Followers or ignorants: Central bank forecasts and price setting behavior of firms

Last registered on July 26, 2022

Pre-Trial

Trial Information

General Information

Title
Followers or ignorants: Central bank forecasts and price setting behavior of firms
RCT ID
AEARCTR-0009793
Initial registration date
July 26, 2022

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
July 26, 2022, 1:55 PM EDT

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
University of Mannheim

Other Primary Investigator(s)

PI Affiliation
University of Mannheim
PI Affiliation
University of Mannheim
PI Affiliation
University of Mannheim
PI Affiliation
University of Mannheim
PI Affiliation
University of Mannheim

Additional Trial Information

Status
In development
Start date
2022-08-01
End date
2024-03-15
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
How firms set their prices and how their inflation expectations relate to this is a key question for economic policy and to understand the inner workings of the firm. In times of high inflation and uncertainty about the future development of prices, it is of interest which information firms and their decision-makers consider when deciding on their price setting strategy as firms directly influence inflation dynamics via their pricing decision. Given a potential level of misperception, we study how the expected development of these variables differs from official statistics and how these expectations influence planned price setting decisions of firms. Moreover, this study is the first to measure a sufficient statistic that shows whether the Calvo or the Taylor pricing model is in line with the evidence and allows to quantify inflation “overshooting”.
External Link(s)

Registration Citation

Citation
Dörrenberg, Philipp et al. 2022. "Followers or ignorants: Central bank forecasts and price setting behavior of firms." AEA RCT Registry. July 26. https://doi.org/10.1257/rct.9793
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Experimental Details

Interventions

Intervention(s)
We use information treatments to test which factors influence firms’ price setting behavior.

First, we ask for estimates of both future (for 2022, 2023) and realized annual inflation rates (for 2021).

We use these prior beliefs
i) to test the effect of our experimental treatments for firms with similar prior inflation expectations on a firm’s price setting behavior

ii) to measure the extend of misperception by comparing the own assessment of inflation dynamics and the inflation rate officially published by the German Bundesbank.

Second, we provide information on different components of inflation to test, which treatments affect the price setting of firms. We randomly assign respondents to one of three treatment groups (INFLATION, ENERGY, WAGES) or a control group (CONTROL). We display the indicated inflation by the respondent together with inflation rates provided by the German Bundesbank for the consumer price index (treatment INFLATION) and together with energy price changes (ENERGY) or wage changes (WAGES), respectively.

In each of the treatment arms, we show participants a table reporting the following inflation rates:
i. Own forecast inflation (CONTROL)
ii. Own forecast inflation + Inflation information (Bundesbank) (INFLATION)
iii. Own forecast inflation + Inflation information (Bundesbank) + Energy price component inflation (Bundesbank) (ENERGY)
iv. Own forecast inflation + Inflation information (Bundesbank) + wages (Bundesbank) (WAGES)
Intervention Start Date
2022-08-01
Intervention End Date
2023-01-20

Primary Outcomes

Primary Outcomes (end points)
• Expectations about the realized (year: 2021) and predicted (years: 2022/2023) inflation rates (in %)
• Price changes of products/services in the next 12 months (in %)
Primary Outcomes (explanation)
• Expectations about the realized and predicted inflation rates are measured via a textbox, in which participants can enter a numerical value in %. The entry range varies from -100% to 100%.
• Price changes of products/services in the next 12 months are measured via a textbox, in which participants can enter a numerical value in %. The entry range is restricted from below by -100%. From this variable, we construct a measure of "overshooting" as defined in Werning (2022).

Secondary Outcomes

Secondary Outcomes (end points)
• Change in sales (in %) for hypothetical price changes
• Determinants of price change
• Change in capital structure (i.e., increase or decrease in debt)
• Price setting interval duration in the past and currently
Secondary Outcomes (explanation)
• Change in sales (in %) for hypothetical price changes:
Measured via textbox where only numerical entries are allowed. The entry range is restricted from below by -100%.
• Determinants of price change:
Participants can choose from the following options: wage costs, material/energy costs, competitor prices, consumer demand, legal regulations, other factors (text field)
• Change in capital structure (i.e., increase or decrease in debt):
Qualitative measure with four options: Reduction, No change, Increase, No indication
• Price setting interval duration in the past and currently:
2 measures:
o Quantitative: Drop down menu with answer options ranging from daily to more than 24 months
o Qualitative: Options ranging from much less often to much more frequently

Experimental Design

Experimental Design
see section "Interventions"
Experimental Design Details
Not available
Randomization Method
Randomization done by a computer through Qualtrics
Randomization Unit
Firm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clusters
Sample size: planned number of observations
Approx. 1,800 questionnaires with valid responses by firm representatives
Sample size (or number of clusters) by treatment arms
Each treatment arm has 450 observations of firm representatives
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We start by assuming a sample size of approximately 1,800 observations. This will give us around 450 observations per experimental group. We also assume a standard deviation of 4.68% (Coibion et al., 2020; Online Appendix Table 1. Descriptive statistics of selected variables; p.61). As an example, we take an expected price change of 8%. For these parameters, we check which minimum detectable percentage point difference we are still able to successfully detect. • Estimated effect size and experimental-group mean: o delta = 0.8750 o expected price change under the alternative = 8.8750
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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