No Incidence Left Behind – Towards a Complete Understanding of Tax Incidence

Last registered on June 23, 2023
View Trial History

Pre-Trial

Trial Information

General Information

Title
No Incidence Left Behind – Towards a Complete Understanding of Tax Incidence
RCT ID
AEARCTR-0011379
Initial registration date
June 15, 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, 4:41 PM EDT

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

Locations

Country
Germany
Region

Primary Investigator

Name
Fabian Eble
Affiliation
University of Mannheim
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Richard Winter
PI Affiliation
University of Mannheim
Contact Investigator
PI Name
Philipp Dörrenberg
PI Affiliation
University of Mannheim
Contact Investigator
PI Name
Davud Rostam-Afschar
PI Affiliation
University of Mannheim
Contact Investigator
PI Name
Johannes Voget
PI Affiliation
University of Mannheim
Contact Investigator

Additional Trial Information

Status
Completed
Start date
2020-11-16
End date
2021-06-24
Keywords
Behavior, Firms & Productivity
Additional Keywords
Tax Incidence, Business Taxation, Asymmetric Incidence, Survey Experiment
JEL code(s)
D25, H20, H22, H25, H26, H32, J23, J30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In this project, we use survey data of high-level decision makers in German firms to provide complementary evidence to the existing findings from the literature in order to facilitate a better understanding of profit tax incidence. We take a straightforward approach to tackle this
issue by asking firm decision makers about the profit tax incidence in their companies, thereby circumventing many challenges inherent to studies relying on observational data. For this purpose, we randomly assign survey respondents hypothetical permanent tax increases and decreases in varying magnitudes and inquire either how the additional funds available after a tax cut would be used or from which sources funds would be diverted to pay for the increased tax burden. By random assignment of the sign of the tax change we are able to test for asymmetries in the stated incidence reported by survey participants, whereas the experimental variation in the size of the tax change allows us to tease out the sensitivity of profit tax incidence with respect to treatment intensity.
External Link(s)

Registration Citation

Citation
Dörrenberg, Philipp et al. 2023. "No Incidence Left Behind – Towards a Complete Understanding of Tax Incidence." AEA RCT Registry. June 23. https://doi.org/10.1257/rct.11379-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Randomized hypothetical tax increase (decrease) of (1/10/25%).
Intervention Start Date
2020-11-16
Intervention End Date
2021-06-24

Primary Outcomes

Primary Outcomes (end points)
Outcomes:

- Depending on sign of the tax change share attributed to each category.
- Range [0,100]
- Must sum to 100 across categories.

Tax Decrease:

tax1: increased payment to employees (wages, variable compensation)
tax2: creation of additional jobs
tax3: increased income for partners
tax4: higher distributions to shareholders
tax5: increase in retained earnings/reserves
tax6: price reductions (for customers)
tax7: higher investments
tax8: less use of tax saving opportunities
tax9: others
tax10: decrease of debt capital

Tax Increase:

tax11: decrease payment to employees (wages, variable compensation)
tax12: reduction of jobs
tax13: decreased payout to partners
tax14: lower distributions to shareholders
tax15: decrease in retained earnings/reserves
tax16: price increases (for customers)
tax17: lower investments
tax18: more use of tax saving opportunities
tax19: others
tax20: increase in debt capital
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We randomly assign the sign (increase/decrease) and the magnitude (1/10/25%) of hypothetical profit tax changes to survey participants. After being confronted with a hypothetical tax change, respondents can distribute the change in the tax burden among different margins (described Primary Outcomes (End Points)), where the assigned shares have to sum up to 100.
Experimental Design Details
Randomization Method
Randomization done by a computer
Randomization Unit
Firm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
8,388 firms
Sample size: planned number of observations
8,388 firms
Sample size (or number of clusters) by treatment arms
1,398 firms per treatment arm

Treatment arms are:
- 1% tax decrease
- 10% tax decrease
- 25% tax decrease
- 1% tax increase
- 10% tax increase
- 25% tax increase
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Committee at the University of Mannheim
IRB Approval Date
2023-06-13
IRB Approval Number
EC Mannheim 23/2023
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

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