<i>Duration Dependence, Functional Form, and Corrected Standard Errors: Improving EHA Models of State Policy Diffusion</i>

Buckley, Jack; Westerland, Chad

doi:10.1177/153244000400400105

Cited by 95 publications

(87 citation statements)

References 36 publications

(41 reference statements)

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“…Strategic interaction between neighbors is said to occur when the levels of policy variables in one jurisdiction are influenced by the levels of those variables in neighboring jurisdictions (Ghosh 2010). The neighbor-induced diffusion theory of policy diffusion does include some important dynamic mechanisms such as spatial autocorrelation (Buckley and Westerland 2004), spatial heterogeneity (Meseguer and Gilardi 2009), neighborhood emulation and dynamics (Gu 2014) in the process of policy diffusion. Therefore, the neighbor-induced diffusion study on policy diffusion can gain insight into what drives policy diffusion between neighboring jurisdictions.…”

Section: Literature Review and Theoretical Frameworkmentioning

confidence: 99%

Spatial Diffusion of Social Policy in China: Spatial Convergence and Neighborhood Interaction of Vocational Education

2015

Appl. Spatial Analysis

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There has been a vast amount of discussion about the positive and negative regional effect on policy diffusion. During this debate, the role of neighborhood structure is ignored and the linear assumption is still prevailing in this field. By analyzing the spatial convergence of local vocational education development with data of 31 provinces from 1995 to 2008 in China, we explore the effects of neighborhood interactions on policy diffusion, paying specific attention to the dynamical role of neighborhood structures in policy diffusion. The empirical results clearly indicate that the development of local vocational education systems in China is spatially autocorrelated to the neighboring provinces. Local vocational education systems converge more slowly if a spatially lagged dependent variable is introduced, while they converge faster if a spatially error variable is introduced. The policy transition between neighbors considering their local spatial context is analyzed with Spatial Markov Chain and a fundamental nonlinear connection between neighborhood structure and policy transition is unveiled. Using spatial econometric models, we also find that the sociospatial diffusion patterns with the social factors such as consumption, urban/rural distribution and occupation serve as barriers to and amplifiers of policy diffusion. These results not only resonate with conventional linear wisdom on policy diffusion but also offer a new nonlinear perspective on socio-spatial patterns of policy diffusion that are clearly embedded within the local neighborhood structures.

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Section: Literature Review and Theoretical Frameworkmentioning

confidence: 99%

Spatial Diffusion of Social Policy in China: Spatial Convergence and Neighborhood Interaction of Vocational Education

2015

Appl. Spatial Analysis

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“…In contrast, external determinants include the influences of other jurisdictions that have previously adopted the policy (diffusion), higher-level governments, or other outside groups (Berry & Berry, 2007;Gray, 1994). Hybrid models considering both internal and external determinants have been applied to adoption of lotteries (Buckley & Westerland, 2004), health care programs (Satterthwaite, 2002), and climate change policy (Pitt, 2010), but such analysis of zoning is lacking.…”

Section: Local Land-use Regulationmentioning

confidence: 99%

Factors influencing zoning ordinance adoption in rural and exurban townships

Locke

Rissman

2015

Landscape and Urban Planning

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“…In statistics, cloglog function is defined as g(x) = 1 − exp[− exp(x)] and it is a discrete analog of the log-logistic hazard function. It is particularly suitable for data with few nonzero outcomes due to the asymmetry of its tails: the right tail converges to one more quickly than the left tail converges to zero, so that the positive values are given more weight (Buckley and Westerland, 2004).…”

Section: Methodsmentioning

confidence: 99%

Effectiveness of Bailouts in the EU

Glowicka¹

2006

SSRN Journal

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Governments in the EU frequently bail out firms in distress by granting state aid. The results are threefold. First, the estimated discrete-time hazard rate increases during the first four years after the subsidy and drops after that, suggesting that some bailouts only delayed exit instead of preventing it. The number of failing bailouts could be reduced if European control was tougher. Second, governments' bailout decisions favored state-owned firms, even though state-owned firms did not outperform private ones in the survival chances. Third, subsidy choice is an endogenous variable in the analysis of the hazard rate. Treating it as exogenous underestimates its impact on the bankruptcy probability. Several policy implications of the results are discussed in the paper.

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Duration Dependence, Functional Form, and Corrected Standard Errors: Improving EHA Models of State Policy Diffusion

Cited by 95 publications

References 36 publications

Spatial Diffusion of Social Policy in China: Spatial Convergence and Neighborhood Interaction of Vocational Education

Spatial Diffusion of Social Policy in China: Spatial Convergence and Neighborhood Interaction of Vocational Education

Factors influencing zoning ordinance adoption in rural and exurban townships

Effectiveness of Bailouts in the EU

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