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 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.

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.

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

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: 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: 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. 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: 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: 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: Andrew C. Harvey (University of Cambridge)