8,402 rated or chosen profiles from 845 respondents, in up to 5 tasks of 2 profiles varying on 4 attributes.

About this table

Description	Paired conjoint on carbon-tax design in South Korea: 845 adults (the control, no-information arm) chose between 5 pairs of carbon-tax proposals varying the monthly household cost, the main taxed energy, and two revenue uses (redistributive and environmental); the outcome is a forced choice.
Reference	Kim, S. E., Kim, S. Y., & Suh, J. (2024). Public support for carbon tax in South Korea: The role of tax design and revenue recycling. Asia & the Pacific Policy Studies, 11(2), e385.
DOI	10.1002/app5.385
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/M7QPIS

Notes

Conjoint table (irw_conjoint). Five paired carbon-tax proposals; choice = which proposal ('탄소세 정책안 A/B') the respondent chose (forced, no opt-out; wording not deposited). Korean level text. Only the no-information control arm is in the deposit (845 respondents); the paper's information-treatment arm is not. No covariates.

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

Size and shape

Respondents	845
Rows (one per respondent, task and profile)	8,402
Tasks per respondent (most)	5
Profiles per task	2
Attributes	4
Tasks with no profile chosen	0

Design

Topic	climate energy environment
A profile represents	policy
Country	KR
Language shown	ko
Language of stored levels	ko
Randomization restrictions	unknown
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Which carbon tax proposal (탄소세 정책안 A or B) do you prefer? (paraphrase) [choice, forced]

Columns

attr_costattr_energyattr_environmentattr_redistributionchoiceidprofiletask

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("kim_2024_carbon_tax_korea", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("kim_2024_carbon_tax_korea", source="conj")

How to cite

@article{Kim_2024, title={Public support for carbon tax in South Korea: The role of tax design and revenue recycling}, volume={11}, ISSN={2050-2680}, url={http://dx.doi.org/10.1002/app5.385}, DOI={10.1002/app5.385}, number={2}, journal={Asia &amp; the Pacific Policy Studies}, publisher={Wiley}, author={Kim, Sung Eun and Kim, Seung Yeob and Suh, Junwoo}, year={2024}, month=Feb }

Version and provenance

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