters) by treatment arms
We plan to use 20 participants in our 2 control sessions, and then 20 participants in each of the sub-treatments (known probability vs unknown probability of tax).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
College of Charleston Institutional Review Board
IRB Approval Date
2017-10-19
IRB Approval Number
IRB-2017-07-12-144346
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS