Cursos de Treinamento

This interactive course introduces professionals and researchers to Stata, covering data management, visualisation, and fundamental analysis techniques. Participants will learn and apply linear and logistic regression using real-world health research examples.

Discover recent developments in causal inference and program evaluation using Stata. This course equips participants with the latest econometric methods, including difference-in-differences, synthetic control methods, and dose-response models. Learn to design, implement, and interpret robust policy evaluations through hands-on practical sessions.

Join us for the 2025 Stata Summer School, a dynamic, four-day online training series designed to equip researchers, data analysts, and students with the skills to manage, visualise, and analyse data effectively using Stata. Whether you're brand new to Stata or looking to refine your statistical analysis skills, this summer school offers flexible learning opportunities tailored to your needs.

Learn to estimate linear models of any size using EViews with cutting-edge techniques like Quantile Regression, Robust Least Squares, and Elastic Net methods. Through hands-on practice, gain the skills to confidently analyse real-world data and enhance model accuracy.

Learn the fundamentals of EViews, a leading econometric software, and gain an introduction to data handling, programming, and regression modelling. This hands-on course covers Classical Linear Regression Model (CLRM) analysis, diagnostic tests, and model refinement techniques.

This course equips participants with practical skills and theoretical insights to apply modern micro-econometric methods for policy evaluation and causal modelling using Stata. Covering techniques like regression adjustment, matching, and difference-in-differences, it prepares learners to design and conduct evaluations across various fields using real-world data.

Master both the fundamentals and advanced techniques of machine learning using Stata in this flexible 4-day course. Students can choose to attend the full course or select either the Introductory (5–6 June) or Advanced (12–13 June) sessions individually. With hands-on training and expert instruction, you'll gain practical skills to extract insights from complex data using Stata's powerful machine-learning tools.

Learn how to analyse longitudinal data with Stata in this comprehensive two-day online course. Covering static and dynamic linear models, you'll explore key methodologies, interpret results, and gain hands-on experience through practical examples and exercises. By the end, you'll be equipped to prepare panel data, select appropriate models, and obtain parameter estimates with confidence.

Modelling Non-Stationary Data in EViews is a one-day advanced course on time series analysis, focusing on unit roots, cointegration, and the Vector Error Correction Model (VECM). Through hands-on sessions, participants will learn to apply key econometric techniques in EViews for real-world data analysis.

Learn how to analyse panel data using EViews in this comprehensive two-day online course. Covering both static and dynamic linear models with exogenous and endogenous variables, you'll explore core econometric techniques such as fixed effects, random effects, GMM, and GLS. The course emphasizes applied learning through hands-on sessions using real-world macro and micro datasets. By the end, you’ll be able to prepare panel datasets, test for serial correlation, select suitable models, and interpret results confidently using EViews.

Theory and Practice of Modelling Stationary Data in EViews is a one-day advanced course on time series analysis, with a focus on ARMA and VAR models. Participants will explore stationarity, unit root testing, and the practical implementation of univariate and multivariate forecasting models in EViews. From the Box-Jenkins methodology to forecasting with stationary VARs, this hands-on course equips attendees with the skills needed to model and predict macroeconomic variables—such as inflation—using atheoretical models. Ideal for analysts and researchers working with macroeconomic time series data.

Join us this July for a five-day, in-person summer school at the University of Cambridge, hosted at the scenic and modern Churchill College, led by world-renowned econometricians Professor Jeffrey Wooldridge and Dr. Melvyn Weeks.