GY428 Half Unit
Applied Quantitative Methods
This information is for the 2024/25 session.
Teacher responsible
Dr Stephen Jarvis
Prof. Hendrik Wolff
Availability
This course is compulsory on the MSc in Environmental Economics and Climate Change and MSc in Environmental Policy, Technology and Health (Environmental Economics and Climate Change) (ÐÓ°ÉÂÛ̳ and Peking University). This course is available on the MPhil/PhD in Economic Geography, MPhil/PhD in Environmental Economics, MPhil/PhD in Regional and Urban Planning Studies, MSc in Geographic Data Science, MSc in Local Economic Development and MSc in Urban Policy (ÐÓ°ÉÂÛ̳ and Sciences Po). This course is available with permission as an outside option to students on other programmes where regulations permit.
The number of students that can be accommodated is limited. If the course is over-subscribed, places will be allocated at the Department’s discretion and a waiting list may be created. For further details, please contact your relevant Programme Coordinator.
Pre-requisites
A background in undergraduate statistics or, preferably, econometrics is required
Course content
This course will provide an introduction to quantitative methods in use in modern environmental and resource economics. Emphasis will be placed on the practical use of empirical tools. This applied focus will be complemented by the investigation of assumptions and proofs that can improve the understanding of empirical results. Students will apply the methods taught using statistical/econometric software and data documenting some topical public policy questions. These applications will take place in ten seminars of one hour each. During the seminars the students will gain understanding of the statistical programming language R. Throughout the course, examples from relevant and topical empirical papers published in the area of applied econometrics and environmental economics will be critically discussed. The module will focus on linear regression methods, with an emphasis on their use for causal inference. The first part of the course will cover the standard linear regression model, its assumptions, violations and testing procedures. Functional forms and non-linear models will also be discussed. The latter part of the course will cover a range of important estimation approaches, including fixed effects with panel data, difference-in-differences, instrumental variables and regression discontinuity designs. The course will conclude with a more general discussion of how these tools can be used in research and policy analysis.
Teaching
In the Department of Geography and Environment, teaching will be delivered through a combination of classes/seminars, pre-recorded lectures, live online lectures and other supplementary interactive live activities.
This course is delivered through a combination of classes and lectures across Autumn Term. This course includes a reading week in Week 6 of Autumn Term.
Formative coursework
There will be an opportunity to get feedback on one or more of the problem sets assigned during the AT.
Indicative reading
Detailed reading lists will be provided to support each course component, but the following texts will be particularly useful:
- Stock J.H. and M.W. Watson (2019). Introduction to Econometrics. Fourth Edition Pearson International Edition;
- J. Wooldridge (2006), Introductory Econometrics: A Modern Approach, Thomson;
- Angrist J and Pischke J.S. (2014) Mastering ‘Metrics, Princeton.
- Angrist J and Pischke J.S. (2009) Mostly Harmless Econometrics, Princeton.
- Cunningham S. (2021) Causal Inference The Mixtape, Yale.
Assessment
Exam (70%, duration: 2 hours) in the January exam period.
Coursework (30%) in the AT.
The coursework assessement will take the form of problem sets or exercises that recap on some of the most important topics.
Student performance results
(2020/21 - 2022/23 combined)
Classification | % of students |
---|---|
Distinction | 71.3 |
Merit | 16.4 |
Pass | 9.4 |
Fail | 2.9 |
Key facts
Department: Geography and Environment
Total students 2023/24: 69
Average class size 2023/24: 36
Controlled access 2023/24: Yes
Value: Half Unit
Course selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Specialist skills