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This module is about econometric methods and how they are applied to estimate and test the unknown parameters of economic relationships. Priority is given to both the statistical reasoning underlying the methodology and the practical considerations involved in using this methodology with a variety of models and real data.
There is a limit to the material that can be covered in less than 160 hours’ study time. In an econometrics module it is difficult to trade-off breadth and depth since, without good groundwork and sufficient information at each stage, ideas may be misunderstood and techniques misapplied. This module follows the standard structure of most econometrics textbooks. It deals only with single-equation models, but by the end of the module the student is ready to tackle simultaneous equation models, which would be the next step in increasing proficiency in applied econometrics.
Objectives and learning outcomes of the course
By the end of the module, you should be able to
- understand the basic principles of regression analysis and statistical inference in the context of a single-equation regression model
- formulate a single-equation regression model and estimate its parameters
- carry out a variety of tests relating to the structural and stochastic specification of your model
- test hypotheses about economic behaviour in the context of your model and interpret the results of these tests
- specify and interpret models using dummy variables and different types of dynamic specification
- incorporate linear restrictions into your regression model and test these restrictions
- test for heteroscedasticity and autocorrelation of the disturbances of a regression model, and take appropriate action
- when these conditions are found to be present
Scope and syllabus
The focus of the module is on the classical linear regression model. This is the basis for much econometric methodology and it provides the framework for organising the module.
The module covers
- the principles of regression analysis and its statistical foundations
- the simple linear regression model
- the multiple linear regression model
- departures from the assumptions of classical linear regression
- modelling economic behaviour