Simulation and it's Implications for Policy Design

At Simudyne, we firmly believe that simulation-assisted policy design is critical for understanding complex social phenomena and crafting effective policies, especially in turbulent times. A research paper from last year (embarrassingly, one that I just read yesterday) titled “Modeling nationalism, religiosity, and threat perception: During the COVID-19 pandemic ” by Bullock, Lane, Miklou?i?, and Shults provides strong evidence supporting this perspective.

The researchers, associated with CulturePulse , grounded their work in two key theories from social psychology: identity fusion theory and moral foundations theory. Identity fusion theory posits that people's identities can become "fused" with a group, causing them to feel a visceral sense of oneness and to be willing to make extreme sacrifices for the group. Moral foundations theory proposes that human morality is based on five innate moral intuitions - care, fairness, loyalty, authority, and purity - and that people's positions on the liberal-conservative spectrum depend on how much they emphasise each foundation. The researchers used these theories to inform their hypotheses about how perceived threats might impact religiosity, nationalism, and attitudes towards out-groups during a crisis like the pandemic.?

The survey revealed intriguing patterns, such as:

• Different types of perceived threats (social, financial, contagion, etc.) had varying effects on nationalism and attitudes towards immigrants. Social threats increased anti-immigrant sentiment while contagion and financial threats decreased it.
• Nationalism and religiosity were affected by similar threat-related variables, suggesting they may be correlated due to common underlying causes rather than direct causation.
• Media consumption’s impact on anti-immigrant sentiment depended on an individual’s level of religiosity.

These nuanced findings highlight the complex, non-linear dynamics at play. Simple polls and traditional statistical methods can uncover correlations, but crafting judicious policies requires deeper understanding of the intricate causal web and feedback loops driving social phenomena.

This is where the researchers’ system dynamics simulation model shines. By formalising the causal assumptions and complex interactions suggested by the survey data, the model serves as an “artificial society” for rigorous theory-testing and scenario analysis. The simulations replicated real-world patterns like the age and gender distributions of nationalism, while also revealing unintuitive possibilities, such as extreme anti-immigrant sentiment among the socially hyper-liberal under certain rare parameter combinations.?

Crucially, the model provides a safe virtual environment to test “what-if” policy scenarios and surface unexpected policy consequences before implementing them in the real world. Agent-based models, our specialty at Simudyne, can further enhance this by simulating the interactions of many heterogeneous individuals, each with their unique attributes, social networks, and decision rules shaped by the macro dynamics.

The research makes a compelling case that in a world growing ever more complex and uncertain, policymakers cannot rely on simplistic models, historical data, and gut intuition alone. Integrating data and qualitative insight with computational social science techniques like system dynamics and agent-based modelling empowers us to diagnose causal mechanisms, forecast alternative futures, and design robust, adaptive policies for navigating the turbulent times ahead. At Simudyne, we are committed to advancing this mission and helping leaders harness the power of simulation for social good.?

This timely research is a prime example of the vital role that computer modelling and simulation must play in 21st century policymaking. Only by embracing these tools can we hope to steer our complex global socio-technical system towards a thriving, sustainable and equitable future for all.