Project - ECO00033M

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Module will run

Occurrence	Teaching period
A	Autumn Term 2022-23 to Spring Term 2022-23

Module aims

to instruct you how to use the various types of data sources that are available to you, both electronically and through libraries;

through case studies to show you how to apply econometric analysis to estimate the parameters of various economic models and to test various economic hypotheses;

to give you practical experience in formulating, estimating and testing a particular model and in writing up your results.

Module learning outcomes

On completing the module a student will:

know how to access and transfer the main UK time series and cross sectional data sets electronically;

know how to access and use a selection of econometric packages;

appreciate how to use economic theory and econometrics to develop empirical models in applied fields;

know how to evaluate models;

have undertaken a study of your own and written up the results.

Students are required to successfully complete Econometrics 1 in the Autumn term of their Master’s program.

Indicative assessment

Task	% of module mark
University - project	100

Special assessment rules

None

Indicative reassessment

Task	% of module mark
University - project	100

Module feedback

Feedback will be returned to students according to University regulations.

Indicative reading

The main references for the microeconometric theory and Stata programming are the following.

Colin Cameron and Pravin K. Trivedi (2005) Microeconometrics: Methods and Applications, Cambridge University Press

Colin Cameron and Pravin K. Trivedi (2010) Microeconometrics using Stata, Stata Press

Greene W.H. (2003) Econometric Analysis, Prentice Hall

Wooldridge J.M. (2002) Econometric Analysis of Cross Section and Panel Data, Massachusetts Institute of Technology

The main references for the macro and time-series econometric theory are:

Hamilton, J., Time Series Analysis, Princeton, 1994.

Enders, W., Applied Econometric Times Series, 3rd Edition, John Wiley, 2009.

The reading for the module is tied to the case studies.