- Docente: Chiara Monfardini
- Credits: 6
- SSD: SECS-P/05
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Economics (cod. 8408)
Learning outcomes
At the end of the course the student has acquired knowledge of the basic instruments used by economists for their empirical investigations: the linear regression model and the Ordinary Least Squares method. In particular, he/she is able:
- to critically understand the applications of this model in the recent empirical economic literature;
- to apply the model and perform his/her own analysis of economic datasets using the software STATA.
Course contents
1. Introduction to the course. Conditional expectations and their features
2. Multiple linear regression analysis: Ordinary Least Squares (OLS) estimator
3. Finite Sample properties of OLS estimator
5. OLS asymptotics and large sample inference
6. Specification tests and model selection
Readings/Bibliography
MAIN TEXTBOOK
- Jeff M. Wooldridge: Introductory Econometrics. A Modern
Approach, 5th Edition, South-Western, 2013
OTHER REFERENCES
- Chris Baum, An Introduction to Modern Econometrics Using Stata, Stata Press
- Fumio Hayashi: Econometrics, Princeton University Press,
2000
- Bruce Hansen, Econometrics, available on line, 2015
Teaching methods
Throughout the course, the presentation of theoretical issues will be complemented by critical discussion of some micro-economic applications from recent research using linear regression models. Students will receive data to practice at the computer and learn the basic skills to perform empirical work using the software STATA.
Assessment methods
There are two components of the course assessment: take home
assignments and written exam.
During the course Computer Exercises will be assigned to small
groups of students and will be due on specific dates. The
average mark of the Computer Exercises will account for 30% of the
final mark.
The written exam is closed book. It is divided in three parts:
- True or False (answer with concise motivation): 3 questions, 12 points
- Open question (formal answer to theoretical question): 1 or 2 questions, 8 points
- Interpretation question (answer on STATA log file with estimation output): 2 or 3 questions, 10 points
Examples of exam text are available on the course webpage
(see "Links to further information" below)
Teaching tools
Course website, with news and updated materials, including lectures' slides (see "Links to further information" below)
Software STATA. available at the Computer Lab of the School of Economics, Management and Statistics.
STATA Introductory course, offered before the beginning of the
course by the teaching tutor in charge.
Links to further information
http://sites.google.com/site/chiaramonfardiniwebpage/home/teaching
Office hours
See the website of Chiara Monfardini