ADVANCED TOPICS IN TIME SERIES
Updated A.Y. 2022-2023
ADVANCED TOPICS IN TIME SERIES (DYNAMIC REGRESSION MODULE)
This module aims at providing a sound knowledge of the main results on regression methods for time series data. It is divided in two parts: the first one deals with small-scale dynamic regression models whereas the second one introduces to econometric dynamic modelling with a large number of predictors.
Dynamic regression models*
Autoregressive Distributed Lag model
Error (Equilibrium) Correction Model
Big data in dynamic econometric modelling#
Regularized Linear Models (Ridge Regression and Lasso)
Dimension Reduction methods (Principal Component Regression and Partial Least Squares)
Applications to macroeconomic and financial modelling and forecasting.
Harvey A. (1990), The Econometric Analysis of Time Series - 2nd Edition, The MIT Press.*
Hendry D. (1995), Dynamic Econometrics, Oxford University Press.*
P Peña D., and Tsay R.S. (2021) Statistical Learning for Big Dependent Data, Wiley.#