3,324 rated or chosen profiles from 277 respondents, in up to 6 tasks of 2 profiles varying on 6 attributes.

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

About this table

Description	277 lab-in-the-field subjects in urban China each compared 6 pairs of hypothetical property tax policies (citizen input, provincial supervision, exemption threshold, tax rate, payment penalty, public-goods spending), choosing one and rating each 1-5.
Reference	Lü, X., Tsai, L. L., Zheng, P., & Trinh, M. (2025). Do government accountability and responsiveness enhance support for property taxes? Experimental evidence from China. World Development, 194, 107051.
DOI	10.1016/j.worlddev.2025.107051
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/KLVEGA

Notes

Conjoint table (irw_conjoint). Lab-in-the-field conjoint: forced choice between two property tax policies (no opt-out) and a 1-5 rating of each (variable rank; wording and anchors not deposited). Level text is the deposit's terse English value labels. Separate design from the online conjoint (six attributes).

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	277
Rows (one per respondent, task and profile)	3,324
Tasks per respondent (most)	6
Profiles per task	2
Attributes	6
Tasks with no profile chosen	0

Design

Topic	tax welfare economy
A profile represents	policy
Country	CN
Language shown	unknown
Language of stored levels	en
Randomization restrictions	unknown
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Which of the two property tax policies do you prefer? (paraphrase) [choice, forced]
rating	unknown (1-5 rating of each policy, variable `rank`; the authors' figure axis calls its effect 'Change in Tax Compliance') (paraphrase) [rating, 1 (unknown) to 5 (unknown)]

Columns

attr_citizen_inputattr_exemption_thresholdattr_payment_penaltyattr_provincial_supervisionattr_public_goodsattr_tax_ratechoicecov_age_groupcov_apartment_ownedcov_ccpcov_educationcov_gendercov_income_catcov_local_hukoucov_marriedidprofileratingtask

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("lu_2025_property_tax_lab", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("lu_2025_property_tax_lab", source="conj")

How to cite

@article{L__2025, title={Do government accountability and responsiveness enhance support for property taxes? Experimental evidence from China}, volume={194}, ISSN={0305-750X}, url={http://dx.doi.org/10.1016/j.worlddev.2025.107051}, DOI={10.1016/j.worlddev.2025.107051}, journal={World Development}, publisher={Elsevier BV}, author={Lü, Xiaobo and Tsai, Lily L. and Zhang, Ping and Trinh, Minh}, year={2025}, month=Oct, pages={107051} }

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