EH348-7-SL-CO:
Spatial Econometrics
2022/23
Essex Summer School in Social Science Data Analysis
Colchester Campus
Summer & Long Vacation
Postgraduate: Level 7
Current
Monday 24 April 2023
Wednesday 04 October 2023
15
03 February 2023
Requisites for this module
(none)
(none)
(none)
(none)
(none)
Spatial dependencies are a universal feature in the social sciences. Phenomena as diverse as the occurrence and outcomes of violent mass protests, policy learning and position taking in party competition, or the competitive setting of tax rates to attract foreign direct investment across neighbouring jurisdictions, all share a similar feature: actions taken by one actor are shaped in a theoretically meaningful way by the actions of one or more other actors. Spatial econometrics allows us to detect, model and estimate such interdependencies, and to work towards a causal interpretation of such relationships. The theoretical substance lies in the nature of interconnectedness between units, which can be geographic, economic, cultural, strategic etc., thus covering a wide ground of social science applications. This course begins with a data-oriented view of spatial patterns and dependencies in the data, then introduces a theory guided approach to building, estimating, and evaluating spatial and spatiotemporal regression models, and ends with a critical evaluation of the spatial approaches in the context of causal analysis.
No information available.
The course starts from the premise that interconnectedness is an important and theoretically meaningful feature of a broad range of phenomena in the social sciences. The main aim is therefore to enable students to identify and incorporate interconnected features in the study of their own data and areas of interest. This will involve learning how to detect spatial patterns, bringing data into a suitable format for spatial analysis, the estimation of structural parameters of spatial and spatiotemporal models and the presentation of effects. The materials provided in the labs will enable the students to undertake their own applied spatial project.
Course Prerequisites
All necessary background materials will be covered (in brief), though students will benefit most from the course if they have some understanding of regression analysis and a basic knowledge of matrix algebra and maximum likelihood, as well as some familiarity with R.
Representative Background Reading
Textbooks
Ward, Michael D and Kristian S Gleditsch. 2018. Spatial Regression Models: Second Edition. Quantitative Applications in the Social Sciences 155. Sage. – This book will be provided by ESS.
Le Sage, James and R. Kelley Pace. 2009. Introduction to Spatial Econometrics. CRC Press.
Module information will be made available at https://essexsummerschool.com/.
Please contact essexsummerschoolssda@essex.ac.uk and govpgquery@essex.ac.uk with any queries.
No information available.
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
No
No
No
Available via Moodle
No lecture recording information available for this module.
Disclaimer: The University makes every effort to ensure that this information on its Module Directory is accurate and up-to-date. Exceptionally it can
be necessary to make changes, for example to programmes, modules, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements,
industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to modules may for example consist
of variations to the content and method of delivery or assessment of modules and other services, to discontinue modules and other services and to merge or combine modules.
The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications and module directory.
The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.