Advocacy and influence: Lobbying and legislative outcomes in Wisconsin

Siena College From the SelectedWorks of Daniel Lewis Summer 2013 Advocacy and influence: Lobbying and legislative outcomes in Wisconsin Daniel C. Lewis, Siena College Available at: https://works.bepress.com/daniel_lewis/8/

Advocacy and Influence: Lobbying and Legislative Outcomes in Wisconsin

Executive Summary Gauging the influence of organized interests in the American legislative process is undeniably a difficult undertaking. Interest groups and their lobbyists have little incentive to publicly reveal their goals and extent of their efforts in pursuing those goals. Nationally, and in most states, lobbyists and interest groups are only required to publicly report their lobbying expenditures and the general policy area in which they are interested in. Thus, it is extremely difficult to assess whether groups are successful in advocating for or against a particular bill. However, a few states have recently begun to require lobbyists and organized interests engaged in lobbying to report each specific bill they have lobbied and, in Wisconsin, whether they support or oppose the bill. These enhanced reporting requirements allow for a more systematic assessment of interest group influence in the legislative process. This study exploits this new data to address the question of lobbying efficacy by examining the outcomes of a random sample of bills introduced in the Wisconsin state legislature during the 2007-2008 session. By looking systematically at the extent to which lobbying and advocacy efforts affect the outcomes of introduced legislation, the analyses are able to show that these efforts, contrary to some of the recent research, have significant effects. While contextual factors remain important, this study shows that advocacy efforts are influential in their own right. In addition, the analyses of this unique data reveal that several types of interest group activities (e.g., campaign contributions) vary in their degree of influence at different points in the legislative process.

Assessing the influence of organized interests in the American policy process is, undoubtedly, a difficult undertaking. Early theories of organized interests, pluralism (e.g., Truman, 1951) and transactionism (e.g., Schattschneider, 1960; Olson, 1965), implicitly assume that groups, once successfully mobilized, do wield significant policy influence. Public perceptions of group influence support these perspectives, with 69 percent of Americans in 2008 agreeing that government is run by a few big interests (American National Election Studies, 2008). Yet, more recent neopluralist theoretical treatments challenge this assumption (Lowery and Gray, 2004), arguing instead that interest group influence is rather limited and contingent upon contextual factors (e.g., Heinz et al., 1993; Baumgartner and Leech, 1998). Empirical research, meanwhile, tends support this latter perspective, showing little evidence of the type of the extensive influence that undergirds the previous approaches to studying organized interests (e.g., Baumgartner et al., 2009). Still, it is unclear whether the prevalence of null findings produced by contemporary empirical research can be unequivocally used to support theories that place organized interests at the periphery of the policy process. Heinz and colleagues (1993) and Baumgartner and colleagues (2009) caution that measurement and methodological limitations remain formidable obstacles to studying organized interests. Organized interests have little incentive to publicly reveal their goals and extent of their efforts in pursuing those goals. Nationally, and in most states, lobbyists and interest groups are only required to publicly report their lobbying expenditures and the general policy area in which they are interested in. This makes an exhaustive, systematic assessment of fruits of these lobbying efforts in American governments exceedingly difficult to undertake. 1

However, one benefit of the negative public perceptions of lobbying is that states have recently enacted a broad series of ethics and lobbying reforms designed to make the lobbying enterprise more transparent. In many states, these reforms include requirements for lobbyists and organized interests to indicate not only the subject areas in which they lobby, but also the specific bills and administrative rules they are active on. A handful of states go even further, requiring lobbying registrants to also indicate the direction in which they are lobbying. This means that in states like Wisconsin and Rhode Island there are records of how every registered lobbyist and interest groups lobbied on every bill under consideration. Combined with bill history information, this data allows for a more comprehensive assessment of group influence, or more precisely, of group lobbying success. In this paper, I analyze this new type of lobbying registration data to answer the following question: Do lobbying activities affect the outcomes of bills introduced to state legislatures? Influence and Lobbying Success Much of the literature on organized interests focuses on the concept of influence. At the most basic level, organized interests are defined by their pursuit of policy goals (Lowery and Brasher, 2004). Organizations seek to realize these goals by influencing the behavior of public policy makers. Wright (1996) writes that influence begins at the point when legislators adjust their beliefs on the basis of lobbying information (p. 81). While this may seem straight-forward, it is often unclear what influence looks like, empirically. Policy makers can be influenced by a variety of factors, including party pressure, personal preferences, and constituency interests (e.g., Denzau and Munger, 1986; Cox and McCubbins, 2007). How do we know when policy decisions are shaped by organized interests or by these other factors? How do we know when policy makers adjust their beliefs base on lobbying efforts? 2

