- Docente: Luca Fanelli
- Credits: 6
- SSD: SECS-P/05
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Economics (cod. 8408)
Learning outcomes
At the end of the course the student has acquired a comprehensive knowledge of the main identification and estimation methods which can be featured by Structural Vector Autoregressions (SVARs) in order to quantify the dynamic causal effects of macroeconomic structural shocks of interest including, among others, the monetary policy shock and uncertainty shocks. In particular, he/she is able to - analyze critically the implications of macroeconomic theories in terms of estimated impulse response functions, and to make inference on the identified dynamic causal effects; - apply SVAR analysis to Euro area and/or U.S. monthly/quarterly data by available econometric packages with the idea of replicating existing results or producing new ones.
Course contents
COURSE CONTENTS
3 hours:
Introduction to the course
What is a shock?
Macroeconomic shocks and their impact: impulse response functions (IRFs).
Illustrative framework: simultaneity problems and shocks identification in a simplified fiscal framework
9 hours:
Vector Autoregressions (VARs)
Representations
Autoregressive representation
VMA representation and impulse response functions (IRFs)
Companion form representation
Estimation and properties of estimators
Estimation under parametric restrictions
Main inferential issues
12 hours:
Structural Vector Autoregressions (SVARs)
Identification problem
Choleski-SVARs
B-model and inference on the IRFs
A-model (and inference on the IRFs)
AB-model (and inference on the IRFs).
6 hours:
"Novel" identification schemes
Sign restrictions approach
Heteroskedasticity approach
Proxy-SVARs approach.
Leading examples during the course with applications in lab: the identification and impact of macroeconomic and financial uncertainty shocks.
Readings/Bibliography
- Slides provided by the teacher which will be available on IOL
- Kilian, L. and Lütkepohl, H. (2017), Structural Vector Autoregressive Analysis, Cambridge University Press
- Lütkepohl, H. (2015), New Intoduction to multivariate time series analysis, Springer
- Amisano, G. and Giannini, C. (1997). Topics in Structural VAR Econometrics, 2nd edn, Springer, Berlin.
Teaching methods
Traditional classes and labs: use of software (Matlab and/or Gretl)
Attending classes is crucial to fully understand the topics of this course
Assessment methods
The exam aims to verify that the student has achieved the basic ingredients necessary to quantify the impact of macroeconomic shocks on the economy by using SVARs.
More in detail, the students is supposed to have acquired:
• the knowledge of VAR models as key tools in order to capture the dynamics of macroeconomic variables;
• the identification problem implied by the use of SVARs;
• the most common identification methodologies.
The student is also supposed to carry out independent empirical work.
The exam is written and a grade of the form xx/30 is given.
Alternatively, the students will be asked to develop a project related to some of the topics discussed during classes.
Teaching tools
Office hours
See the website of Luca Fanelli