Applied Economics for Business
Module description
The ability to perform and critically discuss applied empirical work is central to a business 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 and business research. The quantitative methods, and the software used to apply them, becoming more and more sophisticated, and 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:
Employability: In today’s electronic world, all businesses are collecting data and need employees who can critically analyse the vast amount of data to smartly drive business decisions. This module attempts to bridge the gap between economic theories learnt in other modules and the data-driven world beyond the classroom.
Full module specification
| Module title: | Applied Economics for Business |
|---|---|
| Module code: | BEE3062 |
| Module level: | 3 |
| Academic year: | 2018/9 |
| Module lecturers: |
|
| Module credit: | 15 |
| ECTS value: | 7.5 |
| Pre-requisites: | Either BEE1022 or BEE1025; and BEE2024 Please note this module cannot be taken by students who have previously studied BEE2025 and BEE2026. |
| Co-requisites: | None. |
| Duration of module: |
Duration (weeks) - term 1: 11 |
Module aims
The aim of this module is to equip you with good practical skills in applied business economics, especially in the application of quantitative research techniques to research questions from different areas of business economics. The module will
focus on data skills (organisation and manipulation of data, descriptive and explorative analysis), survey data and applied econometrics (regression models). You will learn to apply those techniques using one of the main statistics software package.
ILO: Module-specific skills
- 1. demonstrate ability to understand the important features and properties of real-world 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 a statistical software
ILO: Discipline-specific skills
- 4. combine knowledge of economic theory with the necessary quantitative and data skills to undertake applied empirical work in business economics
ILO: Personal and key skills
- 5. demonstrate analytical and critical thinking
- 6. demonstrate the ability to use statistical software
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 27 | 123 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled Learning and Teaching | 22 hours | Lectures |
| Scheduled Learning and Teaching | 5 hours | Tutorials |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| In class discussion/exercises | One term | 1-6 | Verbal |
| Preparatory exercises for practical exam | One term | 1-6 | Verbal |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 30 | 0 | 70 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Practical Exam | 70 | Three hours | 1-6 | Written |
| Homework | 30 | 1 problem set with 10-15 questions | 1-6 | Written |
| 0 | ||||
| 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 and homework | Take-home assignment (100%) | 1-6 | August Examination Period |
Syllabus plan
- Module aims and limitations
- Introduction to Statistical Software (STATA)
- First steps in empirical analysis: descriptive statistics and explorative analysis
- Organising your work
- Hypothesis Testing
- Applied linear regression, diagnostics and tests
- Prediction, Goodness-of-fit and Modelling issues
- Non-linear regression models
- Binary choice models
- Working with Surveys
Indicative learning resources - Basic reading
Basic reading:
Hill, R.C, Griffiths, W.E and Lim, G.C (2011) Principles of Econometrics, 4th edition, John Wiley & Sons.
Adkins, L.C. and Hill, R.C. (2011) Using Stata for Principles of Econometrics, 4th edition, John Wiley & Sons.
Module has an active ELE page?
Yes
Indicative learning resources - Web based and electronic resources
ELE.
Indicative learning resources - Other resources
A Gentle Introduction to Stata by Alan C. Acock
Data Analysis Using Stata by Ulrich Kohler and Frauke Kreuter
Cortinhas, C. and Black, K. (2012), Statistics for Business and Management, 1st European Edition, Wiley
Data:
UK Data Service (http://ukdataservice.ac.uk/ )
Origin date
10/07/2015
Last revision date
12/09/2018