Laboratory of econometrics for macroeconomics and finance

A.A. 2019/2020
Insegnamento per
Crediti massimi
Ore totali
Obiettivi formativi
The course introduces the student to modern techniques in the area of financial (empirical) econometrics and macro-econometrics; in particular, the interaction between theory and empirical analysis is emphasised. Empirical examples will be discussed during the classes and the results replicated using appropriate econometric softwares.

Struttura insegnamento e programma

Edizione attiva
Attivita' di laboratorio: 20 ore
1) Review of time series econometrics
- Univariate stationary ARMA models
- Stationary vs non-stationary time series
- Cointegration and error-correction models
- VAR and SVAR models
- ARCH and GARCH models

2) On the transmission of monetary policy shocks
- Estimating the univariate Taylor rule
- Monetary policy shocks and SVAR models
- Monetary policy shocks and local projection

3) Estimating ARCH and GARCH models
- Using the estimated volatility in financial and macroeconomic models

4) On the relationships between uncertainty and the business cycle
- Measuring uncertainty
- Measuring the transmission of uncertainty
Time Series Analysis
Prerequisiti e modalità di esame
Students can participate to the laboratory only after having passed the Time Series Analysis exam. For participating, students must register by sending an email to the professor at A maximum number of 20 students will be admitted (the first registered 20 students).
Materiale didattico e bibliografia
Reference Literature


Verbeek M. - A guide to modern econometrics John Wiley & Sons, Ltd. (main reference)

Cochrane H.J. - Time Series for Macroeconomic and Finance, downloadable from ARIEL - Advanced Econometrics

Brooks C. - Introductory Econometrics for Finance, Cambridge university Press, Chapters 5-6-7-8.

Favero C.A. - Applied Macroeconometrics, Oxford University Press.


Bacchiocchi, E. and Fanelli, L. (2015), Identification in Structural Vector Autoregressive models with structural changes, with an application to U.S. monetary policy, Oxford Bulletin of Economics and Statistics 77, 761-779.

Bacchiocchi, E., Castelnuovo, E. and Fanelli, L. (2017), Give me a break! Identification and estimation of the macroeconomic effects of monetary policy shocks in the U.S., Macroeconomic Dynamics, forthcoming.

Beetsma, R. and Giuliodori, M. (2012), The changing macroeconomic response to stock market volatility shocks, Journal of Macroeconomics 34, 281-293.

Bekaert, G., Hoereva,M. and Lo Duca, M. (2013), Risk, uncertainty and monetary policy, Journal of Monetary Economics 60, 771-786.

Bloom, N. (2009), The impact of uncertainty shocks, Econometrica 77, 623-685.

Boivin, J., and M. Giannoni (2006): Has Monetary Policy Become More Effective?, Review of Economics and Statistics, 88(3), 445-462.

Christiano, L., M. Eichenbaum, and C. Evans (1996), The effects of monetary policy shocks: Evidence from the ow of funds, Review of Economics and Statistics 78(1), 16-34.

Jurado, K., Ludvigson, S.C. and Ng, S. (2015), Measuring uncertainty, American Economic Review 105(3), 1177-1216.
Secondo trimestre
Secondo trimestre
Modalità di valutazione
Giudizio di approvazione
Giudizio di valutazione
superato/non superato
Nella settimana 9-14 settembre 2019, il ricevimento studenti avrà luogo martedì dalle 12:00 alle 15:00.
stanza 31