Learning from Neighbors: The Spatial Spillover Effect of Crisis Learning on Local Government
Yun Tang and
Ying Wang
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Yun Tang: School of International Relations and Public Affairs, Fudan University, Shanghai 200433, China
Ying Wang: School of Government, Nanjing University, Nanjing 210033, China
Sustainability, 2022, vol. 14, issue 13, 1-20
Abstract:
Accident prevention is an important prerequisite for achieving sustainable development, and effective crisis learning is a necessary path to it. This article focuses on whether local governments in non-accident areas learn from crises in accident areas, that is “learn from the mistakes of neighbors” and “grow in wisdom.” Using panel data from 2006–2017 for 30 provinces in China, our empirical test discovered that there is not a one-to-one relationship between “learning from neighbors” and “growing in wisdom”; it is a U-shaped relationship between the frequency of major accidents and the crisis learning effect of local government. When the occurrence frequency of major accidents is low, the regulatory effect caused by major accidents leads to the effective crisis learning of local governments. However, when major accidents occur frequently and reach a certain threshold, the crisis learning effect will deteriorate due to an excessive deterrent effect. In this non-linear relationship, the impact of political pressure occurs on two fronts, a gentle U-shaped curve and a shift in the inflection point to the left, implying that political pressure plays a dual role in the crisis learning process of local government. Accordingly, local governments should fully seize the window of time to initiate crisis learning with regulatory effects and delegate political authority to supervise local crisis learning with reasonable compliance.
Keywords: crisis learning; local governments; major accidents; spatial spillover effect (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:13:p:7731-:d:847045
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