Resilience in a time of crisis
Resilience in a time of crisis: The importance of financial and non-financial resources
Building resilience is high on economic, political, and public health agendas in many countries. Governments now have dedicated departments, advisory groups, forums, and online portals aimed at providing information and training to improve resilience. For instance, the UK Government has introduced a Community Resilience Development Framework (Government Digital Service 2019) that includes steps to develop community resilience, and Public Health England (2014) has supported schools in building children’s resilience. Similarly, large-scale resilience training programmes have emerged, including the Penn Resilience Program, the UK Grit Program, and Australia’s Resilient Youth. There is also a plethora of ‘resilience courses’, ranging from those targeted at emergency service workers, to commercial training programs for corporate leaders.
The COVID-19 pandemic has further highlighted the need to increase resilience in the population in order to manage and reduce the adverse effects of the crisis (Habersaat et al. 2020). Veer et al. (2020) note that, “[t]here is urgent need for knowledge about factors that can protect mental health (resilience factors) in this world-wide crisis, which is different in nature from other crises that have so far been studied in resilience research”.
What is resilience and why is it important?
Fundamentally, resilience describes the ability of individuals “who are exposed to an isolated and potentially highly disruptive event to maintain relatively stable, healthy levels of psychological and physical functioning” (Bonanno 2004: 20). Resilience is important because nearly every individual will experience a major adverse event at some point in their life, be it at the individual level (e.g. illness, bankruptcy) or community level (e.g. natural disaster, terrorism). Having a resilient population reduces the costs (i.e. reduces the ‘damage function’) of future crises, which is important in an increasingly uncertain global environment. Therefore, increased resilience provides a form of self-insurance against future risk.
Psychological distress during COVID-19
Our recent paper (Johnston et al. 2020) documents our exploration of resources that resilient individuals have relied on during the COVID-19 pandemic, and undoubtedly in other difficult situations. Our data is sourced from the UK Household Longitudinal Study (Understanding Society), which conducted separate supplementary surveys in April, May, June, and July 2020 to capture respondents’ experiences over the COVID-19 outbreak.
During the course of the pandemic there was a remarkable increase in psychological distress. Figure 1 shows that prior to the pandemic (2017-2019), the sample mean of the 12-item General Health Questionnaire (GHQ) score equalled about one, indicating that the mean person was commonly experiencing one symptom of psychological distress (such as feeling ‘unhappy or depressed’ or ‘constantly under strain’). In April 2020, with UK residents in lockdown, GHQ scores drastically increased. For women, the mean GHQ score almost tripled in size to three symptoms of psychological distress.
Figure 1 Psychological distress (GHQ Caseness scores) in the UK population between 2014 and July 2020
What resources do resilient individuals rely on?
We focus on identifying the financial, cognitive, non-cognitive, and social resources (measured prior to the pandemic) that predicted a resilient response on average, and that predicted a resilient response to particularly intense health and economic shocks experienced by some sub-samples of people.
The outcome in the regression analysis is an indicator for whether the person’s GHQ score increased by ≥ 5 relative to the survey wave immediately prior to the pandemic. One in seven individuals in our sample reported experiencing this considerable increase in psychological distress, which we interpret as a non-resilient response. Details of the resources that were potential predictors of this response, and which we empirically explored, are described in Table 1.
Table 1 Potential resources for resilience measured in the from the UK Household Longitudinal Study
We estimated the effects of these resources using a fixed-effects modelling approach, in which individuals were exactly matched on a wide range of pre-2020 demographic and socioeconomic characteristics. Specifically, we identified effects by comparing individuals with identical gender, age-band, ethnicity, health, number of children and adults in the household, education, employment status, rurality, and region of residence (corresponding to 7,939 demographic groups).
Our surprising result is that financial resources – captured by household income, savings, and debt – were not predictors of resilience. A priori this finding was unexpected. For example, higher incomes in previous years may have allowed for more comfortable housing and amenities within which to isolate. In addition, more savings and less debt may have provided a buffer during the economic recession, and therefore reduced financial-related stress and anxiety.
Neither do we find any protection from better cognitive ability, religiosity, or neighbourhood social capital. This is despite well-established positive associations between cognition and health (Bijwaard et al. 2015), strategic thinking (Carpenter et al. 2013), and financial decision-making (Agarwal and Mazumder 2013), as well as how religiosity (VanderWeele et al. 2016) and social capital (Xue et al. 2020) predicts better psychological outcomes in the population.
Figure 2 Estimated associations between self-efficacy and the likelihood of experiencing a non-resilient outcome, for separate population subgroups
What we do find is robust evidence that the non-cognitive skill ‘self-efficacy’ is strongly predictive of resilience: a one-standard deviation increase in the self-efficacy index is estimated to reduce the likelihood of a large increase in psychological distress by around three percentage points (Figure 2, full sample estimate), which amounts to around 20% relative to the sample mean. Self-efficacy is the belief that one can perform novel or difficult tasks to attain desired outcomes, and therefore represents a self-confident view of one’s capability to deal with life’s stressors. This is close to the concept of locus of control, which is the focus of a growing literature on the role of non-cognitive skills in economic behaviour (e.g. Caliendo et al. 2020, Caliendo et al. 2015, Cebi 2007, Cobb-Clark et al. 2016, Lekfuangfu et al. 2018, McGee 2015, Schurer, 2017).
