The Silver Economy.
Work, participation, and welfare at older ages

Leader: Agar​ Brugiavini, UNIVE
Co-Leader: Claudio Lucifora, UNICATT


Spoke Themes

This Spoke addresses the consequences of the demographic transition for older people, affecting the labour market, the goods and services market, and the financial markets in a new socioeconomic landscape.
It will propose solutions for a new architecture of the welfare state, including pensions, health care and long-term care, by uncovering the relevant connections between the health, the economic and the social domains over the life course. These actions aim at empowering older people ability to take decisions and improving their well-being and standards of living.
Researchers in Spoke 6 adopt an evidence-based interdisciplinary approach and impact evaluation methodologies, to ensure an effective policy design.


Spoke 6 is designed to develop life-course analysis and interventions which relate to labour market risks and opportunities and activities at older ages. Three packages (WP1, WP2 and WP3) focus on active ageing both in the labour market and in society, including the role of firms, innovation, green and digital transition, human capital, health capital and social capital. Spoke 6 maps the availability of resources in different forms (public pensions, private saving and insurance opportunities): WP4 and WP5 focus on the welfare system as well as saving, consumption patterns and insurance design. It builds on quantitative analysis of micro-level dynamic data, to design policies.


Economics, statistics, econometrics, mathematics and actuarial science, sociology, psychology, law, engineering.

Work Packages

Prof. Claudio Lucifora, UNICATT

WP1 aims to: 1) develop an evidence-based work-related map of risks and trigger points over the life course, with permanent impact on well-being in old age; 2) define KPIs of the impact of ageing on human capital, at the individual and firm level, with measures of productivity, and the impact of automation for older workers; 3) evaluate the effects of the digital and green transition on the young-old labour demands, within the firm; 4) estimate a “career tracker”, to identify the policy interventions – discussed and developed in close collaboration with Spoke 10 – necessary to make ageing at work sustainable and active.

Prof. Agar Brugiavini, UNIVE

WP2 aims to: 1) estimate pathways to retirement related to the risk of injuries and health hazards; 2) estimate the role of co-designing a safe environment and of training on the job; 3) develop a multidimensional indicator of “ageing at work” linked to type of job, hazardous and risky tasks, mental health; 4) measure objective and subjective life-work balance for older workers; 5) assess “health and safety literacy” and derive KPIs for social health; 6) simulate the impact of the digital and green transition on working patterns, also in light of an increasing demand for health-related jobs (with WP5).

Prof. Mario Paolucci, CNR

WP3 aims to: 1) identify the KPIs that foster the transmission of “know-how” between generations – especially for arts & crafts, and learn about best practices of intergenerational knowledge sharing; 2) foster the creation of new forms of entrepreneurship at older ages; 3) understand changes in preferences and attitudes of the older people for demand for goods and services; 4) identify the drivers of co-creation given new products and technological changes; 5) identify investment patterns for a silver ecology and civic engagement.

Prof. Margherita Borella, UNIVE

WP4 aims to: 1) analyse life course welfare interventions with an impact at older ages; 2) obtain a map of the “geography of retirement” in terms of services, purchasing power and amenities in relation to welfare provisions and for people most at risk of poverty or financial distress; 3) assess the degree of welfare coverage and any mismatch making use of an impact evaluation methodology; 4) learn about models of integrated welfare (including occupational pensions and firm-level health insurance) and the North/South gradient; 5) measure the “pension gap”, i.e., situations of poverty in old age due to lack of resources or lack of information and develop and “integrated model” of saving for retirement.

Prof. Emilia Di Lorenzo, UNINA

WP5 aims to: 1) estimate the impact of the pension reform process on labour supply, wealth accumulation and well-being; 2) understand the role of the public/private pension mix for an ageing workforce and the role financial literacy as a determinant of the pension gap; 3) provide a full map of the financial/insurance instruments which accompany the ageing process using a life course approach; 4) analyse – in collaboration with Spoke 9 – technical solutions in different risk-environments that satisfy the demand for protection in old age; 5) provide a complete taxonomy and regional distribution of the existing LTC provisions and provide estimates and future projections of the sustainability of a Long-Term care (LTC) system.

Key Outputs

  • Recruitment of researchers.
  • Recruitment of PhDs.
  • Access to data (Administrative archives; Survey data; Firm-level surveys; Companys' balance-sheets, "Osservatorio Anziani").
  • Identification of KPI, construction of indicators, financial literacy.
  • Working papers: state-of-the-art, literature review, modelling and empirical strategies.
  • Ageing process on productivity, between and within firms - memorandum of agreement GPTW.
  • Identification and mapping of work-related risks and trigger points in working careers - modelling of "earnings ability".
  • Identification and mapping of health-related working conditions - quality of life indicators.
  • Taxonomy and evolution of preferences for goods and services and behaviours - memorandum of agreement Oss.Salute.
  • Innovation, green and digital transition in the silver economy - model and access to data.
  • Identification and measurement of the dimensions of "unequal ageing" - indicators and data.
  • Modelling welfare systems, saving and consumption patterns - modelling a “pension gap”.
  • Modelling and measuring financial literacy - indicators and data.
  • Retirement policies, financial provision and insurance design - modelling.
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