Covariance in policy diffusion: Evidence from the adoption of hyperlocal air quality monitoring programs by US cities

被引:3
|
作者
Qamar, Farid [1 ,2 ,3 ]
Pierce, Andrea L. [1 ,4 ]
Dobler, Gregory [1 ,3 ,5 ]
机构
[1] Univ Delaware, Biden Sch Publ Policy & Adm, Newark, DE 19716 USA
[2] Univ Delaware, Dept Civil & Environm Engn, Newark, DE 19716 USA
[3] Univ Delaware, Data Sci Inst, Newark, DE 19716 USA
[4] Univ Delaware, Dept Geog & Spatial Sci, Newark, DE 19716 USA
[5] Univ Delaware, Dept Phys & Astron, Newark, DE 19716 USA
关键词
Covariance; Multicollinearity; Policy diffusion; Air quality monitoring; Local government; MCMC; CLIMATE-CHANGE; CALIFORNIA CITIES; GLOBAL DIFFUSION; DURATION MODELS; CLEAN HEAT; INNOVATION; STATE; IMPLEMENTATION; PROTECTION; ENERGY;
D O I
10.1016/j.cities.2023.104363
中图分类号
TU98 [区域规划、城乡规划];
学科分类号
0814 ; 082803 ; 0833 ;
摘要
The diffusion of urban policy may occur through multiple mechanisms with complex interactions that obscure the interpretation of independent effects. In this work, we present a case study to explore the potential impact of covariance on the identification of the independent effects of the explanatory variables. We explore the influence of multiple diffusion mechanisms: learning, imitation, and coercion; policy mobility factors; and internal de-terminants on the likelihood of hyperlocal air quality monitoring program (HAMP) adoption by large cities in the US with a population >300,000 over the past decade. In general, results imply the adoption of HAMPs over the past decade has been motivated by sociopolitical rather than environmental goals. However, comparing the outcomes of a common, but limited, method to detect covariance and those from an expanded systematic var-iable selection exploration, shows that a third of the variables have covariance effects that can alter their impact and level of significance. The absence of coercion is found to lead to half of the variables exhibiting different results. These results highlight the importance of variable selection methods in determining a variable's sig-nificance and impact on the likelihood of policy adoption.
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收藏
页数:16
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