Laboratory of Econometrics for Macroeconomics and Finance
A.Y. 2019/2020
Learning objectives
The course introduces the students to modern techniques in the area of financial econometrics and macro-econometrics; in particular, we will start from theoretical economic models and derive the appropriate relationships to test whether such economic theories can find empirical support. Empirical examples will be discussed during the classes and the results replicated using appropriate econometric softwares.
Expected learning outcomes
At the end of the laboratory, thanks also to the theoretical notions taught during the course of Time Series Analysis, students will be able to deal independently with empirical studies on macroeconomic and financial topics. Starting from a specific economic model, students will be able to define the research question, to obtain the data from institutional databases, as well as to specify an appropriate univariate or multivariate econometric model. Moreover, students will be able to estimate the unknown parameters through an econometric software and interpret critically the estimated coefficients according to the main theoretical economic frameworks. The empirical studies proposed during the lessons will represent a starting point for students intending to pursue an empirical final thesis.
Lesson period: Second trimester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
Second trimester
Course syllabus
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 impact of uncertainty on the business cycle
- Measuring uncertainty
- Measuring the impact of uncertainty on the real economy
- 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 impact of uncertainty on the business cycle
- Measuring uncertainty
- Measuring the impact of uncertainty on the real economy
Prerequisites for admission
Basic course of Time Series Econometrics.
Teaching methods
Lassons and classes in the computer lab.
Teaching Resources
Books:
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.
Papers:
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.
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.
Papers:
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.
Assessment methods and Criteria
No final exam but it is mandatory to participate to all lessons.
SECS-P/05 - ECONOMETRICS - University credits: 3
Laboratory activity: 20 hours
Professor:
Bacchiocchi Emanuele
Shifts:
-
Professor:
Bacchiocchi Emanuele