THE COURSE IS DELIVERED BOTH IN ONLINE MODE AND IN PRESENCE
PARTICIPANTS MAY EXPRESS THEIR PREFERENCE UPON ACCEPTANCE
Bertinoro, 30 August - 5 September 2020
Università di Firenze
Dipartimento di Statistica, Informatica, Applicazioni “G. Parenti”
Viale Morgagni 59
Giorgio Calzolari , University of Firenze
Francesca Di Iorio, University of Napoli Federico II
Marco Lippi , Einaudi Institute for Economics and Finance, Roma
Giulio Palomba , Università Politecnica delle Marche
Umberto Triacca, University of L'Aquila
The course requires a working knowledge of basic linear algebra, statistical inference and multiple linear regression model with the notation of linear algebra (matrices and vectors).
To this aim the following preliminary readings are suggested:
Chapt. 1, 2, 3, 6 in Greene, W. H. (2002): Econometric Analysis (5-th edition). Upper Saddle River (NJ): Prentice Hall.
Or chapt. 1-6 in Johnston, J. (1984): Econometric Methods (3rd edition). New York: McGraw-Hill, Inc. Italian translation by M. Costa and P. Paruolo (1993): Econometrica (3rd edition). Milano: Franco Angeli.
Reference textbook for the course:
Handouts, readings and further material will be provided before the beginning of the course and during the lectures.
Schedule of the course:
Linear regression, seemingly unrelated regressions, simultaneous equations, maximum likelihood
Classical linear regression model (refresh).
Elements of asymptotic theory: law of large numbers and central limit theorem (outline).
Introduction to stochastic processes and Wold representation
Introduction to time series analysis
Likelihood: definition, score vector, information matrix, Cramer-Rao inequality, maximum likelihood, consistency, asymptotic efficiency.
Seemingly unrelated regression equations (SURE): generalized least squares (GLS), feasible GLS, maximum likelihood (iterative GLS, hints).
Simultaneous equations model: structural form and reduced form, static and dynamic solution, impact and dynamic multipliers, forecast, scenarios and economic policy.
Identification: rank and order condition.
Estimation: instrumental variables, limited-information methods (2SLS, LIVE, IIV)
Practical applications using the freeware software Gretl (download here).
For the computer tutorials participants will use the Gretl package, which will have to be installed on their own laptops. In exceptional cases, when students cannot use their computer, we may be able to supply an alternative solution, but please inform the course coordinator beforehand.
Program is conditional to the recruitment of a minimum of 15 participants
Venue and timetables
The course will last one week and will be held in the University Residential Centre, Via Frangipane 6, 47032 Bertinoro (FC).
Participants will be hosted in the Centre guest quarters, (as an exception, in case of reduced availability of rooms in the Centre, they will be accommodated in local hotels).
Lectures and tutorials will be in English, with the following schedule:
Monday to Friday: lectures: 9.00-13.00, 15.30-17.30; tutorials: 17.40-19.30.
Saturday: lectures: 9.00-13.00.
Fees and Enrollment
* Course in Bertinoro
- Students, new graduated students, PhD students and temporary university staff: 690€
- University staff: 800€
- Others: 2300€
Fee includes: accommodation (breakfast and lunch starting from Sunday evening).
* Online Course
- Students, new graduated students, PhD students and temporary university staff: 340 euro
- University staff: 450 euro
- Others: 1500 euro
In case of enrollment in two or more courses Student and Staff participants are entitled to a discount of 100 euros on each course. Other participants are entitled to a discount of 300 euros on each course.
Application Deadline: July 15th, 2020
Deadline for Fee Payment is August 10th 2020
- For more information: Antonella Mallus e-mail: firstname.lastname@example.org
- For administrative issues : Alessandra Picariello phone:+39 0512092637; e-mail: email@example.com
- For travel and accommodation: Monica Michelacci (firstname.lastname@example.org), Roberta Partisani (email@example.com) phone: +39 0543446500