#145978 | AsPredicted

'What does it mean to trust a central bank?'
(AsPredicted #145978)


Created:       10/05/2023 02:55 AM (PT)

This is an anonymized version of the pre-registration.  It was created by the author(s) to use during peer-review.
A non-anonymized version (containing author names) should be made available by the authors when the work it supports is made public.

1) Have any data been collected for this study already?
It's complicated. We have already collected some data but explain in Question 8 why readers may consider this a valid pre-registration nevertheless.

2) What's the main question being asked or hypothesis being tested in this study?
Question 1: What does the "trust in central banks" question in household surveys capture?
Question 2: How does correcting misperceptions about central banks influence trust in the central bank?

The following are predictions with directional outcomes:
1) Most households believe that the European Central Bank's (ECB) projection will undershoot actual inflation. This belief has a negative cross-sectional correlation with trust in the ECB.
2) Information interventions positively influence subcomponents of trust and aggregate trust.

3) Describe the key dependent variable(s) specifying how they will be measured.
There are 6 items for which the respondent must indicate his/her level of agreement on a scale of 1 to 7. I consider each item as a dependent variable, but I will also aggregate them into a single score. These items are designed to capture different motives for trusting central banks.

4) How many and which conditions will participants be assigned to?
There are four conditions in the experiment. The first group is a pure control group that receives no information. The second group receives the latest inflation news (i.e., annual inflation in the euro area is 5.3% in July 2023). The third group receives information about the European Central Bank's (ECB) inflation projection for December 2023, which was made in December 2022 (i.e., 6.3%). The fourth group receives information about both recent inflation and the ECB's inflation projection. The assignment of treatments is between-subject and balanced.

5) Specify exactly which analyses you will conduct to examine the main question/hypothesis.
Before the information intervention, I elicit three variables: General trust in the ECB on a scale of 0-10 (gen_trust), perception of the ECB's projection (perc_proj), and inflation expectations for December 2023 (inf_exp).

First, I will perform a correlation analysis between gen_trust, individual item scores, and "perc_proj - inf_exp" for respondents who were in the control group.

I will run several regressions to estimate treatment effects. The short regression I will run is a linear regression where the dependent variable is the aggregate trust score (average score across all items) and the independent variables are treatment indicators. I will then stepwise include the following regressors: "inf_exp - perc_proj", "gen_trust", "perc_proj - actual_proj", and "inf_exp - actual_inflation".

When it comes to individual item scores, I will run a seemingly unrelated regression (SUR) where the scores of each item are the dependent variables and the treatment indicators are exogenous regressors. As an extension, I will include the four variables mentioned above in each regression and run the SUR again.

6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations.
The survey allows respondents to choose "No answer" or "I don't know" for each question. In the main sample, I will only include subjects who gave an answer to questions gen_trust, perc_proj, and inf_exp (restricted_sample). I will also exclude subjects who expect inflation in December 2023 to be greater than 25% and less than -5%.

If the restricted sample is significantly different from the full sample on at least three observed demographics (gender, age, education, employment, regions), I will use survey weights. If the exclusion rate is greater than 15%, I will run the short regressions (DV~Treatments) based on the available data with the full sample.

7) How many observations will be collected or what will determine sample size?
No need to justify decision, but be precise about exactly how the number will be determined.

The sample size will be determined by the Bundesbank in cooperation with the research company "forsa". About 4000 respondents are expected to participate in my experiment.

8) Anything else you would like to pre-register?
(e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?)

This experiment is integrated into the Bundesbank Online Panel Households (BOP-HH) survey. Data collection started on September 15, 2023 and ended at the end of September 2023. However, this is a pre-registration, as the Bundesbank will make data from waves 43-45 available to researchers on October 23, 2023. Therefore, the data was not observed at the time I created this pre-registration.

I intend to use part of this experiment in another paper (pre-registered at #107388).

I will perform the following robustness checks: Use an alternative aggregation mechanism (standardized scores, regression method, PCA, CFA) for the post-treatment trust score. Include demographic controls in the regressions. Separate by refresher and panel member.