2008 - Research Associate, Health Economics Group, University Of East Anglia, UK
2008 - MSc in Applied Economics and Data Analysis (with merit), University of Essex, UK
2007 - PhD in Economics, University of Bologna, Italy
2004 - Member of CAPP, Centre for the Analysis of Public Policies, University of Modena and Reggio Emilia, Italy
2003 - BA in Economics (cum laude), University of Modena and Reggio Emilia, Italy.

 

• Pension and Long Term Care policies
  
• Public finance and redistribution: measurement and analysis of poverty and inequality
  
• Well-being of older people in ageing societies
  
• Static and dynamic micro-simulation models
   

My current research projects are mainly along the lines of: (a) distributional effects of social policies with a particular focus on pension and LTC policies; (b) poverty measurement and analysis; (c) development of static and dynamic micro-simulation models; (d) the use of disability measures; (e) unit non-response in longitudinal studies.

My research is aimed to produce high quality analysis to inform public debate and development of long-term care and pension policy. It included work to explore current and projected future public expenditure costs of various options of reform. Reforms of social policies are likely to produce both macroeconomic and distributive effects. The first can be analyzed using macroeconomic simulation models, which examine relationships between national economic sectors and aggregates variables. The distributive effects are mainly explored by means of micro-simulation models which examine the effects of policy at the micro level, such as individuals, families or households. Given a survey which collects detailed information on the socio-economic characteristics of the micro-units, micro-simulation models allow to assess "what happen if..." we impose some changes in the tax/benefit system. This analysis can be focussed in estimating the immediate impact of policy changes (using static model) as well as in the long-run (dynamic model) where the characteristics of micro-units are projected forward through time.

The importance of disability as a social problem is only matched by the vast range of survey questions that have been developed to measure it. The measurement issue is more than a statistical curiosity because strong policy conclusions have often been drawn, on the basis of these survey measures, about important issues like the targeting of the system of public assistance for disabled people and the need for policy reform. Some of my researches are devoted to investigate whether different indicators of disability are consistent with a common set of findings relating to the targeting of disability benefits for older people, using latent factor simultaneous equation models.

Longitudinal surveys are rich sources of information to study the dynamics of socioeconomic and health outcomes allowing to isolate the effects of unobserved differences among individuals of a population of interest. However, because of a variety of reasons, survey data are often incomplete. Incomplete data may arise because of unit or item non-response depending whether the decision of a sampled person is to do not participate in the survey at all or not fully cooperated with it. These behaviours not only reduce the efficiency of the estimates through reduction in the sample size but -more importantly- may introduce bias if the mechanism that causes non-response is non-random and correlated to the phenomena of interests. I am interested in the theoretical and empirical analysis of the individuals' willingness of participating in a survey and its determinants and the potential effects of selective sample selection in modelling target efficiency of disability benefits.