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Personal profile

Personal information

Siem Jan Koopman is Professor of Econometrics at the Department of Econometrics, Vrije Universiteit Amsterdam. He is also a research fellow at Tinbergen Institute and a long-term Visiting Professor at CREATES, University of Aarhus. Furthermore, he is a Journal of Applied Econometrics Distinguished Author, and Fellow of the Society of Financial Econometrics (SoFiE).

He held positions at London School of Economics and CentER (Tilburg University), and had long-term visits at US Bureau of the Census, European University Institute, and European Central Bank, Financial Research.

The monograph Time Series Analysis by State Space Methods is written by J. Durbin and SJK. The book originally appeared in 2001, the Second Edition in 2012. The book An Introduction to State Space Time Series Analysis appeared in 2007 and is written by J.J.F. Commandeur and SJK. His other books (co-authored, software and editorial) are listed here.

He is a Statistical Software Developer: STAMP, SsfPack.


The research interests of SJK cover topics in time series econometrics, financial econometrics, forecasting and simulation-based estimation. His current research focusses on score-driven time-varying parameter models (GAS models), state space models and dynamic factor models. He fullfills editorial duties at Journal of Business and Economic Statistics, Journal of Applied Econometrics, and Journal of Forecasting. Finally, SJK is an OxMetrics software developer for STAMP and SsfPack.

For more information see: http://sjkoopman.net/


Time Series Econometrics -- VU Amsterdam, MSc Econometrics

Advanced Econometrics III -- Tinbergen Institute, MPhil

Ancillary activities

No ancillary activities

Ancillary activities are updated daily

Education/Academic qualification

PhD, The London School of Economics and Political Science

1 Sep 198930 Mar 1992

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Research Output 1992 2019

Accelerating score-driven time series models

Blasques, F., Gorgi, P. & Koopman, S. J., 2019, In : Journal of Econometrics. 212, 2, p. 359-376

Research output: Contribution to JournalArticleAcademicpeer-review

Time series models

Bayesian Risk Forecasting for Long Horizons

Borowska, A., Hoogerheide, L. F. & Koopman, S. J., 2019, 018/III ed., Amsterdam: Tinbergen Institute, 40 p. (TI Discussion Paper Series; vol. 2019, no. 018/III).

Research output: Working paperAcademic

Forecasting economic time series using score-driven dynamic models with mixed-data sampling

Gorgi, P., Koopman, S. J. & Li, M., 2019, In : International Journal of Forecasting. 35, 4, p. 1735-1747

Research output: Contribution to JournalArticleAcademicpeer-review

Economic forecasting
GDP growth

Forecasting football match results in national league competitions using score-driven time series models

Koopman, S. J. & Lit, R., 1 Jan 2019, (Accepted/In press) In : International Journal of Forecasting.

Research output: Contribution to JournalArticleAcademicpeer-review

Time series models
Model specification

Long-term forecasting of El Niño events via dynamic factor simulations

Li, M., Koopman, S. J., Lit, R. & Petrova, D., 1 Jan 2019, (Accepted/In press) In : Journal of Econometrics.

Research output: Contribution to JournalArticleAcademicpeer-review

Dynamic factor
Long-term forecasting
Prediction error
Long-term forecast

Activities 2002 2016

  • 49 Lecture / Presentation
  • 14 PhD thesis examination
  • 13 Editorial work
  • 9 Membership

Aarhus University, Denmark (External organisation)

S.J. Koopman (Member)

Activity: MembershipAcademic

Society of Financial Econometrics (External organisation)

S.J. Koopman (Member)

Activity: MembershipAcademic

Journal of Business and Economic Statistics (Journal)

S.J. Koopman (Member of editorial board)

Activity: Peer review and Editorial workEditorial workAcademic

NYU Stern (External organisation)

S.J. Koopman (Member)

Activity: MembershipAcademic

Predicting time-varying parameters with parameter-driven and observation-driven models

S.J. Koopman (Speaker)
18 Jan 2013

Activity: Lecture / PresentationAcademic