Some studies have sought to identify influence through Congressional roll call behavior, positing that votes that run counter to partisan and constituent preferences may be affected by group activities like campaign contributions and lobbying (e.g., Grenzke, 1989; Wawro, 2001). The focus on individual voting behavior produces little evidence of group influence. While null findings may indicate that organized interests are not influential, it may also indicate that lobbying efforts are not designed to change beliefs. Indeed, groups tend to focus most of their lobbying efforts on allies those policy makers that share their preferences or whose constituency shares their preferences (Bauer et al., 1963; Hojnacki and Kimball, 1998). Thus, it may be more appropriate to turn our attention to other stages of the policy process, like agenda setting, committee participation and policy implementation (Kingdon, 1984; Wright, 1996; Webb Yackee and Webb Yackee, 2006). Still, these approaches are often limited in that it is unclear what influence looks like. Also, it is not always evident that access and participation necessarily equate to policy influence. Each of the preceding approaches to assessing interest group and lobbying influence hone in on the production of policy. Yet these indicators of group influence, whether at the agenda setting stage or final voting stage of the legislative process, are all means to an end. An alternative approach is to conceptualize organized interests as driven by policy objectives. It is the ends that interest groups are ultimately concern about, not necessarily the means. Thus, this alternative approach examines the ability of groups to achieve their goals. In other words, are group lobbying efforts successful, regardless of tactics used to achieve that success? Studies taking this approach have produced results that emphasize the contextual factors to group success when examining specific policies or policy areas (Heinz et al., 1993; Baumgartner et al., 3

2009). Organized interests tend to have only peripheral influence (though they may be more central in the long term). One limitation of these existing studies is that they rely on estimates of group goals, either through interviews or subjective evaluations. This makes a comprehensive analysis of the success that they have in achieving their goals difficult to undertake and analyses are necessarily limited to a sample of issues and organized interests. However, in states that require groups that lobby to report their policy goals, as they pertain to each bill they lobby, we can get a more systematic and comprehensive assessment of lobbying efficacy. Prior work using this new lobbying registration data focused on the success rates of individual groups (Lewis et al., 2011). This study found that group characteristics and lobbying effort had little to no impact on their lobbying success rates in a legislative session. Rather, the political context in which the groups lobbied namely, how often they supported the majority party and defended the status quo policy - determined how successful they were. This type of group-level analysis, however, may overlook the influence of lobbying on individual bills. It cannot account for the environmental factors surrounding each bill that a group lobbies and the aggregate effect of all lobbying activity on a particular bill. Here, I try to address this gap by examining whether the progress of individual bills through the legislative process is affected by the lobbying efforts of organized interests. Determinants of Lobbying Influence Though theories of organized interests and lobbying often yield competing conclusions about the nature of group influence, they do provide guidance about the factors that might affect whether organized interests can affect the legislative process. Three contrasting theoretical 4

perspectives to lobbying provide insight to the determinants of lobbying influence, with a focus on the efforts of organized interests. The vote-buying perspective suggests that groups that contribute to electoral campaigns and spend more on lobbying efforts are more likely to achieve their lobbying goals through implicit trades and increased access (e.g., Langbein, 1986; Stratmann, 1991; Stratmann, 2005). Though the literature generally finds little empirical evidence of group contributions significantly altering the voting behavior of legislators (Grenzke, 1989; Wawro, 2001), studies have found strong links between contributions and legislative agendas (Hall and Wayman, 1990; Powell, 2012). Thus, organized interests that can spend more on campaigns and lobbying should be more likely to achieve their policy goals by increasing their access to the legislative process. Another theoretical perspective conceptualizes lobbying as persuasion (e.g., Hansen, 1991; Austen-Smith and Wright, 1994). Rather than viewing lobbying as an exchange of benefits, this approach places an emphasis on information and reputation. It follows that groups which spend more time in direct communication and have more lobbyists with positive reputations should be more likely to be successful. The emphasis on information may also suggest that the number of groups lobbying on each side of issue would provide important cues to legislators about the relative popularity of a bill. The last theoretical perspective views lobbying as legislative subsidy (Hall and Deardorff, 2006). Similar to the service bureau conception of lobbying (Bauer et al., 1963), this approach sees lobbying as a way to supplement a legislator s efforts and, by doing so, allow the legislator to spend more time on the issues important to the group. This approach emphasizes the ability of a group to spend significant time (and money) on both direct communication and other efforts. The reputations of the lobbyists are less important, as the goal 5

