Monetary Policy Communications and their Effects on Household Inflation Expectations
Last registered on December 06, 2018

Pre-Trial

Trial Information
General Information
Title
Monetary Policy Communications and their Effects on Household Inflation Expectations
RCT ID
AEARCTR-0003649
Initial registration date
December 05, 2018
Last updated
December 06, 2018 8:37 AM EST
Location(s)

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Primary Investigator
Affiliation
University of Texas at Austin
Other Primary Investigator(s)
PI Affiliation
University of Chicago
PI Affiliation
University of California at Berkeley
Additional Trial Information
Status
On going
Start date
2018-04-30
End date
2019-01-31
Secondary IDs
Abstract
We study how different forms of communication can influence inflation expectations of individuals in a randomized controlled trial. We first solicit individuals’ distribution of inflation expectations and provide eight different forms of information regarding inflation. We then study how these different types of information affect the beliefs of individuals over time relative to those in control groups that either receive no information or irrelevant information.
External Link(s)
Registration Citation
Citation
Coibion, Olivier, Yuriy Gorodnichenko and Michael Weber. 2018. "Monetary Policy Communications and their Effects on Household Inflation Expectations." AEA RCT Registry. December 06. https://www.socialscienceregistry.org/trials/3649/history/38448
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2018-04-30
Intervention End Date
2018-06-30
Primary Outcomes
Primary Outcomes (end points)
Inflation expectations
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We study how different forms of communication can influence inflation expectations of individuals in a randomized controlled trial. We first solicit individuals’ distribution of inflation expectations and provide eight different forms of information regarding inflation. We then study how these different types of information affect the beliefs of individuals over time relative to those in control groups that either receive no information or irrelevant information.
Experimental Design Details
Not available
Randomization Method
Randomization done by private contracting firm that implements survey.
Randomization Unit
individual.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
no clusters
Sample size: planned number of observations
20,000 individuals
Sample size (or number of clusters) by treatment arms
2200 individuals per treatment group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number