Skip to main content

Unit information: Empirical Industrial Organisation in 2020/21

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Empirical Industrial Organisation
Unit code EFIMM0097
Credit points 15
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Alessandro Iaria
Open unit status Not open
Pre-requisites

ECONM1010 Microeconomics, ECONM1022 Econometrics

Co-requisites

Nil

School/department School of Economics
Faculty Faculty of Social Sciences and Law

Description including Unit Aims

//undefined

//undefined

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.

//undefined

//undefined

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.

Intended 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 Information

Teaching will be delivered through a combination of synchronous and asynchronous sessions such as online teaching for large and small group, face-to-face small group classes (where possible) and interactive learning activities

Assessment Information

Coursework

Reading and References

1) “Microeconometrics, Methods and Applications.” A. C. Cameron and P. K. Trivedi, Cambridge University Press, 2005.

2) “Microeconometrics Using STATA.” A. C. Cameron and P. K. Trivedi, Stata Press, 2009.

Feedback