Inflation expectations and Policy preferences

Last registered on January 04, 2021

Pre-Trial

Trial Information

General Information

Title
Inflation expectations and Policy preferences
RCT ID
AEARCTR-0006743
Initial registration date
December 24, 2020

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
January 04, 2021, 9:18 AM EST

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

Locations

Region
Region
Region
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Region
Region

Primary Investigator

Affiliation
Cornell University

Other Primary Investigator(s)

PI Affiliation
IDB
PI Affiliation
IDB

Additional Trial Information

Status
In development
Start date
2020-12-22
End date
2021-01-30
Secondary IDs
Abstract
This online survey experiment has two objectives. First, to study how individuals update their inflation expectations. Second, to examine how these inflation expectations affect policy preferences and preferences for redistribution. Bayesian learning models are typically used when studying expectations, however the endogenous nature of individual's updating has not yet been addressed. We will launch a large-scale online survey experiment across 17 countries of Latin America and the Caribbean.
External Link(s)

Registration Citation

Citation
Bottan, Nicolas, Bridget Hoffmann and Diego Vera-Cossio. 2021. "Inflation expectations and Policy preferences." AEA RCT Registry. January 04. https://doi.org/10.1257/rct.6743
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2020-12-22
Intervention End Date
2021-01-30

Primary Outcomes

Primary Outcomes (end points)
Survey measures of inflation expectations
Primary Outcomes (explanation)
The main outcome is an individual's inflation expectations, that is, the percent indicated by the respondent in the survey. There is a related 'intermediate' outcomes which is the individual's confidence in their response.

Secondary Outcomes

Secondary Outcomes (end points)
Survey measures of policy preferences
Secondary Outcomes (explanation)
We are interested in studying how inflation expectations affect different policy preferences and preferences for redistribution. We will study how they relate to preferences for helping the poor, reducing inequality, agreement with policy and government perceptions. We will also test whether changes in inflation expectations affect changes in perceptions about economic recovery.

Experimental Design

Experimental Design
This information experiment is embedded in the BID/Cornell coronavirus follow-up study, that has the objective of studying how the coronavirus is impacting households in Latin America and the Caribbean.

Subjects are first be asked about their prior beliefs about inflation expectations over the next 12 months and the degree of confidence in their answer. Next subjects will be randomly assigned into four groups: control, information on past inflation, information on precision, information on past inflation and precision. After answering a section unrelated to this study, posterior beliefs are elicited (ie, they are re-asked the original question). After this, subjects are asked about perceptions about recovery of the economy and about policy and redistribution preferences.

Our main regression will exploit not only information provision, but heterogeneity in the precision of subjects in the guess they made during the baseline. This feedback on precision also has a random component as explained above. We will also exploit heterogeneity between countries, exploiting not only variation in information but also heterogeneity in responses by country and cohort characteristics (like inflation history).
Experimental Design Details
Randomization Method
Randomization done by the online survey platform
Randomization Unit
Randomization is at the individual level
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Treatment is not clustered
Sample size: planned number of observations
Approximately 10,000
Sample size (or number of clusters) by treatment arms
Approximately 2,000
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Cornell University Institutional Review Board
IRB Approval Date
2020-09-21
IRB Approval Number
2009009806
IRB Name
Cornell University Institutional Review Board
IRB Approval Date
2020-11-18
IRB Approval Number
2011009932

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
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