GY460      Half Unit
Techniques of Spatial Economic Analysis

This information is for the 2017/18 session.

Teacher responsible

Prof Steve Gibbons S511


This course is available on the MSc in Environmental Economics and Climate Change, MSc in Local Economic Development, MSc in Real Estate Economics and Finance, MSc in Regional And Urban Planning Studies and MSc in Statistics (Social Statistics). 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


Students must have a good understanding of statistics and applied micro-econometrics at an undergraduate level or, for example, have studied Applied Quantitative Methods (GY428) in Michaelmas term or another course which introduces topics such as instrumental variables and panel data methods. It is advisable to look at the first two key readings listed below before signing up for this course. Students who are comfortable working with computers, data and already have basic familiarity with STATA or other statistics/econometrics software will get the most out of this course.

Course content

The aim of the course is to develop the technical tools necessary to understand and analyse spatial economic and social phenomena and to apply quantitative techniques to analyse economic and social problems, processes and policies at the urban and regional scale. The course also provides a hands-on introduction to using Geographical Information Systems and other spatial computer applications for research purposes, but you should not expect to get a full training in GIS from this course.


Topics typically include: Spatial representation, spatial data and Geographical Information Systems; spatial weights, aggregation and smoothing methods; spatial econometric models and neighbourhood effects; answering causal questions in the spatial context; spatial interaction and discrete choice models; spatial cluster and point pattern analysis; inequality, competition and diversity.


10 hours of lectures and 20 hours of seminars in the LT.

30 hours of teaching in LT comprising computer classes and lectures. The majority of sessions will take place in a computer classroom and these sessions combine lecture and practical material. Formative feedback will be available on submitted answers to seminar exercises and/or a past exam paper.

Formative coursework

Throughout the term, students are given the opportunity to provide answers to problem sets, written answers to class exercises and computer workshop tasks, and past examination questions, on which feedback will be given.

Indicative reading

A reading list and outline is available on Moodle. Important readings are

Gibbons, S., H.G Overman and E. Patacchini (2015) Spatial Methods, Ch. 3 in Duranton, G, J.V. Henderson and W. Strange (eds) Handbook of Urban and Regional Economics Vol 5a, Elsevier

Baum-Snow, N. and F. Ferreira (2015) Causal Inference in Urban Economics, Ch. 1 in Duranton, G, J.V. Henderson and W. Strange (eds) Handbook of Urban and Regional Economics Vol 5a, Elsevier

An overview of some topics is provided by: A Fotheringham, C Brunsdon; M Charlton, Quantitative Geography: Perspectives on Spatial Data Analysis. Sage Publications, 2000.


Project (100%, 5000 words) in the ST.

A quantitative research project of not more than 5000 words to be handed in at a specified date in the ST (100%).

Student performance results

(2013/14 - 2015/16 combined)

Classification % of students
Distinction 5.8
Merit 43.5
Pass 33.3
Fail 17.4

Key facts

Department: Geography & Environment

Total students 2016/17: 28

Average class size 2016/17: 29

Controlled access 2016/17: Yes

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Self-management
  • Team working
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills