Geographic Proximity in the Diffusion of Concealed Weapons Permit Laws

Tucker, Justin A.; Stoutenborough, James W.; Beverlin, R. Matthew

doi:10.1111/j.1747-1346.2012.00399.x

Cited by 12 publications

(6 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both theory and previous research support the contention that states do not act independently when enacting legislation, even after accounting for states’ similarities 26 . As a result, we formulate a class of social network models in which each state's legislative actions can impact those of other states.…”

Section: Methodsmentioning

confidence: 52%

Modeling State Firearm Law Adoption Using Temporal Network Models

CLARK,

MACINKO,

PORFIRI

2023

Milbank Quarterly

View full text Add to dashboard Cite

Policy Points Promoting healthy public policies is a national priority, but state policy adoption is driven by a complex set of internal and external factors. This study employs new social network methods to identify underlying connections among states and to predict the likelihood of new firearm‐related policy adoption given changes to this interstate network. This approach could be used to assess the likelihood that a given state will adopt a specific new firearm‐related law and to identify points of influence that could either inhibit or promote wider diffusion of specific laws. ContextUS states are largely responsible for the regulation of firearms within their borders. Each state has developed a different legal environment with regard to firearms based on different values and beliefs of citizens, legislators, governors, and other stakeholders. Predicting the types of firearm laws that states may adopt is therefore challenging.MethodsWe propose a parsimonious model for this complex process and provide credible predictions of state firearm laws by estimating the likelihood they will be passed in the future. We employ a temporal exponential‐family random graph model to capture the bipartite state law–state network data over time, allowing for complex interdependencies and their temporal evolution. Using data on all state firearm laws over the period 1979–2020, we estimate these models’ parameters while controlling for factors associated with firearm law adoption, including internal and external state characteristics. Predictions of future firearm law passage are then calculated based on a number of scenarios to assess the effects of a given type of firearm law being passed in the future by a given state.FindingsResults show that a set of internal state factors are important predictors of firearm law adoption, but the actions of neighboring states may be just as important. Analysis of scenarios provide insights into the mechanics of how adoption of laws by specific states (or groups of states) may perturb the rest of the network structure and alter the likelihood that new laws would become more (or less) likely to continue to diffuse to other states.ConclusionsThe methods used here outperform standard approaches for policy diffusion studies and afford predictions that are superior to those of an ensemble of machine learning tools. The proposed framework could have applications for the study of policy diffusion in other domains.

show abstract

Section: Methodsmentioning

confidence: 52%

Modeling State Firearm Law Adoption Using Temporal Network Models

CLARK,

MACINKO,

PORFIRI

2023

Milbank Quarterly

View full text Add to dashboard Cite

show abstract

“…Tucker and others (2012) find that neighboring jurisdictions often adopt similar policies. They use the diffusion of shall‐issue permit laws, which require a state to provide a good reason why an applicant's concealed carry permit should be denied.…”

Section: Resultsmentioning

confidence: 96%

“…They use the diffusion of shall-issue permit laws, which require a state to provide a good reason why an applicant's concealed carry permit should be denied. Rather than a morality policy, the authors conceptualize gun control as a social regulatory policy, in which advocacy groups often play a big role in aiming to "modify existing beliefs and values as well as regulate behaviour through the law" (Tucker et al, 2012(Tucker et al, , p. 1085. These policies spread more quickly across neighboring jurisdictions than the authors would have expected, independent of the levels of NRA lobbying.…”

Section: Policy Diffusion and Feedbackmentioning

confidence: 99%

Taking stock: The contribution of policy studies to our understanding of gun policy

Schwartz

2023

Politics & Policy

View full text Add to dashboard Cite

In the summer of 2022, the tragic mass shooting in Uvalde, Texas once again thrust firearms policy onto the public agenda and opened an agenda window for bipartisan gun reforms in the Senate. Almost simultaneously, the Supreme Court struck down restrictions on concealed carry in New York state in the first major ruling on Second Amendment Rights since MacDonald v. Chicago. Given the salience of firearms policy to contemporary policy debates, it is important to take stock of how the discipline of policy studies has contributed to our understanding of this pressing area of policy. As we see, scholars of policy studies have largely left discussions of firearms policy to disciplines like criminology, sociology, economics, and public health. Despite this, a small group of scholars has used the theoretical toolkit of our discipline to better understand this issue. This short review article will present the contribution of policy studies to our understanding of firearms policy from Sandy Hook to Uvalde and provide suggestions for areas where the discipline can contribute to our understanding of this vitally important regulatory issue. Most importantly, more work is needed to develop robust and multidimensional evaluations of firearms policies. Related Articles Cook, Philip J., and Jens Ludwig. 2019. “Understanding Gun Violence: Public Health vs. Public Policy.” Journal of Policy Analysis and Management 38(3): 788–95. https://doi.org/10.1002/pam.22141. Haider‐Markel, Donald P., and Mark R. Joselyn. 2017. “Special Issue Editors' Introduction: Gun Politics.” Social Science Quarterly 98(2): 377–81. https://doi.org/10.1111/ssqu.12415.

show abstract

“…My quantitative analysis employs event history analysis, otherwise known as survival regression. Event history analysis is a standard technique for the quantitative analysis of diffusion widely used across subfields of political science (Berry and Berry, ; Bush, ; Francesco, ; Kim, ; Shipan and Volden, ; Sugiyama, ; Tucker et al ., ). Event history analysis permits inferences about the influence of covariates on the probability of some event occurring, allows for the incorporation of time‐varying covariates, and handles right‐censored data (i.e., units in which the event of interest did not occur during the entire period of observation) (Box‐Steffensmeier and Jones, ).…”

Section: Quantitative Analysismentioning

confidence: 97%

International Coercion and the Diffusion of Regulatory Data Protection

Michael¹

2016

World Intellectual Property

View full text Add to dashboard Cite

Prior to 1990, regulatory data protection existed only in 14 highly developed countries. Since then, 60 additional countries have adopted regulatory data protection. New adopters include a large number of countries with no domestic pharmaceutical industry. These countries will face higher pharmaceutical prices as a result of offering regulatory data protection. Why would countries that stand to lose from offering regulatory data protection choose to do so? The author argues that the global diffusion of regulatory data protection can be directly traced to international coercion from the United States and the European Union (EU). The US coerces weaker trading partners into adopting regulatory data protection by requiring such protection as a condition of concluding trade agreements or bilateral intellectual property agreements. Meanwhile, the EU coerces applicants by demanding that they adopt such rights during EU accession negotiations, on average four years prior to accession. He tested these claims using a multi-method research design that combines event history analysis with evidence from leaked US diplomatic cables and public EU accession documents. His findings demonstrate that coercive diffusion can take place by means of threats, and that countries often actively oppose adopting intellectual property rights, but nevertheless adopt them due to international coercion.

show abstract

Geographic Proximity in the Diffusion of Concealed Weapons Permit Laws

Cited by 12 publications

References 40 publications

Modeling State Firearm Law Adoption Using Temporal Network Models

Modeling State Firearm Law Adoption Using Temporal Network Models

Taking stock: The contribution of policy studies to our understanding of gun policy

International Coercion and the Diffusion of Regulatory Data Protection

Contact Info

Product

Resources

About