Designing Effective Policy Responses: A Policy Mix Perspective

• In Event: Policy Design for Democracy: Theoretical Perspectives

Abstract

The research explores the significance of policy design in addressing complex challenges such as the COVID-19 pandemic. Motivated by the acknowledged importance of policy design and a recognized gap in understanding how specific design characteristics influence public policy effectiveness, the study adopts a policy mix perspective. This perspective emphasizes the nuanced examination of individual policy tools and their collective impact, particularly concerning dynamic challenges like the ongoing pandemic.
RQ1: To what extent does the policy design characteristics such as tools, stringency, and sanctions influence the effectiveness of pandemic response policies?
H1: More stringent COVID-19 risk mitigation policies will be more effective at reducing pandemic problem indicators than less stringent policies.
H2: Policies that include sanctions for violations will be more effective at reducing pandemic problem indicators than those without sanctions.
RQ2: To what extent does the implementation robustness and speed embedded in policy design contribute to the effectiveness of pandemic response policies?
H3: Policies with higher levels of robustness are more effective at reducing pandemic-related problem indicators.
H4: The quicker policies are adopted at the start of the pandemic (such as stay at home orders), the more effective the policy will be at reducing pandemic-related problem indicators.

In conclusion, the findings reveal that political factors significantly influence the selection of policy tools, stringency levels, and the use of sanctions across various policy topics. Democratic governors tend to adopt certain tools and utilize sanctions more extensively, while Republican governors show preferences in stringency levels. The panel regression results provide insightful nuances into the effectiveness of policy design characteristics in addressing the spread and severity of COVID-19. The study indicates that higher levels of policy robustness are generally associated with worse policy effectiveness. Specific policy tools, such as Tool3 (Persuasion) and Tool5 (Learning), demonstrate better effectiveness in reducing the severity of spread across different policy topics. However, Tool6 (Mandate) exhibits mixed patterns of effectiveness, showing associations with higher levels of policy robustness in various contexts but a different pattern in mask policies. Stricter policy stringency is generally associated with higher effectiveness in mitigating the spread and severity of COVID-19. Additionally, the study supports the notion that quicker policy adoption is linked to better effectiveness in reducing both the spread and severity of COVID-19.

Author

• Manli Zhang, University of Science and Technology Beijing