Time-series analysis using Stata

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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: $1,395

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

Course leader

David Schenck is a Senior Econometrician at StataCorp LLC. He earned his bachelor's degree in economics from Vanderbilt University and a PhD in economics from Boston College. His interests include time series, Bayesian analysis, and macroeconomics. At Stata, he is the primary developer of DSGE and other time-series features.

Course topics

A quick review of the basic elements of time-series analysis
Managing and summarizing time-series data
Univariate models
- Moving average and autoregressive processes
- ARMA models
- Stationary ARMA models for nonstationary data
- Multiplicative seasonal models
- Deterministic versus stochastic trends
- Autoregressive conditionally heteroskedastic models
- Autoregressive fractionally integrated moving average model
- Tests for structural breaks
- Markov switching models
Introduction to forecasting in Stata
Filters
- Linear filters
- A quick introduction to the frequency domain
The univariate unobserved components model
Multivariate models
- Vector autoregressive models
- A model for cointegrating variables
State-space models
Impulse response and variance decomposition analysis
Dynamic-factor models
Multivariate GARCH

Prerequisite

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

Next session

Currently, there are no scheduled sessions of this course.

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Notes

Enrollment is limited. This course may be offered in a classroom or web-based setting. The type (classroom or web-based) will be designated above when scheduled.

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.

Web-based training courses are four-day courses that run for three and a half hours 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 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.

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