Our course An introduction to State-Space models and the Kalman filter in EViews introduces the state-space representation and its estimation via the Kalman filter. The course features an applied perspective: participants are shown how to implement state-space estimation via practical exercises conducted with EViews 11 software. By the end of the training day, participants leave with the know-how to independently undertake time-series analysis and modelling.
State Space models and the Kalman filter
The course will cover the following:
The State-Space model: representation, main assumptions and their variants, and estimation through the Kalman filter.
Application: the time-varying regression model - representation, laws of motion, EViews syntax.
Application: models with unobserved components - representation, EViews syntax, application to the NAWRU.
Application: the Nelson-Siegel approach to the term structure.
Principal texts for pre-course reading:
J. Hamilton, Time Series Analysis, Princeton University Press
Principal texts for post-course reading:
- These will be recommended during the course.
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||Arrival & Registration
Basic knowledge of regression analysis and the most common estimation techniques (OLS and Maximum Likelihood)
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, lunch and refreshments.
- 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. (Alternatively, we can also provide laptops for a small daily charge).
- If you need assistance in locating hotel accommodation, please notify us at the time of booking.
- 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.
The number of delegates is restricted. Please register early to guarantee your place.