John M. Noble
Mathematical Statistics
Institute of Applied Mathematics
University of Warsaw
February - June 2020
Econometrics: Course Information
Language: English
Type of course: elective
Class Schedule There are 13 lectures and 13 tutorials. The lectures take place Tuesdays 12.15 - 13.45 in Room 5820 and the tutorials Tuesdays 14.00 - 15.30 in 2044. The dates for the classes are:
25th February,
3rd, 10th, 17th, 24th, 31st March,
7th, 21st, 28th April,
5th, 12th, 19th, 26th May.
Description
Econometrics is the application of mathematics, statistical methods, and computer science, to economic data and is described as the branch of economics that aims to give empirical content to economic relations. More precisely, it is the quantitative analysis of economic phenomena based on observation and theory, using appropriate methods of inference. The first known use of the term `econometrics' was by the Polish economist Paweł Ciompa in 1910. Ragnar Frisch is credited with the term in the sense in which it is used today.
The basic tool for econometrics is the linear regression model. In modern econometrics, other statistical tools are frequently used, but linear regression is still the most frequently used starting point for an analysis.
This course considers econometrics using the R programming language. The topics covered are:
Main Regression
- Principles of Estimation (Ordinary Least Squares, Generalized Least Squares and Maximum Likelihood Estimation with Micro-Econometric applications)
- Principles of Testing (t- and F-test; Wald, Likelihood Ratio, Lagrange Multiplier Testing Principles).
- Time Series: Basic Time Series Processes; Stationarity and Nonstationarity - Unit roots and Cointegration.
Estimation Methodology
- Endogeneity in linear regression models; Instruments; 2SLS estimator and Generalized IV estimator; Simultaneous equations.
- Motivation, definition and asymptotic properties of GMM estimator; Efficient GMM estimation; Over-identifying restrictions.
- Introduction to Panel Data Models: Fixed effect and random effect models.
- Introduction to Quantile estimation.
Assessment
Assessment is based on
- tutorial participation
- assignments distributed during the semester:
- distributed 3rd March, submission date 17th March 12 noon, worth 30%
- distributed on 28th April, submission date 12th May 12 noon, worth 30%.
- distributed 2nd June, submission date 24th June 12 noon, worth 40%
These assignments should be submitted in p.d.f. format, presenting the conclusions, along with tables and the results that justify these conclusions. Some R code may be included, but please limit this and put it in an appendix. The interpretation of the output and clear presentation is the important point.
Lecture Notes and Tutorial Exercises
Click
here for the data directory.
(Last updated: 28th May 2020 by John M. Noble)