Working together to advance ideas for research in economic sociology
CSES organizes research around Laboratories and Working Groups. The labs and working groups provide an opportunity for faculty and graduate students to work together through regular meetings to advance ideas for research, present research in progress, and discuss topics of interest.
Economic Sociology Laboratory
The lab is directed by Victor Nee with the aim to develop a network-and-institutions approach in economic sociology. The research activity of the Lab centers on theory-driven empirical research examining the interplay of social networks and institutions on economic performance. The Lab provides a workshop environment enabling and guiding independent and collaborative research by students, post-doctoral fellows and faculty in advanced studies in economic sociology.
This networks and computational sociology lab is directed by Michael Macy. Designed to study the interplay between network topology and the dynamics of social interaction, this Lab employs computational models, data from on-line networks, and laboratory experiments with human participants to advance understanding of the dynamics of complex social structures.
This CSES Working Group aims to advance understanding of how in the global economy of the 21st century, the comparative advantage of regions turns on the entrepreneurs and start-up firms driving innovative activity and creative destruction. Its research activity involves a global network of researchers at Cornell University, Lund University (Sweden) and Renmin University (Beijing). Current research involves an ongoing large-scale study of firms in the Yangzi delta region and a study of tech start-up firms in New York City.
This CSES Working Group aims to advance understanding of the sociological foundations of the modern financial system. In particular, we bring together like-minded scholars—including faculty, postdoctoral fellows, and graduate students—to uncover and examine the mechanisms shaping how the complex and interdependent financial system functions.
This CSES Working Group aims to advance a sampling methodology that combines “snowball sampling” with a mathematical model that weights the sample (to compensate for the fact that the sample was collected in a non-random way). RDS is an advancement in sampling methodology because it resolves what had previously been an intractable dilemma, a dilemma that is especially severe when sampling hard-to-reach groups, that is, groups that are small relative to the general population, and for which no exhaustive list of population members is available.