552 rated or chosen profiles from 138 respondents, in up to 4 tasks of 1 profile varying on 7 attributes.

About this table

Description	138 European migration professionals each evaluated 4 vignettes describing 2021-2030 changes in 7 binary drivers (MENA youth share, fundamentalism, political stability, unemployment gap; European ageing, attitudes, policy) and estimated the change in family, work, refugee and return migration from MENA to Europe by 2030 (multiplication factor) and in the difficulty of achieving safe, orderly and regular migration.
Reference	Boissonneault, M., & Costa, R. (2022). QuantMig survey on the future of migration between Europe and the Middle East & North Africa [Data set]. Zenodo.
Licence	CC BY 4.0
Source data	https://doi.org/10.5281/zenodo.7404130

Notes

Conjoint table (irw_conjoint). Factorial vignette survey of 138 European migration professionals (web, English, Nov 2021-Jan 2022), 4 vignettes each from a blocked full 2^7 design (trial_block). rating_family/work/refugees/return: 'Based on [the situation described by the vignette], compared to 2019, the number of family [work/return] migrants [refugees] from the Middle East & North Africa to Europe will be in 2030…' stored as multiplication factor 0.2-5 (1 = No change); rating_compact: more or less difficult to achieve safe, orderly and regular migration, -3 much more to 3 much less difficult. Factor order one of two fixed orders, recorded in attrpos_.

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

Design

Topic	immigration asylum
A profile represents	scenario
Country	unknown
Language shown	en
Language of stored levels	en
Randomization restrictions	yes (stated by the source): fixed blocked design: the 128 vignettes of the full 2^7 factorial split by AlgDesign::optBlock into 32 questionnaire versions of 4 distinct vignettes (block numbers 1-64, presumably x 2 factor orders), assigned round-robin; vignettes within a respondent are fixed by the block
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_compact	Based on [the situation described by the vignette], compared to 2019, do you believe that it will be more or less difficult to achieve by the year 2030 safe, orderly and regular migration? [rating, -3 (Much more difficult) to 3 (Much less difficult)]
rating_family	Based on [the situation described by the vignette], compared to 2019, the number of family migrants from the Middle East & North Africa to Europe will be in 2030… [rating, 0.200 (Divided by 5) to 5 (Multiplied by 5)]
rating_refugees	Based on [the situation described by the vignette], compared to 2019, the number of refugees from the Middle East & North Africa to Europe will be in 2030… [rating, 0.200 (Divided by 5) to 5 (Multiplied by 5)]
rating_return	Based on [the situation described by the vignette], compared to 2019, the number of return migrants from the Middle East & North Africa to Europe will be in 2030… [rating, 0.200 (Divided by 5) to 5 (Multiplied by 5)]
rating_work	Based on [the situation described by the vignette], compared to 2019, the number of work migrants from the Middle East & North Africa to Europe will be in 2030… [rating, 0.200 (Divided by 5) to 5 (Multiplied by 5)]

Columns

attr_employmentattr_favourableattr_fundamentattr_oldattr_policiesattr_stableattr_youngattrpos_employmentattrpos_favourableattrpos_fundamentattrpos_oldattrpos_policiesattrpos_stableattrpos_youngcov_certaincov_compact_nochangecov_educationcov_familiaritycov_mig_nochangecov_sectorcov_thinkcov_years_expidprofilerating_compactrating_familyrating_refugeesrating_returnrating_worktasktrial_block

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("boissonneault_2022_migration_experts", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("boissonneault_2022_migration_experts", source="conj")

How to cite

@misc{https://doi.org/10.5281/zenodo.7404130,
  doi = {10.5281/ZENODO.7404130},
  url = {https://zenodo.org/record/7404130},
  author = {Boissonneault, Michaël and Costa, Rafael},
  title = {QuantMig survey on the future of migration between Europe and the Middle East &amp; North Africa},
  publisher = {Zenodo},
  year = {2022},
  copyright = {Creative Commons Attribution 4.0 International}
}

Respondents	138
Rows (one per respondent, task and profile)	552
Tasks per respondent (most)	4
Profiles per task	1
Attributes	7

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

boissonneault_2022_migration_experts