GY428 Half Unit
Applied Quantitative Methods
This information is for the 2018/19 session.
Dr Benjamin Groom (STC 420) and Dr Daniele Fanelli (COL 7.07)
This course is compulsory on the MSc in Environmental Economics and Climate Change. 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 Local Economic Development and MSc in Urban Policy (LSE 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.
A background in undergraduate statistics or econometrics is required
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 software STATA. Additionally, in the lectures and sometimes seminars, selected papers in quantitative environmental economics will be critically discussed. In general the course will attempt to use examples from relevant and topical empirical papers published in the area of applied econometrics and environmental economics. The module will cover several estimators. We will start with the standard linear regression model, its assumptions, violations and testing procedures. Some non-Linear models will also be presented, including Multivariate Probit and Logit Models (Maximum Likelihood). Extensions of the Linear regression model to incorporate panel data estimators and Instrumental Variables (IV) approaches (e.g. Two Stage Least Squares and Fixed and Random Effects models) will be also covered. The course will conclude with a discussion of programme evaluation methods and randomised control trials (RCTs).
20 hours of lectures and 9 hours of seminars in the MT. 1 hour of seminars in the LT. 2 hours of lectures in the ST.
A selection of seminar exercises will be marked for formative appraisal.
Detailed reading lists will be provided to support each course component. The following texts will be particularly useful: a) Stock J.H. and M.W. Watson (2011). Introduction to Econometrics. Third Edition Pearson International Edition; b) J. Wooldridge (2006), Introductory Econometrics: A modern approach, Thomson; c) Angrist J and Pischke J.S. (2009) Mostly Harmless Econometrics, Princeton.
Exam (100%, duration: 2 hours) in the summer exam period.
Student performance results
(2014/15 - 2016/17 combined)
|Classification||% of students|
Department: Geography & Environment
Total students 2017/18: 61
Average class size 2017/18: 21
Controlled access 2017/18: Yes
Lecture capture used 2017/18: Yes (MT)
Value: Half Unit
Personal development skills
- Problem solving
- Application of information skills
- Application of numeracy skills
- Specialist skills
Course survey results
(2014/15 - 2016/17 combined)1 = "best" score, 5 = "worst" score
The scores below are average responses.
Response rate: 80%
Reading list (Q2.1)
Course satisfied (Q2.4)