Currently, all of our training courses are being held online.
All of our courses are hosted by expert certified trainers and research professionals who teach through a mix of demonstrative and practical sessions to provide high-class, practical training.
You can register for our courses online. To discuss any of our courses or specific training requirements, please call +44 (0) 20 8697 3377 .
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: Andrew C. Harvey (University of Cambridge)
Dynamic conditional score (DCS) - or Generalized Autoregressive Score (GAS) - models have developed rapidly over the last ten years and continue to be a fruitful area for research. They offer a united and comprehensive theory for a class of nonlinear time series models in which the dynamics of a changing parameter, such as location or scale, are driven by the score of the conditional distribution.Our Stata Summer school provides a very popular and flexible course framework allowing cost-effective attendance at any course separately, or the entire school. This is a great opportunity for students, academics and professionals to expand their econometrics skills and learn how they can apply econometrics and statistics from professionals pioneering research at the forefront of their specialist fields.
For the first time, we will be running our Summer school entirely online, so you can join from the comfort of your home, anywhere in the world.
Live sessions 10.00-12.00; 13.00-15.00; 15.30-17.00 including Q&A
The course follows the Panel data Analysis with Stata and aims at provide participants with a theoretical and practical understanding of advanced panel methods, i.e. non-linear panel models.
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: Prof. Lorenzo Trapani & Dr. Malvina Marchese (Cass Business School)
The 2020 EViews Summer School comprises a series of 5 1-day courses running consecutively.
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 course will be taught in Chinese (Mandarin), all masteries and handouts are written in English. It will be run online, via Zoom.
The course will provide audience with an introduction to the popular and powerful statistical and data management software Stata with a clear applied focus.
The aim of this course is to provide participants with an in-depth understanding of how a good MSc dissertation should look, and how to easily use Stata to obtain any required econometrics.
Participants will receive a free temporary Stata license, as well as a recording of the training session, that will be live for 30 days.
The course is meant for any MSc student writing their MSc dissertation, who needs guidance on the best structure, and most suitable econometric methods to apply. No previous knowledge of Stata is required.
The aim of this course is to provide participants with an in-depth understanding of how a good MSc dissertation should look, and how to easily use Eviews to obtain any required econometrics.
Participants will receive a free temporary EViews license, as well as a recording of the training session, that will be live for 30 days.
The course is meant for any MSc student writing their MSc dissertation, who needs guidance on the best structure, and most suitable econometric methods to apply. No previous knowledge of EViews is required.
Presented By: Dr. Malvina Marchese
This course is for researchers from all academic disciplines who are new to Stata. The course assumes only limited statistical knowledge and experience of using statistical software. Participants will be introduced to Stata and will be taught the statistical theory behind linear and non-linear regression methods . Practical sessions will use macro economic and finance datasets.
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: 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.
Presented by Prof. Christopher F Baum, Boston College, USA and Dr. Malvina Marchese, Cass Business School, London
This course will be delivered as an online webinar, via Zoom.
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. Mata programming techniques will illustrate how this language can be used to simplify and accelerate computations.
