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 

Regression analysis with EViews
Online Course – UK Time
Half day (20th May 2019 – 20th May 2019)
From 13.00 – 17.00 (UK Time)

Our web based Regression Analysis with EViews course provides a complete and comprehensive discussion of linear and non–linear, simple and multiple, regression models with EViews. Regression modelling is the building block of any econometric and statistical research and as such, it is of extreme importance. The course is ideal for participants who wish to obtain a deep yet practical understanding of such powerful tool and apply it to empirical questions arising from economics, finance, health economics, and social science in general.

Instructor: Dr Malvina Marchese, Cass Business School

For further details visit or e-mail

Vector Autoregression (VAR) Using EViews (Dubai)
2 days (22nd May 2019 – 23rd May 2019)
Sofitel, Downtown Dubai

This two–day course covers essential VAR estimation and analysis using EViews.

Day 1 introduces how to model and test for the presence of various time series properties (trend, seasonality, volatility, and correlation) using single–equation methods. Also discussed is how and why we should differentiate between deterministic and stochastic properties. Unit root tests and selected approaches to modelling variability are presented and compared. The course also looks at model and lag selection criteria, and adjusts the interpretation of the estimated coefficients to the presence of lagged variables.

In Day 2, both the restricted and unrestricted VAR models are intuitively explained, along with an introduction to post–estimation techniques such as impulse response and variance decomposition. Subsequently, residual–based and Johansen methods of detecting co–integration are discussed. The last part of the course addresses the short run dynamics in the presence of co–integration as well as VAR forecasting techniques. The topics are presented intuitively without theoretical derivations, and are demonstrated using real data.

Instructor: Dr. Samer Kherfi (American University of Sharjah)

For further details visit or e–mail

Financial Time series analysis with EViews
Online Course – EST Time
Half day (28th May 2019 – 28th May 2019)
From 10.00am – 2.00pm (EST Time)

Our web based Financial Time Series Analysis with EViews course provides a complete introduction to time series modelling and forecasting with EViews. It provides a good and practical understating of the best performing univariate and multivariate time series models used in financial applications and strong background in forecasting.

Instructor: Dr Malvina Marchese, Cass Business School

For further details visit or e–mail

EViews Summer School, London
5 days (3rd June 2019 – 7th June 2019)
Cass Business School

The 2019 EViews Summer School comprises a series of five 1–day courses running consecutively from 3–7 June 2019. The courses are to be delivered by Prof. Lorenzo Trapani of the University of Nottingham.

All courses will teach econometrics from an applied perspective and demonstrate techniques using EViews 11 software.

The Summer School comprises the following courses:

  • Course 1: EViews Basics
  • Course 2: Atheoretical Models in EViews
  • Course 3: Panel Data Models in EViews
  • Course 4: Volatility Modelling and Forecasting
  • Course 5: Discrete Choice Models

All courses will teach econometrics from an applied perspective and demonstrate techniques using EViews software.

Instructor: Prof. Lorenzo Trapani (University of Nottingham)

For further details visit or e–mail

EViews Programming
2 days (11th June 2019 – 12th June 2019)
New Horizons, Computer Learning Centre
New York City, USA, EST Time

EViews is a great statistical package that is used by many people for both research and teaching purposes. From EViews drop down menu one can easily run simple OLS regressions, conduct hypothesis testing, obtain misspecification tests, estimate non–linear least squares, estimate simultaneous equation models, test for unit roots and cointegration, estimate long–memory models and time varying conditional variance specifications, run VARs, VECMs and Bayesian VARS, obtain impulse responses from structural VARs and estimate mixed frequency models (MIDAS). There are efficient modules that provide estimates of a bunch of models and report the best one in terms of goodness of fit and/or information criteria. It is also possible to estimate models with hundreds of equations and to implement policy simulations and scenarios. EViews community is very large and researchers have written small packages, called Add–ins that can be directly downloaded in EViews to perform additional operations.

