becker_2025_tax_packages

9,210 rated or chosen profiles from 921 respondents, in up to 5 tasks of 2 profiles varying on 3 attributes.

About this table

DescriptionTax-reform conjoint: 921 German adults (Lucid quota sample, 2021 federal election campaign) each compared 5 pairs of reform packages varying personal income, inheritance and corporate taxes, and chose which package contributes more to reducing inequality and which more to economic growth.
ReferenceBecker, B., Castanho Silva, B., & Lierse, H. (2025). Taxing your cake and growing it too: Public beliefs on the dual benefits of progressive taxation. Journal of Public Policy, 46, 1-20.
DOI10.1017/S0143814X25100858
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/R5SDWN

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents921
Rows (one per respondent, task and profile)9,210
Tasks per respondent (most)5
Profiles per task2
Attributes3

Design

Topictax welfare economy
A profile representspolicy
CountryDE
Language shownde
Language of stored levelsen
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choice_growthTo which of the reform packages do the following statements apply more? Contributes to the growth of the economy. (translated) [choice, forced]
choice_inequalityTo which of the reform packages do the following statements apply more? Contributes to the reduction of economic inequality. (translated) [choice, forced]

Columns

attr_corporate_taxattr_income_taxattr_inheritance_taxchoice_growthchoice_inequalitycov_firm_sizecov_income_percentilecov_left_rightcov_wealth_percentileidprofiletask

The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("becker_2025_tax_packages", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("becker_2025_tax_packages", source="conj")

How to cite

@article{Becker_2025, title={Taxing your cake and growing it too: public beliefs on the dual benefits of progressive taxation}, volume={46}, ISSN={1469-7815}, url={http://dx.doi.org/10.1017/S0143814X25100858}, DOI={10.1017/s0143814x25100858}, number={1}, journal={Journal of Public Policy}, publisher={Cambridge University Press (CUP)}, author={Becker, Bastian and Castanho Silva, Bruno and Lierse, Hanna}, year={2025}, month=Nov, pages={1–20} }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v44.0