Office: Hagey Hall 201
Phone: 519-888-4567 ext. 32047
What follows is a paraphrased interview with Professor Xu
What courses do you teach?
ECON 421 Econometrics currently and ECON 405 Quantitative Finance, 422 Topics in Econometrics in the past.
What do you enjoy most about teaching?
Connecting with students. Small class sizes allow for better student engagement. It’s easier for students to ask questions in a smaller class. Jokes also relax the atmosphere and create a more casual and relaxed learning environment. It also helps with retaining student attention because in larger classes some students can become disinterested and get away with surfing the internet or playing games.
What topics are the hardest to understand for students? why do you think that is?
The foundations required in advanced econometric theory: matrix algebra, calculus (derivatives and integrals) and probability theory. Students should have a concrete understanding of these topics before taking a course like 421 or 422. The topics students struggle with most are Maximum Likelihood Estimation because of uncertainties with the foundations.
Students also have difficulty with grasping the theory without examples. Students always ask for examples but the theory is general enough that it can easily fit many situations. It can be applied to all areas such as health, labour, financial econometrics and more. Understanding the theory and what’s inside the black box of regressions is very important for an undergraduate student interested in graduate studies in economics.
What is a book that you recommend all aspiring econometricians read?
For students seriously considering graduate studies and taking advanced econometrics courses there are a few introductory textbooks available in many editions at the library
Econometrics Analysis by W. H. Greene.
Time Series Analysis by J. D. Hamilton.
What are some interesting research questions in your area of expertise that undergraduates can investigate as a senior essay research topic?
Some topics are distributional considerations for time series data (such as stock returns, foreign exchange rates, indices...); Monte Carlo methods in time series analysis; comparisons across estimation methods for time series just to list a few.