The retirement of old workers increased during the COVID-19 pandemic, and health concerns are considered to be a critical factor. To understand the effect of pure health concerns during the pandemic, we analyze the impact of the aggregate health shock on retirement decisions using a life cycle model. The aggregate health shock changes the economy from the normal state to the pandemic state, where the probability of adverse idiosyncratic health shock increases, especially if agents are working. Simulation results suggest that the shock accelerates the retirement of agents aged over 60. The increase in retirement is significant even though the shock is expected to be temporary. Also, the effect hinges on the assumption that working poses a greater risk of receiving a negative health shock than retiring. Even accounting for the large income and wealth changes that US households experienced in 2020, a counterfactual experiment suggests that the aggregate health shock plays a prominent role in increasing retirement.

Personal finance is a challenging topic which can benefit from a scientific approach to individual financial planning. This paper presents an individual asset liability management (iALM) model for life cycle planning which uses the methodology of dynamic stochastic optimisation and incorporates ideas from both classical and behavioural finance. Its implementation is in the form of a decision support tool for use by financial advisers or wealth managers. The investment universe is given by a set of indices for major asset classes and their returns are simulated forward over the lifetime of a household. On the liability side the foreseen cash flows of incomes and outgoings are simulated and punctuated by life events such as illness and death. The household's utility function is constructed for each time period over a range of monetary values in terms of household financial goals and preferences. Taxes and pension savings are treated using the tax shielded saving accounts specific to a national jurisdiction in terms of constraints in the optimisation sub-models. The paper goes on to present an analysis of iALM model recommendations for a representative UK household, together with an evaluation of the sensitivity of the financial plan generated to changes in market environments such as the 2007–9 crisis. The promise of this new technology is to bring modern decision support tools to individual investors in order to facilitate custom designed consumption, savings and investment policies.