Agenda

Speaker:
Mattia Stival, Department of Economics, Ca' Foscari University of Venice

Abstract:
Repeated cross-sectional surveys are a valuable source of information for monitoring social phenomena, including those related to people’s well-being and health. Their main strength lies in their ability to collect large volumes of representative data over time, covering multiple aspects of people’s lives, such as health conditions, behavioral habits, and beliefs. For this reason, they offer important opportunities for social scientists. At the same time, making sense of these data is far from straightforward. Their analysis often involves several challenges: relationships among measured variables can be complex; the available data may not be sufficient to capture all the relevant dimensions of the phenomena under study; the size and complexity of the problems can easily increase; and results often need to be communicated to stakeholders with different levels of statistical literacy. In this talk, I will present a set of examples and methodological solutions to address some of these challenges, using data from the Italian behavioral risk factor surveillance system, PASSI. In particular, I will discuss applications related to health, the environment, and the communication of statistical results, showing how repeated cross-sectional data can be used to better understand social change, while also highlighting their analytical limitations and suggesting directions for future research.

Bio sketch:
Mattia Stival is RTD-A in Social Statistics. His research interests primarily involve the development of statistical models for the analysis of complex data, with a particular focus on time series data and Bayesian methods for social and environmental sciences.