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):.
Paolo Gorgi
University
Vrije Universiteit Amsterdam
E-mail
Research field
Econometrics
Interests
Econometric Methodology, Econometric Theory, Econometrics, Time Series Econometrics
Website
Biography
Paolo Gorgi is Associate Professor at Vrije Universiteit Amsterdam. He obtained his BSc and MSc in the field of Statistical Sciences at the University of Padova, Italy. He was awarded a double PhD from the University of Padova and the Vrije Universiteit Amsterdam. His main research interests concern: time series analysis, statistical inference for dynamic models and forecasting economic variables.
Key publications
Gorgi, P., Koopman, S.J. and Schaumburg, J. (2024). Vector autoregressions with dynamic factor coefficients and conditionally heteroskedastic errors Journal of Econometrics, 244(2):.
Armillotta, M. and Gorgi, P. (2024). Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models Journal of Econometrics, 246(1-2):.
Gorgi, P. and Koopman, S.J. (2023). Beta observation-driven models with exogenous regressors: A joint analysis of realized correlation and leverage effects Journal of Econometrics, 237(2):1--21.
Blasques, F., Gorgi, P. and Koopman, S.J. (2021). Missing observations in observation-driven time series models Journal of Econometrics, 221(2):542--568.
List of publications
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):.
Blasques, F., van Brummelen, J., Gorgi, P. and Koopman, S.J. (2024). A robust Beveridge–Nelson decomposition using a score-driven approach with an application Economics Letters, 236:1--5.
Gorgi, P., Koopman, S.J. and Schaumburg, J. (2024). Vector autoregressions with dynamic factor coefficients and conditionally heteroskedastic errors Journal of Econometrics, 244(2):.
Armillotta, M. and Gorgi, P. (2024). Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models Journal of Econometrics, 246(1-2):.
Gorgi, P. and Koopman, S.J. (2023). Beta observation-driven models with exogenous regressors: A joint analysis of realized correlation and leverage effects Journal of Econometrics, 237(2):1--21.
Blasques, F., Gorgi, P. and Koopman, S.J. (2021). Missing observations in observation-driven time series models Journal of Econometrics, 221(2):542--568.
Gorgi, P. (2020). Beta–negative binomial auto-regressions for modelling integer-valued time series with extreme observations Journal of the Royal Statistical Society. Series B. Statistical Methodology, 82(5):1325--1347.
Blasques, F., Gorgi, P. and Koopman, S.J. (2019). Accelerating score-driven time series models Journal of Econometrics, 212(2):359--376.
Gorgi, P., Koopman, S.J. and Li, M. (2019). Forecasting economic time series using score-driven dynamic models with mixed-data sampling International Journal of Forecasting, 35(4):1735--1747.
Gorgi, P., Hansen, P.R., Janus, P. and Koopman, S.J. (2019). Realized wishart-garch: A score-driven multi-Asset volatility model Journal of Financial Econometrics, 17(1):1--32.
Angelini, G. and Gorgi, P. (2018). DSGE Models with observation-driven time-varying volatility Economics Letters, 171:169--171.