The risk and consequences of multiple breadbasket failures: an integrated copula and multilayer agent-based modeling approach

Abstract

Climate shocks to food systems have been thoroughly researched in terms of food security and supply chain management. However, sparse research exists on the dependent nature of climate shocks on food-producing breadbasket regions and their subsequent cascading impacts. In this paper, we propose that a copula approach, combined with a multilayer network and an agent-based model, can give important insights on how tail-dependent shocks can impact food systems. We show how such shocks can potentially cascade within a region through the behavioral interactions of various layers. Based on our suggested framework, we set up a model for India and show that risks due to drought events multiply if tail dependencies during extremes drought is explicitly taken into account. We further demonstrate that the risk is exacerbated if displacement also takes place. In order to quantify the spatial-temporal evolution of climate risks, we introduce a new measure of multilayer vulnerability that we term Vulnerability Rank or VRank. We find that with higher food production losses, the number of agents that are affected increases nonlinearly due to cascading effects in different network layers. These effects spread to the unaffected regions via large-scale displacement causing sudden changes in production, employment and consumption decisions. Thus, demand shifts also force supply-side adjustments of food networks in the months following the climate shock. We suggest that our framework can provide a more accurate picture of food security-related systemic risks caused by multiple breadbasket failures which, in turn, can better inform risk management and humanitarian aid strategies.

Addressing the human cost in a changing climate

“…Beyond probabilistic and deterministic disaster displacement risk models, there are other modeling approaches that can increasingly be put to the task. Agent-based network models can assess individual-level impacts and costs through a bottom-up methodology that can reflect how shocks to one part of a system (community, economy, country, or region) can cascade through the whole system and also spill over into other systems (12). Further, a system dynamics approach can describe in a relatively comprehensive manner the relationships between a wide range of dimensions and indicators, although it requires granular datasets that are often unavailable and is highly cost-and labor-intensive to develop.…”

Assessing the cascading impacts of natural disasters in a multi-layer behavioral network framework

“…Since bread-basket regions also employ a large share of the working population at the regional level, usually at very low wages, a climate-induced disaster (for example, a flood) could create conditions for food insecurity in the directly-impacted locations. Additionally, this can also spillover to other locations through trade and migration networks causing cascading losses 28 , 33 . Understanding how the distributional impacts of natural disasters evolve is crucial for assessing socioeconomic vulnerability and to inform policy response 11 , 23 .…”

Risk-Layering for Indirect Effects

“…In contrast to direct risk, where only the elements exposed to natural hazards need to be looked at, the hazards' effects experienced beyond these areas and elements must be considered when assessing indirect risk (Naqvi et al 2020). To achieve this, a systems perspective is beneficial and, in this case, we suggest defining a system to be a set of interconnected elements within a defined system boundary (Hochrainer-Stigler et al 2020b).…”

“…For example, while the system boundary for insurance is only the assets that can be damaged due to natural hazards, the economic consequences may include all elements (for example, households, firms, banks) indirectly affected due to the connectedness among the elements. Hence, defining clear system boundaries separately for risk-layering for indirect risks and for direct risks is essential as they might differ substantially (Naqvi et al 2020).…”

“…However, a similar approach could be applied to other hazards, such as drought events, compound events, and different dimensions of indirect effects as well. For example, in Naqvi et al (2020) a loss distribution for yield losses for certain states in India were estimated and used to shock the respective elements, farmers and agricultural labor, in the system. A two-layer network ABM approach was used, which made it possible to assess effects also outside the agricultural sector, namely displacement and consequences of displacement on prices in other regions.…”