Comparing differences between people living in the same household (i.e. including household fixed effects), controlling for personality traits, restricting our sample based on past levels of psychological distress, and measuring distress in May, June, or July 2020, did not alter these conclusions.
In addition, the importance of self-efficacy is apparent across most population subgroups. Figure 2 illustrates no significant differences in the magnitude of the association between males and females; core working-age adults and older people; people with and without a university degree; and people above and below median household income. In other words, self-efficacy appears to play an important protective (resilience enhancing) role across the population. At the same time, economic resources were unimportant predictors of resilience in all of these subgroups.
Does self-efficacy moderate the negative effects of adverse events?
We also explored whether the protective role of self-efficacy is more pronounced among people who experienced greater adversity during the pandemic. Unsurprisingly, individuals who experienced a large reduction in earnings (≥ 30% between January-February 2020 and April 2020), had symptoms that could be caused by COVID-19 (e.g. a fever), or suffered loneliness because of the lockdown, were much more likely to have reported a large increase in psychological distress.
We find that having higher self-efficacy lessened the negative effect of the earnings shock, but not the health and loneliness shocks. Among people experiencing the earnings shock, those with high self-efficacy were significantly less likely to have experienced serious psychological distress compared to those with low self-efficacy.
Talk about resilience is everywhere nowadays: there has been a growing interest in building resilience in the general population – in economic, political, and public health agendas alike. However, learning who is resilient, and who is not, is important when planning the most cost-effective interventions to promote resilience.
We find robust evidence that the non-cognitive skill self-efficacy was strongly associated with a more resilient response to the COVID-19 pandemic, while financial resources are not. Cognitive skills, religiosity, and neighbourhood social capital were similarly non-protective.
Importantly, self-efficacy is viewed as amenable and can be trained and strengthened, and may have a social multiplier effect. This points to a clear target for investment that reduces the psychological impact of future adverse events.
Agarwal, S and B Mazumder (2013), “Cognitive abilities and household financial decision making“, American Economic Journal: Applied Economics 5(1): 193 – 207.
Bijwaard, G E, H van Kippersluis and J Veenman (2015), “Education and health: The role of cognitive ability“, Journal of Health Economics 42: 29–43.
Bonanno, G A (2004), “Loss, trauma, and human resilience: Have we underestimated the human capacity to thrive after extremely aversive events?”, American Psychologist 59(1): 20–28.
Buckner, J (1988), “The development of an instrument to measure neighborhood cohesion“, American Journal of Community Psychology 16: 771–791.
Caliendo, M, D A Cobb-Clark, C Obst, H Seitz and A Uhlendorff (2020), “Locus of control and investment in training“, Journal of Human Resources, forthcoming.
Caliendo, M, D A Cobb-Clark and A Uhlendorff (2015), “Locus of control and job search strategies“, Review of Economics & Statistics 97(1): 88–103.
Carpenter, J, M Graham and J Wolf (2013), “Cognitive ability and strategic sophistication“, Games and Economic Behavior 80: 115–130.
Cebi, M (2007), “Locus of control and human capital investment revisited“, Journal of Human Resources XLII(4): 919–932.
Cobb-Clark, D A, S C Kassenboehmer and M G Sinning (2016), “Locus of control and savings“, Journal of Banking & Finance 73: 113–130.
Government Digital Service (2019), “Community resilience development framework“.
Habersaat, K B, C Betsch, M Danchin et al. (2020), “Ten considerations for effectively managing the COVID-19 transition“, Nature Human Behaviour 4(7): 677–687.
Johnston, D W, C S J Kung and M A Shields (2020), “Who is resilient in a time of crisis? The importance of financial and non-financial resources“, IZA Discussion Papers, 13720.
Lekfuangfu, W N, N Powdthavee, N Warrinnier and F Cornaglia (2018), “Locus of control and its intergenerational implications for early childhood skill formation“, The Economic Journal 128(608): 298–329.
McFall, S (2013), “Understanding Society: UK Household Longitudinal Study: Cognitive ability measures“.
McGee, A D (2015), “How the perception of control influences unemployed job search“, ILR Review 68(1): 184–211.
Public Health England (2014), “Local action on health inequalities: Building children and young people’s resilience in schools“.
Schurer, S (2017), “Bouncing back from health shocks: Locus of control and labor supply“, Journal of Economic Behavior & Organization 133: 1–20.
Schwarzer, R and M Jerusalem (1995), “Generalized self-efficacy scale”, in M Johnston, S Wright and J Weinman (eds.), Measures in Health Psychology: A User’s Portfolio, pp. 35–37, NFER – Nelson.
VanderWeele, T J, S Li, A C Tsai and I Kawachi (2016), “Association between religious service attendance and lower suicide rates among US women“, JAMA Psychiatry 73(8): 845–851.
Veer, I M, A Riepenhausen, M Zerban, C Wackerhagen, L Puhlmann, H Engen …and R Kalisch (2020), “Psycho-social factors associated with mental resilience in the Corona lockdown“, PsyArXiv.
Xue, X, W R Reed and A Menclova (2020), “Social capital and health: A meta-analysis“, Journal of Health Economics 72: 102317.