20203 - ECONOMETRICS
Course taught in English
For a fruitful and effective learning experience, it is strongly recommended a preliminary knowledge in basic calculus, probability theory and linear algebra and a good knowledge of statistics.
The course offers an introduction to a variety of econometric methods and models, focusing on the basic theory and some more advanced results. In the second part, there is a focus on econometric methods for macroeconomic and financial variables. The course is completed by a set of applications based on simulated and actual data, implemented using STATA and Eviews.
- Finite simple properties of the OSL estimator in the classical regression model.
- Asymptotic properties of estimators and tests in the presence of possible endogeneity.
- Error heteroskedasticity and serial correlation.
- Panel data models.
- Univariate and multivariate time series models.
- Forecast evaluation, comparison and combination.
- Define the key elements of an econometric analysis.
- Recognize the proper data and estimation method to be used.
- Explain the outcome of the estimation and testing.
- Select the most appropriate econometric model.
- Interpret the results of advanced empirical analyses using cross-sectional, time series and panel data.
- Compare the outcome of alternative estimation and testing procedures.
- Evaluate the validity of the assumptions underlying specific econometric methods.
- Predict the future evolution of economic variables.
- Face-to-face lectures
- Exercises (exercises, database, software etc.)
- Solution of theoretical questions related to the various topics in the syllabus.
- Empirical applications based on simulated and actual economic data.
|Continuous assessment||Partial exams||General exam|
Written exam(s) with open ended questions aimed at assessing whether the students are capable of:
- Defining the key elements of an econometric analysis.
- Recognizing the proper data and estimation method to be used.
- Interpreting the results of empirical analyses using both cross sectional and time series data.
- Comparing the outcome of alternative estimation and testing procedures.
- Evaluating the validity of the assumptions underlying specific econometric methods.
- Using the models for predicting the future evolution of economic variables.
- E. GHYSELS, M. MARCELLINO, Applied Economic Forecasting, Oxford University Press, 2018.
- J.M. WOOLDRIGE, Introductory Econometrics: A Modern Approach, South-Western College Pub, 2013, 5th edition.
- Additional required texts are communicated at the beginning of the course and additional material is posted on Bboard.