Teaching code

4S02464

Teacher

Alessandro Bucciol

Coordinator

Alessandro Bucciol

Credits

9

Language

English

Scientific Disciplinary Sector (SSD)

SECS-P/05 - ECONOMETRICS

Period

secondo semestre (lauree magistrali) dal Feb 21, 2022 al May 13, 2022.

Lessons timetable Moodle Seminars 0

Learning outcomes

The course provides an overview of the main econometric tools, with particular emphasis on economic applications, developed interactively using professional packages. The program covers standard econometric models (OLS regression and its diagnostics) as well as more advanced models for the analysis of cross-sectional, time series and panel data (IV, probit, tobit, random and fixed effects). Particular attention will be given to the intuition behind each topic, in addition to more formal issues. Towards the end of the course a voluntary assignment will be proposed, with the aim of translating research questions into empirical analyses, applying on real data the tools learnt in class, and stimulating discussion among students. At the end of the course, students should be able to: i) read and critically interpret empirical works developed by other researchers, ii) manage small and large datasets in order to extract useful information, and iii) design and implement on their own empirical analyses based on real data.

Program

1) Introduction
1.1) What is Econometrics?
Definition; cross-section, time series and panel data.
1.2) R tutorial
Data management; basic statistics; graphics.

2) Ordinary Least Squares (OLS) Estimator
2.1) Introduction
Univariate and multivariate regression; marginal effects and elasticity; R-squared and adjusted R-squared; outliers.
2.2) Properties
Gauss-Markov assumptions; unbiasedness; efficiency; consistency; asymptotic normality.
2.3) Testing
t-test on one restriction; F test on several restrictions.

3) OLS Diagnostics
3.1) Specification
Collinearity; superfluous and omitted variables; RESET test of specification; Chow test of structural stability.
3.2) Heteroskedasticity
White test and Breusch-Pagan test; White robust standard errors.

4) Instrumental Variable (IV) Estimator
4.1) Estimator
Assumptions; Simple instrumental variable (SIV) and generalized instrumental variable (GIV); properties; two-stage derivation (2SLS).
4.2) Instrument selection
Relevance test; weak instruments; Sargan validity test; Hausman exogeneity test.

5) Limited Dependent Variable (LDV)
5.1) Binary dependent variable
Linear probability model (LPM); probit and logit models; marginal effects; maximum likelihood estimate; goodness of fit; hypothesis testing.
5.2) Truncated and censored data
Truncated regression; tobit-I model; tobit-II and heckman models; marginal effects; goodness of fit.

6) Further types of data
6.1) Time series
Stationarity; AR processes; Durbin-Watson and Breusch-Godfrey tests; Newey-West robust standard errors.
6.1) Panel data
Diff-in-diff; Pooled effects, fixed effects and random effects; goodness of fit; comparison tests; attrition.

Lecture method: frontal teaching

Bibliography

Examination Methods

The exam is written; no oral integration is planned.
The exam is made of one written essay and one individual homework. The final grade is given by the average of the grades in the essay and the homework, with 80% and 20% weights respectively. In order to pass the exam, it is necessary to obtain a grade not below 16/30 in the written essay. Students can separately reject the essay grade and the homework grade. However, the homework grade can be rejected only once.
The written essay lasts one hour and thirty minutes and covers the whole program of the course. Use of handheld calculators is allowed, but use of personal notes or other teaching material is not allowed.
The homework is developed individually, and can be of two types (Homework I or Homework II). Homework I aims to develop analytical skills through personal data analysis. Homework II aims to develop critical skills with respect to empirical applications. Each student can choose which type of homework to deliver, but must deliver one of them. Once the deadline for delivery of Homework I has expired, it is possible to deliver Homework II only. The homework has to be delivered before taking part in the written essay; its grade remains valid throughout the academic year.