BETTI GIANNI

Gianni
Betti
Professore Ordinario

Presentation

Profile of Gianni Betti: 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).

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Office hours

New office hours: Tuesday 10-12, by appointment.

Curriculum Vitae

Teaching activities

Completion accademic year: 2024/2025

Course year: 2 Second cycle degree (Laurea Magistrale) METODI STATISTICI E DATA ANALYTICS A.Y. 2023/2024
Course year: 3 First cycle degree (DM 270) ECONOMICS AND BUSINESS A.Y. 2022/2023

Completion accademic year: 2023/2024

Course year: 2 Second cycle degree (Laurea Magistrale) STATISTICS FOR SAMPLE SURVEYS A.Y. 2022/2023
Course year: 3 First cycle degree (DM 270) ECONOMICS AND BUSINESS A.Y. 2021/2022
Course year: 1 Second cycle degree (Laurea Magistrale) ECONOMICS AND MANAGEMENT OF FINANCIAL INSTITUTIONS A.Y. 2023/2024

Completion accademic year: 2022/2023

Course year: 2 Second cycle degree (Laurea Magistrale) STATISTICS FOR SAMPLE SURVEYS A.Y. 2021/2022
Course year: 3 First cycle degree (DM 270) ECONOMICS AND BUSINESS A.Y. 2020/2021
Course year: 1 Second cycle degree (Laurea Magistrale) ECONOMICS AND MANAGEMENT OF FINANCIAL INSTITUTIONS A.Y. 2022/2023

Completion accademic year: 2021/2022

Course year: 2 Second cycle degree (Laurea Magistrale) STATISTICS FOR SAMPLE SURVEYS A.Y. 2020/2021
Course year: 3 First cycle degree (DM 270) ECONOMICS AND BUSINESS A.Y. 2019/2020

Research

Ultime pubblicazioni:

  • FLORES TAVARES, F., Betti, G. (2024). Gender Differences in Multidimensional Poverty in Brazil: A Fuzzy Approach. SOCIAL INDICATORS RESEARCH, 1-38 [10.1007/s11205-024-03312-z]. - view more
  • Betti, G., Evangelista, D., Gagliardi, F., Giordano, E., Riccaboni, A. (2024). Towards Integrating Information Systems of Statistical Indicators on Traceability, Quality and Safety of Italian Agrifood Systems for Citizens, Institutions and Policy-Makers. SUSTAINABILITY, 16(15) [10.3390/su16156330]. - view more
  • Betti, G., D’Agostino, A., Lemmi, A., Neri, L. (2023). The Fuzzy Approach to Poverty Measurement. In J. Silber (a cura di), Research Handbook on Measuring Poverty and Deprivation (pp. 489-500). Cheltenham : Edward Elgar Publishing. - view more
  • Handastya, N., Betti, G. (2023). The ‘Double Fuzzy Set’ Approach to Multidimensional Poverty Measurement: With a Focus on the Health Dimension. SOCIAL INDICATORS RESEARCH, 166(1), 201-217 [10.1007/s11205-023-03065-1]. - view more
  • Betti, G., Molini, V., Pavelesku, D. (2023). Using poverty maps to improve the design of household surveys: the evidence from Tunisia. STATISTICAL METHODS & APPLICATIONS, 1-17 [10.1007/s10260-023-00703-3]. - view more