Training Calendar

Regime Switching Models with EViews (Online Course)

Online Half day (26th September 2019 - 26th September 2019) EViews Intermediate, Introductory
Delivered by: Dr Malvina Marchese, Cass Business School, City – University of Londonv

Overview

Our web based Regime Switching models with EViews course provides a complete introduction to modelling and forecasting Regime Switching models in EViews. It provides a sound and practical understating Threshold models, Markov-switching models and Smooth Transition autoregressive models used in economic and financial applications and strong background in forecasting. The course targets researchers, practitioners and policy makers who are interested in gaining an in-depth knowledge of Regime Switching models and learning how to use them in their research.

The course runs from 13.00 - 17.00 (UK Time) / 17:00 - 21:00 (UAE Time)

Agenda

Linear regression is one of the primary tools for econometric and statistical analysis. There is, however, considerable evidence that nonlinear modelling is sometimes appropriate, especially in the analysis of financial and macroeconomic relationships that are subject to regime change.

This course provides a comprehensive introduction to switching regression models in EViews—linear regression models with nonlinearities arising from discrete changes in regime. Taking a “learning-by-doing” approach we aim to present Threshold regression models, Smooth Transition models and Markow switching models.

Dynamics specifications are discussed for all three classes using lagged dependent variables as explanatory variables and through the presence of auto-correlated errors. The course employs plenty of financial and macroeconomic data and a constant stream of challenging exercises.The course specifically focuses on forecasting methodologies with regime switching models. Participants leave with the know-how on a wide range of regime switching models and the ability to identify which one to use for a specific modelling and forecasting purpose. Advanced topics such as regime switching VAR and Smooth transition GARCH models can be discussed according to participants’ needs and background.

The course is intentionally flexible. The agenda emerges dynamically and depends on the group’s prior background and knowledge of EViews. By the end of the course, all participants will feel comfortable with the following:

  • Testing for structural breaks in the multiple linear regression model
  • Threshold regression models (sample splitting, TAR and SETAR models)
  • Threshold regression models estimation and diagnostic (selecting the threshold, specifying regime varying and non-varying variables, choosing the delay parameter, sequential LS estimation and post estimation diagnostic)
  • Smooth Transition regression models (STR and STAR models)
  • Smooth Transition regression models estimation and diagnostic (choosing weights and transition functions, testing for linearites, testing for parameter constancy)
  • Markow Switching models (regime probabilities, likelihood evaluation and filtering, smoothing, initial probabilities, dynamic regression)
  • Which regime switching? How to choose the most appropriate (and efficient) regime switching model for your data

Learning Ratio

80% practical; 20% theory

Principal texts for pre-course reading:

Adkins L.C , Hill R.C Using EViews for principle of Econometrics (Appendix C and Chapters 2 and 3)

Principal texts for post-course reading:

Adkins L.C , Hill R.C Using EViews for principle of Econometrics (Chapters 9, 12, 13,14)

Basic knowledge of hypothesis testing is needed.

Basic knowledge of EViews is helpful. Basic understanding of regression analysis is helpful.

Terms & Conditions

  • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
  • Additional discounts are available for multiple registrations.
  • Cost includes course materials that will be posted to you prior to the start of the course.
  • Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course.
  • Payment of course fees required prior to the course start date.
  • Registration closes 5-calendar days prior to the start of the course.

    • 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
    • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
    • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.
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    Online - 26 September 2019 (26/09/2019 - 26/09/2019)

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