Econometric Theory - ECO00033I
Module summary
The module gives student a thorough introduction to the theoretical concepts underlying modern Econometrics.
Related modules
Additional information
Prerequisite modules: Probability and Statistics, Mathematics for Economists
Co- requisite: Econometrics
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Semester 2 2024-25 |
Module aims
The module covers the following topics:
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Distribution Theory: Relations between normal, chi-square, F, and t distributions. Multivariate normal distributions, marginal and conditional normal distributions.
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Asymptotic theory: Limits, continuous functions, law of large numbers, convergence in probability, convergence in distribution and the central limit theorem.
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The Classical Linear Regression Model: Matrix algebra, Ordinary Least Squares (OLS) estimator, F and t tests
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Maximum Likelihood (ML) Estimation: ML estimator, Cramer-Rao lower bound, Neyman-Pearson lemma, likelihood ratio, Wald, and LM tests.
Module learning outcomes
On successfully completing the module the student will be able to:
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apply key concepts and methods from statistical theory relevant for economic data analysis
choose statistical models and tests relevant for the analysis of small and large datasets
Module content
Subject to changes:
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Finite sample results: review matrix, least squares
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gauss Markov theorem
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F test
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Finite sample results: MLE, Information, MVUE
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Elements of Asymptotic theory: review sequence, limits, boundedness, lim sup
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Convergence in distribution, Convergence in probability, Slutsky, cmt, WLLN, iidCLT (and inid/dependent data?
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asymptotic properties of OLS estimator: consistency and asymptotic normality
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2sls estimator and its asymptotic properties.
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asymptotic properties of MLE estimator: consistency and asymptotic normality
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MLE of a parameter vector and Wald, LR and LM tests, with the regression example.
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LM test for error serial correlation or intro to times-series analysis
Indicative assessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 100 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 100 |
Module feedback
For the formative work students are set exercises prior to the seminars, and submit at least one piece of work to be marked which is returned within 25 working days of submission.
For the summative assessment a breakdown of marks by question will be provided also within 25 working days of the exam.
Indicative reading
Bartle, R.G., Sherbert, D.R., Introduction to Real Analysis, Wiley.
Robert V. Hogg, R.V., McKean, J.W., Craig, A.T., 2019, Introduction to Mathematical Statistics, 8th ed., Pearson.
White, H., Asymptotic Theory for Econometricians, revised edition, Academic Press.
Abadir and Magnus, Matrix Algebra, CUP.
Johnston and Dinardo, Econometric Methods, McGrow-Hill.