Quantitative Sociology

Sociologists at CREST and the Economics Department of IP Paris address questions of scientific and public relevance, guided by sociological theory and supported by empirical data and quantitative or computational methods. The group has strong expertise in statistical methodology and in the analysis of quantitative data, drawing on both traditional sources such as national and international surveys or administrative registers, and new forms of data, including large-scale digital traces, sensor data, and text data.

Our current research covers a broad range of topics, including social mobility and inequality, demography, urban sociology, consumption and spending, lifestyles and cultural practices, environmental attitudes and actions, social networks, economic sociology, work and labor, migration and immigration, health and well-being, and politics.

The group is also active in the field of computational social sciences, which uses computers and digital data to advance social scientific research. We regularly host international events such as summer schools and conferences. For more information, visit css.cnrs.fr.

Our monthly research seminar brings together French and international scholars. The agenda is available online on the CREST website.

We welcome visiting scholars interested in spending time with our group in Paris. Please feel free to contact us if you wish to collaborate or visit.

Training future quantitative and computational sociologists is at the core of our mission. Our dynamic group of doctoral students actively contributes to the daily life and research activities of the team. We teach courses in the ENSAE Paris curriculum, the Master’s program in Quantitative Sociology and Demography, and the newly opened Master’s program in Computational Social Sciences. In addition, we organize an annual Summer School in Computational Social Science.

Each Spring, we recruit students for our PhD program in sociology, offering a 3-year contract. Interested candidates are encouraged to contact potential supervisors early to discuss research interests and application procedures.