of lobbying is not persuasion, but legislative assistance. Thus, groups that spend more time in their lobbying activities should be more successful. Finally, neopluralist theories place an emphasis on the context of the lobbying environment (Lowery and Gray, 2004). This may be reflected in varying success of different organized interests across issue areas and economic sectors (Rothenberg, 1992; Kollman, 1998). It is also reflected in the location of the status quo policy (Baumgartner et al., 2009). Groups generally have a defensive advantage when advocating against new policies because of the many obstacles to policy change. In addition, the preferences and partisan affiliations of policy makers can affect a group s lobbying success. Ideologically liberal groups should be more successful when they are lobbying in a policymaking environment controlled by like-minded policy makers. Partisanship may be even more important in most legislatures, as majority status gives parties a great ability to control the legislative agenda and policy access (e.g., Cox and McCubbins, 2007). Groups that share the policy goals of the majority party should be more successful in their lobbying efforts. Since new state lobbying registration laws require groups to disclose their positions on bills they lobby, we can examine the lobbying activity on every bill introduced to the legislature and the factors that influence their outcomes. With this new data it is possible to empirically evaluate the implications of many theories of organized interests and lobbying. In addition, this data can be used to broadly evaluate the nature of organized interest influence in state legislatures. In the following analyses, I exploit the new lobbying reporting requirements in the Wisconsin state legislature to test whether lobbying activities affect the outcomes of legislative bills. 6

Data & Hypotheses To examine the lobbying influence of interest groups in the Wisconsin state legislature, I collected lobbying registration data provided by the Government Accountability Board from the 2007-2008 session. 1 All organizations that employ an individual, who for compensation communicates with state officials to attempt to influence state legislation or administrative rulemaking on its behalf on five or more days must register (Government Accountability Board, 2010). Each organization registered to lobby provides the number of lobbyists employed (or contracted with), total amount of lobbying expenditures (dollars), total hours spent communicating with legislators or their staff (direct lobbying), total hours spent on other lobbying-related efforts, each specific bill lobbied, the direction of their lobbying efforts, and the percent of their total effort spent on each bill. In the 2007-2008 session, 1,874 bills were introduced and 784 organizations registered to lobby. In this study, I analyzed a random sample of 300 bills. For each bill, I coded the final outcome on a five point ordinal scale: 1) died in committee; 2) died on the floor; 3) passed first chamber and died in second chamber s committee; 4) died on second chamber s floor; 5) Passes. Only 41 of these bills passed the legislature, with nearly half of the bills (145) not even making it out of committee. I then recorded the number of groups that had lobbied on the bill for its passage, against passage, or with no declared position. Similarly, I gathered the number of hours the groups had lobbied and the amount of money groups spent on lobbying the bill. Finally, I matched the lobbying registration data with campaign contribution data from the National Institute for Money in State Politics. 2 For each interest group, the total amount of campaign 1 http://ethics.state.wi.us/lobbyingregistrationreports/lobbyingoverviewprior.htm 2 http://www.followthemoney.org/ 7

