Below is a listing of the course materials available from courses previously offered by Estima. See Current Courses for current and upcoming courses.
The cost for course materials is $50 per course. You will receive a PDF handbook containing the lecture materials, as well as all of the example programs, data sets, and RATS procedures used in the course.
To place an online order for any of the course materials (delivered by email), see Course Registrations.
To order by email or phone, contact us at email@example.com or 1-847-864-8772.
Note that the $50 price does not include access to the private forums used for the original course presentations and discussion. Access to these forums may be available at an additional cost—please contact us for details.
This covers estimation of univariate and multivariate ARCH and GARCH models, using both the built-in GARCH instruction and estimation with more general likelihood maximization and simulation techiques. It includes detailed discussions of replications of papers which have been popular downloads by RATS users.
This course treats a broad range of material, including tests for structural breaks and threshold effects, and estimation of threshold autoregression (TAR) and smooth transition (STAR) models, endogenous Markov switching models, and Markov switching VAR, State Space, and ARCH and GARCH models. It covers both maximum likelihood and Bayesian estimation techniques.
The course covers identifying and estimating VAR models, computing impulse responses and variance decompositions, historical decomposition and counterfactual simulations, structural and semi-structural VARs, and sign restrictions. We focus on techniques designed to elicit information from the data without the use of informative Bayesian priors. This has been expanded over 50% from the first edition.
The "State Space" part of this course is based largely on Durbin and Koopman's Time Series Analysis by State Space Methods book, supplemented by material from Harvey's Forecasting, Structural Time Series Models and the Kalman Filter, and from West and Harrison's Bayesian Forecasting and Dynamic Models. This has been greatly expanded (more than doubled in size) from the 1st edition, covering many new topics.
About 80% of the course is devoted to State Space models, with the remainder focusing on DSGE models. The example programs require version 9.0 or later of RATS (with a few requiring 9.2 or later).
This course covers the techniques of panel data econometrics, with an emphasis on the time-series aspects, including treatments of Dynamic Panels, Unit Root Tests, Cointegration, and Vector Autoregression (VAR) models. It also includes several examples of the use of Gibbs sampling for panel data, with applications to linear and non-linear random effects, random coefficients models, and VAR's.
The course also serves to demonstrate most of the new panel data capabilities added to RATS with Version 8.1.
Most of the course is devoted to working through Gary Koop's book of the same name (see Bayesian Econometrics for details), although it also covers some topics (such as Bayesian VARs) not included in the text.