Bertsch, C., Hull, I., Lumsdaine, RobinL. and Zhang, X. (2025). Central bank mandates and monetary policy stances: Through the lens of Federal Reserve speeches Journal of Econometrics, 249:.
217 Key Publications
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Margaritella, L. and Sessinou, R. (2025). Precision Least Squares: Estimation and Inference in High-Dimensions Journal of Business and Economic Statistics, :. -
Paap, R. and Franses, P.H. (2025). Shrinkage estimators for periodic autoregressions Journal of Econometrics, 247:. -
de Santis, R., Goeman, JelleJ., Hemerik, J., Davenport, S. and Finos, L. (2025). Inference in generalized linear models with robustness to misspecified variances Journal of the American Statistical Association, https://doi.org/10.1080/01621459.2025.2491775:. -
He, Y. (2024). Ridge Regression Under Dense Factor Augmented Models Journal of the American Statistical Association, 119(546):1566--1578. -
Lange, R. (2024). Bellman filtering and smoothing for state-space models Journal of Econometrics, 238(2):. -
Ahmed, H., Einmahl, JohnH.J. and Zhou, C. (2024). Extreme value statistics in semi-supervised models Journal of the American Statistical Association, 120(549):291--304. -
Kleen, O. (2024). Scaling and measurement error sensitivity of scoring rules for distribution forecasts Journal of Applied Econometrics, 39(5):833--849. -
Frazier, DavidT., Renault, E., Zhang, L. and Zhao, X. (2024). Weak Identification in Discrete Choice Models Journal of Econometrics, :. -
D'Innocenzo, E. and Lucas, A. (2024). Dynamic partial correlation models Journal of Econometrics, 241(2):. -
de Haan, L. and Zhou, C. (2024). Bootstrapping Extreme Value Estimators Journal of the American Statistical Association, 119(545):382--393. -
Creal, D., Koopman, S.J., Lucas, A. and Zamojski, M. (2024). Observation-driven filtering of time-varying parameters using moment conditions Journal of Econometrics, 238(2):1--14. -
Blasques, F., Francq, C. and Laurent, S. (2024). Autoregressive conditional betas Journal of Econometrics, 238(2):1--22. -
Gorgi, P., Koopman, S.J. and Schaumburg, J. (2024). Vector autoregressions with dynamic factor coefficients and conditionally heteroskedastic errors Journal of Econometrics, 244(2):1--23. -
Friedrich, M. and Lin, Y. (2024). Sieve bootstrap inference for linear time-varying coefficient models Journal of Econometrics, 239(1):1--29. -
Armillotta, M. and Gorgi, P. (2024). Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models Journal of Econometrics, 246(1-2):. -
Camehl, A., Fok, D. and Gruber, K. (2024). On superlevel sets of conditional densities and multivariate quantile regression Journal of Econometrics, 249:. -
Naghi, AndreaA., O'Neill, E. and Danielova Zaharieva, M. (2024). The benefits of forecasting inflation with machine learning: New evidence Journal of Applied Econometrics, 39(7):1321--1331. -
Blasques, F., van Brummelen, J., Gorgi, P. and Koopman, S.J. (2024). Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions Journal of Econometrics, 238(1):. -
Kleibergen, F. and Kong, L. (2024). Identification robust inference for the risk premium in term structure models Journal of Econometrics, :.