Comparative literature on institutional reforms in multi-level systems proceeds from a global trend towards the decentralization of state functions. However, there is only scarce knowledge about the impact that decentralization has had, in particular, upon the sub-central governments involved. How does it affect regional and local governments? Do these reforms also have unintended outcomes on the sub-central level and how can this be explained? This article aims to develop a conceptual framework to assess the impacts of decentralization on the sub-central level from a comparative and policyoriented perspective. This framework is intended to outline the major patterns and models of decentralization and the theoretical assumptions regarding de-/re-centralization impacts, as well as pertinent cross-country approaches meant to evaluate and compare institutional reforms. It will also serve as an analytical guideline and a structural basis for all the country-related articles in this Special Issue

In this article, we explain how the COVID-19 wicked crisis context influences the quality of critically needed epistemic policy learning and undermines policy effectiveness. We explore those influences on two main dimensions: Vertically (pertaining to the selection of core scientific advice) and horizontally (pertaining to managing scientific interdisciplinarity). We apply the concept using COVID-19 policy responses from England and Belgium, offer an explanatory framework, and provide recommendations for policymakers, including (i) Crafting a policy-science-public narrative maintaining independence, openness, and trust. (ii) Outlining the limitations of science and public expectation setting. (iii) Enhancing interdisciplinarity in policy formulation by utilizing boundary and discipline-spanning structures, and systems thinking mechanisms for dynamic problem synthesis.

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.

Understandings of different policy learning types have matured over recent decades. However, relatively little is known about their nonlinear and interactive nature, particularly within crisis contexts. In this article, we explore how two of the most prominent learning types

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