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Unit information: Econometrics beyond the mean 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 Econometrics beyond the mean
Unit code EFIMM0096
Credit points 15
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Stouli
Open unit status Not open
Pre-requisites

ECONM1022 Econometrics

Co-requisites

Nil

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

Description including Unit Aims

The aim of this unit is to introduce students to some modern micro econometric techniques, including a range of recent methods in the econometric analysis of the distributional impact of a policy or treatment. These techniques are used for the modelling of heterogenous effects in economic analysis.

The topics include heterogenous effects, quantile regression, distributional regression and causal modelling. The unit aims to build in students the ability to know, apply, and evaluate these tools and to implement them when undertaking novel research.

Intended Learning Outcomes

At the end of the course, students will be able to:

1. Demonstrate knowledge and understanding of econometric models incorporating heterogeneity in individual and policy effects.

2. Use quantile regression and distributional regression methods in their research and work.

3. Demonstrate knowledge and understanding of econometric properties of quantile regression and distributional regression methods.

4. Access the journal articles in the discipline, evaluate them critically and start independent research projects involving some recent econometric techniques.

This unit provides a thorough and in-depth treatment of the basic concepts and methods in micro econometrics and distributional modelling.

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

timed open book assessment

Reading and References

J. Angrist & J.S. Pischke (2009), Mostly Harmless Econometrics, Princeton.

A. Cameron & P. K. Trivedi (2012), Microeconometrics. Methods and Applications, Cambridge.

R. Koenker (2005), Quantile Regression, Cambridge.

M. Verbeek (2012), A Guide to Modern Econometrics, (Fourth Ed.), J. Wiley and Sons.

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