Insegnamento a.a. 2009-2010

Go to class group/s: 31

MM-LS (6 credits - II sem. - AI) - AFC-LS (6 credits - II sem. - AI) - CLAPI-LS (6 credits - II sem. - AI) - CLEFIN-LS (6 credits - II sem. - AI) - CLELI-LS (6 credits - II sem. - AI) - DES-LS (6 credits - II sem. - AI) - CLG-LS (6 credits - II sem. - AI) - M-LS (6 credits - II sem. - AI) - IM-LS (6 credits - II sem. - AI) - ACME-LS (6 credits - II sem. - AI) - EMIT-LS (6 credits - II sem. - AI)

Course Director:
LUCA SALA

Course Objectives

The course aims to improve the knowledge of time series econometrics and will discuss the most recent developments in the literature. Interest is focused on the estimation and testing of dynamic models derived from macroeconomic and financial theories. The course will deal with both the theoretical foundations and a number of applications to real data, with the aid of computer sessions.

Course Content Summary

Part I:  Single equation models

• Introduction to time series econometrics
• ARMA and ARIMA models
• Trend-cycle decompositions
• Models of conditional eteroskedasticity

Part II: Multiequation models

• VAR Models
• SVAR Models (with short and long run restrictions)
• Common trends and cointegration
• Cointegrated VAR models
• Error Correction Mechanisms 

Detailed Description of Assessment Methods

The final grade will be based on a written exam

Textbooks

• A complete and up-to-date reading list is provided at the beginning of the course
• The reference books for this course are:
  - W. ENDERS, Applied Econometric Time Series, Wiley Series in Probability
     and Statistics, 2004, 2^nd edition
  - J. D. HAMILTON, Time Series Analysis, Princeton University Press, 1994
• Lectures notes will be distributed during the course.

Exam textbooks & Online Articles (check availability at the Library)

Prerequisites

A basic knowledge of econometrics is highly recommended.

Last change 06/05/2009 16:14