| Unit name | Empirical Industrial Organisation |
|---|---|
| Unit code | ECONM0013 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Alessandro Iaria |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
Economic Analytics, Econometrics with Python |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Economics |
| Faculty | Faculty of Social Sciences and Law |
The aim of this unit is to provide a hands-on introduction to the toolkit of the empirical industrial economist: the focus will mostly be on “doing things” by combining individual- and firm-level data and computer programming for the economic modelling of consumer and firm behaviour in the marketplace.
Companies such as Google and Amazon, consulting firms, and competition authorities employ techniques developed in the field of empirical industrial organisation to enhance their understanding of the markets they operate in, to make more informed profit-maximizing decisions, and to design welfare-improving market regulations. This course guides students in the transition from the theory of econometrics and industrial economics to their practice in the real world.
An overview of content
First, we will introduce the main ideas of structural econometrics and compare them with those behind non-structural methods. Second, we will discuss methods useful for the estimation of production functions and productivity. Third, we will study methods commonly used to estimate demand functions. Fourth, we will revisit classical games of price and quantity choices. Fifth, we will discuss the estimation of discrete games. In case of any remaining time, we will conclude by introducing single-agent dynamic discrete choice models.
After completing this unit, students will be able to critically select and apply a range of methods that can be used to analyse firms’ productivity and to critically evaluate their decisions, such as pricing and quantities choices, or whether to enter in a specific market. Students will learn how to assess the impact of firms’ decisions on their profits but also on the welfare of consumers, and consequently how to quantify the value of market outcomes for stakeholders.
Learning Outcomes
At the end of the course, students will be able to:
1) Synthesise and critically assess economic theory and econometric methods in order to translate models of industrial economics into statistical models.
2) Estimate models of industrial economics using the appropriate software.
3) Generate counterfactual economic predictions in industrial economics.
4) Evaluate and interpret empirical results and predictions to make policy and market recommendations.
Teaching will be delivered through a combination of large and small group classes supported by online resources. There will be large group lectures introducing different economic and econometric theory and concepts, supported by online resources. The small group sessions will focus on problem solving exercises and computer lab sessions on empirical applications of the methods.
Tasks which help you learn and prepare you for summative tasks (formative):
Weekly exercises and computer lab sessions.
Tasks which count towards your unit mark (summative):
When assessment does not go to plan
The reassessment for students who have not been able to take or pass the unit summative assessments will take the form of a single empirical project coursework assessing all the ILOs.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. ECONM0013).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
