Investigating the social, economic and political consequences of Covid-19: A rolling cross-section approach

  • Cristiano Vezzoni Dep. Social and Political Sciences, University of Milan
  • Riccardo Ladini Department of Social and Political Sciences, University of Milan
  • Francesco Molteni Department of Social and Political Sciences, University of Milan
  • Giulia M. Dotti Sani Department of Social and Political Sciences, University of Milan
  • Ferruccio Biolcati Department of Social and Political Sciences, University of Milan
  • Antonio Chiesi Department of Social and Political Sciences, University of Milan
  • Marco Maraffi Department of Social and Political Sciences, University of Milan
  • Simona Guglielmi Department of Social and Political Sciences, University of Milan
  • Andrea Pedrazzani Department of Social and Political Sciences, University of Milan
  • Paolo Segatti Department of Social and Political Sciences, University of Milan
Keywords: survey methods, dynamic analysis, rolling cross-section, Covid-19, policy-making, research infrastructure

Abstract

In this article, we present an application of the rolling cross-section (RCS) design to monitor changes in public opinion during the COVID-19 pandemic in Italy (ResPOnsE Covid-19 project, University of Milan Statale). The RCS is a dynamic survey tool used predominantly in the analyses of public opinion during electoral campaigns. Because of its dynamic nature, we argue that it is an ideal instrument to monitor public opinion during a pandemic. Specifically, we present an RCS online survey implemented in Italy from April to July 2020 and we present some illustrative analyses of changes in behaviors, attitudes, and opinions during the Covid-19 crisis to highlight the potential of the design. Ultimately, we assert that RCS surveys could be very powerful instruments to inform policy makers of the dynamics of public opinion during a crisis, especially when inserted within existent high-quality survey infrastructures.
Published
2020-06-02
How to Cite
Vezzoni, C., Ladini, R., Molteni, F., Dotti Sani, G. M., Biolcati, F., Chiesi, A., Maraffi, M., Guglielmi, S., Pedrazzani, A., & Segatti, P. (2020). Investigating the social, economic and political consequences of Covid-19: A rolling cross-section approach. Survey Research Methods, 14(2), 187-194. https://doi.org/10.18148/srm/2020.v14i2.7745