heermann_2022_covid_aid_2020

9,550 rated or chosen profiles from 4,775 respondents, in up to 2 tasks of 1 profile varying on 3 attributes.

One of 2 tables from the same source; this one is the 2020 table. The others are listed under Related tables.

About this table

DescriptionGerman online-panel respondents (n = 4,775, April/May 2020) each read a medical-aid and a financial-aid COVID-19 vignette with randomized recipient community (German state/EU/non-EU), control (health system or fiscal discipline) and costs (medical risk or tax increase), and rated support 1-7.
ReferenceHeermann, M., Koos, S., & Leuffen, D. (2022). Who deserves European solidarity? How recipient characteristics shape public support for international medical and financial aid during COVID-19. British Journal of Political Science.
DOI10.1017/S0007123422000357
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/RCO69B

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

Respondents4,775
Rows (one per respondent, task and profile)9,550
Tasks per respondent (most)2
Profiles per task1
Attributes3

Design

Topicinternational economy
A profile representsplace
CountryDE
Language shownde
Language of stored levelsen
Task orderunknown
Profile positionrecorded in the deposit

Outcomes:

ratingWould you support such an initiative? (medical aid: your state provides ventilators to another German state; financial aid: Germany provides financial assistance to another EU country) (translated) [rating, 1 (not support at all) to 7 (strongly support)]

Columns

attr_communityattr_controlattr_costscov_age_groupcov_altruismcov_cosmopolitanismcov_eastcov_educationcov_eu_identitycov_gendercov_incomecov_left_rightcov_survey_weightidprofileratingtasktrial_celltrial_vignette

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("heermann_2022_covid_aid_2020", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("heermann_2022_covid_aid_2020", source="conj")

How to cite

@article{Heermann_2022, title={Who Deserves European Solidarity? How Recipient Characteristics Shaped Public Support for International Medical and Financial Aid during COVID-19}, volume={53}, ISSN={1469-2112}, url={http://dx.doi.org/10.1017/S0007123422000357}, DOI={10.1017/s0007123422000357}, number={2}, journal={British Journal of Political Science}, publisher={Cambridge University Press (CUP)}, author={Heermann, Max and Koos, Sebastian and Leuffen, Dirk}, year={2022}, month=Dec, pages={629–651} }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint_2 v1.4
Redivis dataset DOI10.57761/hk97-wv30
Manifest pin for this IRW versionv1.4
Metadata sourceirw_meta v44.0