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Interest system density influences internal dynamics within interest organizations, how they lobby, and policy conditions. But how do political conditions influence interest system density? How does politics create demand for interest representation? We examine these questions by assessing how legislative party competition and ideological distance between parties in state legislatures affect the number of lobby groups. After stating our theoretical expectations, we examine 1997 and 2007 data on legislative competition and party polarization to assess their influence on system density. We find mixed results: Whereas politics slightly influenced the structuring of nonprofit interest communities, they seem to have not affected the structuring of for-profit interest communities or interest communities as a whole.

Leading theories of grassroots lobbying assert that legislators should respond positively to the volume of grassroots lobbying messages because volume indicates the salience of an issue among constituents. This notion rests on the idea that the costs of producing a large volume of grassroots lobbying signals the value of the information to legislators. Advances in technology and strategy, however, have flattened the costs associated with producing such information—it costs much less to generate one additional e-mail message than before. In this environment, the volume of grassroots lobbying no longer signals the value of the information it contains. Instead, I believe trust becomes the critical factor in evaluating grassroots lobbying. I test this theory using a survey of state legislators. I find that lobbying message volume has no effect on legislator responses to higher salience issues, and a negative effect on lower salience issues.

Two very different kinds of models—cross-sectional models based on the logic of island biogeography and time series models of density dependence—are used to understand interest system density. While they share much in common, it is not at all clear how results derived from cross-sectional models are to be understood in terms of the temporal focus of the time series approach. Thus, the first purpose of this article is to more thoroughly think through how these two modeling strategies and their empirical findings are related to each other. We empirically assess several theoretical conjectures about the relationship of the two modeling strategies by adding a temporal element to the typical cross-sectional analysis of state interest systems via modeling density dependence pooled across four cross-sections from 1980, 1990, 1997, and 2007. By doing so, we add to the literature on state interest system density by examining how it has changed since 1980. Finally, we discuss the nature of this change and what it implies for the temporal development of state interest communities, the second focus of this analysis.