11,664 rated or chosen profiles from 1,458 respondents, in up to 4 tasks of 2 profiles varying on 4 attributes.
| Description | US MTurk respondents (2021; 1,458, of whom 1,249 form the authors' quota sample) chose four times between two hypothetical societies varying bottom-20%, middle-60% and top-20% incomes and upward income mobility, under a 'distant society' or 'nearby society' framing. |
|---|---|
| Reference | Lara E., B., & Shores, K. A. (2024). Measuring preferences for income equality and income mobility. Review of Economics and Statistics, 106(6), 1542-1557. |
| DOI | 10.1162/rest_a_01240 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/QRQNCF |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,458 |
|---|---|
| Rows (one per respondent, task and profile) | 11,664 |
| Tasks per respondent (most) | 4 |
| Profiles per task | 2 |
| Attributes | 4 |
| Tasks with no profile chosen | 0 |
| Topic | tax welfare economy |
|---|---|
| A profile represents | place |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Task order | recorded in the deposit |
| Profile position | inferred from row order |
Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.
Outcomes:
| choice | Choose between two hypothetical societies, A and B (paraphrase) [choice, forced] |
|---|
attr_bottom20_incomeattr_middle60_incomeattr_mobilityattr_top20_incomechoicecov_agecov_belief_mobility_commoncov_diag_pctrightcov_duration_seccov_educationcov_future_mobilitycov_gendercov_household_incomecov_party_idcov_past_mobilitycov_personal_incomecov_preferred_samplecov_racecov_survey_weightcov_weight_preferredidprofiletasktrial_framing
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("lara_2024_equality_mobility", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("lara_2024_equality_mobility", source="conj")
@article{Lara_E__2024, title={Measuring Preferences for Income Equality and Income Mobility}, volume={106}, ISSN={1530-9142}, url={http://dx.doi.org/10.1162/rest_a_01240}, DOI={10.1162/rest_a_01240}, number={6}, journal={Review of Economics and Statistics}, publisher={MIT Press}, author={Lara E., Bernardo and Shores, Kenneth A.}, year={2024}, month=Nov, pages={1542–1557} }
| 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 |