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We compare the intergovernmental health system responses to the first wave of the COVID-19 pandemic in Italy and Spain, two countries where healthcare is managed at the regional level and the impact of the first wave was highly localized. However, whereas in Italy the regional government allowed for a passively accepted central level of coordination without restricting autonomy (“descentralised coordinantion”), in Spain, the healthcare system was de facto centralized under a “single command” (“hierarchical centralization”). We argue that the latter strategy crowded out incentives for information sharing, experimentation and regional participation in decision-making. This article documents evidence of important differences in health outcomes (infected cases and deaths) and outputs (regular and emergency hospital admissions) between the two countries, both at the national and regional levels. We then discuss several potential mechanisms to account for these differences. We find that given the strong localized impact of the pandemic, allowing more autonomy in Italy (compared to centralized governance in Spain) can explain some cross-country differences in outcomes and outputs.

We compare health system responses to the first wave of COVID-19 pandemic in Italy and Spain. In both countries, healthcare is managed at the regional level, but the central government behaved differently in the uncertainty surrounding the first wave, leaving more autonomy to regional governments in Italy than in Spain. Upon documenting national and regional health system responses, we show evidence of a significant gap in the number of infected cases, alongside regular and emergency hospital admissions, and mortality in the two countries, both at the national and at the regional level. We then discuss several potential mechanisms, such as policy stringency, the localization of the pandemic and mobility restrictions, measurement error, and especially the regional autonomy, enjoyed by Italian regions but not by Spanish regional governments amidst a state of alarm in both countries. We find that, given the strong localized effect of the pandemic, allowing more autonomy, and fostering experimentation and local solutions explains the gap between Italy and Spain in the first wave of the pandemic.

Does removing the constraints of time and place of work increase the utility of workers and firms? We design a randomized experiment on a sample of workers in a large Italian company: workers are randomly divided into a treated group that engages in flexible space and time job (which we call "smart-working") one day per week for 9 months and a control group that continues to work traditionally. By comparing the treated and control workers, we find causal evidence that the flexibility of smart-working increases the productivity of workers and improves their well-being and work-life balance. We also observe that the effects are stronger for women and that there are no significant spillover effects within workers of a team.

We explore the role of financial and pension information in increasing women's knowledge and awareness of their future pension status, and consequently, in reducing the gender pension gap. A representative sample of 1249 Italian working women were interviewed to assess their knowledge about pensions and financial issues and about their own savings and personal wealth planned for retirement. The responses showed that their knowledge and awareness of retirement planning was limited. We then ran a randomized experiment to evaluate the effect of increased information regarding pensions on women's awareness, knowledge, and behaviors. Women in the treated group were provided information in the form of three short online tutorials. A follow-up survey shows that these women became more interested and aware of pension schemes and retirement options after completing the tutorials and were more likely to be better informed and keen to obtain further information. When looking at changes in behavior, we find that treated women who are closer to retirement are more likely to believe that they would make different work-life decisions if they received specific pension information in a timely fashion. They are also more likely to have a supplementary pension fund if they are concerned about their standard of living after retirement.

The concept of a joint approach in regard to Multilevel Models and Stochastic Frontiers developed in light of the increasing levels of interest in costs related to health care services, including hospitals, over the last few years. At the same time, both consumers and policy makers prioritize the quality of these services, and a holistic approach is required to identify areas for improvement in this regard. Quality in healthcare services means the ability to meet specific requirements, and it is the result of scientific, technical and technological, organizational, procedural and relational factors , where the human variable plays a primary role, interacting closely in the production process . In the present day many industrialized countries have healthcare systems which designate resources to hospitals according to predefined tariffs for each pathology. For example, the Lombardy Region in Northern Italy establishes an annual tariff for Diagnostic Related Groups (DRG). Therefore, the structure of the public health system depends on national and regional political decisions, but it becomes self-governing from an operational point of view. Accordingly, hospitals can be compared to firms, thus admitting functional models in an entrepreneurial way and introducing competition between the various healthcare structures. Hospitals try to devise an organizational model which allows the reduction of costs by optimizing the use of available resources, while simultaneously increasing patient satisfaction by providing optimal medical assistance. Healthcare is currently following this trend and in many countries it is based on a mixed welfare system made of private profit-oriented agents, private non-profit companies and public hospitals. The purpose of this work is to create decisional models similar to those used in financial planning, with a large number of variables, with the aim of estimating the risks involved in some enterprises, and devising accordingly appropriate allocations of funds. This study is on the basis of the following structure: the first chapter is dedicated to the multilevel model. The multilevel model is contextualized in the measure of the health care, so the first aspect considered is the adjustment of data according to patient-specific and hospital-specific variables. The second chapter is dedicated to the stochastic frontier, and is a theoretic description of this model with a different possible application. The interesting aspect is the possibility of seeing the hospital in terms of distance from its frontier of optimality. In this way we take the economic aspects of the structure into account, and we can see its effectiveness in terms of efficiency. It is clear that inside the frontier there is no consideration for the hierarchical structure of the data, but is important to not neglect the real structure of data (as we have explained in the previous chapter). This is an evident reason that allow us to consider both the models together, with all the strength stressed, and all the weaknesses overcome. Chapter number three is about the characterization of data, while chapter four comprises a description of the model that we have applied to the data. We have here proposed a section with possible future developments that we have elaborated during this work. Finally chapter five is about the results we obtained through the analysis. The conclusion section contains some considerations we have made in light of the whole work.