Invited Speaker---Prof. Gianni Betti


Department of Economics and Statistics, University of Siena, Italy

Biography: Gianni Betti was born on July the 21st 1970 in Siena (Italy). Graduated in Statistics and Economics at the University of Siena in 1994, obtained his PhD degree in Applied Statistics at the University of Florence in 1998. In 1998 has been Visiting Researcher at the ESRC Research Centre on Micro-social Change, University of Essex; in 1999 was Lecturer in Statistics at the Department of Statistics, London School of Economics; from 2000 to April 2005 was Permanent Researcher (Lecturer) at the Department of Quantitative Methods; from May 2005 to December 2016 was Associate Professor at the Department of Economics and Statistics; and since January 2017 is Full Professor in Economic Statistics at the Department of Economics and Statistics, University of Siena.

Research fields of interest and expertise: Personal income distribution theory and models; measures of living conditions with special reference to poverty analysis and inequality; models of economic behaviour with special to consumers’ expenditures; equivalence scales and cost of children. Statistical methods for longitudinal (panel) analyses; nonresponse, interviewer effect, panel attrition and weighting problems; sampling theory with particular reference to small areas. Statistical matching of different sources (Census, Surveys, Administrative data, etc…). Long experience in working with SILC and Household Budget Surveys, included some eastern European countries (Albania, Macedonia, Montenegro, Poland, Romania and Ukraine). Publications: about 60 published papers in journals or book chapters in economics and statistics. Scientific Societies Memberships: SIS (Società Italiana di Statistica), IASS (International Association of Survey Statistician).

Speech Title: Fuzzy Measures of Graduates’ Educational Mismatch
Abstract: In this paper we propose an innovative methodology for measuring educational mismatch by using a multidimensional and fuzzy set approach. Educational mismatch cannot be treated as a unidimensional concept because of its very complex nature; for this reason, here we propose a step-by-step procedure: first of all, we begin by identifying the items to be included in the index or indices, which should be the more meaningful and useful ones; then, for each item, we determine a quantitative mismatch indicator in the range [0,1]: such indicators are used in a first exploratory factor analysis in order to identify underlined latent “dimensions”. The empirical analysis is based on the Professional placement of graduates’ survey for year 2015, that is conducted by the Italian national statistical institute (ISTAT).