Econometrics: Cause and Effect
Establishing whether a relationship is causal or not is at the core of economic analysis and its potential for societal impact.
The module will introduce the notion of causality used in modern applied microeconomic research. It will present a set of tools and methods that help to uncover causal relationships in economics and illustrate their applications with real world examples: from the causal effect of minimum wages on employment rates to the effects of education on earnings.
The applications discussed in the module are based on research carried out around the world.
The main aim of this module is to develop a clear understanding of the notion of causality when thinking of a relationship between any two variables, a skill which is highly sought after in the workplace.
Research in Teaching
Students will study several examples of empirical research.
Full module specification
|Module title:||Econometrics: Cause and Effect|
|Duration of module:||
Duration (weeks) - term 2: |
The aim of this module is threefold: (1) introduce students to the notion of causality in economic research, (2) present a set of tools and methods that help to uncover causal relationships in economics, and (3) illustrate the application of these techniques with real world examples.
ILO: Module-specific skills
- 1. explain the notion of causality in economic research;
- 2. explain the notion of identification strategy and different types of identification strategies;
- 3. explain the pros and cons of experimental and non-experimental data.
ILO: Discipline-specific skills
- 4. link economic theory with data;
- 5. critically assess empirical studies in economics.
ILO: Personal and key skills
- 6. demonstrate analytical and critical thinking.
Learning activities and teaching methods (given in hours of study time)
|Scheduled Learning and Teaching Activities||Guided independent study||Placement / study abroad|
Details of learning activities and teaching methods
|Category||Hours of study time||Description|
|Scheduled Learning and Teaching Activity||22||Lectures|
|Scheduled Learning and Teaching Activity||10||Tutorials|
|Guided Independent Study||118||Reading, preparation for classes and assessments|
|Form of assessment||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|In class discussion/exercises||Weeks 2, 4, 6, 8||1-6||Verbal/ELE|
Summative assessment (% of credit)
|Coursework||Written exams||Practical exams|
Details of summative assessment
|Form of assessment||% of credit||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|Mid-Term Exam||30||1 hour||1-6||Tutorial Discussion|
|Final Exam||70||2 hours||1-6||Online|
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|
|Midterm exam (30%)||Midterm exam (1 hour) (30%)||1-6||August Examination Period|
|Final exam (70%)||Final exam (2 hours) (70%)||1-6||August Examination Period|
-Causality in economics
-Potential outcomes framework
-Regression with experimental data
-Regression with observational data
-Experiments in economics
-Quasi-experiments in economics
Indicative learning resources - Basic reading
Ashenfelter Orley, Phillip B. Levine, and David J. Zimmerman (2002) "Statistics and Econometrics: Methods and Applications", Wiley.
Angrist, Joshua D., and Jörn-Steffen Pischke (2014) "Mastering ’Metrics: The Path from Cause to Effect", Princeton University Press.
Angrist, Joshua D., and Jörn-Steffen Pischke (2009) "Mostly Harmless Econometrics: An Empiricist's Companion", Princeton University Press.
Module has an active ELE page?
Indicative learning resources - Web based and electronic resources
ELE – College to provide hyperlink to appropriate pages
Last revision date