17,736 rated or chosen profiles from 2,217 respondents, in up to 4 tasks of 2 profiles varying on 5 attributes.
| Description | US MTurk respondents (Aug 2014, n=2,217) rated on a 1-9 oppose-support scale each of two hypothetical US foreign-aid packages in 4 tasks; packages varied extra benefits to the US, cost, a potential issue in the recipient (none, placebo, aid theft, rigged elections, torture, media crackdown) and remedial aid (amount and channel). |
|---|---|
| Reference | Heinrich, T., & Kobayashi, Y. (2020). How do people evaluate foreign aid to "nasty" regimes? British Journal of Political Science, 50(1), 103-127. |
| DOI | 10.1017/S0007123417000503 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/TKTN5J |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 2,217 |
|---|---|
| Rows (one per respondent, task and profile) | 17,736 |
| Tasks per respondent (most) | 4 |
| Profiles per task | 2 |
| Attributes | 5 |
| Topic | international economy |
|---|---|
| A profile represents | policy |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Randomization restrictions | yes (stated by the source): remedy amount is 0 (no remedy) whenever the potential issue is None or the Olympics placebo; otherwise drawn from 0/1/2/5/10/15/20/25 million; the remedy target is only shown with a nonzero amount. Level weights: the codebook gives rand() draws without probabilities; observed issue shares are None 10%, Olympics placebo 10%, each regime issue about 20%; with a regime issue the eight remedy amounts (incl. 0, not shown) are about equally likely |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Because the attribute levels were not randomized independently, an estimator has to account for the restriction; a plain difference in means across levels can mislead.
Outcomes:
| rating | Please express your support for each aid package by checking the buttons. [rating, 1 (Oppose) to 9 (Support)] |
|---|
attr_benefitsattr_costsattr_issueattr_remedy_amountattr_remedy_targetcov_birth_yearcov_cc415rcov_duration_seccov_econ_changecov_educationcov_employcov_faminccov_gendercov_party_id7cov_screener_failurescov_stateidprofileratingtask
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.
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("heinrich_2020_nasty_aid", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("heinrich_2020_nasty_aid", source="conj")
@article{Heinrich_2018, title={How Do People Evaluate Foreign Aid To ‘Nasty’ Regimes?}, volume={50}, ISSN={1469-2112}, url={http://dx.doi.org/10.1017/S0007123417000503}, DOI={10.1017/s0007123417000503}, number={1}, journal={British Journal of Political Science}, publisher={Cambridge University Press (CUP)}, author={Heinrich, Tobias and Kobayashi, Yoshiharu}, year={2018}, month=Feb, pages={103–127} }
| 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 |