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Time-Series Analysis Using Stata

Description

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.

Price: $1,295  

We offer a 15% discount for group enrollments of three or more participants.

Course topics

Prerequisite

A general familiarity with Stata and a graduate-level course in regression analysis or comparable experience.

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Notes

Enrollment is limited. Computers with Stata installed are provided at all public training sessions. All training courses run from 8:30 a.m. to 4:30 p.m. each day. A continental breakfast, lunch, and an afternoon snack will also be provided; the breakfast is available before the course begins.

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