Unit name | Applied Economics |
---|---|
Unit code | ECONM1008 |
Credit points | 15 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
Unit director | Dr. Bergemann |
Open unit status | Not open |
Pre-requisites |
None |
Co-requisites |
ECONM1010, ECONM101, ECONM1009 |
School/department | School of Economics |
Faculty | Faculty of Social Sciences and Law |
This unit will consist of lectures in applied econometrics and statistics with the applications drawing from both microeconomics and macroeconomics. The unit will emphasise the practical issues arising from the analysis of data. An important component of this will be the continuous application, throughout the unit, of statistical tools being taught in the co-requisite unit, QME. To help students in their preparation for doing a dissertation, they will also be introduced to the process of doing quantitative research, with a discussion of initial data analysis, the pre-suppositions needed to actually collect or create data, the meaning of statistical testing (especially when tests are inter-linked), strategies for exploring data and the appropriate means of presenting empirical research. Although not an important part of the course, the implicit assumptions of the modern scientific method will be discussed and alternative methodologies (eg Bayesian versus classical statistical methods) compared and contrasted. Material will be delived by lectures accompanied by practical exercises on data collection and analysis. Students will obtain practice in organising data using EXCEL and more sophisticated analysis using the statistical package STATA in computer classes. Topics considered will include the use of Indices, Demand Theory and the Consumption Function.
20 hours of lectures of which 4 are exercise lectures plus 5 hours of classes
The unit will be summatively assessed by the completion of an applied economics project (maximum 12 pages). The project will test the intended learning outcomes specified above. In particular (a) students will be asked to access, merge and transform data, (b) they will be expected to read specified papers and critique them and (c) they will then use their data to conduct their own empirical analysis that will link into the critique in (b). Formative assessment will be done based upon a mini project. There will be further exercises done during class work.