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Media Information Processing of Economic Statistics and Policy Preferences During the COVID-19 Crisis
Last registered on November 20, 2020


Trial Information
General Information
Media Information Processing of Economic Statistics and Policy Preferences During the COVID-19 Crisis
Initial registration date
November 08, 2020
Last updated
November 20, 2020 10:13 AM EST
Primary Investigator
Friedrich Schiller University Jena
Other Primary Investigator(s)
PI Affiliation
Friedrich Schiller University Jena
Additional Trial Information
Start date
End date
Secondary IDs
We investigate the effect of media information processing on policy preferences in the context of the COVID-19 crisis. For that purpose, we conduct a survey experiment to study the event of the publication of a highly regarded annual report about the state of the economy in Germany. In our experiment, individuals are exposed to information on a key economic statistic covered in the report which differs in terms of its medial framing. This design allows us to disentangle effects which are related to the original press released information and its coverage in newspaper articles. Our examination accounts for public evaluation of economic policy in general as well as important subdomains. We aim to inform about policy implications on the relationship between media coverage, belief updating and public opinion formation in times of economic recession and pronounced public interest in statistical reporting.
External Link(s)
Registration Citation
Bareinz, Patrick and Fabian Koenings. 2020. "Media Information Processing of Economic Statistics and Policy Preferences During the COVID-19 Crisis." AEA RCT Registry. November 20. https://doi.org/10.1257/rct.6716-3.0.
Experimental Details
The information which is provided to respondents stems from a highly regarded report about the state of the German economy by the German Council of Economic Experts (GCEE).

The annual report is presented to the public regularly in November and includes a press release pointing out key information from the comprehensive report. We employ both the original press release as well as its media coverage in large German newspapers which is generated by the publication of the GCEE report.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Assessment of COVID-19 policy in general
Preferences/assessment of particular COVID-19 policies
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Assessment of credibility of information provided (for treatment groups/active control group only)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Our experimental design consists of four stages and four experimental groups. Survey respondents are randomly assigned to one of the three treatment arms which differ with respect to the framing of the information provided, or to the passive control group which does not receive any information.

In the first stage, we elicit respondents’ beliefs about a key economic statistic covered in the GCEE report.

In the second stage, random subsets of respondents are exposed to differently framed information on the key statistic:
- Treatment arm I: receives rather positively framed information from the GCEE report as covered by a German newspaper
- Treatment arm II: receives rather negatively framed information from the GCEE report as covered by a German newspaper
- Control group I (active): receives the original information from the GCEE
- Control group II (passive): does not receive any information

In the third stage, respondents are asked our outcome measures on the assessment of general COVID-19 policy and particular COVID-19 policies. Each of these outcomes are measured on an 11-point scale. As secondary outcomes, we investigate assessments of the usefulness and credibility of the information provided for those groups which receive information.

In the fourth stage, we elicit posterior beliefs about the key economic statistic covered in the GCEE report for those respondents who received information on the topic.
Experimental Design Details
Randomization Method
Randomization done by a computer
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
No clustering
Sample size: planned number of observations
3000 individuals
Sample size (or number of clusters) by treatment arms
Approximately 750 individuals for each experimental group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
Friedrich Schiller University Jena
IRB Approval Date
IRB Approval Number
Analysis Plan
Analysis Plan Documents

MD5: 1a4af34e0094a3b6c44da8e486b979ac

SHA1: 2e3691ebeb9ffaaed213875d9af4cf89bc5c1599

Uploaded At: November 14, 2020

Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)