Unit name | Quantitative Methods for Economics, Finance and Management |
---|---|
Unit code | ECONM1012 |
Credit points | 15 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
Unit director | Dr. Crespo |
Open unit status | Not open |
Pre-requisites |
None |
Co-requisites |
None |
School/department | School of Economics |
Faculty | Faculty of Social Sciences and Law |
An introduction to quantitative methods for economics, finance and management including statistics and econometrics. The first part of the course concentrates on basic statistical techniques which are required for the study of econometrics in the second part of the course. Although a number of key theoretical concepts are introduced, the emphasis is on applying statistical and econometric techniques to applied problems in economics, finance and management.
Unit aims:
Students should be able to understand and use fundamental ideas in statistics; Probability distribution, moments of a distribution, estimation, and hypothesis testing. They should be able to use simple estimation and hypothesis testing procedures in econometrics and to understand econometric results techniques to analyse and test economic hypotheses. They should also be able to read and understand texts and journal articles which involve econometric work and appreciate the problems which researchers are faced with when dealing with real data. On completion of the course students should be in a position to apply econometric techniques to their dissertation topic.
Lectures, exercise lectures and tutorials.
The unit will be assessed by an individual assignment which will have a weight of 25 per cent of the final mark, and a two-hour written exam which will have 75 per cent weight. In the assignment the student has to answer questions related to a given real-world dataset. This course work is designed to examine:
In the examination, questions will be set to test understanding of key concepts and the methods of statistical and econometric inference (estimation, testing and confidence intervals). Similarly, econometric models will be provided so that students can demonstrate their ability to interpret empirical results.