Here I share data I have collected, including data that I haven’t analysed yet (in this case, please contact me at didier.ruedin@unine.ch): If it’s something I’ve been planning to do with these data, let’s collaborate; if it’s something else, good for you! A citation would be appreciated.
Note: I haven’t prepared all the documentation yet. If you can’t wait, send me an e-mail.
Discrimination and Attitudes
Meta-Analysis on Ethnic Discrimination in Hiring
- OECD countries, 1990 to 2015:
on Dataverse.
We’re working on an update as of 2023.
Discrimination in the Housing Market, Switzerland
- Correspondence test, national coverage, Switzerland, March to October 2018, N=11k queries sent (paired design). [TBA]
- Perception of names, self-select student sample [TBA]
- Perception of names, online survey 2020 [TBA]
- Update of the field experiment in 2020 [TBA]
- A reduced version of the correspondence test and the names survey are available on OSF: https://osf.io/ru8y6/
Discrimination using Footballers
- Online vignette experiments using footballers to measure discrimination, Germany, N=1117, 2018. [TBA]
- Online experiments, Germany, N=7k, 2019-20. [TBA]
Attitudes to Immigrants in Switzerland
Telephone survey asking about several specific immigrant groups as potential new neighbours.
- N=1008, Switzerland, May 2013. On Dataverse.
We have re-run some of these questions in 2020 using an online panel. [TBA]
Labour Market Vignettes, Switzerland
Following a survey with students on attitudes to minority groups, I included a vignette experiment on hiring discrimination. The result suggests no discrimination. I also run the experiment with a sample of the general population. The results suggest no discrimination, but I don’t trust them.
- N=197, Switzerland, November 2014, student sample. On Dataverse.
- N=17, Switzerland, May 2015, student sample, priming test. On Dataverse.
- N=216, Switzerland, November 2016. On Dataverse.
Survey on Minorities with Students
80 questions on attitudes to different minority groups, haphazard sample of 197 university students
- N=197, Switzerland, November 2014. On Dataverse
Meta-Analysis on Ethnic Pay-gaps
We’re currently coding the last articles. [TBA]
Media Analysis
Political Claims Analysis
These are the data by the SOM project. The original data are already freely available from the project, but I have cleaned the original data extensively, and enriched them with a few variables. This extension includes the gender and ethnicity (Western/not-Western) of claims-makers as coded by myself. The second datafile contains aggregates by country-years for several variables, and is also enriched them with new variables.
- N=10k, SOM countries (AT, BE, CH, ES, IE, NL, UK), November 2016. All information on Dataverse.
- N=115, SOM countries, August 2018: Aggregated data (country-years) with additional contextual data on Dataverse.
- several additional datasets by the SOM project (demographics, legal situation, political opportunity structures) are freely available: on the SOM project website
- N=4.9k political claims on migration in newspapers, extension 2010 to 2018, mostly 1 newspaper per country. The extension is only partial in some countries (AT, UK, BE-NL, NL, IE); coding and data cleaning continues (especially AT, UK) but this extension will fall short of the target for the foreseeable future (N=400 random days covered in CH, BE-FR, ES). Previews on Zenodo.
Participation and Representation
Political Participation in the Canton of Geneva, 2015
These are data on political participation and voting at the municipal level in the Canton of Geneva, 2015. I have designed the questionnaire together with Rosita Fibbi, and we have re-used many questions from the Swiss Electoral Study to ensure comparability. We have also added variables we thought are relevant for the (non-) participation of immigrants and their children. The raw data are on FORS, the cleaned data on Dataverse:
- N=832, Canton of Geneva, Switzerland, September-October 2015. All information on Dataverse.
Immigrants in Swiss Politics (Experimental)
I have started to collect information on politicians in Switzerland who are immigrant, or descendants of immigrants. There is no system in the collection of these data, I simply jotted down when I came across relevant information.
- N=121, Switzerland, 1816 to 2016. All information on Dataverse.
