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A Statistical Analysis of Lobbying Networks in Legislative Politics∗

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A Statistical Analysis of Lobbying Networks in Legislative Politics∗ Mapping Political Communities: A Statistical Analysis of Lobbying Networks in Legislative Politics∗ In Song Kimy Dmitriy Kuniskyz January 3, 2018 Abstract A vast literature demonstrates the significance for policymaking of lobbying by special inter- est groups. Yet, empirical studies of political representation have been limited by the difficulty of observing a direct connection between politicians and interest groups. We bridge the two with an original dataset of two distinct observable political behaviors: (1) sponsorship of con- gressional bills, and (2) lobbying on congressional bills. We develop a latent space network model to locate politicians and interest groups in a common \marketplace", where proximity implies a closer political connection or alignment of interests. In contrast to repeated find- ings of ideological latent dimensions in previous literature on such models, we find distinct issue-specific political communities of interest groups and politicians. To validate the existence and interpretation of the community structure, we apply stochastic block models and a bipar- tite link community model to explicitly model political actors' community memberships. We consistently find that the latent preference structure of politicians and interest groups is non- ideological and primarily corresponds to industry interests and topical congressional committee memberships. Our findings therefore provide evidence for the existence of powerful political networks in U.S. legislative politics that do not align with the ideological polarization observed in electoral politics. Keywords: Network analysis, lobbying, ideal point estimation, scaling, stochastic block model, link community model, community detection. ∗We thank J. Lawrence Broz, Devin Caughey, Nolan McCarty, Cristopher Moore, Michael Peress, Yunkyu Sohn, and Hye Young You for helpful comments. Kim acknowledges financial support from the National Science Foundation (SES-1264090 and SES-1725235). yAssistant Professor, Department of Political Science, Massachusetts Institute of Technology, Cambridge, MA, 02139. Email: [email protected], URL: http://web.mit.edu/insong/www/ zPh.D. Student, Department of Mathematics, Courant Institute of Mathematical Sciences, New York University, New York, NY, 10012. Email: [email protected]. 1 Introduction Special interest groups engage in lobbying to promote their political objectives (e.g., Wright, 1990; Grossman and Helpman, 2001).1 A dominant view among political scientists holds that interest groups take part in such costly political activity in order to retain access to policymakers, and in return policymakers gain an effective means of informing their legislative decisions (Bauer, Dexter, and Poll, 1972; Potters and Van Winden, 1992; Austen-Smith and Wright, 1992; Austen-Smith, 1995; Wright, 1996; Ansolabehere, Snyder, and Tripathi, 2002). Others argue that lobbying serves instead as a \legislative subsidy" through which lawmakers work with their \allies" to achieve a common objective (Hall and Deardorff, 2006). In either case, despite the significance of political connections between interest groups and politicians (Khwaja and Mian, 2005; Faccio, Masulis, and McConnell, 2006; Faccio, 2006; Kang and You, 2017), empirical studies of legislative politics have been limited by the difficulty of directly observing these political ties, let alone the actual policy context in which they are formed. In this article, we identify a type of political connection that can be observed tractably between every Member of Congress and every actively lobbying special interest group. We construct a large network dataset of lobbying activity on 108,086 congressional bills introduced between the 106th and the 114th Congress. Our data is unique in joining two distinct types of political behavior around each bill: (1) sponsorship2 by a politician, and (2) lobbying by interest groups. Based on how often politicians and interest groups performing these two political activities coincide on individual bills, we infer the structure of political networks underlying the legislative process of the U.S. Congress. Although lobbying on a single bill does not necessarily imply political ties to its sponsor, recurring instances of lobbying that involve the same interest group / sponsor pair across various bills, which our network data also captures, do reliably encode close political relationships.3 Figure 1 shows that numerous bills are introduced in each Congress, the majority of which are lobbied by at least one interest group. Furthermore, as the right panel shows, the distribution of the number of unique interest groups lobbying on a given bill is highly skewed to the right, implying that lobbied bills tend to reflect narrow interests and legislative expertise. A typical example: Mitch McConnell (R-KY) sponsored \A bill to exempt the aging process of distilled spirits from the production period for purposes of capitalization of interest costs" (113th S. 1457), and the 1We use the term special interest groups to refer to any political actors who have particular policy objectives, including firms, trade associations, labor unions, business associations, and professional associations. 