34481 - Econometrics 2

Learning outcomes

The module aims at introduce students to the field of time series econometrics and layout of the econometric theory of time series analysis. By the end of the module students will have learnt how to carry out empirical analysis using time series data, how to interpret the results of such analysis and will have acquired an ability to critically assess empirical papers in time series literature.

Course contents

1. Basic concepts of Stochastic Processes. Heterogeneity and memory of a process.

2. Stationarity and Ergodicity: simplifying restrictions.and practical consequences

3. The rationale of dynamic models, and some simple time series models.

4. Stationary linear models, trending behavior, unit roots and testing for stationarity

5. Spurious regression versus cointegration

6. Multivariate time series models, Vector autoreression (VAR) models, testing.

7. Granger causality, Impulse response functions, structural VAR models.

8. Non stationary multivariate models, Vector error correction models.

9. Testing for cointegration, estimating cointegrating rank and vectors.

Dynamic model behavior and model evaluation

1. Basic concepts of Stochastic Processes. Heterogeneity and memory of a process.

2. Stationarity and Ergodicity: simplifying restrictions.and practical consequences

3. The rationale of dynamic models, and some simple time series models.

4. Stationary linear models, trending behavior, unit roots and testing for stationarity

5. Spurious regression versus cointegration

6. Multivariate time series models, Vector autoreression (VAR) models, testing.

7. Granger causality, Impulse response functions, structural VAR models.

8. Non stationary multivariate models, Vector error correction models.

9. Testing for cointegration, estimating cointegrating rank and vectors.

Dynamic model behavior and model evaluation

Readings/Bibliography

W. Enders, Applied Econometric Time Series, 4^th Edition, J. Wiley, 2015

In addition, I will post some additional lecture material on the class web page, mostly my typed notes: “Introduction to Dynamic Models for time series data” (2011) and “Multiple Time Series Models” (2016)

W. Enders, Applied Econometric Time Series, 4^th Edition, J. Wiley, 2015

In addition, I will post some additional lecture material on the class web page, mostly my typed notes: “Introduction to Dynamic Models for time series data” (2011) and “Multiple Time Series Models” (2016)

Teaching methods

The book by Enders will be our main reference source. I will often explain technical details left out of the book. I will comment results of some empirical analysis from recent research. Practical exercises will be carried out in class, and students will be provided economic data so that they can practice on their behalf using the software Gretl.

Assessment methods

- Final written exam 70%, exam duration an hour and a half

- Homework 30%

Students will be divided into groups of two people and each group will be assigned a homework. The final report, which must not exceed 10 pages, to be delivered before the final exam date.

Teaching tools

Lessons will take place both on the board and with the use of slides. Econometric applications will be carried out with the use of Gretl software, that is free to use, and each of you can download it, install on the personal computer and practice at home

Office hours

See the website of Renzo Orsi