Improving policy-making: a research agenda

Forthcoming paper by Stauffer, Snoeij, Seifert, and Amman (2019)

How to understand and approach policy-making as an outside actor? How to improve policy-making such that decisions rely more on evidence and reason while taking behavioral and institutional realities into account? We are writing a research agenda that provides research and implementation directions to tackle these questions. The research agenda is divided in three sub-sections.

First, we detail out the need for a better understanding of policy-making dynamics. We start by looking at the stability and instability of various properties of policy-making, such as agenda-setting, windows of opportunity, inertia, attention, and the interaction with the media. Then, we investigate the underpinnings of individual and collective decision-making, and how close it approximates the ideal of reason. A current knowledge gap in the literature is found regarding the scaling of decision-making from individual preferences to group level, and whether the improved decision-making of an individual results in better collective decisions.

Second, we delve into the intervention space; i.e. the considerations and research questions related to improving policy-making. The section starts with variables that one must weigh against one another, such as assessing the value of one-off workshops versus longitudinal interventions, or Tetlock-style calibration training versus training in Bayesian thinking. Subsequently, the section covers existing organisations that implement methods to improve decision-making. Lastly, an attempt to describe the state of evidence of existing initiatives illustrates the need to conduct more trials and evaluations.

Third, we present hypotheses that narrow down the intervention space. Particularly, we draw the hypothesis that technical rather than political engagement is more promising, more important, and less risky. We argue that aiming for the pivotal actors in policy networks, i.e. central decision-makers, is key. A third hypothesis is that we should reduce uncertainty while increasing agreement, as well as deal with issues for which uncertainty and agreement cannot be altered. Fourth, we explain that the expected value of an intervention will vary depending on the current state of policy dynamics, notably policy bubbles. This suggests that the content of the intervention should change in function of its timing.

We are currently conducting expert interviews. Please get in touch if you think you can contribute.