In the first part of the project, I started implementing the data preparation of the SHARE data to build the panel dataset and the retrospective data, I also include the EUROSTAT data and the NUTS level information in the dataset, to map the availability of healthcare supply. At the same time, I explore the existing literature and the econometric methods to be developed in the project. This part took place between September 2022 to January 2023.
I exploit several sections of the SHARE survey in order to build the dataset for the empirical analysis. SHARE is the largest pan-European social science panel study providing internationally comparable longitudinal micro data. The data are available at different level of investigation: current waves where individuals are interviewed about their current situation and the retrospective life. The information were merged with EUROSTAT data from which information about the healthcare supply is collected at NUTS2 level.
Data preparation was organized in several step: merging of the current waves of share, merging of the retrospective analysis including the working career history and the childhood health and housing information, merging of the information of SHARE at NUTS2 level, finally merging of the EUROSTAT data information on healthcare supply at NUTS2 level. The EUROSTAT data have been merged together with the SHARE data at NUTS2 level. As a following steps, I proceed with data cleaning, variable selection and measure construction. As a result, the datasets are prepared and stored in PSE server for proper use for research. They cannot be publicly shared due to the SHARE user agreement condition, but the raw data are publicly accessible from the SHARE website (upon signature of the agreement). The codes to prepare the data are ready and will be available when the papers are published.
Furthermore, I include an additional source of data coming from the European Values Study, which incorporates information about gender norms and have been used for the second part of the project. This information is very detailed and asked multiple questions on the role of women in the society. For example, it asks whether women are suited for a working careers, or if men can be good fathers, if both men and women should work, and more. It aimed at capturing how the role of women is perceived in the family and work context. This data preparation was then used for the second part of the project when working on gender health inequalities.
I proceed by working on health inequalities and setting up an econometric analysis. The work focused on health inequalities across the life course using the SHARE data and combining current and retrospective information.
This part includes a descriptive and econometric analysis of the determinants of health inequalities using a panel data perspective. The innovation of this project is the methodology that has been implemented using the cutting-edge econometric literature on event study. The analysis has aimed at identifying the main causes of health inequalities from childhood and how these affects later life outcome. The econometric method was a difference in difference method with treatment at different timing, since individuals could have had health shocks at different points in time during childhood. The results of the analysis have found that infection diseases are among the most impactful events during childhood that can affects health and late life outcomes. The working paper is under preparation and will be publicly available by the end of November 2024.
In the second part of the project, from September 2023 to June 2024 I work on the gender health inequalities project and set up descriptive and econometric analysis to understand the role of social norms on the gender health gap. I have prepared the paper for gender health inequalities in Europe to inform policy makers and scholars in the field. This section aimed at addressing how gender health disparities originates and the role of healthcare utilization. Originally, this section wanted to exploit the vignettes (method used in sociology, psychology and experiment economics), which are present in the SHARE dataset in wave 3. However, a more innovative information has been used by exploiting the European Value Study survey, such as the gender norms measures. As anticipated, this survey contains information about norms towards women and men in the society in Europe. The analysis has focused on the role of gender norms in different domains and their effect on the men and women health. This part of the project was targeted on the gender dimension and it was among the first study in the field of health economics that looked at the role of gender norms on health outcomes and healthcare.
The evidence of the analysis show that women are affected by traditional gender norms which see them as the one in charge for family and caring activities. The evidence suggest that this type of norms increased women’s depression and poor health status. This result is consistent across different specification of the gender norms as well as heterogeneous group analyses (for example at different education level or age). The results are available in the working paper entitled “How Gender Norms Shape the Health of Women and Men?”, published under the Paris School of Economics working paper series.