Lange, R.J., van Os, B. and van Dijk, D. (2026). Implicit score-driven filters for time-varying parameter models Journal of Econometrics, 255.
Rutger-Jan Lange
University
Erasmus University Rotterdam
E-mail
Research field
Econometrics
Interests
Econometrics, Finance, Financial Econometrics, Mathematical Methods, Operations Research, Time Series Econometrics
Website
Biography
Rutger-Jan Lange is Associate Professor of Econometrics at the Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, and a Research Fellow at Tinbergen Institute. His research focuses on time-series econometrics, filtering methods, stochastic gradient methods, real options, and optimal stopping. He holds a PhD from the University of Cambridge and has published in journals including the Journal of Econometrics, Journal of Economic Theory, Journal of Financial and Quantitative Analysis, and Operations Research.
Key publications
List of publications
Lange, R.J., van Os, B. and van Dijk, D. (2026). Implicit score-driven filters for time-varying parameter models Journal of Econometrics, 255.
Lange, R. and Teulings, C.(. (2024). Irreversible investment under predictable growth: Why land stays vacant when housing demand is booming Journal of Economic Theory, 215.
Lange, R. (2024). Bellman filtering and smoothing for state-space models Journal of Econometrics, 238(2).
Grubb, M., Lange, R.J., Cerkez, N., Sognnaes, I., Wieners, C. and Salas, P. (2024). Dynamic determinants of optimal global climate policy Structural Change and Economic Dynamics, 71:490--508.
Lange, R., Ralph, D. and Store, K. (2019). Real-Option Valuation in Multiple Dimensions Using Poisson Optional Stopping Times Journal of Financial and Quantitative Analysis, 55(2):653--677.
Niesert, R., Oorschot, J., Veldhuisen, C., Brons, K. and Lange, R. (2019). Can Google search Data help predict macroeconomic series? International Journal of Forecasting.
Lange, R., Atkinson, A. and Kress, M. (2016). When Is Information Sufficient for Action? Search with Unreliable yet Informative Intelligence Operations Research, 64(2):315--328.