Does the source of uncertainty matter in central bank communication?

Last registered on June 23, 2023

Pre-Trial

Trial Information

General Information

Title
Does the source of uncertainty matter in central bank communication?
RCT ID
AEARCTR-0011509
Initial registration date
June 12, 2023

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
June 23, 2023, 4:17 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
Dongbei University of Finance and Economics

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2023-06-19
End date
2023-07-28
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We investigate the impact of central banks communicating uncertainty on investor expectation formation and on market price dynamics. In a lab experiment, we vary the type of and the source of uncertainty central banks communicated and form a 2 by 2 design, i.e., 2 types of communicated uncertainty (communicating risk vs. communicating ambiguity) X 2 sources of communicated uncertainty (communicating uncertainty from policy implementation source vs. policy intensity source). With this design, we are able to examine the difference of impact between communicating risk and communicating ambiguity within each source. Furthermore, between different sources of uncertainty, we are able to examine the difference of impact between communicating uncertainty from the policy implementation source and communicating uncertainty from the policy intensity source. Finally, we are also able to examine the difference between communicating risk and communicating ambiguity in different sources.
External Link(s)

Registration Citation

Citation
Li, Jiangyan. 2023. "Does the source of uncertainty matter in central bank communication?." AEA RCT Registry. June 23. https://doi.org/10.1257/rct.11509-1.0
Experimental Details

Interventions

Intervention(s)
Intervention 1: The source of uncertainty communicated by central banks
In this study, we classify the uncertainty central banks communicated as from two different sources, i.e., from policy implementation source and from policy intensity source. To investigate whether the impact of central banks communicating uncertainty is source dependent, we add our first intervention concerning the source of communicated uncertainty. Specifically, the communicated uncertainty arises from the implementation of a policy in one pair of treatments while arises from the intensity of a policy in another pair of treatments.

Intervention 2: The type of uncertainty communicated by central banks
To investigate whether central banks communicating different types of uncertainty results in different impacts, we add our second intervention about the type of uncertainty central banks communicated. Specifically, within each source of uncertainty, central banks communicate risk in one treatment while communicate ambiguity in another treatment.
Intervention Start Date
2023-06-20
Intervention End Date
2023-07-15

Primary Outcomes

Primary Outcomes (end points)
Market price dynamics, Individual price forecast, and individual forecasting rule in each treatment
Primary Outcomes (explanation)
1. Market price bubble: Measuring bubble size by calculating the deviation of market price from the steady state price in the Learning-to-Forecast Experiment.
2. Market price dynamics: The variance of market price
3. Individual forecast accuracy: The difference between market price and individual price forecasts
4. Individual coordination speed: The standard deviation of individual price forecasts

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Basic setup:
- A learning-to-forecast experiment with interest rate policy incorporated.
- A policy maker communicates both the policy implementation probability and policy implementation magnitude with participants.

Treatments:
Policy implementation source
1) treatment IMP-RISK: communicating risk concerning the implementation probability, i.e., communicating the certain implementation probability.
2) treatment IMP-AMB: communicate ambiguity regarding the implementation probability, i.e., the certain implementation probability is not known.

Policy intensity source
3) treatment INT-RISK: communicating risk concerning the possible policy intensity, i.e., communicating the certain probability for each type of policy intensity
4) treatment INT-AMB: communicating ambiguity concerning the possible policy intensity, i.e., the certain probability for each type of policy intensity is not known.
Experimental Design Details
Randomization Method
Randomization will be done by a computer.
Randomization Unit
Randomization mainly occurs for the ways policy communication information is conveyed.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
no
Sample size: planned number of observations
192 students
Sample size (or number of clusters) by treatment arms
48 students per treatment
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

Post-Trial

Post Trial Information

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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