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Lisa Crosato

Lisa Crosato

Economic Statistics

Let’s talk about you: what is your background, what do you teach, and what are your research interests?
I am Lisa Crosato and I currently teach Statistics and Data Analytics. Ever since my PhD thesis I have been mainly interested in Italian firms. My recent research focuses in particular on the prediction of SMEs default based on traditional and machine learning models applied to new versus traditional sources of data. I also work on robust models for time series analysis, inequality indexes estimation and the distribution of wages.

Tell us about your academic path.
After graduating in Mathematics from the University of Ferrara, I obtained a PhD in Quantitative Models for Economic Policy from the Università Cattolica del Sacro Cuore in Piacenza, during which I spent several months at the LSE statistics department. Since 2007 I have been working as an Assistant Professor in Economic Statistics, first at the University of Milano-Bicocca and, from November 2019, at Ca’ Foscari.

What are you most passionate about in your field of research?
What I like the most about Economic Statistics is surely the approach: it always starts with an economic issue to be tackled and answered through careful data analysis. I love the process that transforms a (sometimes huge!) mass of data into information for decision making. It’s still a wonder, to me, the way statistical models reproduce reality and the part I am really excited about is the opening gun, when a new research path shapes up.

What do studying and researching mean to you?
To me, teaching means enabling students to understand even the more complex methods while keeping in mind the ways in which they can be applied. It means that at the end of their classes, students have a toolbox to be used in subsequent studies and in the world of work. I like trying to make students understand the beauty and power of statistics, and staying beside them for some time during their studies.
As for research, it is made of exploration, intuition and perseverance. It requires asking (or collecting) the right questions and providing scientifically grounded answers. It involves discovering and revealing, and finally adding your contribution to the existing knowledge.

Can you offer any advice to researchers in the early stages of their career?
Young people who are passionate about research should really try to make it their job. There could be loneliness and there could be discouragement, due to high competition and delays in achieving results, but there will also be the thrill of seeing your ideas take shape and of sharing and discussing ideas with other researchers. Work hard, study around the world, and build a solid network: you will be paid for thinking.