GY428      Half Unit
Applied Quantitative Methods

This information is for the 2019/20 session.

Teacher responsible

Prof 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, 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 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.

Formative coursework

Following the seminars, exercises will be submitted for formative appraisal, and feedback will be provided.

Indicative reading

Detailed reading lists will be provided to support each course component, but the following texts will be particularly useful:

Part I: (Weeks 1-7 with Daniele Fanelli):

A Agresti & B Finlay, Statistical Methods for the Social Sciences.

Part II: (Weeks 8-11 with Ben Groom):

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

(2015/16 - 2017/18 combined)

Classification % of students
Distinction 35.8
Merit 30.2
Pass 22.8
Fail 11.1

Key facts

Department: Geography & Environment

Total students 2018/19: 66

Average class size 2018/19: 21

Controlled access 2018/19: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills