Learning objectives

The course provides the main econometric tools to develop, based on the available data, an empirical analysis on the relationship between economic variables and to correctly interpret and use the results obtained. In fact, many economic decisions require quantitative answers to quantitative questions, and decisions based on empirical evidence are generally considered more helpful and effective.
The course uses a scientific language based on deductive reasoning. Technical aspects of econometrics, however, will be introduced only when necessary, whereas key attention will be given to the development of an intuitive comprehension of the material, in such a way to allow for an effective and creative use of the acquired knowledge.
At the end of the course the student is expected to (a) have critical skills with respect to empirical applications made by others and (b) be able to autonomously set up and run empirical analyses in the broad areas of economics and finance.

Prerequisites and basic notions

We require basic knowledge of calculus. The course material relies on prior knowledge of basic statistics and probability theory.

Program

1. INTRODUCTION (Stock-Watson, ch.2-3)
1.1. What is econometrics?
1.2. Probability
1.3. Statistics
2. REGRESSION ANALYSIS (Stock-Watson, ch.4-9)
2.1. Linear regressione with a single regressor and hypothesis testing
2.2. Linear regression with multiple regressions and hypothesis testing
2.3. Diagnostics of the regression model: specification, heteroskedasticity, autocorrelation
3. EXTENSIONS (Stock-Watson, ch.10-12)
3.1. Regression with instrumental variables
3.2. Regression with binary dependent variable
3.3 Regression with panel data
4. INTRODUCTION TO TIME SERIES REGRESSIONS (Stock-Watson, ch.15, sections 15.1-15.3)
4.1 Introduction to time series data
4.2 Stationarity
4.3 Autoregressions

Bibliography

Didactic methods

The course consists of 9 credits lectures (72 hours). During the semester students will be given problem sets to attempt at home to encourage systematic studying and self-feedback.

Learning assessment procedures

The exam consists of a written test and a homework assignment to be completed in groups. To pass the exam, students must achieve a score of at least 18/30 on the written test. The written test is administered in class and can be taken in one of the two following modes, at the student's choice: (a) a single exam, lasting two hours, which covers the entire course syllabus; (b) two partial exams (midterm exam and final supplementary exam), lasting one hour each. Calculators are permitted during the exam, but notes or other teaching materials are not permitted. The homework consists of an empirical analysis performed using the open-source econometrics software Gretl.

Evaluation criteria

To obtain full marks, students should show knowledge of the various econometric methodologies to understand and solve the diverse issues posed by regression models.

Criteria for the composition of the final grade

The final grade is given by the average of the grades in the essay and the homework, with 75% and 25% weights respectively.

Exam language

Italiano