1,974 rated or chosen profiles from 1,974 respondents, in up to 1 tasks of 1 profile varying on 2 attributes.
| Description | 1,974 US adults (CCES module, YouGov/Polimetrix, October 2009) read one vignette: their state offered a tax incentive package greater than or equal-or-less than competing states' and did or did not receive a 1,000-job manufacturing plant. Outcome: 1-5 likelihood of voting for the governor (5 = much more likely). |
|---|---|
| Reference | Jensen, N. M., Malesky, E., Medina, M., & Ozdemir, U. (2014). Pass the bucks: Credit, blame, and the global competition for investment. International Studies Quarterly, 58(3), 433-447. |
| DOI | 10.1111/isqu.12106 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/dvn/ayrhdo |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 1,974 |
|---|---|
| Rows (one per respondent, task and profile) | 1,974 |
| Tasks per respondent (most) | 1 |
| Profiles per task | 1 |
| Attributes | 2 |
| Topic | international economy |
|---|---|
| A profile represents | scenario |
| Country | US |
| Language shown | en |
| Language of stored levels | en |
| Task order | inferred from row order |
| 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:
| rating | If your state [receives/does not receive] this investment, how would this effect your evaluation of your governor's performance in office? (1) I would be much more likely to vote for the governor in the next election ... (3) My vote choice would not be altered ... (5) I would be much less likely to vote for the governor (the deposit inverts the scale: 5 = much more likely) [rating, 1 (much less likely to vote for the governor) to 5 (much more likely to vote for the governor)] |
|---|
attr_investmentattr_tax_incentive_packagecov_party_id_codecov_registeredcov_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("jensen_2014_incentive_credit", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("jensen_2014_incentive_credit", source="conj")
@article{Jensen_2013, title={Pass the Bucks: Credit, Blame, and the Global Competition for Investment}, volume={58}, ISSN={0020-8833}, url={http://dx.doi.org/10.1111/isqu.12106}, DOI={10.1111/isqu.12106}, number={3}, journal={International Studies Quarterly}, publisher={Oxford University Press (OUP)}, author={Jensen, Nathan M. and Malesky, Edmund and Medina, Mariana and Ozdemir, Ugur}, year={2013}, month=Dec, pages={433–447} }
| IRW version | v584 |
|---|---|
| Redivis dataset | irw_conjoint_2 v1.4 |
| Redivis dataset DOI | 10.57761/hk97-wv30 |
| Manifest pin for this IRW version | v1.4 |
| Metadata source | irw_meta v44.0 |