90349 - STRUCTURAL MACROECONOMETRICS

Anno Accademico 2022/2023

  • Docente: Luca Fanelli
  • Crediti formativi: 6
  • SSD: SECS-P/05
  • Lingua di insegnamento: Inglese
  • Modalità didattica: Convenzionale - Lezioni in presenza
  • Campus: Bologna
  • Corso: Laurea Magistrale in Economics (cod. 8408)

Conoscenze e abilità da conseguire

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.

Contenuti

Introduction to the course: What is a shock? Macroeconomic shocks and their impact: impulse response functions (IRFs).

Examples: the impact of uncertainty shocks, the impact of monetary policy shocks, the impact of fiscal shocks.

Vector Autoregressions (VARs): representations and estimation issues (short account)

Structural Vector Autoregressions (SVARs):

    - Cholesky-SVARs;

    - B-model: identification and estimation;

    - A-model: identification and estimation;

    - AB-model: identification and estimation;

    - Confidence bands for impulse responses: bootstrap methods (short account) 

    - Identification through long-run restrictions

 

Novel identification schemes:

    - Sign restrictions (frequentist approach)

    - Identification through heteroskedasticity

    - Proxy-SVARs

    - Local Projections

Testi/Bibliografia

- Slides provided by the teacher available online

- Kilian, L. and H. Lutkepohl (2017), Structural Vector Autoregressive Analysis, Cambridge University Press.

- Lutkepohl. H. (2015), New Introduction to Multivariate Time Series Analysis, Springer

- Amisano, G. and C. Giannini (1997), Topics in Structural VAR Econometrics, 2nd edn, Springer, Berlin.

 

Metodi didattici

Traditional classes and "virtual labs" (i.e. the students bring their laptops in the classroom with freely or Unibo licenzed econometric softwares installed).


In case the course will be held online the exam will consist in the development of exercises that will be sent online to the professor according to the rules that will be negotiated

 

Attending classes is crucial to fully understand the spirit of this course

Modalità di verifica e valutazione dell'apprendimento

The exam aims to verfy that the student has achieved the basic ingredients necessary to quantify the impact of macroeconomic shocks on the macroeconomy by SVAR methods.

More in detail, the students is supposed to have acquired:

  - the knowledge of VAR models as key tools to capture dynamic properties of macroeconomic variables;

   - methods to address the identification problem implied by the SVAR methodology;

The student is also supposed to carry out independent empirical work.

The exam consists in writing a short paper on a project (related to the topics covered during classes) assigned by the teacher.

Alternatively, the student can propose a topic of interest whose consistentcy with the course contents must be evaluated and approved by the teacher.

Grades of the form XX/30 are given. Overall, the meaning of grades is as follows

<18 failed
18-23 sufficient
24-27 good
28-30 very good
30 e lode excellent.

Should the course be held online (because of Pandemic issues etc.) the exam will still consist in writing a short paper on a project (related to the topics covered during classes) assigned by the teacher.

 

 

 

Strumenti a supporto della didattica

Software used are:

Gretl wich open source and is freely downloadle from the web

Matlab for which Unibo has a licence which means that students can download and freely install it on their laptops, etc.

 

Orario di ricevimento

Consulta il sito web di Luca Fanelli

SDGs

Istruzione di qualità Parità di genere Lavoro dignitoso e crescita economica Imprese innovazione e infrastrutture

L'insegnamento contribuisce al perseguimento degli Obiettivi di Sviluppo Sostenibile dell'Agenda 2030 dell'ONU.