Which Policies Work? Causal Methods for Policy Evaluation
| Module title | Which Policies Work? Causal Methods for Policy Evaluation |
|---|---|
| Module code | SPA3024 |
| Academic year | 2025/6 |
| Credits | 15 |
| Module staff | Dr Michael Ganslmeier (Lecturer) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
| Number students taking module (anticipated) | 10 |
|---|
Module description
The ability to assess the effects of policies on social, political, and economic outcomes is fundamental to understanding whether they achieve their intended goals. This module explores a range of theoretical and practical approaches to measuring the causal impact of policies and programmes, covering research methods whose advancements were recognized with the 2021 Nobel Prize in Economics. We will examine applications across diverse policy domains, including conditional cash transfers, family planning, public health, education, gender, and diversity. You will learn about true and quasi-experimental research designs to uncover causal effects, their respective strengths and limitations, and gain hands-on experience applying these methods using R.
Module aims - intentions of the module
This module will equip you with a set of tools to conduct an independent policy oriented research. You will also gain an understanding of the criteria required for assessing causality and ability to critically assess existing policy studies and research findings.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. Develop understanding of key concepts and principles of causal methods
- 2. Understanding the advantages and limitations of different research designs
- 3. Understanding the conditions for assessing causality and underlying assumptions
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 4. Gaining knowledge of various research methods used for causal methods
- 5. Develop understanding of issues posed by evidence based decision-making and policy analysis
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 6. Become familiar with a range of data analysis techniques
- 7. Designing policy related research
Syllabus plan
Whilst the module’s precise content may vary from year to year, it is envisaged that the syllabus will cover some or all of the following topics:
- Introduction to causal inference and potential outcomes
- Experiments and Randomized controlled trials
- Propensity Score Matching
- Difference-in-differences
- Regression Discontinuity Designs
- Instrumental Variables
- Synthetic Control Methods
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 22 | 128 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled learning and teaching activity | 22 | 11 x 2 hours per week comprising of lectures and lab sessions |
| Guided independent study | 38 | Reading and preparing for seminars (around 4-6 hours per week); |
| Guided independent study | 90 | Researching and writing assignments (researching, planning and writing the course work). |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Practical exercises x 2 | Short exercises to be completed in class | 1-6 | Peer and Oral feedback |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 100 | 0 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Research plan | 20 | 500 words | 1-7 | Written feedback |
| Research report | 80 | 3000 words | 1-7 | Written feedback |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Research plan | Research plan | 1-7 | August reassessment period |
| Research report | Research report | 1-7 | August reassessment period |
Indicative learning resources - Basic reading
- Cunningham, Scott. "Causal inference –The Mixtape”. Yale University Press, 2021.
- Huntington-Klein, Nick. The effect: An introduction to research design and causality. Chapman and Hall/CRC, 2021.
- Angrist, Joshua D., and Jörn-Steffen Pischke (2009) “Mostly Harmless Econometrics: An Empiricist’s Companion”, Princeton University Press
- Angrist, Joshua D., and Jörn-Steffen Pischke (2014) “Mastering ’Metrics: The Path from Cause to Effect”, Princeton University Press.
- Hernán MA, Robins JM (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC
- Goldthorpe, J. H. (2001). Causation, statistics, and sociology. European Sociological Review, 17(1): 1- 20.
- Gertler, Paul J., et al. Impact Evaluation in Practice, Second Edition, World Bank Publications, 2016
- Llaudet, E. and Imai, K. (2023). Data Analysis for Social Science: A Friendly and Practical Introduction
- Stoker, G., & Evans, M. (Eds.). (2016). Evidence-based policy making in the social sciences. Bristol: Policy Press.
Indicative learning resources - Other resources
In this module, we will make use of administrative data from the office for National Statistics: https://www.ons.gov.uk/
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | None |
| Module co-requisites | None |
| NQF level (module) | 6 |
| Available as distance learning? | Yes |
| Origin date | 03/02/2025 |
