Courses

Presented By: Laurent Ferrara (Skema Business School) & Matteo Mogliani (Banque de France)

Forecasting in a time-series framework arises numerous issues, such as the choice of the model, the variables to be used, and the appropriate testing strategy. Recently, the collection and the availability of high-dimensional data has been posing new challenges to applied economists that classic regression approaches cannot address.

This course is designed to cover the basic topics in macroeconomic forecasting as well as advanced topics in Machine Learning for time-series analysis.

Presented By: Dr. Malvina Marchese (Cass Business School, City, University of London)

This comprehensive webinar is hosted through Zoom and runs over a total of 9 hours, with 4 hours each day (2 in the morning and 2 in the afternoon) with an extra Q&A session on the second day.

Each session briefly introduces the different methodologies, discussing strengths and weaknesses with a focus on the interpretation of the results. Hands-on sessions with many practical examples and exercises to discuss the different methodologies on panel data analysis.

Presented By: Dr. Lorenzo Trapani (Cass Business School)

The course offers an intermediate/advanced level overview of stationary VARs, cointegrated VARs and the VECM, and an introduction to Structural VARs (SVARs). It is a mixture, with equivalent weights, of methodology and practice, and each session is complemented by a data example. The SVAR part is also based on discussing several examples which are commonly encountered in macroeconometrics and monetary economics.

Presented By: Dr. Vincent O’Sullivan (Lancaster University)

This comprehensive webinar is hosted through Zoom and runs over a total of 9 hours, with 4 hours each day (2 in the morning and 2 in the afternoon) with an extra Q&A session on the second day.

This course is for professionals and researchers from all academic disciplines who are new to Stata, assuming only limited statistical knowledge and experience of using statistical software.

Presented By: Dr. Malvina Marchese (Cass Business School, City, University of London)

At times of great uncertainty for financial markets, this course provides participants with an understanding of the time series methods involved in modelling and forecasting financial markets volatilities. Participants will learn how to build, estimate and assess alternative models of volatility of financial time series. Each concepts will be explained from an econometric perspective and by means of many examples and applications in Eviews or Oxmetrics

Presented By: Dr. Malvina Marchese (Cass Business School, City, University of London)

Our web-based Time Series Analysis and Forecasting with EViews course provides a complete introduction to time series modelling and forecasting with EViews. It provides a good and practical understanding of a wide range of time series models used in various fields, including macroeconomics and financial applications with a strong background in forecasting.

This course is an essential step for any more advanced courses in forecasting such as the Midas Touch or Regime Switching models in EViews.

Presented By: Fiona Wiltshier (Official NVivo Trainer)

The first of 3 modules on the Nvivo software, this session addresses basics such as creating projects, importing data, creating memos and coding.

Please note that this training will be hosted on Windows OS. If you wish to request a Mac OS demonstration, please contact us.

This session runs from 12:00-15.00 GMT.

Presented By: Dr. Giovanni Cerulli, IRCrES-CNR

This comprehensive webinar is hosted through Zoom and runs over a total of 9 hours, with 4 hours each day (2 in the morning and 2 in the afternoon) with an extra Q&A session on the second day.

This course provides participants with the essential tools, both theoretical and applied, for a proper use of instrumental variables (IV) and structural equation models (SEM) for statistical causal modelling using Stata. After attending the course, the participant will be able to master causal designs by identifying, estimating and testing both direct and indirect causal effects in the presence of unobservable endogeneity, selection bias, and measurement error.

Presented By: Fiona Wiltshier (Official NVivo Trainer)

The second of 3 modules on the Nvivo software. This session includes a Q&A from the previous session, and covers aspects such as capturing characteristics, working with surveys and social media and exploring your data through queries

Please note that this training will be hosted on Windows OS. If you wish to request a Mac OS demonstration, please contact us.

This session runs from 12:00-15.00 GMT.

Presented By: Elisabetta Pellini (Centre for Econometric Analysis, Cass Business School)

OxMetrics 8 is a family of software packages providing an integrated solution for the econometric analysis of time series, forecasting, financial econometric modelling, and statistical analysis of cross-section and panel data. OxMetrics8 consists of a front-end program called OxMetrics, and individual application modules such as Ox, CATS, PcGive, STAMP and G@RCH.

Presented By: Dr. Vincent O’Sullivan (Lancaster University)

This course is for data managers and researchers who want to learn Stata programming concepts and skills. These programming concepts and skills will enable participants to perform complex data operations such as mapping the characteristics of an observation or a group of observations to another observation or group. Participants will also be able to automate tasks to avoid repetition and to allow quick and easy implementation of changes to data and tasks. Finally, participants will be able to automate the production of high-quality tables from stored estimates.

Presented By: Dr. George Naufal (Texas A&M University)

Our web-based 'Introduction to Panel Data Analysis with Stata' course provides an overview of the most-used panel data techniques and is ideal for the beginner/intermediate-level user who wants to learn how to implement panel data estimation with Stata commands.