Frederick J. Boehmke

Disentangling Diffusion: The Effects of Social Learning and Economic Competition on State Policy Innovation and Expansion

When modeling regional policy diffusion effects, scholars have traditionally made appeals to both social learning and economic competition as causes of diffusion. In their empirical studies of policy adoption, however, they do not attempt to determine which of these two processes are at work. In this article, we argue that these two types of diffusion may have different implications for when a state first adopts a policy and subsequent changes in the extent of that policy and that these effects vary by policy area. In the specific policy area that we study, Indian gaming, we expect social learning diffusion to influence adoption but not expansion; economic competition should influence both policy adoption and policy expansion. Our empirical results confirm these predictions. To study both policy adoption and innovation, we apply models for event counts to state policy data, which allows us to model the extent of policy adoption over time, rather than just the timing of first adoption as is common with event history models.

State Policy Innovativeness Revisited

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.

The Effect of Direct Democracy on the Size and Diversity of State Interest Group Populations

This article studies the effect of direct democracy on the size and diversity of state interest group populations, providing an empirical test of a formal model of how access to the initiative process affects group formation and activities (Boehmke 2000). The model predicts that more groups mobilize and become active in initiative states; this prediction is confirmed by the regression analysis in this paper: direct democracy increases a states interest group population by about 17%. With an additional assumption, I also generate and test the hypothesis that the increase is disproportionately centered among traditionally underrepresented citizen groups, relative to business and economic groups. This hypothesis is also empirically supported: citizen interest group populations are increased by 29% whereas the increase is only 12% for economic groups, suggesting that direct democracy increases diversity in interest group representation.

Policy Emulation or Policy Convergence? Potential Ambiguities in the Dyadic Event History Approach to State Policy Emulation

I demonstrate a source of bias in the common implementation of the dyadic event history model as applied to policy diffusion. This bias tends to severely overstate the extent to which policy changes depend on explicit emulation of other states rather than on a states internal characteristics. This happens because the standard implementation conflates policy emulation and policy adoption: since early adopters are policy leaders, later adopters will appear to emulate them, even if they are acting independently. I demonstrate this ambiguity analytically and through Monte Carlo simulation. I then propose a simple modification of the dyadic emulation model that conditions on the opportunity to emulate and show that it produces much more accurate findings. An examination of state pain management policy illustrates the inferential differences that arise from the appropriately modified dyadic event history model.

Approaches to Modeling the Adoption and Diffusion of Policies with Multiple Components

Scholars have begun to move beyond the dichotomous dependent variable–indicating whether a state adopts a policy or not in a given year–usually employed in event history analysis. In particular, they have devoted increasing attention to the components of policies that states adopt. I discuss a variety of estimators that have been employed to analyze the adoption and modifcation of policies with multiple components, including various forms of event history analysis, OLS, and event count models. With various modifications, the researcher can estimate models that treat each component as distinct, pool these models to leverage commonalities across components, or treat the components as identical parts of the same process. Each of these has its strengths and may be appropriate in certain circumstances. Nonetheless, in the majority of cases, some version of event history analysis for multiple or repeat failures is likely to be preferred. The different approaches are illustrated by studying state adoption of various obesity-related policies.

Sources of Variation in the Frequency of Statewide Initiatives: The Role of Interest Group Populations

In this article I study the factors that determine the number of initiatives that appear on statewide ballots, with an emphasis on the characteristics of state interest group populations. In particular, I test whether the size of state citizen or economic group populations influences the frequency of initiative use. The relationship between these two categories of groups and initiative use is important in light of recent claims that the initiative process no longer benefits citizen groups and is now dominated by economic interests. In addition, I consider the role of other factors, including initiative regulations, state political characteristics, state economic performance and state demographic characteristics. My results indicate that states with more citizen groups have more initiatives overall and in specific issue areas and that the number of economic groups has a negative or negligible effect.

Business as usual: interest group access and representation across policy-making venues

We provide the first comprehensive study of lobbying across venues by studying interest group registrations in both the legislative and administrative branches. We present four major findings based on Federal and state data. Firstly, groups engage in substantial administrative lobbying relative to legislative lobbying. Secondly, the vast majority of groups lobby the legislature, but a large proportion of groups also lobby the bureaucracy. Thirdly, representational biases in legislative lobbying are replicated across venues: business groups dominate administrative lobbying at least as much as they do legislative lobbying. Finally, the level of interest group activity in one venue for a given policy area is strongly related to its level in the other venue. The findings potentially have important implications for the impact of institutional design on both the form and promotion of broad participation in policy-making as well as the ultimate content of policies chosen by democratic governments, broadly construed.

Whose Ear to Bend? Information Sources and Venue Choice in Policy-Making

Important conceptualizations of both interest groups and bureaucratic agencies suggest that these institutions provide legislatures with greater information for use in policy-making. Yet little is known about how these information sources interact in the policy process as a whole. In this paper we consider this issue analytically, and develop a model of policy-making in which multiple sources of information – from the bureaucracy, an interest group, or a legislatures own in-house development – can be brought to bear on policy. Lobbyists begin this process by selecting a venue – Congress or a standing bureaucracy – in which to press for a policy change. The main findings of the paper are that self-selection of lobbyists into different policy-making venues can be informative per se, and that this self-selection can make legislatures prefer delegation to ideologically distinct bureaucratic agents over ideologically close ones. Changes within the FederalTrade Commission during the 1970s are reinterpreted in the context of our model.

Direct Democracy and Individual Interest Group Membership

Direct democracy has been shown to increase the number and diversity of interest groups in American states, but no research has extended this finding to the individual level. Direct democracy may influence individual joining behavior through three distinct processes: first, by affecting the interest group population in a state, direct democracy should increase opportunity for joining. Second, direct democracy opens new policy areas for representation, which may increase the scope and level of political conflict and draw in new participants. Third, by providing more opportunities for involvement in policymaking, direct democracy may create a more engaged citizenry, spurring the joining of groups. We utilize data from the pooled General Social Survey merged with state-level measures of the presence and use of the initiative process. Using multilevel modeling to test the initiative’s effect on individual joining behavior, we find that the initiative does indeed foster greater levels of group membership.

Persistent Policy Pathways: Inferring Diffusion Networks in the American States

The transmission of ideas, information, and resources forms the core of many issues studied in political science, including collective action, cooperation, and development. While these processes imply dynamic connections among political actors, researchers often cannot observe such interdependence. One example is public policy diffusion, which has long been a focus of multiple subfields. In the American state politics context, diffusion is commonly conceptualized as a dyadic process whereby states adopt policies (in part) because other states have adopted them. This implies a policy diffusion network connecting the states. Using a dataset of 187 policies, we introduce and apply an algorithm that infers this network from persistent diffusion patterns. The results contribute to knowledge on state policy diffusion in several respects. Additionally, in introducing network inference to political science, we provide scholars across the discipline with a general framework for empirically recovering the latent and dynamic interdependence among political actors.