Ethnic Groups in National Legislatures
- N=131 (+46) countries, 2006. Ethnic representation scores and detailed data: on Dataverse.
- N=131 countries, 2006, Ethnic quotas: on Dataverse.
- N=131 countries, 2006, Ethnic concentration: on Dataverse.
Migration Policies and Party Positions
MIPEX Extensions
There is full coverage of MIPEX in Switzerland, 1848 to 2014; for the SOM countries, we have collected information for 1995, 2000, 2004, 2007, and 2009. I have gone through the documentation to identify the years of policy changes, yielding yearly data.
- MIPEX Switzerland, 1848 to 2014 on Dataverse.
- SOM countries (AT, BE, CH, ES, IE, NL, UK), 1995 to 2009 yearly on Dataverse.
Cantonal Migration Policies 2018
Data need documentation to be useful. [TBA]
Party Positions on Immigration
The basic data on Austria, Belgium, Switzerland, Spain, France, Ireland, the Netherlands, and the UK are included in the supplement of the Party Politics paper. Additional manifestos from Austria, Switzerland, Ireland, South Africa, the UK, and the US and their coding were included in the data on OSF.
- Checklist coding, N=442 manifestos coded. On OSF.
- Sentence-by-sentence coding, N=9,147 sentences coded, some with corresponding sentences. On OSF.
- Sections on migration, manually selected, N=461 text documents. On OSF.
- Word counts of the sections on migration. On OSF.
Laura Morales might have more data on Germany, Italy, and Greece.
Citizenship, Migration and Mobility in a Pandemic (CMMP)
Migrant Behaviour
Migration Plans and (Returnable) Fees
Location Decisions
Conjoint experiment on location choice of immigrants. N=1,596 participants, N=15,960 observations. cases in total. Switzerland, 2020-21. On Zenodo.
Survey on Migration in Kenya, Nigeria, South Africa
Survey carried out as part of the Swiss Subsaharan Africa Migration Network (S-SAM). Questions include internal migration, migration ambitions, push factors, health and migration, remittances, the impact of Covid-19 on migration ambitions, motivations for irregular migration, expected challenges during migration, reasons for not migrating, narratives of migration, and a survey experiment on whom in the family should emigrate.
N=1750 respondents in each country (of which 21 to 117 migrants), May 2021. [TBA]
South African Survey: Trust, Representation, Immigration
I have combined many things in this survey in South Africa. Using random quotas, these data are supposedly representative of the general population. There are two trust games, questions about political participation and representation, including two experiments on skin colour and gender, a question on who immigrants are, a feeling thermometer to mixed-race people using blended images, a question on fitting a team focusing on skin colour and gender, and the obligatory questions on the respondents. I also included questions on the composition of respondents’ network, multiple identity, racial segregation, risk aversion, and norms (by Heiko Rauhut).
- N=1378, South Africa, July 2017. All information will be added on Dataverse [TBA]
US Survey: Trust, Immigration
This survey re-uses many questions from the South African survey, adapted for the US. There’s the same trust game, a feeling thermometer to mixed-race people, questions on redistribution (by Sergi Pardos-Prado), a question on who immigrants are, along with questions on the respondents.
- N=1353, US, November 2017. All information will be added on Dataverse [TBA]
Swiss Survey: Trust, Immigration
This survey includes a trust game in Switzerland, and questions on who immigrants are, alongside questions on respondents.
- N=436, Switzerland, December 2016. All information will be added on Dataverse [TBA]
Trust Game Pilot
In this survey, I tested the trust game in Switzerland using an online panel. There are more extensive manipulation and comprehension checks than in the surveys above, and a limited set of questions on the respondents.
- N=213, Switzerland, June 2016, continuous outcome. All information will be added. [TBA]
- N=231, Switzerland, November 2016, binary outcome. All information will be added on Dataverse [TBA]
Last update: 22 March 2023
Didier Ruedin 