Courses

Presented By: Dr. Malvina Marchese (CASS Business School, 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 April 3rd.

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. 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 (Associate Professor, University of Cambridge)

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.

The course is designed to provide both the tools to undertake projects using machine learning (ml) but critically ensure that participants understand and can explain how the methods work. This is imperative since without this understanding it will not be able to communicate how these methods work.

Presented By: 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: 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 (Public Policy Research Institute (PPRI), 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. The course is ideal for beginner/intermediate level user who wants to learn how implement panel data estimation with Stata commands. The course will be very practical, employing plenty of examples and a constant stream of challenging exercises. Participants leave with the know-how and courage to independently perform their own panel data analysis.

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 data managers and researchers who wish to learn Stata programming concepts and skills.

Presented By: 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 George Naufal (Public Policy Research Institute (PPRI), 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: Professor Christopher F. Baum

Stata Programming Workshop is an opportunity for graduate students, academics, researchers and professionals to expand their knowledge of Stata. This 3-day course introduces programming skills to those who have never written a program in Stata.

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: Pierre Hoonhout (School of Economics and Management, University of Lisbon)

The Summer School aims to provide the full set of tools and techniques that any modern applied economist needs to know, and how to apply them using Stata. The Summer School is suitable for Academic Staff, Masters/PhD students and professionals that need to analyse data. The course will be taught in English.