Courses

Our web based GARCH & MGARCH modelling with Stata course provides an introduction to Stata’s GARCH and MGARCH commands. The course is ideal for intermediate level user who wants to learn how to model and forecast financial markets volatility via most used volatility models

The aim of this course is to provide students with the theoretical knowledge of regression analysis and with the practical skills to implement regression analysis with econometric software.

Mixed modelling is a modern and powerful data analysis tool for modelling clustered data, typically used for modelling data collected in studies where the levels of a factor are considered to be a random selection from a wider pool, or in the presence of a multi-level structure with different levels of variability.

The course will focus on medical and health related applications of mixed modelling. Specific applications include multi-centre trials and cross-over trials in addition to the analysis of repeated measurements.

This course is a primer to machine learning techniques using Stata. Stata owns today various packages to perform machine learning which are however poorly known to many Stata users. This course fills this gap by making participants familiar with (and knowledgeable of) Stata potential to draw knowledge and value from rows of large, and possibly noisy data. The teaching approach will be based on the graphical language and intuition more than on algebra. The training will make use of instructional as well as real-world examples, and will balance evenly theory and practical sessions.

This two-day course offers a comprehensive overview on panel data methods with Stata, covering linear models with exogenous and endogenous variables, dynamic linear models, and some nonlinear models.

This course is a primer to machine learning techniques using Stata. Today, various machine learning packages are available within Stata, but some of these are not known to all Stata users. This course fills this gap by making participants familiar with Stata's potential to draw knowledge and value from rows of large, and possibly noisy data. The teaching approach will be based on the graphical language and intuition more than on algebra. The sessions will make use of instructional as well as real-world examples, and will balance theory and practical sessions evenly.

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

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.

This course will cover topics at the intersection of machine learning and econometrics.

The course covers 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.

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.

This two-day course introduces participants to Panel Data analysis and will be taught the statistical theory behind these methods, and they will apply these methods to specially chosen datasets using examples from economic, social, and medical research.

The course focuses on practical programming needs arising when dealing with large datasets, multiple data sources and the programming tools which may help in routinising complex tasks and automating pieces of your work.