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Estimation and inference techniques for models involving a single equation and systems of equations are introduced. Normally topics include asymptotic theory, maximum likelihood estimation, classical testing procedures, generalised least squares estimation, seemingly unrelated regression models, stochastic regressors, instrumental variables, generalised method of moments, simultaneous equations models (including VARs) and model-selection procedures.
Intended learning outcomes
On successful completion of this subject students should be able to:
- Investigate the characteristics of data that influence the choice of model and estimation technique for modelling and estimating economic relationships.
- Apply suitable estimation techniques to a range of economic and econometric models, interpret the results from these models, and use the results for forecasting and policy analysis.
- Describe the theory underlying inference techniques used in econometrics.
On successful completion of this subject, students should have improved the following generic skills:
- Evaluation of ideas, views and evidence
- Synthesis of ideas, views and evidence
- Critical thinking
- Application of theory to economic policy and business decision making
- Accessing economic and other information
- Summary and interpretation of information
- Application of Windows software
- Using and designing computer programs
- Statistical reasoning
- Problem solving skills
- Collaborative learning and teamwork
- Written communication
Last updated: 3 November 2022