Professor J Hidalgo, STC. S578

This course is for MSc Econometrics and Mathematical Economics, MSc Statistics, MSc Applicable Mathematics and for other graduate students with the permission of the course lecturer. Students on MRes/PhD Economics may take the course with the permission.

This course gives an advanced treatment of the theory of estimation and inference for econometric models.

Part (a) Matrix background; symptotic statistical theory: modes of convergence, asymptotic unbiasedness, stochastic orders of magnitude, central limit theorems, applications to linear regression. Part (b) Non-linear-in variables systems: maximum likelihood and instrumental variables estimates, optimal instrumental variables estimates for static and dynamic models, and models with autocorrelated disturbances. Simultaneous equations systems, identification, estimation, asymptotic behaviour of estimators and hypothesis testing. Wald, generalised likelihood ratio and Lagrange multiplier hypothesis tests, asymptotic null and local behaviour and consistency.

Lectures EC484: 60 hours MT and LT. Classes EC484.A 30 hours MT and LT.

No one book covers the entire syllabus; a list of references will be provided at the start of the course, and lecture notes and relevant articles will be circulated.

A three-hour written examination in the ST.