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The Italian NDC pension system - resilience to the COVID-19 and chances for an LTC coverage with ABMs

Authors: FRATONI, LORENZO;

The Italian NDC pension system - resilience to the COVID-19 and chances for an LTC coverage with ABMs

Abstract

The COVID-19 pandemic is affecting the financial sustainability and the social adequacy of public pension systems. All the countries worldwide faced severe crises, even increased by the containment measures that temporarily closed the work activities, resulting in revenue losses for enterprises and income reductions for many workers, hence lower revenues for the state’s finance. Consequently, the COVID-19 crisis is undermining the present and future retirement benefits, which evolution also depends on economic indexes currently under stress. Meanwhile, the ageing population is raising concerns to the social security systems to deal with new socioeconomic risks, like the need for Long Term Care (LTC) services for older adults, stressing health care systems. The LTC public spending is expected to rise by 1% of GDP in 30 years in Italy. Developing an integrated strategy can help reduce costs and uncertainty and increase the perception of the LTC need. This thesis has a twofold objective. Firstly, it aims to measure the impact of the COVID-19 crisis on the financial sustainability and the social adequacy of a Notional Defined Contribution (NDC) pension system. Secondly, it wants to investigate the effect of embedding an LTC benefit into an NDC pension scheme, either through a Life Care Annuity (LCA) or an Enhanced Pension Annuity (EPA). We also introduce two symmetric Automatic Balance Mechanisms (ABM) - one based on a Liquidity ratio (LR) and the other one on a Solvency ratio (SR) - which modify the notional rate and benefits indexation to restore the financial wealth of the system. The macroeconomic and demographic variables involved in evaluating the pension system, such as unemployment rate, wage growth rate, inflation rate, mortality rates and disability inception rates, are modelled in a stochastic environment. Numerical applications are performed on the Italian NDC pension system over a 75 years time horizon. The results show that the pandemic shock worsens the system’s financial sustainability in the short and medium-term, being financially resilient in the long run. However, in a stressed scenario where the unemployment rate converges more slowly to the long-run trend, a social adequacy issue may also arise in the medium term. Embedding an LTC coverage in the pension scheme would allow the system to adapt to the different needs without creating instabilities, either with an LCA or an EPA. The introduction of the ABMs results in a variability reduction for all the indicators, being the LR ABM more effective in this sense. Moreover, the LR ABM allows for higher benefit ratios in the long term and achieves intergenerational fairness in the medium and long run. However, the SR ABM is more robust since the correction on benefit indexation and the notional rate is more steady over time, leading to a financially sustainable system and generating a positive fund at the end of the projection.

Country
Italy
Related Organizations
Keywords

Pension system; NDC; COVID-19; LTC; ABM

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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