Professor
Swedish institute for social research
Telephone
Visiting address
Universitetsvägen 10 F
Room F 945
Postal address
Institutet för social forskning
106 91 Stockholm
Carina Mood is a professor in the Level-of-living team at SOFI, Stockholm University, and heads research teams there and at the Institute for Futures Studies. Her research interests include poverty, inequality, integration, intergenerational transmission of advantage, and the welfare and well-being of children and youth.
She currently heads the following research programs and projects:
- MINQ (Interlocking inequalities: A multidimensional perspective on inequality in contemporary Sweden). Funded by Forte.
- IntegrateYouth. A collaboration with Nuffield College, Oxford University, and Fafo, Norway, using primarily the CILS4EU and CILS-NOR data. Funded by NordForsk.
- Intergenerational mobility: Shifting the focus. Funded by Vetenskapsrådet.
She is also co-PI for the 2020 Level of Living Survey, the 7th of the Swedish Level of Living Surveys.
Integration among youth
- Karriärer och barriärer: En ESO-rapport om skolgång och etablering för unga med utländsk bakgrund can be downloaded for free here.
- Integration bland unga: En mångkulturell generation växer upp (Integration among youth: A multicultural generation grows up) can be ordered here or downloaded for free here.
And check out the companion website with facts about integration among youth in Sweden!
Logistic regression
Note August 2017: Due to other research commitments, I will not have time to engage in pure methodological research or discussions about logistic regression and related topics in the foreseeable future. For anyone interested, I provide a link to an unsubmitted article draft from April 2017. I had planned to do more work on it but will not have the time, so I instead publish it online only. Please note that I will not have time to respond to questions about the manuscript. Feel free to develop these insights, as long as you cite the source.
(Unpublished manuscript 2017) Logistic regression: Uncovering unobseved heterogeneity