Year of entry: 2022
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Course unit details:
|Unit level||Level 1|
|Teaching period(s)||Semester 2|
|Available as a free choice unit?||No|
The course will provide an introduction how economists use statistics and econometrics to test and interpret 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.
Available to BSc Economics students only.
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 statistics and econometrics to test and interpret economic theories. It will also introduce how to design controlled lab experiment and analyse and interpret the data from the lab. 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.
Students will learn how to:
- Develop empirically testable hypotheses from economic theory.
- Manipulate data in order to test interesting economic hypotheses.
- Apply basic econometric methods to data.
- Interpret empirical results derived from applying econometric methods to data.
- Understand some of the limitations and potential pitfalls of empirical work in economics
- Design controlled behavioural lab experiment to test ex-ante policy evaluation, test theories and understand some pattern of behaviour which is difficult to explain using standard economic theory.
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.
The course will cover the structure of data, basic statistical methods, Ordinary Least Squares, hypothesis testing and other relevant statistical methods.
A strong emphasis will be placed on the theoretical foundations of applied work and the interpretation that can be given to estimated coefficients.
We will look at issues around various economic topics, such as:
- Empirical models and Ordinary Least Square Regression
- Empirical Models of Discrimination
- Geography and Development
- Behavioural and Experimental Methods
- Social Preferences
- Environmental and Resource Economics
- Social Inequality (e.g. gender)
Teaching and learning methods
Synchronous activities (such as Lectures or Review and Q&A sessions, and tutorials), and guided self-study.
- Group/team working
- Oral communication
- Problem solving
- Enhances transferable skills including self-management and presentational skills.
10% Mid-term Exam
40% Project: Written project
50% Exam: Final Exam
- Online quizzes.
- Tutorials classes.
- Office hours
- Revision sessions.
- Discussion boards.
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.
|Scheduled activity hours|
|Assessment written exam||3|
|Independent study hours|
|Matheus Vianna||Unit coordinator|
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.