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Vector Autoregression (VAR) Modelling using EViews

  • Duration: 3 days
  • Software: EViews
  • Level: Advanced, Intermediate
  • Delivered By: Prof. Lorenzo Trapani
  • Topic: Econometrics, Various methods
Vector Autoregression (VAR) Modelling using EViews

COURSE DATE: 9th - 11th April 2018 | 19th - 21st September 2018

Vector Autoregression (VAR) is used to capture the linear interdependencies among multiple time series.

The course will cover: stationary VARs, starting from the basics and tackling more advanced techniques such as dealing with over-parameterisation via Bayesian estimation; non stationary VARs and Johansen approach to cointegration; and structural VARs, and what can be done in EViews 9, will also be explored.

Click here to view the full course agenda.

Course Agenda

Day 1 - Stationary VARs

Session 1: Stationary VARs (Part 1)

  • VAR representation and estimation

Session 2: Stationary VARs (Part 2)

  • Testing with multivariate regression
  • Granger causality
  • Lag selection
  • Misspecification tests
  • VAR forecasting

Session 3: Bayesian VARs (Part 1)

  • Introductory notions on priors and shrinkage
  • The BVAR object in EViews

Session 4: Bayesian VARs (Part 2)

  • Further discussion of priors; exercises on stationary VARS and BVARS

Day 2 - Non-Stationary VARs

Session 1: Non-Stationary VARs (Part 1)

  • Cointegrated VARS in EViews: Johansen’s test for cointegration

Session 2: Non-Stationary VARs (Part 2)

  • The Vector (Error) Correction Model (VECM)
  • Estimating and interpreting a VECM in EViews

Session 3: Non-Stationary VARs (Part 3)

  • Granger causality analysis in cointegrated VAR
  • Forecasting

Session 4: More on the impulse response function

  • Worked examples using VARS, non-stationary VARS and BVARS

Day 3 - Structural VARs and foundations of time-varying VARs

Session 1: Structural VARs (Part 1)

  • Structural restrictions: syntax and preliminary information

Session 2: Structural VARs (Part 2)

  • Short-run restrictions: theory, obtaining response to shocks and exercises

Session 3: Structural VARs (Part 3)

  • Long-run restrictions: theory, obtaining response to shocks and exercises

Session 4: Time varying VARs

  • An introduction to the time-varying parameter model in EViews; specifying a multivariate time varying parameter model

Principal texts for pre-course reading

  • Hamilton, J.D., 1994. Time Series Analysis. Princeton University Press.

Principal texts for post-course reading

  • Pesaran, M.H., 2015. Time Series and Panel Data Econometrics. Oxford University Press.

Daily Timetable

Subject to minor changes

09:00-09:20   Registration
09:30-11:00   Session 1
11:00-11:15   Tea/coffee break
11:15-12:45   Session 2
12:45-14:00   Lunch
14:00-15:15   Session 3
15:15-15:30   Tea/coffee break
15:30-17:00   Session 4

Prerequisites

  • Econometrics knowledge - Knowledge of basic econometrics (at a minimum: time series regression, least squares estimation, mis-specification testing, univariate cointegration).
  • Software knowledge - In terms of software knowledge: basic knowledge of EViews (any version, although version 9 is preferable).

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.
  • Attendees 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.
  • 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 seats available is restricted. Please register early to guarantee your place.

  •  CommercialAcademicStudent
    April (09/04/2018 - 11/04/2018)
    September (19/09/2018 - 21/09/2018)

All prices exclude VAT or local taxes where applicable.

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