This being said, sometimes one would like to go further, to do something that is not implemented (yet?) in the existing EViews routines. In addition, one may wish to make life easier and to ask EViews to perform some repetitive tasks. This is where EViews Programming starts. The goal of this training course is to make life easier, namely to do things with only a small investment instead of learning a completely new language. The course shows how it is possible to remain in the user–friendly EViews environment without using external resources (e.g. using R, GAUSS), with the need to save data, to read them, to reimport output in EViews.

Instructor: Professor Alain Hecq, Maastricht University

For further details visit or e–mail

EViews Forecasting Summer School
5 days (22nd July 2019 – 26th July 2019)
Cass Business School
200 Aldersgate Street, London

The 2019 EViews Forecasting Summer School, taking place at Cass Business School, London, UK comprises a series of five 1–day courses running consecutively between 22–26 July 2019.

This is a great opportunity for students, academics and professionals to expand their forecasting skills and learn how they can apply a range of techniques. All courses will teach forecasting from an applied perspective and demonstrate techniques using EViews software.

The School comprises 5x 1–day courses providing complete flexibility to the participants to attend one, a combination of, or all five courses.

The Forecasting Summer School comprises the following courses:

  • Course 1: Introduction to EViews
  • Course 2: Forecasting with EViews Part 1
  • Course 3: Forecasting with EViews Part 2
  • Course 4: Forecasting non–stationary series
  • Course 5: State Space Modelling in EViews

Our EViews Forecasting Summer School is a dedicated series of short courses aimed at the forecasting practitioner. The courses will appeal to both new and experienced users of EViews and will provide attendees with valuable insights on forecasting (and problems encountered with forecasting) completed empirically using EViews software.

Instructor: Professor Lorenzo Trapani (Nottingham University)

For further details visit or e–mail

Business Forecasting with EViews:
A Practical Course for Business,
Economic and Financial Forecasters
2 days (25th September 2019 – 26th September 2019)
Sofitel, Downtown Dubai

The aim of this workshop is to give delegates a practical understanding of the main statistical forecasting tools that are available to support marketing, production, supply chain, and financial decision making.

Who will benefit?
A background in statistics is not necessary to enjoy the course. You will need to be comfortable working with numbers, with evidence–based thinking, and tolerant of a little algebraic notation. Methods are however explained at an intuitive level, and delegates throughout get hands–on experience using the popular and accessible professional–standard forecasting software package EVIEWS.

Why is this important?
Every rational decision depends on a forecast. It is important for decision–makers to understand what techniques are available to make the best possible forecasts.

Choice of forecasting method depends on context, and the availability of information. In business, for long established products there is often plenty of data, and reasons to believe that sales may be readily predictable, at least in the short term. In financial markets, there is an abundance of data, but reasons to believe most price changes are close to random, making forecasting a real challenge, though changes in risk – volatility – are to some extent predictable

EVIEWS gives you easy access to all the methods relevant to these situations.

And everywhere – in business, finance, politics, demographics, crime, fashion, epidemiology, meteorology – enhanced computing power and behaviours revealed through social media have propelled us into an era of “big data”, which is being mined for regularities by a new generation of algorithms.

The methods explained and implemented in this workshop provide the foundation for these more complex “predictive analytics” methods. And in many cases, these simpler models give us more reliable forecasts.

What happens in the workshop?
Every session is a mix of taught principles, explaining how each method might be applied (on average 30% of time), and practical implementation of these methods using EVIEWS (70% of your time).

Delegates are encouraged to bring along their problems and data, and time will be set aside in the final sessions to discuss how EVIEWS can help improve their forecasting processes.

Instructor: Prof. Roy Batchelor, Cass Business School

For further details visit or e–mail

Panel Data Methods and Factor Models with EViews
2 days (21st October 2019 – 22nd October 2019)
2 days (13th November 2019 – 14th November 2019)
Cass Business School, UK

This two–day course will explore two important topics in Econometrics; Panel Data estimation and the use of factor models in economic forecasting and analysis.

