Florence, Italy

Analysing Micro Data in Stata

TStat’s AnalysiNG Micro Data in Stata Summer School offers participants a comprehensive introduction to the principle methodologies used in the analysis of micro data. Micro data contains information at the level of a specific unit (such as individuals, firms or entities), by its very nature micro data has become an increasingly important source of information offering researchers and policy makers an effective tool with which to obtain a more in-depth understanding of an array of political, socio-economic and Public Health phenomena. The collection and subsequent analysis of micro data has over recent years therefore proved to be the key to policy formulation, the targeting of interventions and the subsequent monitoring and measurement of the impact of such interventions and policies.

Although micro data analysis techniques were originally developed and applied in the field of economics, the increasing availability of micro data has resulted in a steady increase in the analysis of such data by researchers working in Political and Social Sciences, Biostatistics, Education, Epidemiology and Public Health.

Throughout the course of the Summer School, the course leaders will focus, from both a theoretical and applied point of view, on the principal methodologies implemented for the analysis of both cross-section and panel data: linear models, count models, binary dependent variable models, multinomial models, Tobit and Interval Regression models, models with Sample Selection, and estimation of Extended Regression Models (ERM), which implement Maximum Likelihood estimators capable of simultaneously treating issues of Sample Selection and the presence of both endogenous regressors and treatment variables.

The school opens with an optional introductory one day course (Module A) to the statistical package Stata, during which participants will be provided with the necessary tools to enable them to use Stata independently and actively participate in the applied empirical Lab sessions during the course of the week.

In common with TStat’s training philosophy, the summer school is composed of both a theoretical component (in which the techniques and underlying principles behind them are explained), and an applied (hands-on) segment, during which participants have the opportunity to implement the techniques using real data under the watchful eye of the course tutor. Theoretical sessions are reinforced by case study examples, in which the course tutor discusses and highlights potential pitfalls and the advantages of individual techniques. The intuition behind the choice and implementation of a specific technique is of the utmost importance. In this manner, the course leader is able to bridge the “often difficult” gap between abstract theoretical methodologies, and the practical issues one encounters when dealing with real data. Special attention is also given to the interpretation and presentation of results.

At the end of the course, participants are expected to be able, with the aid of the Stata routines implemented during the sessions, to independently implement the methodologies and techniques acquired during the course by adopting the Stata routines to their own particular research needs.

Course leader

Dr. Una-Louise BELL, TStat Training | TStat S.r.l.
Dr. Giovanni BRUNO, Bocconi University, Milan

Target group

The Summer School program has been particularly developed for both doctoral students and young researchers working in biostatistics, business, economics, epidemiology, finance, public health, psychology, social and political sciences needing to acquire the necessary toolset to independently conduct empirical analysis using micro data, but who may not have access to a specific micro data analysis course in their home institution. It is however, also particularly useful to professionals working in one of these fields needing to either refresh their existing micro data skills or acquire new ones.

Course aim

Throughout the course of the Summer School, the course leaders will focus, from both a theoretical and applied point of view, on the principal methodologies implemented for the analysis of both cross-section and panel data: linear models, count models, binary dependent variable models, multinomial models, Tobit and Interval Regression models, models with Sample Selection, and estimation of Extended Regression Models (ERM), which implement Maximum Likelihood estimators capable of simultaneously treating issues of Sample Selection and the presence of both endogenous regressors and treatment variables.

Fee info

EUR 1890: ENTIRE WEEK (MODULES A plus B, 7 days)
Full-Time Students*: € 1890.00
Ph.D. Students: € 2770.00
Academic: € 3080.00
Commercial: € 4550.00

MODULE B (6 days)
Full-Time Students*: € 1620.00
Ph.D. Students: € 2380.00
Academic: € 2640.00
Commercial: € 3900.00

**To be eligible for full-time student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters, access to our student registration rates. Part-time master and doctoral students on the other hand, who are also currently employed will however, be assigned the standard academic registration fee. Residential costs for full-time students are completely covered TStat Training through our Investing in Young Researchers Programme. Participation is however restricted to a maximum of 3 students.

Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number.

Please note that a non-refundable deposit of €100.00 for full-time students and €250.00 for Academic and Commercial participants, is required to secure a place and is payable upon registration. The number of participants is limited to 15. Places will be allocated on a first come, first serve basis.

Course fees cover: i) teaching materials (copies of lecture slides, databases and Stata routines used during the summer school; ii) a temporary licence of Stata valid for 30 days from the day before the beginning of the school; iii) half board accommodation (breakfast, lunch and coffee breaks) in a single room at the CISL Studium Centre or equivalent (7 nights for entire school, 6 nights for Modules B). Participants requiring accommodation the night of the final day of the school, are requested to contact us as soon as possible.

To maximize the usefulness of this summer school, we strongly recommend that participants bring their own laptops with them, to enable them to actively participate in the empirical sessions.

Individuals interested in attending this summer school must return their completed registration forms by email (training@tstat.eu) to TStat by the 18th August 2022.