Training Courses

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 Prof. Christopher F Baum, Boston College, USA and Dr. Malvina Marchese, Cass Business School, London

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. The participants will learn how to implement new Stata commands with ado-files and egen functions. Mata programming techniques will illustrate how this language can be used to simplify and accelerate computations.

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.

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.

Presented By: Dr. Giovanni Cerulli, IRCrES-CNR

This course is for professionals and researchers from all academic disciplines who wish to improve their use of Stata.

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.

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.