Modelling Non-stationarity Data in EViews

Modelling Non-stationarity Data in EViews

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190,00 €
Pagamento seguro e garantido
–
1 Day
Online
EViews

Overview

This one-day course provides an in-depth exploration of advanced time series modelling techniques for non-stationary data using EViews. Designed for analysts, researchers, and professionals working with economic and financial data, the course covers essential concepts such as unit roots, cointegration, and vector error correction models (VECM). Participants will gain both theoretical insights and hands-on experience, enabling them to confidently apply these techniques in real-world scenarios.

How It Works
What You’ll Learn

Understanding Non-Stationarity and Unit Roots
  • The importance of stationarity in time series analysis.
  • Detecting unit roots using the Dickey-Fuller test in EViews.
Cointegration and Long-Run Relationships
  • The concept of cointegration and its significance in modeling economic relationships.
  • Implementing the Engle-Granger two-step method in EViews.
Multivariate Cointegration and the VECM
  • Johansen’s test for identifying cointegration in multivariate time series.
  • Introduction to the Vector Error Correction Model (VECM) and its applications.
Practical Hands-On Session
  • Applying VECM techniques to real-world datasets using EViews.
  • Interpreting results and making data-driven decisions.
Why This Course?

By the end of the course, participants will have a solid foundation in modelling non-stationary variables, equipping them with the skills needed to analyze complex time series data effectively.

Course Highlights
  • Comprehensive Coverage: From fundamental concepts to advanced dynamic models.
  • Practical Learning: Real-world case studies and hands-on exercises with Stata.
  • Expert Insights: Gain clarity on complex topics like endogeneity and serial correlation.
  • Interactive Format: Live Q&A sessions to address individual questions and challenges.
Who Should Attend?

By the end of the course, participants will have a solid foundation in modelling non-stationary variables, equipping them with the skills needed to analyze complex time series data effectively.

Agenda

Non-Stationarity I - Unit Roots

Introduction to Stationarity and Unit Roots:
  • Fundamentals of stationarity and its importance in time series analysis. 
  • Definition and significance of unit roots. 
  • The Dickey-Fuller test for detecting unit roots in time series data. 
  • Session 2: Non-Stationarity II - Cointegration 
Introduction to Cointegration:
  • Preliminary theory on cointegration and its relevance. 
  • Engle-Granger analysis: Understanding and implementing in EViews. 
  • Session 3: Multivariate Cointegration I - The VECM 
Cointegrated VARs in EViews:
  • Johansen’s test for cointegration in multivariate time series. 
  • Introduction to the (Vector) Error Correction Model (VECM). 
  • Estimating and interpreting a VECM in EViews. 
  • Session 4: Multivariate Cointegration II - The VECM 
Practical Session:
  • Hands-on application of VECM concepts learned in the previous session. 
  • Utilizing EViews for practical exercises and real-world scenarios. 
Day 2:

Session 1
  • Comparing estimators for static panel models for your research question 
  • Testing for serial correlation
Session 2: Dynamic Panel Models
  • The Arello Bond estimator and post-estimation diagnostic test 
  • The Blundell Bond estimator and post estimation diagnostic tests
  • Case study: the determinants of bank risk-taking in European banks.

Prerequisites

Previous knowledge of regression analysis is highly desirable; some knowledge of models for stationary time series (chiefly, ARMA models) would also be beneficial.

Terms

  • 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.
  • Temporary, time limited licences for the software(s)  used in the course will be provided. You are required to install the software provided prior to the start of the course.
  • Payment of course fees required prior to the course start date.
  • Registration closes 1-calendar day 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 attendees is restricted. Please register early to guarantee your place.

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