Applied econometrics

Forecasting. Violations of the ... R.S. TSAY, Analysis of Financial Time Series, Wiley, 2010. ... Lecture will be complemented by tutorial exercises a...

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Applied econometrics PROF. GIOVANNI GUASTELLA; PROF. LUCA BAGNATO COURSE AIMS The course aims at acquainting students with the fundamental aspects of econometric methods from both classical and time-series standpoints. The purpose is to prepare the student to competently handle the basic econometric tools for the measurement, modelling, interpretation and forecast of macro, micro-economic and financial phenomena. The course has a solid content of econometric practice to complement basic theory. COURSE CONTENTS Introduction: the nature and scope of Econometrics. The Classical Linear Model: Basic Assumptions. The Ordinary Least Squares Method. The normality assumption and the maximum likelihood method. Multicollinearity, a-priori information and Restricted Least Squares method. Forecasting. Violations of the Classical Model Assumptions. Model selection: criteria and tests. Models with stochastic regressors: instrumental variable estimator, two-stage least-squares estimator and over identification test. Univariate and Multivariate time series models: –

Linear Processes.



Integrated processes and unit root tests.



The concept and role of cointegration.

Models for heteroskedastic time series: –

ARCH and GARCH models.



Extensions of ARCH and GARCH models.

READING LIST D.N. GUJARATI-D.C. PORTER, Basic Econometrics, Mc.Graw-Hill, Fifth Edition, 2009. J.M. WOOLDRIDGE, Introductory Econometrics, a modern approach, South-Western, Cencage Learning, 2013. R.S. TSAY, Analysis of Financial Time Series, Wiley, 2010. S M. ZOIA, Topics in Time Series Econometrics, EDUCatt, 2014. Students will be provided with a detailed reading list of papers, class notes and supplementary teaching material which will be uploaded on the teachers’ web pages.

TEACHING METHOD Lecture will be complemented by tutorial exercises and the practical application of economic and financial data using appropriate econometric packages. ASSESSMENT METHOD Students are required to sit a written exam at the end of each semester’s module consisting of openanswer questions on topics covered in the course. Depending on the results attained, the written test may be supplemented by an oral exam to complete the student assessment. The final mark assigned on completion of the module is based on this evaluation procedure. Alternatively, students may choose to sit a final exam on the contents of the two modules at the end of the course. The exam format follows the format described above. The exam procedure is the same in each exam session and applies to attending and non-attending students. Additional information will be provided on the lecturers’ on-line site. NOTES R and Gretl empirical applications will be carried out to help students in deepening their understanding of the econometric theory and techniques developed in the course. All the necessary teaching material, including codes for elaborations and datasets, will be provided by the professors.