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
Bootstrapping Autoregressive Duration Models
Anders Rahbek (University of Copenhagen, Denmark)
- Erasmus Econometric Institute Series
Extremes with Random Covariates
Just de Groot
- PhD Seminars
Learning, Heuristics and Anchored Inflation: How do Different...
Kevin Lee (The University of Nottingham, United Kingdom)
- Erasmus Econometric Institute Series
Sparse Tree-Based Aggregation for Time Series Regressions
Ines Wilms (Maastricht University)
- Econometrics Seminars and Workshop Series
Title to be announced
Kevin Dano (Princeton University, United States)
- Econometrics Seminars and Workshop 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