Time Series Analysis II: Advanced Topics


This course covers advanced topics in time series analysis. Topics will include vector autoregression models, vector error correction models, state-space models, dynamic factor models, controversies in the use of error correction models, count time series, change-point models, dynamic conditional correlation models, and forecast evaluation.

This course is intended for those who have taken the four-week workshop on Time Series Analysis I: Introduction or the equivalent.

A sound background in time series fundamentals is assumed. The course will make use of basic matrix algebra. The lab component of this course will employ STATA. Familiarity with STATA is assumed but a STATA crash course will be provided outside the lecture on day two. If you are unfamiliar with STATA, we suggest that you attend one of the many STATA tutorial sessions or lectures offered as part of the Summer Program.

Fees: Consult the fee structure.

Tags: Time Series, vector autoregression, count time series, VAR, dynamic factor model, forecasting, vector error correction model, state-space model

Course Sections