Clara Latini

Youth Perspectives: New Economic Lessons on Resilience Learned from COVID

Abstract

Our society relies on increasingly complex and interconnected systems. It is vulnerable to stress events anticipated by current capabilities. The Global Financial Crisis of 2008 already showed how our society has been exposed to systemic disruption and how policymakers were challenged by threats of recession and socio-political crisis. COVID-19 demonstrated how damage to a natural system, such as biodiversity loss, can heavily deteriorate socio-economic conditions. Current risk management theories are often based on maintaining the leanest possible operations for efficiency purposes, reducing redundancy to zero. However, without redundancy, greater vulnerability is at risk. Due to increasing interconnectedness, there is a strong need to adopt a systemic approach to resilience that focuses on the resilience of complex systems in response to a shock event. Aiming for system resiliency will enable rapid and effective protection of socio-economic conditions than tools currently available to most governments.

Introduction

The COVID-19 pandemic represented a shock to our society and a moment of reflection to move forward with better ways to rethink resilience, risk management, and recovery. This paper will discuss how a resilience approach can support systems to address uncertainty and complexity and overcome disruptions. The economic system is interlinked through financial markets, global supply chains, social networks, and ecological foundation. Complex interactions at the individual level could raise unstable properties at the macro level, such as shocks that may emerge from various sources, including pandemics, financial crises, natural disasters, geopolitical conflicts, and cyber-attacks (Hynes et al., 2020). Resilience offers a topic of increasing interest not only for academia but for international organizations, national and local governments. As both a governing philosophy and a tool for system assessment, resilience represents the capacity to understand the ability to recover and adapt to unpredictable circumstances.

Lessons from the financial crisis

Before the financial crisis, most economists provided a favorable view of financial globalization's effects on resilience. The majority thought that the growth of the financial sector would allow economic agents and countries to diversify risk through financial instruments. The expectation was that cross-border financial integration would lead to more risk-sharing. However, former IMF Chief Economist Raghuram Rajan (2005) warned that “even though there are far more participants who can absorb risk today, the financial risks that are being created by the system are indeed greater. [...] They may also create a greater probability of a catastrophic meltdown”. In fact, between 2007 and 2008, issues related to the national home loans market escalated into a financial crisis that heavily impacted the global banking system. As a result, the 2008-09 recovery was fragile. Employment, private investment, and productivity growth rate remained below pre-crisis levels in multiple countries, while public debt continued to increase. During these years, countries suffered from various economic shocks, sovereign debt crises, and volatility in the world economy, further causing social unrest (Caldera-Sánchez et al., 2017). The financial crisis demonstrated that economic fragility could develop under the appearance of stable macroeconomic conditions, putting into question rethinking tools to predict economic risks and the urgency of strengthening the resilience of our societies to adverse shocks (Caldera Sánchez et al., 2015). The crisis showed us that the search for efficiency and eliminating redundancy negatively impacted the global financial system of the mid-2000s, exposing society to systemic disruption and showing that focusing on hardening core governance and finance systems may not adequately protect against future shocks (Hynes et al., 2020).

COVID-19 crisis

After the financial crisis, the world economy experienced another shock: the COVID-19 pandemic. The virus has killed over six million people so far (WHO, 2022), causing unprecedented pressure on healthcare systems (Nicola et al., 2020) and severely deteriorated socio-economic conditions worldwide. Restrictions in mobility caused severe effects on the labor market and poverty rates (Delardas et al., 2022). Global poverty increased for the first time in a generation, and income losses dramatically increased inequality across countries (World Bank, 2022). The World Bank (2021) estimated that the pandemic pushed between 119 and 124 million people into extreme poverty around the globe in 2020. According to the IMF (2022), the cost of COVID-19 is predicted to reach $12.5 trillion by 2024 and the amount the world is losing due to this crisis is costing as much as 500 years' worth of investment in preparedness for global health crises (Global Preparedness Monitoring Board, 2020). The Wellcome Global Monitor Report (2020) found that the pandemic disproportionately impacted low-income countries and people with low incomes across all countries. Forty-five percent of workers in low and lower-middle-income countries lost their jobs or businesses due to the crisis, compared to just 10 percent in high-income countries. In addition, the costs of school closure negatively impacted students' mental health and learning, also underlining how a less skilled workforce implies lower national economic growth rates (Hanushek and Woessman, 2020).

Furthermore, the COVID-19 crisis has reinforced the economic links between households, companies, the financial sector, and the government. The pandemic exacerbated financial fragilities, such as a dramatic increase in private and public sector debt which currently represents a serious threat to a solid long-term recovery (World Bank, 2022).

