delponte_2020_debt_dilemmas

648 rated or chosen profiles from 648 respondents, in up to 1 tasks of 1 profile varying on 2 attributes.

About this table

Description648 MTurk workers each read one vignette about a country (Avalon) that owes a loan to another (Freedonia), randomized on the number of jobs lost by repaying (6,000 to 100,000) and full vs partial default; outcomes are what the government should do and moral-wrongness and punishment judgements.
ReferenceDel Ponte, A., & DeScioli, P. (2020). Pay your debts: Moral dilemmas of international debt. Political Behavior.
DOI10.1007/s11109-020-09675-6
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/XJ2BDK

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

Respondents648
Rows (one per respondent, task and profile)648
Tasks per respondent (most)1
Profiles per task1
Attributes2
Tasks with no profile chosen322

Design

Topicinternational economy
A profile representsscenario
Countryunknown
Language shownen
Language of stored levelsen
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:

choiceWhat should the government of Avalon do? repay or default (whatDo; wording not in the deposit; coding 1 = repay inferred) [choice, opt-out allowed]
rating_cuts_punishHow strong of a punishment for making cuts? (0-10) [rating, 0 (unknown) to 10 (unknown)]
rating_cuts_wrongHow morally wrong to make cuts? (0-10) [rating, 0 (not wrong (inferred)) to 10 (wrong (inferred))]
rating_cuts_wrong_binaryWould it be morally wrong to make cuts? No (0) or Yes (1) [rating, 0 (No) to 1 (Yes)]
rating_stop_punishHow strong of a punishment for stop repaying? (0-10) [rating, 0 (unknown) to 10 (unknown)]
rating_stop_repay_wrongWould it be morally wrong to stop repaying? No (0) or Yes (1) [rating, 0 (No) to 1 (Yes)]
rating_stop_wrongHow morally wrong to stop repaying? (0-10) [rating, 0 (not wrong (inferred)) to 10 (wrong (inferred))]

Columns

attr_default_typeattr_jobs_lostchoicecov_agecov_genderidprofilerating_cuts_punishrating_cuts_wrongrating_cuts_wrong_binaryrating_stop_punishrating_stop_repay_wrongrating_stop_wrongtask

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("delponte_2020_debt_dilemmas", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("delponte_2020_debt_dilemmas", source="conj")

How to cite

@article{Del_Ponte_2021, title={Pay Your Debts: Moral Dilemmas of International Debt}, volume={44}, ISSN={1573-6687}, url={http://dx.doi.org/10.1007/s11109-020-09675-6}, DOI={10.1007/s11109-020-09675-6}, number={4}, journal={Political Behavior}, publisher={Springer Science and Business Media LLC}, author={Del Ponte, Alessandro and DeScioli, Peter}, year={2021}, month=Jan, pages={1657–1680} }

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