contributions to legislative candidates (from either party) from the previous electoral cycle was recorded. On each bill, the campaign contributions were aggregated by the side of the bill (for, against, no position). Together, this data comprises the foundation for the lobbying activity variables used in the subsequent analyses (see Table 1). The extant literature suggests that these efforts should influence the outcomes of the legislative process, which implies the following hypotheses: H1) All else equal, a bill will be more likely to progress through the legislative process when there is more activity (number of groups, hours spent lobbying, spending on lobbying, and campaign contributions) in favor of passage. H2) All else equal, a bill will be less likely to progress through the legislative process when there is more activity (number of groups, hours spent lobbying, spending on lobbying, and campaign contributions) opposing passage. However, given the well-documented defensive advantage, an additional hypothesis can be made: H3) Lobbying activities by opponents of bills will have larger impact than activities by supporters. In addition to lobbying activity data, information on the context of each bill in the sample was also collected: the chamber of origin, the party of the primary sponsor, the position of the primary sponsor (committee chairs and party leaders), the number of cosponsors, whether the cosponsors included members of both parties and chambers, the subject of the bill, the original committee referral, and the date of introduction. 8

[Table 1 about here] Lobbying Activity and Bill Outcomes: Ordered Probit Analyses To test whether lobbying activities by interest groups have an effect on the progress of bills through the legislative process, I estimate a series of multiple regression models. I begin by modeling the five-point ordinal scale of the bill outcome as a function of the number of groups on lobbying on all sides of the bill (for, against, neutral), the amount of spending and hours spent lobbying on all sides of the bill, total campaign contributions on all sides of the bill, and contextual control variables (see Table 1). With an ordinal measure of the bill outcome, the models are estimated as ordered probit regressions. In addition to the measures of interest groups activity and contextual factors, the models also include fixed effects for the topic of each bill covering19 nineteen topics ranging from agriculture to veterans affairs. Further, to account for any bias stemming from the differences the committees to which the bills are assigned, I estimate robust standard errors clustered on the original committee referral (51 in total). Since the number of hours groups spent lobbying is highly collinear with the amount of spending by the groups, I estimate separate models using each indicator of lobbying activity one with spending variables and one with the variables gauging time spent lobbying. A third model is also estimated using a measure of advocacy efforts on each side of a bill generated from a principle components analysis of the number of groups, spending on lobbying and hours spent lobbying. The estimation results are presented in Table 2. In each of the models, the variables gauging lobbying activities (number of groups, spending, and hours spent lobbying) do not significantly affect how far a bill progresses through the legislative process. Instead, the models 9

suggest that campaign contributions and contextual factors drive the bill outcomes. As expected, bills sponsored by members of the majority party and committee chairs are more likely to progress through the legislative process. Bills introduced later on in the session are less likely to move out of their original committee and continue on through the process. [Table 2 about here] Though the advocacy efforts of groups that lobbied on these bills does not seems to affect the bill outcomes, campaign contributions on both sides of the bills do have a significant impact. The magnitude of the effects of campaign contributions from the third model are shown in Figure 1. 3 As suggested by the defensive advantage hypothesis, the effect of contributions on behalf of the side opposed to passage is larger than contributions from groups on the side in favor of passage. While the campaign contributions do show consistent effects on bill outcomes, it is important to be cautious interpreting these coefficients. Since the contributions are aggregated for each side, they are moderately correlated with the number of groups. Thus, it is possible that the contributions are tapping an informational effect similar to the one expected for the group number variable rather than a vote/access buying effect. [Figure 1 about here] Alternative Specifications To further explore the relationship between lobbying activity and bill outcomes. I also estimated three additional models of bill outcomes using alternative specifications. The first three models used simple counts of groups, spending and hours spent lobbying without directly differentiating between bills with one-sided lobbying efforts and those with more competitive 3 The effects of campaign contributions from the first two models produce similar patterns. 10

lobbying. To address this issue, I incorporate variables that measure the differences in lobbying activities (groups, spending, hours communicating) between supporters and opponents. Positive values indicate that supporters of the bill have an advantage and negative values indicate an advantage for opponents. The total number of groups, spending on lobbying, and hours spent communicating are also included to test a competing explanation of lobbying influence: institutional sclerosis where increased lobbying results in gridlock (Olson, 1982). The results from these alternative specifications are presented in Table 3. Unlike the first three models, these specifications show some evidence that advocacy efforts of interest groups do affect the progress bills make in the legislature. When one side has an advantage in the number of groups that are lobbying, the progress of the bill is more likely to reflect that side s preferences for or against passage. However, as in the effects of campaign contributions, the side opposing passage seems to have a relatively larger impact, as suggested by the negative coefficient on of the total number of groups lobbying. Since the effects of lobbying are realized through the number of groups rather than their specific efforts (measured in spending or hours communicating), these results are consistent with an informational model of lobbying. By signaling their preferences on a bill, the groups can convey policy and political information to legislators but their persuasive or subsidizing efforts may not affect bill outcomes. However, Model 6 does show a significant composite effect of lobbying efforts, as seen in Figure 2. Having an effort advantage seems to have a particularly large effect on the probability of bill passage, which swings from a less than ten percent chance of passing on bills dominated by opponents to nearly forty percent on bill dominated by supporters. [Table 3 about here] 11

