Class Econometrics II

Estimation of Regression Models with Time Series. Applications focused on Macroeconomics and Financial Economics using STATA software

Not applicable

1. Autocorrelation 1.1. Nature of the problem 1.2. The 1st order auto-regressive process 1.3. Detection tests: from Durbin-Watson, from Breusch-Godfrey 1.4. Estimation methods 2. Models with lagged variables 2.1. Distributed lag models 2..2. Koyck transformation 2..3. Partial adjustment models 2.4. Adaptive expectations models 2.5. Estimation of autoregressive models 3. Univariate stationary and non-stationary models 3.1. Stationary and Unit Root Tests 3.2. ARMA / ARIMA models 4. Models of conditioned heteroscedasticity and volatility: ARCH / GARCH 5. Stationary and non-stationary multivariate models 5.1. Multivariate models - VAR (Vector auto-regression) 5.2. Granger Causality and Cointegration, 5.3. VECM (vector error correction models) and Johansen Method models;

The approaches are primarily aimed at developing advanced econometric skills. This requires an understanding of the specific techniques of econometrics and a knowledge of economic analysis. To achieve these requirements, the aim is to consolidate and develop students' theoretical foundations and analytical skills. Classes are supported by the reading of teaching and research material, PowerPoints with the relevant topics of the lessons, keywords and the analysis and discussion of practical problems associated with empirical research in Economics. The modus operandi used in the teaching-learning process seeks to encourage students to participate actively in class. Practical classes focus on solving exercises and collecting and processing economic data. These classes aim to promote debate based on analytical arguments, as well as synthesis, critical thinking and proficiency in oral communication  

Asteriou, Dimitrios e Hall, Stephen G., Applied Econometrics, Palgrave Macmilan, 3rd Ed., 2015. Wooldridge, J.M. (2015), "Introductory Econometrics: A Modern Approach", 7th Ed., Cengage Leraning (2020),