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  • When loss strikes twice: Health shocks and household financial distress

    Financial distress affects roughly one in five adults in OECD countries (OECD 2024). It constrains access to credit, impairs labour market outcomes, and makes the economy less resilient to macroeconomic shocks (Dobbie et al. 2020, Bos et al. 2018, Maturana and Nickerson 2020, Kaur et al. 2025, Mustre-del-Río et al. 2025).

    While prior studies have examined the role of individual characteristics and abilities in shaping financial distress (Parise and Peijnenburg 2019, Keys et al. 2023), less is known about how health shocks – especially fatal ones – trigger financial instability.

    To address this gap, we examine the financial consequences of a spouse’s illness or death, using data from Sweden (Majlesi et al. 2025). We use population-wide administrative data, linking detailed health and mortality records with information on all unpaid financial claims handled by the Swedish Enforcement Authority. This captures both households with and without access to formal credit markets. Because Sweden’s universal healthcare limits out-of-pocket medical costs and strategic default is rare, these records provide an unusually precise measure of genuine financial distress.

    When tragedy triggers financial strain

    We compare households that experience a severe health shock to otherwise similar households that experience the same event a few years later. This quasi-experimental design isolates the causal effect of the health shock on financial well-being.

    The results are striking. The death of a spouse raises the likelihood of default on financial claims by about 20%, with effects persisting for several years (Figure 1). Spouses exposed to a fatal health shock are nearly 1 percentage point more likely to receive a debt claim within four years – a 56% increase from baseline – showing that more individuals continue to fall into financial distress over time.

    Defaults are not driven by forgetfulness or grief: small debts are repaid promptly, while large debts (over roughly $1,000) often enter debt collection. These findings point to liquidity constraints rather than inattention as the key mechanism.

    Even among financially stable households with no prior defaults, the incidence of unpaid bills rises sharply after a spouse’s death. The shock effectively pushes many previously solvent households into financial trouble.

    Figure 1 Dynamic effects of a fatal health shock on the probability of receiving a claim from the Swedish Enforcement Authority

    Note: This figure shows the estimated effect of a fatal health shock on the probability of receiving a claim from the Swedish Enforcement Authority. Estimates are obtained using the difference-in-differences method of Callaway and Sant’Anna (2021). The figure reports coefficient estimates with 95% confidence intervals, along with the average treatment effect on the treated (ATT) and the effect in percentage terms relative to the mean one year before the event. Standard errors are clustered at the household level.

    Housing wealth as self-insurance

    Income losses following a spouse’s death are substantial: households’ disposable income falls by about 50%.  But the ability to draw on housing wealth determines who can cope. Homeowners generally avoid defaults by liquidating their homes, whereas renters face a higher risk of entering debt collection (Figure 2).

    Figure 2 Dynamic effect of a fatal health shock on the probability of entering collection for a large debt

    Note: This figure displays the dynamic treatment effects of a fatal health shock on the likelihood of facing collection for a large debt, estimated separately for renters and homeowners. Estimates are obtained using the difference-in-differences method of Callaway and Sant’Anna (2021). The figure reports coefficient estimates with 95% confidence intervals, along with the average treatment effect on the treated (ATT) and the effect in percentage terms relative to the mean one year before the event. Standard errors are clustered at the household level.

    Although the loss of a spouse can also take a toll on mental health, this does not explain the financial divide. Both homeowners and renters experience similar increases in prescriptions for antidepressants and diagnoses of mental disorders after the event. These differences are not observed when comparing households with different incomes, suggesting that wealth, rather than income alone, provides a financial buffer.

    Intergenerational echoes

    The financial repercussions extend beyond the immediate household. Adult children of survivors also experience higher financial stress, particularly when the surviving parent suffered a large income loss and lacked home equity (Figure 3). For this group, the probability of entering debt collection rises by about 10%, and reliance on social benefits increases markedly. All children reduce labour earnings following these shocks, but those with vulnerable parents are less able to cope.

