Leader: Francesco Moscone (UNIVE); Other collaborator(s): Claudio LUCIFORA (UNICATT), Rosa Cocozza (UNINA)
Analyse welfare interventions over the life course, both related to the labour market and to demographic characteristics of households. Investigate the “geography of retirement” with reference to the territorial differences in services, purchasing power and amenities. Provide a full map of “contextual variables” i.e. welfare provisions and fiscal policies over the life course and over time as to relate individual trajectories with policy interventions (from education policies, to unemployment and health provisions to retirement policies).
Brief description of the activities and of the intermediate results:
Spatial regression models have further showed spatial autocorrelation in local expenditure decisions, suggesting policy interdependence among neighbouring municipalities. The role of local expenditure in welfare services for older individuals, particularly within the context of health inequalities. Specifically, the research aims to discern the extent to which municipalities' spending on social care for the elderly mirrors that of neighbouring municipalities and how these decisions either mitigate or exacerbate disparities in health service provision. The study hypothesizes various local-global shocks and explores potential mechanisms underlying the relationship between social care expenditures across neighbouring municipalities. These mechanisms include contextual effects, shared resource effects, imitation, information dissemination, and competitive dynamics among municipalities. Also: examine the influence of primary health care on hospital mortality rates. Utilizing data on hospital admissions for elderly patients with Acute Myocardial Infection in the Lombardy region, we will integrate this information with pharmaceutical prescription data sourced from their General Practitioners.
Main policy, industrial and scientific implications
Important interdependence among neighbouring municipalities. This insight offers valuable guidance for both central and local decision-makers, such as regional and municipal authorities, by revealing the factors influencing local spending levels and disparities across municipalities. Furthermore, by identifying these interconnections and understanding their formation mechanisms, we can assess whether certain municipalities or clusters thereof demonstrate heightened resilience during unforeseen shocks. Important role of General Practitioner prescriptions in mitigating hospital mortality rates among the elderly population.
Through an in-depth examination of patient data and prescription trends, our aim is to demonstrate the significant impact of GP-prescribed medications on patient outcomes, particularly within the realm of cardiovascular diseases. These findings may to underscore the importance of proactive primary care interventions in averting adverse health events necessitating hospitalisation.
Brief description of the activities and of the intermediate results:
1. Estimates of pathways to retirement related to the health status, health hazards and to the risk of injuries. The role of co-designing to guarantee a safe environment for older workers.
2. “Aging at work” measured with physical health - type of job, hazardous and risky tasks, chronic health conditions and/or disabilities; mental health - presence of cognitive impairment, mental distress (anxiety, depression). Indexes of “work capacity” with health demands of each job.
3. Strategies for older workers transiting into retirement emphasize maintaining work-life balance. These are keys to enhance workforce retention and inform policies aimed at supporting aging workers.
4. Estimates of the role of local spending for old age and managing resource scarcity by municipalities: preliminary findings suggest that local spending may not be enough to counteract unequal ageing.
5. Estimates of gender imbalances in older age groups, which also interact with the health of female workers and the gender pension gap (see also WP5).
Brief description of the activities and of the intermediate results:
The majority of the activities undertaken after the General Meeting in May 20-22 consisted in incorporating the feedback received during the meeting. In particular, we have collected additional data on Health districts and Ambiti Territoriali Sociali and connected these data with the welfare expenditure for older individuals at the municipal level. After this we have re-estimated all the models additionally controlling for these sources of variation. We have also run robustness and sensitivity analysis related to the spatial model benchmark specification. The project is now at a writing stage given that all the main results are now being estimated.
Our results show a significant positive spatial correlation in per capita expenditure for welfare services for older individuals, concentrated across territories. Spatial regression models unveil spatial autocorrelation in local expenditure decisions, indicating policy interdependence among neighboring municipalities. Comparative analysis with classical models underestimates the impact of spatial patterns on regression coefficients, emphasising the necessity of spatial econometric techniques. Importantly these results are robust to including information at the health district level and information on the Ambiti Territoriali sociali. Finally, the results are not sensitive to different model specifications.
Main policy, industrial and scientific implications
The existence of such positive spatial correlation in per capita spending highlights some degree of policy interdependence between neighbouring municipalities. This provides insights for both central and local decision-makers (e.g. regions and municipalities), shedding light on the factors influencing local spending levels and variations between municipalities. Finally, by identifying these networks and understanding the mechanisms through which they are formed, we can ascertain whether these municipalities or cluster of municipalities show higher resilience during periods of unexpected shocks.
Brief description of the activities and of the intermediate results:
The majority of the activities undertaken since September 2024 consisted in incorporating the feedback received and harmonizing the data even further. In particular, we have further analysed data on collected on Health districts and Ambiti Territoriali Sociali. We have also run robustness and sensitivity analysis related to the spatial model benchmark specification. The project is now at a writing stage given that all the main results are now being estimated. Our results show a significant positive spatial correlation in per capita expenditure for welfare services for older individuals, concentrated across territories. Spatial regression models unveil spatial autocorrelation in local expenditure decisions, indicating policy interdependence among neighboring municipalities. Comparative analysis with classical models underestimates the impact of spatial patterns on regression coefficients, emphasising the necessity of spatial econometric techniques. Importantly these results are robust to including information at the health district level and information on the Ambiti Territoriali sociali. Finally, the results are not sensitive to different model specifications.
Main policy, industrial and scientific implications
The existence of such positive spatial correlation in per capita spending highlights some degree of policy interdependence between neighbouring municipalities. This provides insights for both central and local decision-makers (e.g. regions and municipalities), shedding light on the factors influencing local spending levels and variations between municipalities. Finally, by identifying these networks and understanding the mechanisms through which they are formed, we can ascertain whether these municipalities or cluster of municipalities show higher resilience during periods of unexpected shocks.
Dissemination Events:
Scientific Output: