Unit information: Empirical Industrial Organisation in 2019/20

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

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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.

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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

- 16 hours of lectures. - 8 hours of small-group classes.

Assessment Information

Summative assessment: Assessed coursework (100%) to evaluate ILOs 1 to 4. Students will be given either a simulated or a real dataset and will have one week to complete a written document that reports their computations and interpretations of empirical results. The assessed coursework is meant to be a mini-dissertation, where students work individually on the provided dataset using the techniques and software introduced in the module. Students will be given a very broad economic question to be addressed based on evidence produced by combining economic models and the available data.

Formative assessment: Computer based group assignments. Each assignment is a practical problem set, and the outcome will be a written document where the students report their answers, including any table of results, figures, and computer codes.

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.