5,020 rated or chosen profiles from 502 respondents, in up to 5 tasks of 2 profiles varying on 4 attributes.

One of 8 tables from the same source; this one is the bailout_malaysia table. The others are listed under Related tables.

About this table

Description	Malaysian adults (Malay, English or Chinese text; trial_language), TGM Research online panels (n = 502), chose between 5 pairs of hypothetical foreign bailout loans for a government in financial crisis varying interest rate, collateral, lender (IMF, Chinese government, US government, private banks) and conditions. One of 8 tables (2 experiments x 4 display-text groups) from the same study.
Reference	Bulman, D., Leng, N., & Ratigan, K. (2025). Foreign borrowing, sovereignty, and public opinion in the Global South: Traditional lenders or China? The Review of International Organizations.
DOI	10.1007/s11558-025-09602-6
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/YTLM5U

Notes

Conjoint table (irw_conjoint). choice = "Which foreign loan would you prefer for <country>?" (Loan 1 / Loan 2, forced; wording from the English screenshot; respondents saw their survey language), 5 tasks, attribute order randomized per respondent (attrpos_*). Text as displayed. N = 502, the bailout-loan half of the sample(s); country counts match supplement Table A1.

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

Design

Topic	international economy
A profile represents	policy
Country	MY
Language shown	ms, en, zh
Language of stored levels	ms, en, zh
Randomization restrictions	unknown
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Which foreign loan would you prefer for <country>? (paraphrase) [choice, forced]

Columns

attr_collateralattr_conditionattr_interest_rateattr_lenderattrpos_collateralattrpos_conditionattrpos_interest_rateattrpos_lenderchoicecov_age_group_codecov_collegecov_countrycov_debt_harm_chncov_debt_harm_imfcov_debt_harm_privcov_debt_harm_usacov_duration_seccov_gender_codecov_income_codecov_region_codecov_unemployedcov_urbancov_user_languagecov_vote_incumbentidprofiletasktrial_language

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 needed Browse on Redivisexplore and query Croissant 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("bulman_2025_bailout_malaysia", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("bulman_2025_bailout_malaysia", source="conj")

How to cite

@article{Bulman_2025, title={Foreign borrowing, sovereignty, and public opinion in the global south: Traditional lenders or China}, volume={21}, ISSN={1559-744X}, url={http://dx.doi.org/10.1007/s11558-025-09602-6}, DOI={10.1007/s11558-025-09602-6}, number={3}, journal={The Review of International Organizations}, publisher={Springer Science and Business Media LLC}, author={Bulman, David Janoff and Leng, Ning and Ratigan, Kerry}, year={2025}, month=Oct, pages={597–629} }

Respondents	502
Rows (one per respondent, task and profile)	5,020
Tasks per respondent (most)	5
Profiles per task	2
Attributes	4
Tasks with no profile chosen	0

IRW version	v584
Redivis dataset	irw_conjoint v4.2
Redivis dataset DOI	10.57761/qkye-q530
Manifest pin for this IRW version	v4.2
Metadata source	irw_meta v44.0

bulman_2025_bailout_malaysia