2For evidence that sponsorship is likely to be a more reliable position-taking signal than the much less costly political action of cosponsorship, see e.g. Rocca and Gordon (2010). 3There is ample empirical evidence that lobbyists help to draft or even write bills on behalf of legislators with whom they have political connections (Nourse and Schacter, 2002). For an example, see http://westernpriorities. org/2016/05/09/how-much-did-rep-scott-tipton-copy-from-his-biggest-donor-this-much/. 1 Bills Introduced 14000 3000 12000 2500 10000 Bills Lobbied 2000 8000 1500 6000 Number of Bills 1000 4000 2000 500 Bills Voted Number of Bills in 113th Congress 0 0 106 108 110 112 114 0 50 100 150 200+ Congress Number of Unique Interest Groups Lobbying per Bill Figure 1: Descriptive Statistics of Lobbying on Congressional Bills. The left panel com- pares the numbers of bills introduced, lobbied, and voted on between the 106th and the 114th Congress. On average, about 12,000 bills are introduced in each Congress; only a very small subset of bills are eventually voted on the floor, while we identify the majority of bills as lobbied by at least one special interest group. Note that fewer bills are identified as lobbied prior to the 110th Congress, because lobbying report filing was not digitized until the Honest Leadership and Open Government Act of 2007 was passed. The right panel shows the distribution of the number of unique interest groups lobbying on each bill in the 113th Congress. The distribution is highly skewed: the median is three, the maximum is 978, and 25% of the lobbied bills are lobbied by only one interest group. Distilled Spirits Council of the U.S. was the only interest group to lobby on the bill.4 The main contribution of this paper is to develop statistical network models to determine whether certain interest groups frequently lobby the bills sponsored by particular legislators (or vice versa). First, we introduce a Bayesian latent space model to estimate a latent \ideal point" (or preferred policy) for each political actor. Unlike existing studies that rely on roll calls over just the small subset of bills that are voted on the floor (Poole and Rosenthal, 2011; Clinton, Jackman, and Rivers, 2004), we analyze all Senate and House bills5 and their sponsorship to infer the underlying policy preferences of legislators and interest groups. Our model bridges legislators and interest groups by locating them in a common \marketplace", in which proximity implies a closer alignment of interests. This approach is similar in methodology to recent studies that uncover ideal points of other political actors through various observable connections to legislators, such as campaign contributions and social media following (Bonica, 2013; Barber´a,2014; Bond and Messing, 2015). We find that the estimated preferred policy locations do not align with existing measures of ideology such as DW-NOMINATE scores (Poole and Rosenthal, 2011). Instead, we observe 4See Kim (2017) for similar patterns in trade bills. 5Many of the bills thought of as \dying" before being voted on are actually amended and merged with other bills that will be voted on the floor eventually, but our dataset allows us to observe political connections before this process takes place, and therefore at a finer granularity. 2 clustering of interest groups and legislators according to their industry affiliations and memberships in committees with jurisdiction over those industries, respectively. This is in contrast to repeated findings in the literature of ideologically-driven preferences for political actors based on other types of political behaviors and connections, such as roll call votes, campaign contributions, and cosponsorship (e.g., Clinton, Jackman, and Rivers, 2004; Fowler, 2006; Shor and McCarty, 2011; Bonica, 2013; Imai, Lo, and Olmsted, 2016). Yet, this result is consistent with Ansolabehere, Snyder, and Tripathi (2002), who find that the political actors who act mainly through lobbying are likely to be more bipartisan and less ideological than those who act mainly through campaign contributions. It also attests to the influence committees have over policy outcomes from the earliest stages of the legislative process (Shepsle and Weingast, 1987). Furthermore, we find that party control over Congress is an important determinant of the \popularity" of
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