COVID-19 resulted in multi-system challenges. In 2020 it was possible to observe a substantial loss of functionality in the system as the pandemic released multiple system vulnerabilities. The pandemic presented critical issues such as the lack of ventilators or PPE, which had an impact on infrastructure failure, business disruption, and further deteriorated human health (Trump et al., 2020). COVID-19 demonstrated how society is vulnerable to systemic shocks and disruption if it relies excessively on prioritizing system efficiency over resilience. Efficiency emphasizes performance at maximum capacity with minimal use of resources. However, in order to meet the rising demands of society, efficiency-based approaches often depend on increasingly complex and interconnected systems. In this case, when an interdependent society encounters stressors beyond its capabilities, highly efficient systems risk catastrophic failure that can prevent recovery (Hynes et al., 2020). COVID-19 further showed how subjective factors such as trust in institutions can influence how a disaster unfolds. For example, at the beginning of the COVID-19 pandemic, the adoption of social-distancing measures was associated with trust in government, and the mistrust in COVID-19 vaccine recommendations represented a clear threat to recovery (Seale et al., 2020). However, a positive consideration of the pandemic resulted in how crises offer opportunities to expand social protection and health measures against future health threats.

Moreover, the pandemic highlighted the need for well-resourced data systems to understand and mitigate social and economic consequences and design short-term responses. For instance, the OECD developed the “Weekly Tracker of GDP” using machine learning and Google Trends data to track countries’ economies during COVID-19 (Woloszko, 2020). The Tracker suggested that the immediate impact on GDP of the global pandemic was heterogeneous across advanced economies and that the economic recovery was much more gradual than following the initial impositions. COVID-19 also demonstrated that damage to a natural system, such as biodiversity loss, will create serious socio-economic consequences (OECD, 2020). The cost of recent losses of ecosystem has been estimated at USD 4 trillion–USD 20 trillion per year. While land degradation is estimated to cost USD 6 trillion–USD 11 trillion per year and oceanic degradation to USD 200 billion per year (Kapnick, 2022). Land-use change influenced by agricultural expansion and infrastructure development is considered to be the most common driver of infectious diseases, accounting for around one-third of all emerging disease urgencies (Loh et al., 2015). According to the OECD (2020), pressures on biodiversity are expected to increase, exposing future risks of facing another pandemic. Investing in biodiversity as part of the COVID-19 response and recovery remains key in mitigating these risks. Scientists have further called for the strengthening of wildlife trade regulations to close loopholes in current governance to reduce the risk of zoonosis and spillover emergence, and consider the need to balance biodiversity conservation with the protection of food security and livelihoods of communities dependent on this trade (e.g., Booth et al., 2021; Borzée et al., 2020; Roe et al., 2020). Finally, it is worth noting that stresses such as the climate emergency are nonlinear as the system seems to continue to function normally or to degrade slowly. However, it can then reach a tipping point and rapidly collapse.

Systemic resilience

The economy can be defined as a system of interconnected institutions and markets that is continuously correcting itself. However, it inevitably reaches a critical state that may lead to cascade effects and a broader type of instability that does not correctly allow capital flows (Bak et al., 1993). Guzman and Stiglitz (2020) introduced a “dynamic disequilibrium” macro framework based on the premise that “a better way to understand deep downturns is to think of the economy experiencing a constant evolution, marked by uncertainty, in which there is continual learning about the economic system.” This means that the system is seen as an adaptive behavior that is both exogenously and endogenously produced by intervention and design. Furthermore, in the ecological modeling literature, natural systems tend to evolve towards higher resilience, defining a balance between efficiency and redundancy (Ulanowicz, 2009). Trade theories also describe trade systems following a highly efficient network. For example, the economic globalization of the past decades has made trade networks vulnerable to cascading economic shocks (Fagiolo et al., 2010), with the decreasing of vital systems characteristics such as redundancy, diversity, and modularity, which enable resilience. It is also crucial to analyze the relationship between redundancy and modularity and measures of resilience to understand their contribution to resilience preparedness (Fath et al., 2015). Conventional risk management is mainly based on preventing a threat from happening or mitigating consequences if prevention does not represent a possible option. However, in an interconnected world, cascading effects are inevitable. This type of risk management is not able to adequately protect economic and social conditions, and prevention seems to be expensive to implement to assure policymakers of adequate protection (Michel-Kerjan, 2012; Linkov et al., 2019). Also, risk management often focuses on keeping the leanest possible operations, aiming for efficiency and reducing redundancy to zero. However, it is more likely to have more vulnerability and less ability to absorb shocks without redundancy, which can quickly turn shock events into failures.

