13,420 rated or chosen profiles from 2,008 respondents, in up to 4 tasks of 2 profiles varying on 5 attributes.

About this table

Description	Moroccan adults recruited on Facebook in 2021 (n = 2,008) compared 4 pairs of bank-account or TV deals whose owner (businessman, councillor, party official), headquarters, cost, party and vote-buying behaviour were randomized; they chose a deal (or both/neither), picked the deal more likely to go wrong, and rated trust in each deal 0-10.
Reference	Bhandari, A., & York, E. (2026). Political connections, patronage, and consumer attitudes: The non-electoral consequences of clientelism. World Development.
Licence	CC BY 4.0
Source data	https://doi.org/10.7910/DVN/QHXQTH

Notes

Conjoint table (irw_conjoint). choice = "Which deal are you more likely to choose?" and choice_wrong = "Which deal is more likely to go wrong?", each with Both and Neither options: those answers are 0 on both profiles, raw answer in trial_choice_response / trial_wrong_response (the authors count Both as chosen). rating = trust in the deal, 0-10 slider. Levels are the authors' English labels; party is stored even for Businessman owners, display undocumented. Bank account rounds 1-2, TV rounds 3-4 (trial_product). 696 unanswered tasks and never-reached respondents dropped.

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

Design

Topic	corruption accountability, consumer products
A profile represents	product service
Country	MA
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 deal are you more likely to choose? [choice, opt-out allowed]
choice_wrong	Which deal is more likely to go wrong? [choice, opt-out allowed]
rating	Stated trust in this profile's deal, 0 (none) to 10 (full) (paraphrase) [rating, 0 to 10 (full)]

Columns

attr_behaviorattr_costattr_hqattr_ownerattr_partychoicechoice_wrongcov_birth_yearcov_connections_selfcov_corruptioncov_educationcov_employmentcov_family_connectionscov_gendercov_gift_for_votecov_incomecov_language_homecov_mp_accesscov_plan_to_votecov_regioncov_trust_councilcov_trust_governmentcov_trust_parliamentcov_trust_partiescov_vote_partycov_voted_2016idprofileratingtasktrial_choice_responsetrial_producttrial_wrong_response

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("bhandari_2026_clientelism_consumers", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("bhandari_2026_clientelism_consumers", source="conj")

How to cite

@misc{https://doi.org/10.7910/dvn/qhxqth,
  doi = {10.7910/DVN/QHXQTH},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/QHXQTH},
  author = {York, Erin and Bhandari, Abhit},
  keywords = {Social Sciences, political connections, clientelism, economic development, cronyism},
  title = {Replication Data for: Political Connections, Patronage, and Consumer Attitudes: The Non-Electoral Consequences of Clientelism},
  publisher = {Harvard Dataverse},
  year = {2026}
}

Respondents	2,008
Rows (one per respondent, task and profile)	13,420
Tasks per respondent (most)	4
Profiles per task	2
Attributes	5
Tasks with no profile chosen	2,686

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

bhandari_2026_clientelism_consumers