EC485
Further Topics in Econometrics
This information is for the 2023/24 session.
Teacher responsible
Professor Javier Hidalgo SAL 4.20
Dr Yike Wang SAL 4.26
Dr Vassilis Hajivassiliou SAL 4.23
Availability
This course is available on the MSc in Econometrics and Mathematical Economics. This course is available with permission as an outside option to students on other programmes where regulations permit.
Pre-requisites
Students must have completed Introductory Course for MSc EME (EC451).
In exceptional circumstances, students may take this course without EC451 provided they meet the necessary requirements and have received approval from the course conveners (via a face to face meeting), the MSc EME Programme Director, and their own Programme Director. Contact the Department of Economics for more information (econ.msc@lse.ac.uk) regarding entry to this course.
Course content
The aim of the course is to introduce the student to topics at the frontier of econometric research of importance both at a theoretical and empirical level. The course consists of four series of ten lectures on specialised topics in econometrics. These lectures change from year to year. For the academic year 2023-2024, they will include: Bootstrap methods; nonparametric and semiparametric methods in econometrics; high dimensionalities and machine learning; and nonlinear dynamic panel data models.
Teaching
20 hours of lectures in the AT. 20 hours of lectures in the WT.
This course is delivered through lectures totalling a minimum of 40 hours across Autumn Term and Winter Term. There are no classes.
Indicative reading
No one book covers the entire syllabus; lists of references will be provided and lecture notes circulated.
Assessment
Exam (50%, duration: 2 hours, reading time: 15 minutes) in the January exam period.
Exam (25%, duration: 1 hour, reading time: 15 minutes) in the spring exam period.
Essay (25%, 2000 words) in the ST.
• The January exam is based on Prof Hidalgo's lectures on bootstrap methods and on nonparametric and semiparametric methods.
• The Spring exam is based on Dr Hajivassiliou’s lectures on panel data methods
The essay due in Spring Term is based on Dr Wang's teaching on high dimensionalities and machine learning, which provides an opportunity to critically review an academic paper.
Key facts
Department: Economics
Total students 2022/23: 4
Average class size 2022/23: Unavailable
Controlled access 2022/23: No
Lecture capture used 2022/23: Yes (MT & LT)
Value: One Unit
Course selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.