ECON30500 Field Experiments Social Sci

Academic Year 2024/2025

In 2019 the Nobel Prize in Economics was awarded to Abhijit Banerjee, Esther Duflo and Michael Kremer for “their experimental approach to alleviating global poverty". Their work has highlighted the importance of using field experiments to find solutions to some of the major issues facing society today.

This module focuses on the use of field experiments in the social sciences to identify the causal impact of policies/interventions/services to address questions such as How can we reduce socio-economic inequalities in children's skills? How can we reduce poverty? How can we reduce the obesity epidemic? How can we reduce discrimination in hiring decisions?

Field experiments, also known as randomised controlled trials (RCTs), are a type of study that uses random assignment of units— e.g., individuals, classrooms, communities—to implement programmes, allocate resources, or enact policies. RCTs are considered the “gold standard” for addressing causal questions, for example, they allow us to answer Did X cause Y?, rather than, Is there an association between X and Y? Over the last twenty years, there has been a major increase in the number, scope, and quality of field experiments in the social sciences, particularly in the disciplines of economics, political science, and sociology.

This module will provide you with a solid foundation in the design, implementation, and analysis of field experiments, including both theoretical and practical issues. You will deepen your knowledge on how to conduct a field experiment including design issues such as identifying and addressing implementation issues. You will also learn about why and when to conduct a field experiment and the key components of a well-designed experiment. Finally, you will also explore the challenges to conducting a field experiment, as well as the tools to address these challenges.

There will be a particular focus on my own field experiment, known as the Preparing for Life, which I have been running in Dublin for over a decade. Through the assignment, you will have the opportunity to design your own field experiment, which will allow you to apply the theoretical frameworks covered in the module to the practical application of a field experiment.

This module may be taken as part of a Structured Elective in Economics. This means that if you combine this module with at least 10 additional credits from other economics modules you will be awarded a ‘structured elective in economics’ on your transcript.

Show/hide contentOpenClose All

Curricular information is subject to change

Learning Outcomes:

At the end of the module, you will be able to:
- Demonstrate theoretical knowledge on recent methodological advances in the design and analysis of field experiments.
- Gain knowledge of influential field experiments in the social sciences and discuss their implications for policy.
- Evaluate the strengths and limitations of field experiments.
- Apply practical experience in designing a field experiment and writing and communicating about experimental research.

Indicative Module Content:

The module will include a range of topics covering both the theoretical and practical aspects of field experiments. Interspersed between these topics we will have a series of lectures showcasing an existing Irish field experiment in the area of early childhood intervention.

Topic 1: Introduction to Field Experiments
- 1A: Background & History of Field Experiments
- 1B: Causal Impact & Selection Bias
- 1C: Counterfactual Approach to Causal Inference
- 1D: Intervention Design & Evaluation

Topic 2: Randomisation for Field Experiments
- 2A: Introduction to Randomisation
- 2B: Types of Randomisation I
- 2C: Types of Randomisation II
- 2D: Unit of Randomisation
- 2E: Methods of Randomisation

Topic 3: Sample Size for Field Experiments
- 3A: Introduction to Sample Size & Power Analysis
- 3B: Hypothesis Testing & Type I and II Errors
- 3C: How to do a Power Analysis
- 3D: Factors Influencing Power Analysis & Rules of Thumb

Topic 4: Data & Measurement
- 4A: Outcomes & Data
- 4B: Measurement
- 4C: Sources of Measurement Error

Topic 5: Planning
- 5A: Ethics of Field Experiments
- 5B: Ethical Review Process
- 5C: Transparency in Field Experiments

Topic 6: Data Analysis
- 6A: Estimating treatment effects
- 6B: Additional analyses

Topic 7: Threats to Validity
- 7A: Compliance
- 7B: Attrition
- 7C: Spillovers
- 7D: Behavioural Responses
- 7E: Generalisability

Case study a field experiment
- The ‘Preparing for Life’ early childhood intervention programme

Student Effort Hours: 
Student Effort Type Hours


Autonomous Student Learning




Approaches to Teaching and Learning:
Multiple different teaching and learning approaches will be used in this module including reflective learning, class discussion, lectures and critical writing. 
Requirements, Exclusions and Recommendations

Not applicable to this module.

Module Requisites and Incompatibles
Not applicable to this module.
Assessment Strategy  
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Exam (In-person): The exam consists of a series of MCQs, short questions, and long questions. End of trimester
2 hr(s)
Alternative linear conversion grade scale 40% No


Group Work Assignment: You will be randomly assigned to a project team to produce a research proposal outlining the theory, design, and analysis of a field experiment of your choice. Week 4, Week 5, Week 7, Week 11 Alternative linear conversion grade scale 40% No



Carry forward of passed components
Resit In Terminal Exam
Summer Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

There is no single “best” textbook for the course. We will draw upon material in:

- Glennerster, Rachel, and Kudzai Takavarasha (2013). Running Randomized Evaluations: A Practical Guide. Princeton: Princeton UP.

This book is available as an ebook through UCD Library. You will need to be logged in to your UCD account to access it.

- Duflo, Esther, Michael Kremer, and Rachel Glennerster (2008). “Using Randomization in Development Economics Research: A Toolkit.” In Schultz, P., and Strauss, J. (Eds), Handbook of Development Economics, Edition 1, 4(5), Elsevier.

This article is available under My Learning on Brightspace.

- Gerber, Alan S., and Donald P. Green. (2012). Field Experiments: Design, Analysis, and Interpretation. New York: W.W. Norton.

Hardcopies of this book (5) are available for short-term loans in the UCD Library.

- See also JPAL’s research resources

Additional readings will be assigned throughout the trimester and will be made available on Brightspace.