EC484
Econometric Analysis
This information is for the 2016/17 session.
Teacher responsible
Dr Taisuke Otsu 32L. 4.25 and Professor Peter Robinson 32L. 4.13
Availability
This course is compulsory on the MSc in Econometrics and Mathematical Economics. This course is available on the MRes/PhD in Economics, MSc in Applicable Mathematics, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.
Pre-requisites
Students must have completed Pre-sessional Course for MSc EME (EC451).
Course content
This course gives an advanced treatment of the theory of estimation and inference for econometric models.
Part (a) Background; asymptotic statistical theory: modes of convergence, asymptotic unbiasedness, uniform integrability, stochastic orders of magnitude, convergence in distribution, central limit theorems, applications to linear regression, extensions to time series, consistency and asymptotic distribution of implicitly defined extremum estimators.
Part (b) General asymptotic theorems, nonlinear regression, quantile regression, nonparametric methods (kernel and series methods), generalized method of moments, conditional moment restriction, many and weak instruments, limited dependent variables, treatment effect, bootstrap, and time series.
Teaching
20 hours of lectures and 10 hours of seminars in the MT. 20 hours of lectures and 10 hours of seminars in the LT.
Formative coursework
Two marked assignments per term.
Indicative reading
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.
Assessment
Exam (50%, duration: 2 hours) in the LT week 0.
Exam (50%, duration: 2 hours) in the main exam period.
Note that EC451 material will be covered on the exam.
Key facts
Department: Economics
Total students 2015/16: 37
Average class size 2015/16: 20
Controlled access 2015/16: Yes
Value: One Unit