reinsberg_2026_imf_messages

1,691 rated or chosen profiles from 1,691 respondents, in up to 1 tasks of 1 profile varying on 6 attributes.

About this table

DescriptionPakistani adults (Gallup Pakistan phone survey, June 2023, n = 1,691) read a short text on Pakistan's IMF credit line with six independently randomized statements (reform costs, social protection, and government/industry/civil-society blame of the IMF), then rated approval of the program, government and IMF responsibility, and confidence in the IMF.
ReferenceReinsberg, B., Abouharb, M. R., & Seiferling, M. (2026). Unlocking public support: How communication about program design affects public perception of IMF interventions. Foreign Policy Analysis, 22(2), orag003.
DOI10.1093/fpa/orag003
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/HJ9OPE

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

Respondents1,691
Rows (one per respondent, task and profile)1,691
Tasks per respondent (most)1
Profiles per task1
Attributes6

Design

Topicinternational economy, political communication
A profile representsmessage
CountryPK
Language shownunknown
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:

ratingTo what extent do you approve or disapprove of this program? [rating, 1 (Disapprove a lot) to 4 (Approve a lot)]
rating_gov_responsibleTo what extent do you think the government of Pakistan under the leadership of Shehbaz Sharif (PML-N) is responsible for the program with the IMF? [rating, 1 (Not responsible) to 3 (Much responsible)]
rating_imf_confidenceOn a scale of 0-10 where 0 means 'no confidence at all' and 10 means 'complete confidence,' to what extent do you have confidence in the International Monetary Fund to do what is right? [rating, 0 (No confidence at all) to 10 (Complete confidence)]
rating_imf_responsibleTo what extent do you think the IMF is responsible for this program? [rating, 1 (Not responsible) to 3 (Much responsible)]

Columns

attr_adjburdenattr_govblameattr_hurtattr_industryblameattr_ngoblameattr_socprogcov_agecov_areacov_educationcov_employmentcov_gendercov_imf_knowledgecov_incomecov_mother_tonguecov_q7cov_q8cov_record_statementcov_sectorcov_survey_weightcov_vote_intentionidprofileratingrating_gov_responsiblerating_imf_confidencerating_imf_responsibletask

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("reinsberg_2026_imf_messages", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("reinsberg_2026_imf_messages", source="conj")

How to cite

@article{Reinsberg_2026, title={Unlocking Public Support: How Communication about Program Design Affects Public Perception of IMF Interventions}, volume={22}, ISSN={1743-8594}, url={http://dx.doi.org/10.1093/fpa/orag003}, DOI={10.1093/fpa/orag003}, number={2}, journal={Foreign Policy Analysis}, publisher={Oxford University Press (OUP)}, author={Reinsberg, Bernhard and Abouharb, M Rodwan and Seiferling, Mike}, year={2026}, month=Jan }

Version and provenance

IRW versionv607
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v47.0