Policy Making and Modelling in a Complex World

The work of policy makers will continue to remain unreliable unless they become conversant with uncertainties and complexities that define the way different social, political, and economic variables interrelate. Complexity refers to interrelated elements and factors, but depicts significant variations in the way they function or express themselves. As a result, their connections are unpredictable. These components can interact to cause expected outcomes. However, they can also generate deviant and unexpected outcomes. The human economy is an example of a complex system because the multiple elements that interact within the social, political, and economic environments make the outcomes indeterminate. Regime shifts may begin with simple adaptable changes only to transition to complex associations with unwanted and devastating effects. Therefore, policy developers should determine when exactly the formulated regulations are likely to shift from the intended purpose towards unexpected consequence if they desire to improve their efficiencies. This understanding will ensure effective policy development because it will highlight when and where restructuring is necessary to improve efficacies. Quantification and compartmentalization are the main drivers of substandard policy development. Quantification explains the tendency to create solutions based on their financial outcomes while secluding the non-quantifiable outcomes. On the other hand, compartmentalization is the process of splitting social systems and treating each section separately even though their functions intertwine. Among the most important models of policy formulation are the formal modeling techniques and agent-based framework. Agent-based framework is more effective because it allows policymakers to understand how key variables of interest (agents) behave. It enables policy makers to predict when social variables will behave as expected or unexpectedly. Agent-based framework can determine how unexpected behavioral change will affect the financial, behavioral, and psychological quality of life. Thus, the main question remains,

how can the agent-based model be accessed and integrated in policy development to yield quality outcomes?