New Data on Education:
New Data on Justice
Lecturer in Economics
The last two years my team of research assistants and I have been digitizing data coming from completed cases from the Supreme Courts.
This data contains information about each case's characteristics,
the judges and the plaintiffs. Soon I am going to circulate a draft
about gender interactions at the Supreme Court.
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)