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Who is resilient in a time of crisis? The importance of financial and non‐financial resources

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  • David W. Johnston
  • Claryn S. J. Kung
  • Michael A. Shields

Abstract

Enhancing population resilience to adverse events is now a policy priority. Accordingly, there have been calls for more evidence on the determinants of resilience. We answer this call by identifying financial and non‐financial resources associated with psychological resilience during the COVID‐19 pandemic. Using longitudinal survey data, psychological resilience is measured by comparing distress reported pre‐COVID‐19 with distress reported during the outbreak and initial lockdown in April 2020. Methodologically, we compare differences in resilience and resources between people with identical gender, ethnicity, health, parenthood status, education, employment status, and region of residence (all measured pre‐2020). We also provide estimates from within‐household comparisons. Surprisingly, income, savings, and debt levels did not affect the likelihood of psychologically resilient outcomes. Cognitive ability, religiosity, and neighborhood social capital also had no protective effect. In contrast, we find robust evidence that non‐cognitive skills, measured by self‐efficacy, strongly protected against psychological distress. Self‐efficacy also dampened the increase in distress caused by large earnings shocks. These findings support investments in non‐cognitive skills that modify the damage‐function from adverse events.

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  • David W. Johnston & Claryn S. J. Kung & Michael A. Shields, 2021. "Who is resilient in a time of crisis? The importance of financial and non‐financial resources," Health Economics, John Wiley & Sons, Ltd., vol. 30(12), pages 3051-3073, December.
  • Handle: RePEc:wly:hlthec:v:30:y:2021:i:12:p:3051-3073
    DOI: 10.1002/hec.4428
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    Cited by:

    1. Xiaoying Gao & Apostolos Davillas & Andrew M. Jones, 2022. "The Covid‐19 pandemic and its impact on socioeconomic inequality in psychological distress in the United Kingdom: An update," Health Economics, John Wiley & Sons, Ltd., vol. 31(5), pages 912-920, May.
    2. Lina Anaya & Peter Howley & Muhammad Waqas & Gaston Yalonetzky, 2024. "Locked down in distress: A quasi‐experimental estimation of the mental‐health fallout from the COVID‐19 pandemic," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 56-73, January.
    3. Gao, Xiaoying & Davillas, Apostolos & Jones, Andrew M., 2021. "The COVID-19 Pandemic and Its Impact on Socioeconomic Inequality in Psychological Distress in the UK: An Update," IZA Discussion Papers 14790, Institute of Labor Economics (IZA).
    4. Zhiming Cheng & Silvia Mendolia & Alfredo R. Paloyo & David A. Savage & Massimiliano Tani, 2021. "Working parents, financial insecurity, and childcare: mental health in the time of COVID-19 in the UK," Review of Economics of the Household, Springer, vol. 19(1), pages 123-144, March.
    5. Chan, Ho Fai & Cheng, Zhiming & Mendolia, Silvia & Paloyo, Alfredo R. & Tani, Massimiliano & Proulx, Damon & Savage, David & Torgler, Benno, 2022. "Societal Movement Restrictions and Adverse Mental Health Outcomes," IZA Discussion Papers 15111, Institute of Labor Economics (IZA).
    6. Paul Fisher & Omar Hussein, 2023. "Understanding Society: the income data," Fiscal Studies, John Wiley & Sons, vol. 44(4), pages 377-397, December.
    7. Nolan, Anne & Smyth, Emer, 2022. "Disrupted transitions: young adults during the COVID-19 pandemic," Research Series, Economic and Social Research Institute (ESRI), number RS142, June.
    8. Tapager, Ina & Joensen, Lene Eide & Vrangbæk, Karsten, 2022. "The role of self-efficacy, well-being capability and diabetes care assessment for emotional and diabetes management challenges during the COVID-19 pandemic: Findings from a follow-up study," Social Science & Medicine, Elsevier, vol. 310(C).
    9. Botha, Ferdi & Dahmann, Sarah C., 2022. "Locus of Control, Self-Control, and Health Outcomes," IZA Discussion Papers 15306, Institute of Labor Economics (IZA).

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    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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