20,426 rated or chosen profiles from 2,081 respondents, in up to 5 tasks of 2 profiles varying on 3 attributes.
One of 4 tables from the same source; this one is the us table. The others are listed under Related tables.
| Description | US respondents (Amazon Mechanical Turk, October 2017; 2,081 respondents, 1,946 in the author's sample) chose which of two hypothetical individuals should pay a higher tax rate, over 5 pairs varying annual income, share of income paid in sales taxes and source of income (effort, family connections, government bailout, lottery). |
|---|---|
| Reference | Alvarado, M. (2024). Compensation and tax fairness: Evidence from four countries. British Journal of Political Science, 54(4), 1023-1042. |
| DOI | 10.1017/S0007123423000698 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/A6115X |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 2,081 |
|---|---|
| Rows (one per respondent, task and profile) | 20,426 |
| Tasks per respondent (most) | 5 |
| Profiles per task | 2 |
| Attributes | 3 |
| Tasks with no profile chosen | 0 |
| Topic | tax welfare economy |
|---|---|
| A profile represents | person |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Task order | recorded in the deposit |
| Profile position | recorded in the deposit |
Outcomes:
| choice | Which of the two individuals would you personally prefer to charge a higher tax rate to? [choice, forced] |
|---|
attr_incomeattr_income_sourceattr_sales_taxattrpos_incomeattrpos_income_sourceattrpos_sales_taxchoicecov_in_authors_sampleidprofiletask
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("alvarado_2024_tax_fairness_us", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("alvarado_2024_tax_fairness_us", source="conj")
@article{Alvarado_2024, title={Compensation and Tax Fairness: Evidence From Four Countries}, volume={54}, ISSN={1469-2112}, url={http://dx.doi.org/10.1017/S0007123423000698}, DOI={10.1017/s0007123423000698}, number={4}, journal={British Journal of Political Science}, publisher={Cambridge University Press (CUP)}, author={Alvarado, Mariana}, year={2024}, month=Mar, pages={1023–1042} }
| 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 |