[Figure 2 about here] In addition to the effects of the number of the number of groups and the advocacy effort advantage, the models also show consistent effects of campaign contributions. The magnitude of this effect, drawn from Model 6, can be seen in Figure 3. 4 Having even a relatively small advantage in campaign contributions, significantly affects the probability of one side achieving its goals in regards to the progress of a bill. However, these effects do tend to be much smaller than the effects Group Advantage and Effort Advantage variables. In terms of relative advantages, the advocacy efforts of the groups particularly the number of groups one each side are more influential than campaign contributions [Figure 3 about here] As in the first three models, the contextual factors are significant influences on the progress a bill makes through the legislative process, regardless of interest group activities. Bills introduced by majority party members and committee chairs are more likely to move forward. Bills introduced later in the session are less likely to proceed. Lobbying Activity and Bill Passage: Probit Analyses Though analyses of bill progress can reveal much about the effects of lobbying, lobbyists and interest groups are ultimately interested in whether a bill passes or not. For either side of an issue, the distinction between a bill dying in committee or failing to pass the second chamber is not substantively very important in terms of their policy goals. For this reason, it is important to also analyze the effect of lobbying activities on the likelihood of bill passage. Thus, in the 4 The effects of campaign contribution advantages from Models 4 and 5 are similar, though slightly smaller I magnitude. 12

following analyses, the dependent variable is a dichotomous variable indicating whether the bill passed the legislature. The rest of models remain the same, as do the expectations of the effects of each of the variables. However, since the 2007-2008 session featured divided control of the legislature, I do expect some of the contextual effects to change. For example, the impact of a bill being sponsored by a member of the majority party may not be a significant factor for passage since the majority party advantages will not translate from one chamber to the other. Similarly, the effect of a committee chairperson sponsoring a bill may affect its progress in their own chamber, but it is less likely that their position of power will have a significant impact in the other chamber. Alternatively, the effect of bipartisan cosponsorship may be significant in this case because, at minimum, some level of bipartisan support is necessary for a bill to pass both chambers. The results from the first three model specifications (comparable to Models 1-3 in Table 2), are presented in Table 4. These results are strikingly different from those produced by the bill outcome models. Many of the advocacy effort variables show significant effects while the campaign contribution variables are not statistically significant. Before discussing these results further, however, it is important to note that these models exclude bills lobbied against by groups that have made campaign contributions because any value above zero perfectly predicts failure to pass. The results presented here are only those bills where the campaign contributions against passage equaled zero. 5 So, while there does not seem to be a significant effect of campaign contributions for passage or neutral contributions in these models, it is critical to recognize that campaign contributions against passage are perfect predictors of failure. [Table 4 about here] 5 N = 242 13

Among those bills included in Models 7 through 9, however, the results do show significant impacts of lobbying efforts. Unlike the first three models presented in this study, the number of groups lobbying against passage has a significant impact. The differential impact of lobbying for and against passage is evident here as the number of groups lobbying for passage does not have a significant effect on the probability that a bill passes. With all other variables at their mean, increasing the number of groups lobbying against a bill from zero to one reduces the probability of passage from nine percent to less than one percent. Adding another group further reduces the probability of passage to nearly zero. Model 7 also shows that spending on lobbying efforts has significant effects for both sides of a bill. Figure 4 shows the magnitudes of these effects. Note that spending in favor of passage can have a substantively significant impact on the probability of passage, especially when opposition spending is relatively low. However, the magnitude of the effect of spending against passage is much larger. The lower graph in Figure 4 demonstrates how quickly the probability of passage approaches zero, no matter how much supporters spend on their lobbying efforts. [Figure 4 about here] As with the bill outcome models presented in the previous section, contextual factors are also significant predictors of whether a bill passes or not. However the types of contextual variables that effect bill passage do differ from those that affect bill outcomes. Senate bills were more likely to pass than their Assembly counterparts. With divided control of the legislature, it may have been easier to craft bill that could attract bipartisan support in the smaller upper chamber. As expected, bipartisan support is a significant influence on whether a bill passes 14

