This article examines the relationship between legislative civility and legislative productivity in US state legislatures. The research employs data from the National Survey of State Legislative Lobbyists and from the State Policy Innovation and Diffusion (SPID) database. The former dataset is used to generate an overall civility index for each state as developed by Kettler et al. The SPID database allows one to measure the legislative productivity of a state legislature. Employing these data, negative binomial and Poisson regression models reveal that state legislatures rated as more civil by their own lobbyists produced significantly more pieces of noteworthy legislation than those legislative bodies rated as less civil. These results suggest that the quality of internal legislative dynamics matters for legislative productivity.

During the most recent round of redistricting, many states have enacted a number of reforms to their mapmaking practices. One reform that has received increased attention in recent years is a ban on prison gerrymandering—the practice of counting incarcerated individuals in prisons instead of their home addresses. Eleven states drew districts while counting incarcerated persons in their homes after the 2020 Census. Though substantial research has investigated redistricting practices, far less attention has been paid to empirically examining the effect of prison gerrymandering on elections. We seek to fill this void by evaluating the effect of New York’s ban on prison gerrymandering on state legislative elections between 2002 and 2020. We find that altering how the prison population is counted, indeed, altered the electoral dynamics across the state.

This article contributes to our understanding of policy diffusion in two ways. First, by explicitly focusing on the competition mechanism of diffusion, I consider how policy externalities contribute to free-rider dynamics or competitive races across the American states. The second contribution is the focus on the interdependence of the early stages of agenda setting as well as policy enactments. Using a unique dataset on four different types of tobacco policies that are introduced and eventually enacted in the states from 1990 to 2010, I find evidence that states engage in free-riding dynamics and that strategic interaction exists in the early stages of agenda setting. There is also evidence that states respond to legitimate policy threats in neighboring states. Overall, the results stress the importance of scholars to explore the conditional nature of policy diffusion dynamics by focusing on variations in policy content and stages of the policymaking process other than policy enactment.

This article puts forward four strategies to improve policy diffusion research in political science: (1) use existing concepts consistently and improve their measurement, (2) clarify whether the goal is to improve the understanding of diffusion itself or to use diffusion research to explain another phenomenon, (3) pay more attention to the quality of the research design, and (4) discuss explicitly the practical implications of diffusion. Taken together, these recommendations trace a distinctive way forward for policy diffusion research.

Pooled event history analysis (PEHA) allows researchers to study the effects of variables across multiple policies by stacking the data and estimating the parameters in a single model. Yet this approach to modeling policy diffusion implies assumptions about homogeneity that are often violated in reality, such that the effect of a given variable is constant across policies. We relax this assumption and use Monte Carlo simulations to compare common strategies for modeling heterogeneity, testing these strategies with increasing levels of variance. We find that multilevel models with random coefficients produce the best estimates and are a significant improvement over other models. In addition, we show how modeling similar policies as multilevel structures allows researchers to more precisely explore the theoretical implications of heterogeneity across policies. We provide an empirical example of these modeling approaches with a unique data set of 29 antiabortion policies.

Despite many important recent advances in the study of policy diffusion, this research has devoted limited attention to what happens after the adoption decision. This article attempts to fill this gap in diffusion research by examining the adoption and subsequent modification of “Three Strikes and You're Out” laws in the American states. Its analysis suggests that distinct political forces affected state-level outcomes at these two stages of the policymaking process. The rapid spread of Three Strikes laws in the 1990s seems to have occurred because states with more conservative leanings and higher proportions of African-American residents gravitated to a salient and visible policy. In contrast, the modification of Three Strikes laws appears to have been encouraged by financial necessity and shifting ideological environments but hindered by the mobilization of stakeholders with an interest in preserving the status quo, including private prison operators and prison officer unions. The contrast illustrates the usefulness of treating policy diffusion as a multistage process, and the stakeholder mobilization results provide empirical support for recent theorizing about policy feedback effects.

Local option sales taxes have become an important source of local revenue across the United States. Thirty-three of the 50 states have granted authorization to their counties or cities (or both) to levy local option sales taxes, and said taxes generated nearly $50 billion in 2005, which accounted for 11% of all local tax revenue nationwide. Even though local option sales taxes have significant impacts on a county's ability to fund programs and services, little has been written about the decisions of counties to place such taxes on the ballot. Using demographic, fiscal, and political variables, a model is developed that explains the decision to place a county transportation sales tax on the ballot. Modeling and analysis reveal that counties behave strategically as the impact of demographic, fiscal, and political factors on the decision to place a local option sales tax on the ballot is shaped by whether the county is making an initial attempt to adopt, a subsequent attempt to adopt after voter rejection, or a renewal attempt when an existing local option sales tax is nearing its sunset date.

How do the American states vary in their propensity for innovativeness, or their willingness to adopt new policies sooner or later relative to other states? Most studies today use event history analysis (EHA) to focus almost exclusively on one policy area at a time at the expense of a broader understanding of innovativeness as a characteristic of states. To return to the concept of innovativeness more broadly, our study revisits and updates the original approach taken by Walker by updating his average innovation scores with new data covering more than 180 different policies. We use these data to construct a new, dynamic measure of innovativeness that addresses biases and shortcomings in the original measure and we provide measures of uncertainty for both. These new scores build on the logic of EHA to address issues such as right-censoring and to facilitate measuring changes in innovativeness over time. We then compare the two measures of innovativeness and evaluate differences across states, spatial patterns, and changes in innovativeness over time.

This article sheds new light on policy diffusion by exploring policy complexity in state-level lesbian, gay, bisexual, and transgender (LGBT) antidiscrimination policies. The multiple component event history approach taken in this research allows for the concurrent study of both policy content and the factors that affect policy adoption. Results reveal that the factors influencing policy adoption vary depending on both the content and scope of the policy in question. In addition to addressing laws that protect gay people from discrimination, this article is one of the first studies in the political science and policy literature to empirically investigate the spread of transgender-inclusive laws. Despite combined advocacy and public conflation of identities, gay and transgender-inclusive laws appear to be influenced by different internal and external factors.