Courses

Our web based ARCH & GARCH modelling with Stata course provides an introduction to Stata’s ARCH/GARCH Commands.

This course provides basic concepts of data management and how to do it efficiently using Stata. We provide several examples and use learning by doing techniques. The course focuses on available Stata commands and additional resources provided by the Stata-users community.

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.

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.

Our Stata course Automatic selection of explanatory variables with Stata aims at introducing methods suitable to automatically select the relevant explanatory variables of linear regression models.

The course is ideal for beginner/intermediate level user who wants to learn how to analyse time-series data and estimate univariate time-series models. The course is based on the textbook Financial Econometrics Using Stata by S.Boffelli and G.Urga (2016), Stata Press

Choosing an appropriate sample size is a common problem and should be given due consideration in any research proposal, as an inadequate sample size invariably leads to wasted resources. This course gives a practical introduction to sample size determination in the context of some commonly used statistical hypothesis tests.

Join us for our fifth annual Stata Winter School, comprising four individual Stata courses providing attendees with the flexibility to register only for the courses that they find most relevant to their research interests. The individual courses will cover: Data Management, Data Visualisation, Panel Data analysis.

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 form row, 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 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.

Join us for our sixth annual Stata Econometrics Winter School taking place in Oporto, Portugal. The school is organised in partnership FEP and CEF.UP with comprises five individual Stata courses providing attendees with the flexibility to register only for the courses that they find most relevant to their research interests.

The individual courses will cover: Introduction to Stata; Data Analysis, Linear Panel Data Models, High-dimensional fixed-effects & Managing Output Files and an Introduction to Programming in Stata, delivered by Prof. Kit Baum (Boston College).

Stata programming 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