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M300 - Econometric Methods
The aim is to provide a graduate level training in econometric methods.
The emphasis of the course is on single equation models together;
empirical examples are provided both to motivate and to illustrate the
methods. Topics will include: least squares and the linear regression
model; instrumental variables; maximum likelihood estimation and test
procedures; binary choice and count data models; time series models;
simple dynamic structures; panel data models.
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M310 - Time Series and Financial Econometrics
The aim of the course is to introduce students to advanced methods for
analysing and modelling time series, with special reference to
macroeconomics and finance. Topics covered include state space models,
spectral analysis, nonlinear models, volatility and multivariate time
series models.
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M320 - Cross-Section and Panel Data Econometrics
This course consists of lectures dealing with estimation and inference
using both cross-section and panel data. Topics covered include
instrumental variable estimators, random utility models in discrete
choice, fixed and random effects estimators for panel data, nonlinear
panel data models, count data models, and techniques to facilitate
comparability using survey data.
The course will also provide:
- a formal treatment of the Generalised Method of
Moments for both linear and nonlinear models.
- an introduction to simulation methods (classical
and Bayesian) in applied econometrics
Applications covered include econometric issues relating to the
estimation of demand systems for differentiated products, and price cap
regulation in natural monopolies.
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M330 - Applied Econometrics
The aim of this module is to illustrate the use of modern econometric
techniques with a particular focus on the use of data analysis to
address policy issues. Students will be instructed in the critical
interpretation of empirical output, and develop an understanding of the
limitations imposed by the econometric techniques and the data
available.
