GY428      Half Unit
Applied Quantitative Methods

This information is for the 2021/22 session.

Teacher responsible

Dr Stephen Jarvis

Dr Juan Ruiz-Tagle


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) (LSE 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 (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 statistical 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).


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 Michaelmas Term. This course includes a reading week in Week 6 of Michaelmas Term.

Formative coursework

There will be an opportunity to get feedback on weekly exercises.

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):

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

Part II: (Weeks 8-11 with Cristobal Ruiz-Tagle):

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 (80%, duration: 2 hours) in the summer exam period.
Coursework (20%) in the MT.

The coursework assessement will take the form of problem sets or exercises that recap on some of the most important topics.

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.

Student performance results

(2017/18 - 2019/20 combined)

Classification % of students
Distinction 57.4
Merit 24.2
Pass 13.2
Fail 5.3

Important information in response to COVID-19

Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: Geography & Environment

Total students 2020/21: 56

Average class size 2020/21: 14

Controlled access 2020/21: Yes

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