Guide to units in Econometrics
In Econometrics the key gateway unit is ECMT2110 Regression Modelling. Not only is this necessary as a prerequisite to many other units, it is also extremely useful in its own right. Regression is the fundamental building block for a multitude of models that are useful in finance (e.g. the capital asset pricing and other market models), economics, marketing and accounting (to name but a few). You will learn how to uncover relationships between variables and build econometric models. The course is practical and involves using statistical software to analyse real data sets. Any student in the Faculty considering an Honours year will likely find this unit quite useful for their thesis topic.
If you are interested in working in the financial services area or have an interest in financial markets or risk management in general, then you will want to carefully consider taking ECMT2130 Financial Econometrics and ECMT3150 The Econometrics of Financial Markets.
ECMT3130 Forecasting for Economics and Business is a unit which is extremely useful; this is certainly a unit to consider for those with a finance interest, but might also be of interest even if you do not take any other second year courses with us (you will need either ECMT1020 or ECMT 2110 as a prerequisite). Forecasting is simply a fundamental and pivotal task in all business decision making, at every level, and this course considers practical issues in forecasting as well as qualitative and quantitative forecasting methods.
If you have an interest in marketing or work and organisational studies then you might want to consider ECMT2120 Analysis of Discrete Choice Data which introduces tools that are highly useful in those disciplines, among others.
Econometrics Major
Econometrics applies mathematical and statistical techniques to the analysis of business and economic data. There has always been a strong demand for graduates with quantitative skills. The impact of information technology has meant that there are huge data sets now available - such as data sets of financial market activity or of consumer markets via supermarket scanning. This adds considerably to the high level prospects for graduates with the quantitative skills to deal with the potential of the data - such as in the analysis of energy demand, greenhouse gas emissions, international trade flows or consumer behaviour.