Seminars and Courses

Although IHS EViews provides its own EViews training options, the following EViews related products and services may be of interest to members of the EViews community. Note that the descriptions and links for third–party products, semiars and courses are strictly informative and provided by the third–party service provider. This is not an endorsement by IHS EViews.

Timberlake Consultants 

Real-World Applications of MIDAS Models and Data Aggregation
21st March 2024 (1 day online, London time)
London, UK

The Course

This course offers a comprehensive discussion of advanced time series models in EViews and their applications to a wide range of fields including: financial econometrics and macro econometrics. The course offers both a theoretical discussion of the models and many practical applications to time series data.

Real World Applications

Participants will gain practical expertise in using MIDAS models and data aggregation techniques for forecasting and nowcasting economic variables at varying frequencies. The course emphasises real-world applications, illustrating how these tools can be applied to enhance decision-making in economic forecasting, making it highly relevant for professionals in finance, economics, and data analytics.

Who is this for

This course is tailored for applied econometricians, financial analysts, and professionals in data-driven fields seeking advanced skills in handling and analysing data at different frequencies. It is ideal for individuals aiming to elevate their forecasting and nowcasting capabilities, particularly those involved in economic research, financial modelling, and policy analysis.

Instructor: Prof. Alain Hecq, Maastrict University

For further details visit http://www.timberlake.co.uk or e-mail training@timberlake.co.uk


EViews Basics
8th April 2024 (1 day online, London time)
London, UK

This course is part one of a five-part EViews training series running throughout 2024.

Other courses in the series below:

  • Course 2: Atheoretical Models in EViews
  • Course 3: Models for Non-Stationarity Variables in EViews
  • Course 4: Volatility Models and Panel Data Models
  • Course 5: Models for Panel Data

This course offers a foundational exploration of EViews, a leading econometric software. Participants learn key concepts like "workfile" and "object," progressing to data handling, programming, and regression modeling. The focus is on the Classical Linear Regression Model (CLRM), covering assumptions, OLS estimation, and misspecification analysis with diagnostic tests and the General-to-Specific (GETS) approach. Practical exercises and a final project ensure participants gain hands-on proficiency in using EViews for data analysis and modeling, setting the stage for more advanced applications

Instructor: Professor Lorenzo Trapani (University of Leicester)

For further details visit http://www.timberlake.co.uk or e–mail training@timberlake.co.uk


Atheoretical Models in EViews
22nd April 2024 (1 day online, London time)
London, UK

This course is part one of a five-part EViews training series running throughout 2024.

Other courses in the series below:

  • Course 1: EViews Basics
  • Course 3: Models for Non-Stationarity Variables in EViews
  • Course 4: Volatility Models and Panel Data Models
  • Course 5: Models for Panel Data

This course focuses on advanced time series analysis using EViews, emphasizing ARMA and VAR models. Participants delve into ARMA model intricacies, stationarity, and unit root testing. Practical aspects include univariate forecasting with ARMA and stationary VAR models. Through hands-on exercises and real-world case studies, participants gain practical skills, preparing them to apply atheoretical models effectively in time series analysis and forecasting using EViews.

Instructor: Professor Lorenzo Trapani (University of Leicester)

For further details visit http://www.timberlake.co.uk or e–mail training@timberlake.co.uk


ARDL models with EViews:
Application to Bank Stress Test Models
9th May 2024 – 10th May 2024 (2 days online, London time)
London, UK

Course Overview

The objective of the course is to learn how to model an ARDL and to understand the advantages of this model for the implementation of forecasting models.

At the end of the course, participants will be able to implement cointegration tests in the framework of ARDL models by respecting a rigorous specification approach, to derive an ECM representation of an ARDL, to interpret it economically, and to build forecasts using an ARDL model.

They will also implement the full specification and validation tests of the ARDL model forecasts available in Eviews.

Course Context

The ARDL (Auto-Regressive Distributed Lag) models were introduced by Pesaran and Shin (1998) and Pesaran, Shin and Smith (2001). ARDL are dynamic time series models that are particularly well suited to projection exercises and banking stress tests. These models have several advantages when it comes to build a forecasting model for a microeconomic series (loss rate, default rate of a credit portfolio, etc.) using macroeconomic series aggregated at the national or sectoral level.

Instructor: Prof. Christophe Hurlin

For further details visit http://www.timberlake.co.uk or e-mail training@timberlake.co.uk



Cambridge Econometrics

Introductory Econometrics
Dates on demand

Designed for people with a basic knowledge of statistics but probably very little econometrics, and introduces topics in both time series and microeconometrics. Includes: introduction to economic modelling; introduction to statistical concepts and data analysis; OLS properties, assumptions and violations; applied micro and time series examples.

Instructor: Ben Gardiner .

For further details email bg@camecon.com

Microeconometrics
Dates on demand

Aimed at intermediate level (some background knowledge / previous econometrics training). Includes: data analysis techniques; policy analysis; dealing with endogeneity; limited / censored dependent variables; introduction to panel techniques.

Instructor: Ben Gardiner.

For further details email bg@camecon.com

Time Series Econometrics
Dates on demand

Aimed at intermediate level (some background knowledge / previous econometrics training). Includes: data analysis techniques; univariate modelling; structural modelling; single-equation cointegration; multiple-equation cointegration.

Instructor: Ben Gardiner.

For further details email bg@camecon.com

Panel Data Econometrics
Dates on demand

Combines elements from both Microeconometrics and Time Series Econometrics to cover a more advanced set of topics, finishing up by looking at leading-edge developments in the field. Includes: panel data analysis; Unobserved effects panel data estimation; dynamic panel estimation; time series panel estimation.

Instructor: Ben Gardiner.

For further details email bg@camecon.com