Disentangling the mechanistic chain for better policy design

Understanding how policy design can incentivize, constrain, and otherwise structure policy targets’ behavior to achieve desired results is vital but requires a clear understanding of the mechanisms that link policy tools to actual behavior. More importantly, it requires reasoning in terms of the processes and interactions that can be activated by policy tools to accomplish desired results. It is therefore imperative that policy designers – both those who study it and those who practice it – specify clearly the linkages between the input (policy design) and the output, via the intended and unintended processes triggered by the design. Many existing analytical efforts focus only on shedding light on what is needed for good policy design and ignore how good policy design works in terms of the types of processes that can be activated to achieve (or not) the desired results. As a result, we know little about how different solutions trigger and drive the achievement of intended outcomes. The literature on policy design is often based on anecdotes and correlations, jumping from proposed solutions to anticipated outcomes without exploring the conditions that are the real determinants of policy results.