The public's preferred level of involvement in local policy-making.

We investigated what people consider the optimal level of citizen involvement in local policy decision-making. This is an important question to answer, given that civil servants and politicians are increasingly confronted with the pressure to add a participatory layer to representative democratic policy-making. Across five empirical studies (total N = 1470), we consistently found that, overall, the most preferred decision-making model is a balanced model in which citizens and the government are equally involved. Despite this preferred 'overall' pattern of equal involvement, we identified three subgroups within the citizenry with different preference curves: Some citizens prefer a model in which citizens and the government are truly equal partners, whereas others prefer a model in which either the government or citizens are relatively more involved in the policy decision-making process. The main contribution of our work is thus that we identified a perceived 'overall' optimal level of citizen engagement, and variations to that optimum depending on citizens' individual traits. This information might be helpful to policy-makers in developing effective citizen participation processes.

In trust we trust: The impact of trust in government on excess mortality during the COVID-19 pandemic.

The COVID-19 pandemic has brought forward myriad challenges to public policy, central of which is understanding the different contextual factors that can influence the effectiveness of policy responses across different systems. In this article, we explore how trust in government can influence the ability of COVID-19 policy responses to curb excess mortality during the pandemic. Our findings indicate that stringent policy responses play a central role in curbing excess mortality. They also indicate that such relationship is not only influenced by systematic and structural factors, but also by citizens' trust in government. We leverage our findings to propose a set of recommendations for policymakers on how to enhance crisis policymaking and strengthen the designs of the widely used underlying policy learning processes.

A Guide to Benchmarking COVID-19 Performance Data.

If the COVID-19 pandemic has taught us anything, it is that policy makers, experts, and public managers need to be capable of interpreting comparative data on their government's performance in a meaningful way. Simultaneously, they are confronted with different data sources (and measurements) on COVID-19 without necessarily having the tools to assess these sources strategically. Because of the speed with which decisions are required and the different data sources, it can be challenging for any policy maker, expert, or public manager to make sense of how COVID-19 has an impact, especially from a comparative perspective. Starting from the question "How can we benchmark COVID-19 performance data across countries?," this article presents important indicators, measurements, and their strengths and weaknesses, and concludes with practical recommendations. These include a focus on measurement equivalence, systems thinking, spatial and temporal thinking, multilevel governance, and multimethod designs.