- UCAS course code
- L102
- UCAS institution code
- M20
Bachelor of Science (BSc)
BSc Economics
- Typical A-level offer: AAA including Mathematics
- Typical contextual A-level offer: ABB including A in Mathematics
- Refugee/care-experienced offer: ABC including A in Mathematics
- Typical International Baccalaureate offer: 36 points overall with 6,6,6 at HL including Mathematics
Course unit details:
Applied Economics
Unit code | ECON10162 |
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Credit rating | 10 |
Unit level | Level 1 |
Teaching period(s) | Semester 2 |
Available as a free choice unit? | No |
Overview
The course will provide an introduction how economists use data and statistics to deal with common economic problems. The aim is to allow students to perform economic analysis using real-world data and standard statistical packages. This will help prepare students for more advanced courses in econometrics and applied economics.
Pre/co-requisites
Available to BSc Economics students only.
Aims
The aim of this module is to introduce students to the tools and techniques used in economics as a practical discipline. The course will provide an introduction to the ways in which economists use data and statistics to tackle economic problems, testing and interpreting economic theories. The aim is to allow students to perform economic analysis using real world data and standard statistical packages. This will help prepare students for more advanced courses in econometrics and applied economics.
Learning outcomes
Students will learn how to:
1. Develop empirically testable hypotheses from economic theory.
2. Manipulate data in order to test interesting economic hypotheses.
3. Apply basic econometric methods to data.
4. Interpret empirical results derived from applying econometric methods to data.
5. Understand some of the limitations and potential pitfalls of empirical work in
economics
Students will have experience of using standard statistical computer packages as a research tool. They will have experience of report writing using appropriate information technology.
Syllabus
The course will cover the structure of data, exploratory data analysis, data visualization techniques, basic statistical methods, hypothesis testing and linear regression, among other data and statistical techniques. Strong emphasis will be placed on the practical element of applied work in problem solving, and the interpretation that can be given to empirical results. We will look at issues around various economic topics, such as: microeconomics, macroeconomics, labour market, inequalities, environmental issues, finance, etc.
Teaching and learning methods
Synchronous activities (such as Lectures, Office hours, and tutorials), and guided self-study.
Employability skills
- Group/team working
- Oral communication
- Problem solving
- Research
- Other
- Enhances transferable skills including self-management and presentational skills.
Assessment methods
40% Weekly Quizzes
60% Written Project - 1500 words max
Feedback methods
- Online quizzes.
- Tutorials classes.
- Office hours
- Revision sessions.
- Discussion boards.
Recommended reading
The course will primarily draw on "The Art of Statistics: Learning from Data" by David Spiegelhalter.
May also refer to other textbooks, such as:
- Wooldridge, J.M. (2013) Introductory Econometrics: A Modern Approach (University of Manchester custom edition).
Additional readings will be provided for various topics during the course.
Study hours
Scheduled activity hours | |
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Lectures | 25 |
Tutorials | 10 |
Independent study hours | |
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Independent study | 65 |
Teaching staff
Staff member | Role |
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Matheus Vianna | Unit coordinator |
Additional notes
For every 10 course unit credits we expect students to work for around 100 hours. This time generally includes any contact times, but also independent study, work for coursework, and group work. This amount is only a guidance and individual study time will vary.