This course will acquaint the student with modern panel data techniques including their use for standard stationary panels, dynamic panels and the broad area of non stationary panels. By the end of the two day course the participants should be able to; understand the structure of a panel data set and know the two ways to define such data sets in EViews. Estimate fixed and random effect models and construct Hausman tests between the two formulations. Conduct standard hypothesis tests. Understand the importance of stationarity for panels and use panel stationarity test. Test cointegration for a panel.

Factor analysis allows us to concentrate the important information contained in a large number of data series into a relatively small number of artificial factors which may be used for various purposes. Factor analysis begins with the single factor model which is estimated in state space form using the Kalman filter. It progresses to the multifactor models using principal components. It then combines these two into the dynamic facto model. These techniques are becoming increasingly important as we move into a world of ‘Big’ data.

Instructor: Professor Stephen Hall, School of Business, University of Leicester

For further details visit or e–mail

Macroeconomic Density Forecasting & Nowcasting (UK)
3 days (28 October 2019 – 30th October 2019)
Cass Business School, UK

Whether you deal with forecasting at a Central Bank, public institution, bank or consultancy firm; or you use forecasting techniques in your research, this is the perfect course to bring you up to date with the latest methods in the forecasting profession. We begin softly by reviewing some classic time series methods and standard point and density forecasting tools (fan charts), but rapidly turn to the state–-of–the–art forecasting methods such as Mixed Frequency Data Sampling (MIDAS), Regime (or Markov) Switching models, and Bayesian forecasting techniques.

The focus will be more on the empirical implementation of the techniques than on their theoretical underpinnings. The techniques will be illustrated with several empirical applications, and then implemented in EViews 10. While experience in forecasting is advantageous, the course is equally suitable for professionals who have just recently began to forecast macroeconomic and financial indicators. We are flexible and the course can easily be accommodated to the level of the participants. Previous knowledge and experience in econometrics is however, essential.

This course is aimed at:

  • Economists and statisticians at Central Banks, public institutions, financial institutions, consultancy firms, or firms who deal with forecasting in their daily work.
  • Academics and research economists who use, or are interested in forecasting techniques for their research.
  • Professionals involved in rating activities.

Instructor: Dr. Andrea Carriero (Queen Mary, University of London)

For further details visit or e–mail


EViews Modelling: Complex Models
20th – 21st September 2019  
3rd – 4th July 2019  
18th – 19th September 2019  
Berlin, Germany

This two day course is an advanced training for the analysis of economic time series data. We start with a recap of basic time series analysis and dynamic models in form of linear regression and ARIMA-models.

As a generalisation of that multivariate regression models and systems of equations are discussed. Vector–-Autoregressive (VAR) and Vector–Error–Correction–Models (VEC) are part of the training as a special case of systems of equations.

Final part of the training describes ways to model volatility of time series in form of Autoregressive Conditional Heteroscedasticity–models (ARCH, GARCH).

  • AR, MA and ARIMA models
  • ARDL – Dynamic regression models
  • Systems of Equations
  • VAR – and VEC–models
  • ARCH – and GARCH–models

Requirements: Participants should have a basic understanding of hypothesis testing, regression analysis and time series analysis in general.

For further details visit or e-mail

EViews – Scripting
28th March 2019
15th August 2019
26th September 2019
Berlin, Germany

This one day course is all about the EViews scripting language. Starting with simple functions (data import, object declaration, ...) the participant becomes familiar with the typical syntax of the EViews scripting language.

The next step is to discuss the typical aspects of a programming language: loops, conditional statements, vectors and matrices. The training will cover database–access as well as graph customization and many real world examples.

  • Automatic data import
  • Overview over objects and commands
  • Loops and conditional statements
  • Database access
  • Vectors and matrices
  • Graph customization

For further details visit or e–mail

Requirements: Participants should be used to work with EViews and have a basic unterstanding of EViews workfiles and objects (e.g. series, equations). Basic programming experience is useful but not required.

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

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

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

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