lopezgarcia_2025_haiti_property_tax

12,006 rated or chosen profiles from 2,001 respondents, in up to 3 tasks of 2 profiles varying on 6 attributes.

About this table

DescriptionHaitian online respondents (RIWI, Dec 2023 - Apr 2024) chose between 3 pairs of hypothetical proposals for the CFPB property tax varying the administering government, tax collector, earmarked purpose, timeline of service improvement, beneficiaries and taxpayer recognition. 2,001 respondents; forced choice; survey weight included.
ReferenceLopez Garcia, A. I., & Berens, S. (2025). Taxing the wealthy in Haiti: Evidence from a conjoint experiment on property tax preferences. World Development, 196, 107193.
DOI10.1016/j.worlddev.2025.107193
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/LMIIRA

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

Respondents2,001
Rows (one per respondent, task and profile)12,006
Tasks per respondent (most)3
Profiles per task2
Attributes6
Tasks with no profile chosen0

Design

Topictax welfare economy
A profile representspolicy
CountryHT
Language shownht
Language of stored levelsen
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choiceConsidering the tax proposals below. If you had to choose which proposal, would you prefer: A or B? [choice, forced]

Columns

attr_administersattr_beneficiaryattr_collectsattr_improvementattr_purposeattr_recognitionattrpos_administersattrpos_beneficiaryattrpos_collectsattrpos_improvementattrpos_purposeattrpos_recognitionchoicecov_agecov_age_groupcov_datecov_educationcov_gendercov_q06_livingcov_q07_housecov_q09_civil_statuscov_q10_employmentcov_q11_racecov_q12_relatives_abroadcov_q13_remittancescov_q14_emigration_intentioncov_q15_classcov_q16_household_incomecov_q17_crime_victimcov_q18_safetycov_q19_gangscov_q20_more_taxescov_regioncov_survey_weightidprofiletask

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("lopezgarcia_2025_haiti_property_tax", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("lopezgarcia_2025_haiti_property_tax", source="conj")

How to cite

@article{L_pez_Garc_a_2025, title={Taxing the wealthy in Haiti: Evidence from a conjoint experiment on property tax preferences}, volume={196}, ISSN={0305-750X}, url={http://dx.doi.org/10.1016/j.worlddev.2025.107193}, DOI={10.1016/j.worlddev.2025.107193}, journal={World Development}, publisher={Elsevier BV}, author={López García, Ana Isabel and Berens, Sarah}, year={2025}, month=Dec, pages={107193} }

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