This course reviews methods for time-series analysis and shows how to perform the analysis using Stata. The course covers methods for data management, estimation, model selection, hypothesis testing, and interpretation. For univariate problems, the course covers autoregressive moving-average (ARMA) models, linear filters, long-memory models, unobserved components models, and generalized autoregressive conditionally heteroskedastic (GARCH) models. For multivariate problems, the course covers vector autoregressive (VAR) models, cointegrating VAR models, state-space models, dynamic-factor models, and multivariate GARCH models. Exercises will supplement the lectures and Stata examples.
We offer a 15% discount for group enrollments of three or more participants.
A general familiarity with Stata and a graduate-level course in regression analysis or comparable experience.
Currently, there are no scheduled sessions of this course.
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Enrollment is limited. This course is offered in both classroom and web-based settings.
Classroom training courses are two-day courses that run from 8:30 a.m. to 4:30 p.m. each day. These courses take place at a training center where computers with Stata installed are provided. A continental breakfast, lunch, and an afternoon snack will also be provided; the breakfast is available before the course begins.
Web-based training courses are four-day courses that run from 12:00 p.m. to 3:30 p.m. Central Time each day. You will be provided with a temporary Stata license to install on your computer, a printed copy of the course notes, and all of the course datasets so that you can easily follow along. Learn more about how our web-based training courses work, watch a video demonstration, and find technical requirements for participating in this type of training.