298 Key Publications

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  Blasques, F., Koopman, S., Lucas, A. and Schaumburg, J. (2016). Spillover dynamics for systemic risk measurement using spatial financial time series models Journal of Econometrics, 195(2):211--223.

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  Blasques Albergaria Amaral, F., Koopman, S., Mallee, M. and Zhang, Z. (2016). Weighted Maximum Likelihood for Dynamic Factor Analysis and Forecasting with Mixed Frequency Data Journal of Econometrics, 193(2):405--417.

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  Christensen, B.J., Posch, O. and van der Wel, M. (2016). Estimating Dynamic Equilibrium Models using Macro and Financial Data Journal of Econometrics, 194(1):116--137.

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  Koopman, S., Lucas, A. and Scharth, M. (2016). Predicting time-varying parameters with parameter-driven and observation-driven models Review of Economics and Statistics, 98(1):97--110.

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  van Dijk, D., Lumsdaine, R. and van der Wel, M. (2016). Market set-up in advance of Federal Reserve policy rate decisions Economic Journal, 126(592):618--653.
• Einmahl, J., De Haan, L. and Zhou, C. (2016). Statistics of heteroscedastic extremes Journal of the Royal Statistical Society. Series B. Statistical Methodology, 78(1):31--51.

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  Boswijk, H., Jansson, M. and Nielsen, M. (2015). Improved likelihood ratio tests for cointegration rank in the VAR model Journal of Econometrics, 184(1):97--110.
• Jungbacker, B. and Koopman, S. (2015). Likelihood-based Dynamic Factor Analysis for Measurement and Forecasting Econometrics Journal, 18(2):C1--C21.

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  Koopman, S., Lucas, A. and Scharth, M. (2015). Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models Journal of Business and Economic Statistics, 33(1):114--127.

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  Kleibergen, F. and Zhan, Z. (2015). Unexplained factors and their effects on second pass R-squared’s Journal of Econometrics, 189(1):101--116.
• Gresnigt, F., Kole, E. and Franses, P.H. (2015). Interpreting financial market crashes as earthquakes: A new early warning system for medium term crashes Journal of Banking and Finance, 56:123--139.
• Blasques, F., Koopman, S. and Lucas, A. (2015). Information Theoretic Optimality of Observation Driven Time Series Models Biometrika, 102(2):325--343.

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  Kleibergen, F. and Mavroeidis, S. (2014). Identification issues in limited-information Bayesian analysis of structural macroeconomic models Journal of Applied Econometrics, 29(7):1183--1207.

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  Zu, Y. and Boswijk, H. (2014). Estimating spot volatility with high-frequency financial data Journal of Econometrics, 181(2):117--135.

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  Lucas, A., Schwaab, B. and Zhang, X. (2014). Conditional euro area sovereign default risk Journal of Business and Economic Statistics, 32(2):271--284.

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  Creal, D., Schwaab, B., Koopman, S. and Lucas, A. (2014). Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk Review of Economics and Statistics, 96(5):898--915.

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  Mesters, G. and Koopman, S. (2014). Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time Journal of Econometrics, 180(2):127--140.

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  Jungbacker, B., Koopman, S. and van der Wel, M. (2014). Smooth Dynamic Factor Analysis with Application to the U.S. Term Structure of Interest Rates Journal of Applied Econometrics, 29(1):65--90.
• Scholtus, M.(., van Dijk, D. and Frijns, B. (2014). Speed, algorithmic trading, and market quality around U.S. macroeconomic news announcements Journal of Banking and Finance, 38:89--105.

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  van Dijk, D., Koopman, S., van der Wel, M. and Wright, J. (2014). Forecasting interest rates with shifting endpoints Journal of Applied Econometrics, 29:693--712.