    These intergenerational effects suggest that when parents cannot self-insure, financial distress cascades down family lines, either because children step in to support parents or because parental assistance dries up.

    Figure 3 The effect of a fatal health shock on adult children, by income loss and homeownership status of the surviving spouse

    Note: This figure presents estimates of the effect of a fatal health shock on adult children, by the homeownership status and income loss of the surviving parent. Panels A–D correspond to children of renters or homeowners, further distinguished by whether the deceased parent was the primary earner (smaller income loss) or the secondary earner (larger income loss). Effects on debt collection, social benefits, and labour income are estimated with 95% confidence intervals using the Callaway–Sant’Anna (2021) difference-in-differences method, controlling for 10-year age bins of the children. The reported coefficients are expressed as percentage impacts relative to the mean outcome one year prior to the event. Standard errors are clustered at the parent level.

    Beyond death: Non-fatal health shocks

    Severe but non-fatal health shocks, such as heart attacks, strokes, or injuries, also raise the risk of default, though by a smaller margin (around 9%). The mechanism differs: income losses are smaller and more temporary, and both homeowners and renters face increased risk of debt collection, unlike after fatal shocks where housing wealth provides protection.

    These findings are consistent with the idea that housing is a ‘consumption commitment’, which is costly to adjust when shocks are temporary (Chetty and Szeidl 2007).

    Policy implications

    Our findings have two key implications.

    • Housing equity acts as self-insurance, mainly for permanent shocks. Households use housing wealth to cushion permanent income losses, such as after a spouse’s death, but home equity is less protective for temporary shocks, consistent with housing as a consumption commitment. For homeowners, formal insurance is therefore more welfare-improving for short-term risks, when selling a home is too costly.
    • Survivor benefits should target the asset-poor. Increasing survivor pensions for renters could prevent long-term and intergenerational hardship by helping them better withstand permanent income losses.

    Concluding thoughts

    Health shocks expose the limits of even generous welfare systems. When one partner dies or falls ill, many families ‘lose twice’ – first emotionally, then financially. Our results underscore the need to evaluate household insurance in terms of both income and wealth access.

    As ageing populations strain public insurance systems, understanding how families self-insure – through housing, savings, and intergenerational transfers – will be central to strengthening financial resilience to life’s most severe shocks.

    References

    Bos, M, E Breza, and A Liberman (2018), “The labor market effects of credit market information”, The Review of Financial Studies 31(6): 2005–37.

    Callaway, B, and P H Sant’Anna (2021), “Difference-in-differences with multiple time periods”, Journal of Econometrics 225(2): 200–230.

    Chetty, R, and A Szeidl (2007), “Consumption commitments and risk preferences”, The Quarterly Journal of Economics 122(2): 831–77.

    Dobbie, W, P Goldsmith-Pinkham, N Mahoney, and J Song (2020), “Bad credit, no problem? Credit and labor market consequences of bad credit reports”, The Journal of Finance 75(5): 2377–419.

    Kaur, S, S Mullainathan, S Oh, and F Schilbach (2025), “Do financial concerns make workers less productive?”, Quarterly Journal of Economics 140(1): 635–89.

    Majlesi, K, E Molin, and P Roth (2025), “Severe health shocks and financial well-being”.

    Keys, B J, N Mahoney, and H Yang (2023), “What determines consumer financial distress? Place-and person-based factors”, The Review of Financial Studies 36(1): 42–69.

    Maturana, G, and J Nickerson (2020), “Real effects of workers’ financial distress: Evidence from teacher spillovers”, Journal of Financial Economics 136: 137–51.

    Mustre-del-Río, J, J M Sánchez, R Mather, and K Athreya (2025), “The effects of macroeconomic shocks: Household financial distress matters”, The Review of Financial Studies 38(2): 564–604.

    OECD (2024), How’s life? 2024: Well-being and resilience in times of crisis, OECD Publishing.

    Parise, G, and K Peijnenburg (2019), “Noncognitive abilities and financial distress: Evidence from a representative household panel”, The Review of Financial Studies 32(10): 3884–919.

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