aklin_2026_climate_transfers

75,876 rated or chosen profiles from 12,646 respondents, in up to 3 tasks of 2 profiles varying on 4 attributes.

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

About this table

DescriptionOnline respondents in ten large emitting countries (Dynata, Oct 2021, n=12,646) chose in 3 tasks which of two hypothetical developing countries should receive financial and technical climate assistance; countries varied unconditional and conditional emission commitments, income level and who monitors; forced choice.
ReferenceAklin, M., Buntaine, M. T., & Mildenberger, M. (forthcoming). Public opinion and the political logic of international climate pledges. Global Environmental Politics.
LicenceCC0 1.0
Source datahttps://osf.io/u8z3n/

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

Respondents12,646
Rows (one per respondent, task and profile)75,876
Tasks per respondent (most)3
Profiles per task2
Attributes4
Tasks with no profile chosen0

Design

Topicclimate energy environment
A profile representsplace
CountryBR, CN, DE, IN, ID, JP, MX, ZA, GB, US
Language shownpt, zh, de, en, id, ja, es, zu
Language of stored levelsen
Randomization restrictionsunknown
Task orderrecorded in the deposit
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:

choiceWhich country would you prefer to see financial and technical assistance given to? [choice, forced]

Columns

attr_conditional_commitmentattr_income_levelattr_monitorattr_unconditional_commitmentchoicecov_comprehension_checkcov_countryidprofiletask

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("aklin_2026_climate_transfers", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("aklin_2026_climate_transfers", source="conj")

How to cite

@article{https://doi.org/10.17605/osf.io/u8z3n,
  doi = {10.17605/OSF.IO/U8Z3N},
  url = {https://osf.io/u8z3n/},
  author = {{Michaƫl Aklin} and {Mark Buntaine} and {Matto Mildenberger}},
  title = {Conditional Climate Pledges and Public Preferences for Ambitious Climate Policy},
  publisher = {OSF},
  year = {2021},
  copyright = {Creative Commons Zero v1.0 Universal}
}

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v44.0