New Data on Justice

New Data on Education:

Rigissa Megalokonomou

​Senior Lecturer in Economics

From 2013 onwards my team of research assistants and I have been digitising data on cases from the Supreme Court. 

​The data collection is now completed.

This data contains rich information on all court litigants and the

characteristics of the cases.

My research addresses original, causal and policy-relevant questions such as: Do students improve their performance when they know their rank? Can teachers' stereotypic behavior explain the gender inequalities in achievements or the gender occupational gaps? Do peer networks (schoolmates and neighbors) affect students' college enrollment? Does class attendance increase educational outcomes?  By how much does a €1200 bursary at the age of 18 raise wages and affect migration decisions? What is the effect of the current financial crisis on students' preferences over college majors?  To answer these questions, I use primary-collected data collected from school authorities in Greece.

Since 2011 my colleague Sofoklis Goulas and I have combined forces in collecting new and original data on Education. So far we have created two novel and unique datasets. This page describes briefly our endeavor.

(1) Data on University Entrance Exam scores, university admission and college major

 We have collected cross-sectional data on university entrance exam performance, university of admission, self-reported college major preferences and actual college major for the universe of high school graduates in Greece between 2003 and 2011.


(2) School transcript data on demographics, school performance, class attendance and class composition.

Our data follows a randomly selected sample of high school students in Greece over the last three grades of secondary education. Our data span ten cohorts between 2001 and 2011 and almost 150 schools. We have visited schools in large cities as well as in isolated islands and we are happy to have got our hands dirty in the collection of primary data.

(3) Data on students' and teachers' class allocations, students' exam schedules and teachers' daily schedules.

This data follows a randomly selected sample of high school teachers over the last three grades of secondary education for around nine cohorts. I collected teachers' daily schedule (classes and subjects allocations) and I am matching them with teachers' personal characteristics. 

(4) Data on students' university scholarships allocated by the State Scholarship Foundation (IKY)