ECONOMETRICS
- Overview
- Assessment methods
- Learning objectives
- Contents
- Full programme
- Bibliography
- Delivery method
- Teaching methods
- Contacts/Info
No previous knowledge is required.
The test is a 1.5-hour written examination based on 8-10 exercises of varying difficulty and score. Some (4/5) questions are closed-ended, the others are open-ended. Wrong answers do not lead to a loss of score. The exam prizes the ability to reason critically and to justify the proposed solution.
The advent of computers and of the Internet has led to the availability of a huge amount of data, in a form and quantity that was not even thinkable until some years ago. This phenomenon, sometimes called 'big data' or 'data deluge', is going to bring about the prophecy of H. G. Wells, that the ability “to think in averages and maxima and minima” will be in the future as necessary “as it is now to be able to read and write.” This is a fortiori true in economics. As such, the course aims at introducing the student to the statistical study of the relations among economic phenomena.
At the end of the course, it is expected that the student is able to
- interpret the results of a linear regression model,
- conduct tests and
- make forecasts.
Examples of data.
Probability, statistics and programming in R.
History of regression.
The method of least squares as a geometric tool.
The simple regression model.
The multiple regression model.
The method of least squares as a statistical tool.
Properties of estimators.
Forecasting.
Confidence intervals.
Statistical tests.
Examples of data.
Probability, statistics and programming in R.
History of regression.
The method of least squares as a geometric tool.
The simple regression model.
The multiple regression model.
The method of least squares as a statistical tool.
Properties of estimators.
Forecasting.
Confidence intervals.
Statistical tests.
Slides written by the instructor.
The course is composed of lectures taught with the support of a set of slides (in English) and programming exercises with the statistical software R. During the class, students are invited to interact with the instructor.
Office hours by appointment arranged by email.