Professor Javier Hidalgo

Dr Yike Wang

Dr Vassilis Hajivassiliou

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.

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.

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 2022-2023, they will include: Bootstrap methods; nonparametric and semiparametric methods in econometrics; high dimensionalities and machine learning; and nonlinear dynamic panel data models.

20 hours of lectures in the MT. 20 hours of lectures in the LT.

This course is delivered through lectures totalling a minimum of 40 hours across Michaelmas Term and Lent Term. There are no classes. 

No one book covers the entire syllabus; lists of references will be provided and lecture notes circulated.

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 summer exam period.
Essay (25%, 2000 words) in the ST.

• The January exam is based on Prof Hidalgo's lectures on bootstrap methods and those of Dr Hajivassiliou on panel data methods.
• The essay due in summer term is based on Dr Wang's teaching on high dimensionalities and machine learning, which provides an opportunity to critically review an academic paper.
• The summer exam is based on Prof Hidalgo's teaching on nonparametric and semiparametric methods.