Courses

Presented By: Dr. Giovanni Cerulli, IRCrES-CNR

Recent years have witnessed an unprecedented availability of information on social, economic, and health-related phenomena. Researchers, practitioners, and policymakers have nowadays access to huge datasets (the so-called “Big Data”) on people, companies and institutions, web and mobile devices, satellites, etc., at increasing speed and detail.

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

Our web-based Volatility modelling in EViews course provides a complete introduction to modelling and forecasting volatility models in EViews. It provides a sound and practical understating of the GARCH model and its more advanced extensions such as the EGARCH, the TARCH, the APARCH and the IGARCH models used in time series and financial applications with a strong background in forecasting.

This course targets researchers, practitioners and policy makers who are interested in gaining an in-depth knowledge on how to model volatility in time series' and how to use the GARCH class of models in their current or future assignments

Presented By: Dr. Giovanni Cerulli, IRCrES-CNR

This course is for professionals and researchers from all academic disciplines who wish to improve their use of Stata.

Econometric modelling for causal inference and program evaluation have witnessed a tremendous development in the last decade, with new approaches and methods addressing an expanding set of challenging problems, both in medical and the social sciences. This course covers some recent developments in causal inference and program evaluation using Stata.

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. Austin Nichols

This course is for professionals and researchers from all academic disciplines who wish to improve their use of Stata.

Participants will be introduced to Stata and causal inference using practical examples. The fundamentals of data analysis and visualization will also be taught, using appropriate Stata commands and programming techniques

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 2020 EViews Summer School comprises a series of six 1-day courses running consecutively, with theory and practical applications. All courses will teach econometrics from an applied perspective and demonstrate techniques using EViews 11 software.

The summer school will run for 6 consecutive days for four hours per day in two sessions per day: morning 10-12 GMT and afternoon 2-4pm GMT. The morning sessions will discuss theory and the afternoon sessions will offer many practical applications in EViews

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. Melvyn Weeks (University of Cambridge)

The course has been adapted to be delivered interactively and online. The course is made up of two-parts, with each part being delivered over two-consecutive days. The course covers topics at the intersection of machine learning and econometrics with a mix of theory and applications. Using Breiman’s (2001) notion of two cultures in the use of statistical modelling, we start with a review of the fundamental differences between machine learning and econometrics.

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

Time series data are nowadays collected for several phenomena in social and empirical sciences. Initially collected at year or quarter level, time series data are now used by marketing analytics, financial technology, and other fields in which data are collected at much smaller intervals (daily, hourly and even by the minute). This course focuses on the fundamental concepts required for the analysis, modelling and forecasting of time series data and provides an introduction to the theoretical foundation of time series models alongside a practical guide to the use of time series analysis techniques implemented in Stata 15. The course is based on the textbook by S. Boffelli and G. Urga (2016), Financial Econometrics Using Stata, Stata Press Publication.

Presented by Prof. Christopher F Baum, Boston College, USA and Dr. Malvina Marchese, Cass Business School, London

This course is taught in two sections. The first, is for Stata users–professionals and researchers from all academic disciplines–who would like to use Stata programming techniques to enhance the efficiency and reliability of their research. The course assumes familiarity with Stata’s command-line interface and the use of do-files and log files to produce reproducible results. The participants will learn how to use do-file programming techniques effectively, including topics such as local and global macros, r-returns and e-returns, implicit and explicit loops and debugging techniques.

The second, is for users who have completed the companion course Introduction to Stata Programming and would like to use more advanced features of the Stata and Mata programming languages. The course assumes familiarity with Stata’s command-line interface and the use of do-files and log files to produce reproducible results. The participants will learn how to implement new Stata commands with ado-files and egen functions. Mata programming techniques will illustrate how this language can be used to simplify and accelerate computations.

Presented By: Professor Andrea Carriero (Queen Mary, University of London)

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.