Data Science and Econometrics
The Netherlands has a strong tradition in econometrics and data analysis. Data science combines these traditions by focusing on quantitative methods to extract knowledge and insights from structured and unstructured data. The methods contain more traditional econometric methods as well as more novel machine learning methods. Applications are in the fields of marketing, management, economics and focus on both obtaining descriptive as well as causal evidence.
Data Science and Econometrics
The Netherlands has a strong tradition in econometrics and data analysis. Data science combines these traditions by focusing on quantitative methods to extract knowledge and insights from structured and unstructured data. The methods contain more traditional econometric methods as well as more novel machine learning methods. Applications are in the fields of marketing, management, economics and focus on both obtaining descriptive as well as causal evidence.
Our people
Key publications
Upcoming events
Estimation of large approximate dynamic matrix factor models...
Matteo Barigozzi (University of Bologna, Italy)
- Erasmus Econometric Institute Series
Reviving Pseudo-Inverses for Large Dimensional Portfolio Selection...
Nestor Parolya (TU Delft)
- Erasmus Econometric Institute Series
An Anatomy of Asset Returns
Roberto Renò (ESSEC Business School, France)
- Econometrics Seminars and Workshop Series
Graph Joinings, Reversible Markov Chains, and Graph Isomorphism
Andrew Nobel (University of North Carolina, United States)
- Erasmus Econometric Institute Series
Title to be announced
Stanislav Anatolyev (CERGE-EI, Czech Republic)
- Erasmus Econometric Institute Series
Academic Distinctions
Frank Kleibergen elected Fellow of the Econometric Society
Frank Kleibergen
Annika receives an NWO Open Competition SSH XS grant
Annika Camehl
NWO Open Competition SSH M Grant
Andre Lucas