This is the rst course in econometric theory for Ph.D. students; well prepared Master students are also welcome to take this course. This course requires knowledge of probability theory, multivariate statistics, and linear (matrix) algebra; econometrics at master level is not a prerequisite, however. In this course, I will follow my own lecture notes and cover various least-squares theories and quasi-maximum likelihood theory. Unlike most econometrics textbooks that are organized according to models, my notes are arranged by theories (methods), with applications to various models. Some textbooks (R2 and R3 below) provide more thorough treatment of these topics. What I hope is that, by introducing econometric theory in this way, students will learn how an econometric method is derived and why it works.

The lectures will be in English; classroom discussion may be in Mandrin if so desired. Students are also required to be familiar with at least one programming language, such as R or Matlab. A senior student will introduce basic programming in R in the beginning lectures; some basic materials about R installation and introduction can be found in the class website (see below).