ECO4016F
- Econometrics
Course Information
This course provides a solid grounding in the fundamental techniques of
econometrics, developing tools with which to estimate models, test hypotheses
and generate forecasts of economic activity. It is a basic but thorough
introduction to econometrics that assumes little prior knowledge of the subject
(although some mathematical and statistical aptitude is required). The main
focus is on the Classical Linear Regression Model (CLRM) and the problems
encountered when its assumptions are violated (i.e. multicollinearity,
heteroscedasticity and autocorrelation). Additional topics include dummy
variables, dynamic models and cointegration analysis. The course has a strong
practical component in which students learn to apply specialist econometrics
software to practical problems.
Welcome
Welcome to Econometrics! This sub-discipline represents the interface between
economic theory and the real world. It provides the tools with which to test
hypotheses and to generate forecasts of economic activity. The skills you will
develop in this course are vital in any applied economic work, and will
constitute an essential ingredient in most jobs in the field of economics,
whether in the public, private or academic sector. More immediately,
econometrics may prove very useful for your Honours Long Paper.
Lecturers
The course will be co-taught by:
Background and Scope
This course is intended to offer a solid grounding in the fundamental
techniques of econometrics. It assumes that students have taken first-year
mathematics and statistics courses and builds on the introductory econometrics
section of ECO3021S (Quantitative Methods in Economics) . Those of you who are
new to econometrics will need to work particularly hard at the start to catch
up. The course is highly applied, with all the theory learnt in lectures being
put into practice in the computer lab using EViews econometrics software.
In the first three weeks the work that was covered in ECO3021S will be revised
and expanded on by introducing the matrix form and just the basic idea of
maximum likelihood - so that you at least get a sense of what the literature is
talking about. Importantly, you will be expected to learn the EViews software
package. The emphasis will be on the application of the body of theory that you
have already learnt. The following three weeks will focus on dummy dependent
variables.
In the second half of the course you will focus on the introduction to time
series analysis. These techniques aim to overcome some serious problems with the
traditional approach to econometrics, i.e. that the relationships may look
statistically satisfactory, but are in fact spurious. So in this section of the
course, you will demonstrate the limitations of OLS techniques in time series
contexts; develop an ability to identify the time series characteristics of the
data and deal with nonstationarity in estimation. In short, this section aims to
develop your appreciation of the unique difficulties imposed by time series
contexts and give you techniques to apply in practical econometric
investigations.
Objectives
This course is intended to develop:
- a useful body of knowledge in econometric methods
- the ability to critically evaluate the results and conclusions of others
who use econometric tools
- the ability to apply econometric techniques in empirical academic work
- several important generic skills for economists, such as analytical &
problem-solving skills and the ability to work co-operatively and
autonomously
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