Under the context of disaster risk, UNDRR (2017) defined resilience as “the ability of a system, community or society exposed to hazards to resist, absorb, accommodate, adapt to, transform and recover from the effects of a hazard in a timely and efficient manner, including the preservation and restoration of its essential basic structures and functions through risk management.” According to the OECD (2020), resilience refers to the ability to absorb and recover from shocks while adapting and transforming their structures for operating during long-term stresses or uncertainty. Another consideration of resilience is how it accepts the uncertain and unpredictable nature of systemic threats and addresses them through building system resilience. Instead of relying on the ability of system operators to prevent, avoid, withstand, and absorb threats, resilience highlights the importance of recovery and adaptation in case of disruption. Furthermore, resilience considers that critical disruptions can occur in the future. Therefore, current systems must develop the capacity to recover and adapt to ensure survival. This approach can contribute to developing a better strategy against multiple uncertain and complex threats, such as climate change or economic and financial challenges, by emphasizing the capacity of these systems to recover from disruption and better adapt to future disruptions efficiently. Moreover, resilience can be applied to stress-test networks and system complexities to evaluate corrective policies to prevent the failure of critical operations (Hynes et al., 2022). Linkov, Trump, and Hynes (2019) recommend the following guidelines to implement resilience:

  1. Design systems, including infrastructure, supply chains, economic, financial, and public health systems, to be resilient, i.e., recoverable and adaptable.
  2. Develop methods for quantifying resilience to make explicit trade-offs between a system’s efficiency and resilience, and guide investments.
  3. Control system complexity to minimize cascading failures resulting from unexpected disruption by decoupling unnecessary connections across infrastructure and making necessary connections controllable and visible.
  4. Manage system topology by designing appropriate connections and communications across the interconnected infrastructure.
  5. Add resources and redundancies in system-crucial components to ensure functionality.
  6. Develop real-time decision-support tools integrating data and automating the selection of management alternatives based on explicit policy trade-offs in real-time.

It is also suggested that four main domains need to be identified in a resilience approach: physical (sensors, system states, and capabilities); information (creation, manipulation, and storage of data); cognitive (understanding, mental models); and social (interaction and collaboration). Moreover, integrating existing modeling tools from different fields and linking environmental models with economic growth and trade models remains crucial to systemic resilience (Hynes et al., 2021).

The International Risk Governance Centre's Guidelines for the Governance of Systemic Risks (2018) need to be further considered in the discussion as those highlight a procedure that analyses systemic risks with multi-system viewpoints regarding possible threats. This procedure supports stakeholders to either prevent the shift of the system under undesirable circumstances or facilitate the transition of the respective system to a preferable regime. The IRGC's guidelines state:

  1. Explore the system, and define its boundaries and dynamics.
  2. Develop scenarios considering possible ongoing and future transitions.
  3. Determine goals and the level of tolerability for risk and uncertainty.
  4. Co-develop management strategies dealing with each scenario.
  5. Address unanticipated barriers and sudden critical shifts.
  6. Decide, test, and implement strategies.
  7. Monitor, learn from, review, and adapt.

Accepting that resilience acknowledges that disruptions can happen, core systems must guarantee the capacity for recovery and adaptation. Therefore, resilience needs to focus on “the ability of a system to anticipate, absorb, recover from, and adapt to a wide array of systemic threats” in order to bounce forward (Linkov et al., 2019). As previously described, efficiency exposes the systems we rely on at risk of sudden disruption. System resilience will allow more receptive protections of economic prosperity and well-being. Uncertainty of events linked with complex systems requires a systemic response.

Resilience and policymaking

COVID-19 demonstrated how government capacity is critical in shaping effective crisis responses (Fukuyama, 2020). Given the complexity of shocks and their multiple consequences, governments must adapt quickly and ensure appropriate capacity for coordination. Identifying systemic threats and reviewing the analytical and governance approaches to manage threats and build resilience to contain their impacts is also crucial. This will allow policymakers to create safeguards of resilience toward economic, social, and environmental shocks. According to Guzman and Stiglitz (2020), societies need to develop institutions to deal with the macro inconsistencies inherent in the functioning of market economies and support adaptable institutions. Usually, the “Centres of Government” take care of the action of crisis and management of government operations. The CoGs have been defined as a “group of bodies that provide direct support and advice to Heads of Government or the Council of Ministers” (OECD, 2018). The structure of the Centres of Government can vary depending on the political system, contextual and historical factors. Thanks to the Survey on the Organisation and Functions of the Centre of Government, the OECD (2017) found that 83 percent of CoGs took responsibility for risk management. However, only around 10 percent of the Centres of Government listed risk management as a vital responsibility. The OECD (2020) mentioned that most countries established ad hoc entities to manage the pandemic and categorized these institutional groups into precise arrangements and structures provided by crisis-management policies. It remains critical for policymakers to prioritize the implementation of resilience methods. Policies must enable governments to tackle various problems simultaneously, such as supporting recovery, easing multiple stressors, and introducing resilience to mitigate threats (OECD, 2020). Finally, reforms are essential in building resilience to future shocks, both within and across countries, and in avoiding negative externalities on a global level.

Conclusion

COVID-19 represented one of the main unpredictable shocks to multiple interconnected systems, where recovery is required in various sectors. This paper describes how it is critical to shift from risk-based to resilience-based approaches to managing shocks properly. Systemic resilience shows that crises are part of complex systems, such as public health, financial or labor markets, and how resilience needs to be prioritized in system management to contain future disruptions. Policymakers need to acknowledge that all systems may fail. Therefore, they must be prepared for tentative failures, even when redundancy does not seem to be effective. This will result in allowing a more robust recovery and “bouncing forward” to a more reliable system.

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