Demand for narratives

Last registered on November 15, 2024

Pre-Trial

Trial Information

General Information

Title
Demand for narratives
RCT ID
AEARCTR-0014533
Initial registration date
November 05, 2024

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 15, 2024, 1:28 PM EST

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

Locations

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Primary Investigator

Affiliation
ifo Institute

Other Primary Investigator(s)

PI Affiliation
PI Affiliation
PI Affiliation

Additional Trial Information

Status
In development
Start date
2024-11-07
End date
2025-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We run a survey among German households and examine whether households' demand for expert narratives ("decoding") differs from households' demand for central bank information. We do this via an incentivized Willingness-to-Pay framework.

External Link(s)

Registration Citation

Citation
Gründler, Klaus et al. 2024. "Demand for narratives." AEA RCT Registry. November 15. https://doi.org/10.1257/rct.14533-1.0
Experimental Details

Interventions

Intervention(s)
We run a survey among German households and examine whether households' demand for expert narratives ("decoding") differs from households' demand for central bank information. We do this via an incentivized Willingness-to-Pay framework.
Intervention Start Date
2024-11-07
Intervention End Date
2024-11-30

Primary Outcomes

Primary Outcomes (end points)
Demand for Information (Willingness-to-pay)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We run a survey among German households and examine whether households' demand for expert narratives ("decoding") differs from households' demand for central bank information. We do this via an incentivized Willingness-to-Pay framework.

Within our survey, we first anchor respondents’ belief about the level of current inflation as well as its past development. We give the respondents the information about the level of the inflation rate in Germany in October 2022. We then ask the respondents about their beliefs on the inflation rate in October 2024. Next, we provide them with the true value of the inflation rate in October 2024.

We then randomize respondents into two groups. We allow the first group to acquire an explanation from the ECB and the second group to acquire an explanation from economic experts on why the inflation rate in Germany has declined over this horizon. Respondents are asked whether they want to acquire the explanation or alternatively get an additional payment. We clearly state that one of the scenarios will be randomly implemented by a computer. We vary the amount of the additional payment – allowing us to derive individual demand curves for each individual.

We also provide the groups with the opportunity to sign up for a cost-free ECB newsletter or a cost-free newsletter from the ifo Institute Munich. The first group will receive the question on the ECB newsletter, the second group the question on the ifo newsletter.

After the computer has decided on a scenario, depending on the respondents' decision in that scenario, respondents' either receive the explanation from the ECB (group 1) or the explanation from experts (group 2) or are informed about the amount of their additional payout (and that they receive no additional information).

Finally, we then ask participants about their posterior expectations on the inflation rate.

Our main hypothesis is that households’ demand for expert narratives is higher compared to households’ demand for central bank explanations.
Experimental Design Details
Not available
Randomization Method
randomization done by Qualtrics software
Randomization Unit
Individuals
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2 groups
Sample size: planned number of observations
2500-2600
Sample size (or number of clusters) by treatment arms
evenly split between 2 groups
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