butler_2019_elite_trust_game

5,555 rated or chosen profiles from 1,389 respondents, in up to 4 tasks of 1 profile varying on 2 attributes.

About this table

DescriptionBosnian politicians and officials (n=1,389) played four rounds of a game with a hypothetical partner whose ethnicity (Serb, Croat, Bosniak) and gender were randomized, giving a 0-10 game decision each round; half were also primed with an EU-benefits question.
ReferenceButler, D. M., & Tavits, M. (2019). Shared interests foster interethnic cooperation among politicians. Political Science Research and Methods.
DOI10.1017/psrm.2019.60
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/WMIMSW

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

Respondents1,389
Rows (one per respondent, task and profile)5,555
Tasks per respondent (most)4
Profiles per task1
Attributes2

Design

Topicsocial identity interpersonal
A profile representsperson
CountryBA
Language shownunknown
Language of stored levelsen
Randomization restrictionsunknown
Task orderinferred from row order
Profile positioninferred from row order

Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.

Outcomes:

ratingGame decision toward the hypothetical partner, 0-10 (q10-q13; dv_game, the trust-game outcome of the authors' experiment 2; wording and unit not in the deposit) (paraphrase) [rating, 0 (lowest (0)) to 10 (highest (10; presumably more trusting))]

Columns

attr_partner_ethnicityattr_partner_gendercov_entity_rscov_ethnicitycov_gendercov_years_in_officeidprofileratingtasktrial_eu_benefits_asked

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("butler_2019_elite_trust_game", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("butler_2019_elite_trust_game", source="conj")

How to cite

@article{Butler_2020, title={Shared interests foster interethnic cooperation among politicians}, volume={9}, ISSN={2049-8489}, url={http://dx.doi.org/10.1017/psrm.2019.60}, DOI={10.1017/psrm.2019.60}, number={3}, journal={Political Science Research and Methods}, publisher={Cambridge University Press (CUP)}, author={Butler, Daniel and Tavits, Margit}, year={2020}, month=Apr, pages={627–640} }

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