EH145-7-SU-CO:
Causal Inference and Experiments in the Social Sciences
2022/23
Essex Summer School in Social Science Data Analysis
Colchester Campus
Summer
Postgraduate: Level 7
Current
Monday 24 April 2023
Friday 30 June 2023
30
03 February 2023
Requisites for this module
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Do campaign messages actually affect public opinion? Does a refugee's religion affect support for her asylum application? Do legislators respond when made aware of district preferences? This course develops a framework and a set of tools centred around answering causal questions such as these. We lay foundations in the potential outcomes model, allowing us to identify causal inferences. We discuss why we might conduct field, survey, and laboratory experiments, best practices for designing and registering experiments, how to overcome common problems, and how to analyse experimental data. We will also address special topics such as interference and mediation. Using experiments as a foundation, we will examine and apply methods for causal inference from observational data, such as matching, regression adjustment, instruments, and discontinuity designs.
No information available.
Participants will gain understanding of the potential outcomes model, and how and why we often register and conduct experiments for causal inference. Participants apply this understanding to experimental design, and will analyse experimental and observational data with attention to causal questions. Throughout, participants will learn application through the R statistical language. This course is suitable for participants at a variety of levels, including exceptional undergraduates, master’s degree and Ph.D. students, and those with a Ph.D.
Course prerequisites
Students should have encountered conventional topics in introductory statistics, such as null hypothesis significance tests, confidence intervals, and linear regression. We will reintroduce such topics as needed. Students should have some familiarity processing data with R or Stata, or be willing to learn.
Representative Background Reading
Freedman, Pisani, and Purves, “Statistics”, 4th edition (2007) Norton, Chapter 1, pages 3-11.
Required Text – this text will be provided by ESS:
Gerber and Green. Field Experiments: Design, Analysis, and Interpretation. WW Norton. ISBN: 978-0393979954.
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 |
| Coursework |
Assessment one |
|
50% |
| Coursework |
Assessment two |
|
50% |
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.
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