Module overview
This module will introduce students to experimental methods in economics. Emphasis will be on the methodology, in particular, statistical techniques necessary for establishing causality and valid inference, non-parametric and other useful non-standard statistical tests for experimental data, formal analysis of how scientific knowledge accumulates, in particular with respect to replication and meta-analysis.
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Adopt and develop a sound quantitative approach to adress economic questions and problems.
- apply quantitative skills necessary for designing experiments and observational studies, and for analysing evidence.
- Critically evaluate the design and analysis of existing empirical research.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- main types of experimental economic research.
- the design of lab and field experiments.
- non-parametric and other state of the art econometric techniques for experimental, quasi-experimental and observational data.
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- reflect on scientific method, including replication and meta-analysis.
Syllabus
This module will start with a general introduction to experimental economics and then focus on the design of economic experiments, covering topics such as randomization, power analysis and controlling for failures of randomization. The module will present insights from the lab on applications such as market and auctions, coordination and public goods, bargaining and social preferences, and individual decision-making. Other approaches, such as field experiments and neuroeconomics, may also be covered. The module will also cover replications and meta-analysis as part of scientific discovery. This is an indicative list of topics that can be altered, depending on student demand and prior knowledge.
Learning and Teaching
Teaching and learning methods
Lectures and masterclasses, including experimental classes. Module hand-outs, lectures notes and problem sets will be made available via Blackboard.
| Type | Hours |
|---|---|
| Independent Study | 125 |
| Teaching | 25 |
| Total study time | 150 |
Resources & Reading list
Textbooks
Harris Cooper, Larry Hedges, Jeffrey Valentine (2009). The Handbook of Research Synthesis and Meta-Analysis. Russel Sage Foundation.
Murray Webster and Lane Sell (2007). Laboratory Experiments in the Social Sciences. Elsevier.
John H Kagel and Alvin ERoth (1995). The Handbook of Experimental Economics. New Jersey: Princeton University Press.
Assessment
Assessment strategy
The module will be assessed through a take-home assignment (worth 70% of the final mark) and two pieces of coursework (each worth 15% of the final mark). This is supported by continuous formative assessment through problem sets. This is the same for internal repeat. Assessment for external repeat and referal is through 100% take-home assignment.
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Coursework | 15% |
| Assignment | 70% |
| Coursework | 15% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Assignment | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Assignment | 100% |
Repeat Information
Repeat type: Internal & External