Time-series analysis using Stata

$1,395 2 days

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.

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Upcoming sessions

Currently, there are no scheduled sessions of this course.

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

All prices USD.

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Course leader

Chris Cheng

Senior Econometrician

Chris Cheng is a Senior Econometrician at StataCorp LLC. He has a master's degree in economics and a PhD in agricultural and managerial economics from Texas A&M University. He has worked with technical support since 2019. Chris frequently interacts with users about technical questions and gives webinars and training courses. His interests focus on demand analysis, panel-data analysis, and other econometrics.

Prerequisite

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

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

Classroom location

United Training

300 E Highland Mall Boulecard

Suite 100

Austin, TX 78752

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Notes

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 for three to four hours daily with hourly breaks. 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.

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