Course 2008-2009 a.y.

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 the methods of analysis of time series econometrics.
Lectures and exercises provide numerous examples and hands on sessions.
Interest is focused on estimation and testing of dynamic models derived from macroeconomic and financial theories. Students consider models of real variables, like GDP, production and unemployment and models for exchange rates, stock markets and interest rates. Having passed an introductory course in econometrics is not strictly required but some knowledge of the linear regression model and basic notions of statistical inference are recommended.

Course Content Summary

Part I:  Single equation models

• Introduction to time series econometrics
• ARMA and ARIMA Models
• Modeling trends and seasonality
• The treatment of aberrant observations
• Non linear models
• Non parametric models
• Models of conditional eteroskedasticity

Part II: Multiequations models

• VAR Models
• SVAR Models
• Common trends and cointegration
• VECM

Detailed Description of Assessment Methods

• Econometric project (max 3 students for group) with integrative oral exam

or

• Written exam

Textbooks

• P.H. FRANSES, Time Series Model for Business and Economic Forecasting, Cambridge University Press, 1998.

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

Last change 18/03/2008 12:33