Module
Applied Econometrics
Module description
Summary:
The ability to perform and critically discuss applied empirical work is central to an economists’ job in today’s workplace. The volume of economic and financial data is ever increasing, and so are the opportunities to use this data to undertake empirical economic research. Quantitative methods and the software used to apply them have become more and more sophisticated. This module aims to provide training in both the empirical methods and in the application of those methods using a modern statistics software package.
Additional Information:
Internationalisation
The module contains many examples of research carried out internationally. Students are encouraged to think about applied topics relevant to the UK as well as Europe and overseas. The datasets used for this module come from various sources, many of them international organisations.
Employability
The main aim of this module is to equip students with practical empirical skills and critical thinking which are highly sought after in the workplace.
Research in Teaching
As part of the module students will study and replicate example of empirical research.
Full module specification
| Module title: | Applied Econometrics |
|---|---|
| Module code: | BEE2032 |
| Module level: | 2 |
| Academic year: | 2021/2 |
| Module lecturers: |
|
| Module credit: | 15 |
| ECTS value: | 7.5 |
| Pre-requisites: | BEE2031 |
| Co-requisites: | BEE2031 or BEE2006 |
| Duration of module: |
Duration (weeks) - term 2: 11 |
Module aims
The aim of this module is to equip students with good practical skills in the application of quantitative research techniques to research questions from different areas of economics. The module will focus on data skills (organisation and manipulation of data, descriptive and explorative analysis) and applied econometrics (especially models for cross-sectional and panel data which have not been extensively covered in previous modules). Students will learn to apply those techniques using the professional statistics software package Stata.
ILO: Module-specific skills
- 1. demonstrate ability to understand the important features and properties of economic data, and perform the necessary operations to organise and manipulate the data
- 2. apply appropriate quantitative techniques based on the research question and features of the data
- 3. perform independent empirical analysis using the software STATA
ILO: Discipline-specific skills
- 4. combine knowledge of economic theory with the necessary quantitative and data skills to complete an empirical research task
ILO: Personal and key skills
- 5. demonstrate analytical and critical thinking
- 6. demonstrate the ability to use state-of-the-art statistical software
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 32 | 118 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Schedule learning and teaching | 22 hours | Lectures |
| Scheduled leaning and teaching | 10 hours | Tutorials |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| In class discussion/exercises | Weeks 1 to 11 | 1-6 | Verbal/ELE |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 20 | 0 | 80 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Practical Exam | 80 | 3 hours | 1-6 | Discussion |
| Homework tasks | 20 | Approx. 6 pages A4 | 1-6 | ELE/Turnitin |
| 0 | ||||
| 0 | ||||
| 0 | ||||
| 0 |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Practical Exam & homework tasks | Practical Exam (100%) 3 hours | 1-6 | August Examination Period |
Re-assessment notes
Re-assessment to take place if the average of both assessment components is below 40.
Syllabus plan
- Introduction to Stata
- First steps in empirical analysis: descriptive statistics and explorative analysis
- Organising your work: do-files, logs and programs
- Applied linear regression, diagnostics and tests
- Nonlinear regression models
- Missing data
- Panel data: methods and applications
- Monte-Carlo methods
- Programming in Stata
Indicative learning resources - Basic reading
The module does not rely on a textbook. All relevant material will be presented in class and in the lecture notes. Additional reading may be given for certain topics.
The theoretical content is covered in Wooldridge, Jeffrey (2015) Introductory Econometrics, 6th edition, cengage.
The following textbooks make use of Stata in examples and applications:
Adkins, L.C. and Hill, R.C. (2011) Using Stata for Principles of Econometrics, 4th edition, John Wiley & Sons.
Hill, R.C, Griffiths, W.E and Lim, G.C (2011) Principles of Econometrics, 4th edition, John Wiley & Sons. Cameron, A.C and Trivedi, P.K. (2010) Microeconometrics using Stata, revised edition, Stata Press.
Module has an active ELE page?
Yes
Indicative learning resources - Web based and electronic resources
UK Data Service (http://ukdataservice.ac.uk/ )
Indicative learning resources - Other resources
A Gentle Introduction to Stata by Alan C. Acock
Data Analysis Using Stata by Ulrich Kohler and Frauke Kreuter
Interpreting and Visualizing Regression Models Using Stata by Michael N. Mitchell
An Introduction to Stata Programming by Christopher F. Baum
Origin date
01/09/2014
Last revision date
20/02/2019