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Modelling Heterogeneity in the Resilience to Major Socioeconomic Life Events

Author

Listed:
  • Fabrice Etilé

    (PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, INRA - Institut National de la Recherche Agronomique, PSE - Paris School of Economics - ENPC - École des Ponts ParisTech - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique - EHESS - École des hautes études en sciences sociales - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Paul Frijters

    (CEPR - Center for Economic Policy Research - CEPR, LSE - London School of Economics and Political Science)

  • David W. Johson

    (Monash University [Malaysia])

  • Michael A. Shields

    (Monash University [Malaysia])

Abstract

Using a novel, dynamic finite mixture model applied to 12 years of nationally representative panel data, we explore individual heterogeneity in the total psychological response (our measure of resilience) to ten major adverse life events, including serious illness, redundancy and crime victimisation. Importantly, this model takes into account that individuals are not randomly selected into adverse events, that some events are anticipated in advance of their occurrence, and that the immediate psychological response and the speed of adaptation may differ across individuals. Additionally, we generate a ‘standardised event' in order to document the distribution of general resilience in the population. We find considerable heterogeneity in the response to adverse events, with the total psychological loss of people with low resilience being several times larger than the average loss. We also find that resilience is strongly correlated with clinical measures of mental health, but only weakly correlated with cognitive and non-cognitive traits. Finally, we find that resilience in adulthood to some extent is predictable by childhood socioeconomic circumstances; the strongest predictor we identify is good childhood health.

Suggested Citation

  • Fabrice Etilé & Paul Frijters & David W. Johson & Michael A. Shields, 2017. "Modelling Heterogeneity in the Resilience to Major Socioeconomic Life Events," PSE Working Papers halshs-01485989, HAL.
  • Handle: RePEc:hal:psewpa:halshs-01485989
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01485989
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    Cited by:

    1. Paul Frijters & Christian Krekel & Aydogan Ulker, 2020. "Machiavelli versus concave utility functions: should bads be spread out or concentrated?," CEP Discussion Papers dp1680, Centre for Economic Performance, LSE.
    2. Asheim, Geir B. & Bossert, Walter & D'Ambrosio, Conchita & Vögele, Claus, 2020. "The measurement of resilience," Journal of Economic Theory, Elsevier, vol. 189(C).

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    Keywords

    Psychological Health; Resilience; Life Events; Childhood; Panel; Data; Mixture Model;
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