Janneke van Brummelen

Emailj.n.van.brummelenvunl

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Janneke van Brummelen is an Assistant Professor (Tenure-Track) at the department of Econometrics and Data Science. Her research interests are Econometric Methodology, Econometric Theory, and Time Series Econometrics.

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3 Article
2 Entry for encyclopedia/dictionary
2 Working paper
1 PhD-Thesis - Research and graduation internal

Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions
Blasques, F., van Brummelen, J., Gorgi, P. & Koopman, S. J., Jan 2024, In: Journal of Econometrics. 238, 1, 22 p., 105575.
Research output: Contribution to Journal › Article › Academic › peer-review

Open Access
Maximum likelihood estimation for score-driven models
Blasques, F., van Brummelen, J., Koopman, S. J. & Lucas, A., Apr 2022, In: Journal of Econometrics. 227, 2, p. 325-346 22 p.
Research output: Contribution to Journal › Article › Academic › peer-review

Open Access
File
371 Downloads (Pure)
A robust Beveridge–Nelson decomposition using a score-driven approach with an application
Blasques, F., van Brummelen, J., Gorgi, P. & Koopman, S. J., Mar 2024, In: Economics Letters. 236, p. 1-5 5 p., 111588.
Research output: Contribution to Journal › Article › Academic › peer-review

Open Access
On the estimation of parameters in observation-driven time series models
van Brummelen, J. N., 18 Oct 2023, 242 p.
Research output: PhD Thesis › PhD-Thesis - Research and graduation internal

Open Access
File
552 Downloads (Pure)
Score-Driven Models: Methodology and Theory
Artemova, M., Blasques, F., van Brummelen, J. & Koopman, S. J., 19 Oct 2022, Oxford Research Encyclopedia of Economics and Finance. Living ed. Oxford University Press, p. 1-33 33 p.
Research output: Chapter in Book / Report / Conference proceeding › Entry for encyclopedia/dictionary › Academic › peer-review

Open Access
File
35 Downloads (Pure)

Differential Privacy and Statistical Inference under Differential Privacy
Ronald de Vlaming
1/09/24 → 31/08/25
Course
Machine Learning for Econometrics and Data Science
Janneke van Brummelen
1/09/24 → 31/08/25
Course

dr. Janneke van Brummelen

Personal profile

Personal information

Ancillary activities

Fingerprint

Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions

Maximum likelihood estimation for score-driven models

A robust Beveridge–Nelson decomposition using a score-driven approach with an application

On the estimation of parameters in observation-driven time series models

Score-Driven Models: Methodology and Theory

Differential Privacy and Statistical Inference under Differential Privacy

Machine Learning for Econometrics and Data Science

dr. Janneke van Brummelen

Personal profile

Personal information

Ancillary activities

Fingerprint

Research output

Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions

Maximum likelihood estimation for score-driven models

A robust Beveridge–Nelson decomposition using a score-driven approach with an application

On the estimation of parameters in observation-driven time series models

Score-Driven Models: Methodology and Theory

Courses

Differential Privacy and Statistical Inference under Differential Privacy

Machine Learning for Econometrics and Data Science