through the split-controlled legislature. Finally, the timing of the introduction of bills, unsurprisingly, remains a significant factor. Alternative Specifications Once again, I also estimated three alternative specifications of the models focusing on relative lobbying efforts rather than absolute efforts. These alternative models are especially helpful in exploring the effects of lobbying efforts and campaign contributions because they allow for all 300 bills to be included. The variables included in these models mirror those from Table 3 (Models 4-6). The results are presented in Table 5. Each of models produced results similar to those in seen Models 7-9, suggesting that the omission of the bills whose opponents had contributed to campaigns did not drastically bias the interpretation of the remaining variables. In these specifications, the effects of lobbying effort advantages are statistically significant. While the Group Advantage variables are only marginally significant, the total number of groups significantly reduces the probability of passage as suggested by the defensive advantage and sclerosis arguments. A similar pattern is seen with spending and hours communicating. The relative advantage that groups have in their efforts significantly increases the likelihood that they achieve their goals. However, this effect for supporters is tempered by a defensive advantage which supplements the efforts of opponents. [Table 5 about here] The magnitude of the effects of spending and hours communicating can be seen in Figures 5 and 6, respectively. While a spending advantage of $10,000 for supporters of a bill can certainly raise the probability of passage to significant degree, these predicted probabilities do 15

not rise above ten percent and vary by the total amount spent by all groups. Compare this effect with a similar $10,000 advantage for opponents, which results in the probability of passage of nearly zero, regardless of the total amount spent. The pattern for the effects of having an advantage in the number of hours spent communicating with the legislature is similar, though the magnitude is smaller. [Figure 5 about here] [Figure 6 about here] Moving down the models, the estimates suggest that advantages in campaign contributions do not significantly affect the probability of bill passage. This finding is surprising give the perfect collinearity of contributions against passage and the failure of a bill to pass, especially in light of the results models of bill outcomes. However, the null results in terms of bill passage are consistent with the existing literature which argues that contributions do not buy votes, but rather affect access and agendas. Thus, campaign contributions should significantly affect whether a bill makes progress through the legislative process by enhancing the access of those contributors. However, the contributions would not affect final passage since they ultimately should not affect the preferences and voting behavior of individual legislators. Contextual factors remain significant predictors of bill passage in these models. Once again, Senate bills are more likely to pass compared with Assembly bills. Bipartisan cosponsorship also increases the probability of bill passage and bills introduced later in the session are less likely to pass. 16

Discussion The new lobbying registration requirements in the American states provide unique opportunities for the exploration and testing of many theories and arguments of interest group influence and lobbying. Analyzing the lobbying data from Wisconsin, it is possible to get a more complete and systematic picture of the influence of groups in U.S. politics. While we should certainly remain cautious in generalizing these results to other settings, this exploratory analysis shows the kind of leverage scholars can gain by exploiting the new registration requirements. At the very least, this study demonstrates that further data collection and analyses of these types of data sources are likely to be quite fruitful in the development of interest group scholarship. That said, the results from the analyses presented here do provide insight into the nature of interest group influence in their own right. In short, the results from these analyses suggest that organized interests can have significant impact on legislation. From the models of the bill progress, it is evident that much of this influence flows through campaign contributions. Groups that contribute to legislative campaigns are more likely to have their favored bills moved out of committee and through the legislative process and the bills they oppose are less likely to move forward. However, the models also showed a significant effect of the advantage a side can have in terms of the number of groups. Though this effect, like many of the group effort variables, is more powerful for the opposition, it is nonetheless consistent with an informational theory of advocacy that emphasizes cues rather than persuasion. The alignment of groups for and against a bill can send important signals to legislators about the projected impact that a bill may have on relevant interests and its viability in the legislative process. Thus, interests may be able to influence the outcome of legislation merely by signaling their support or opposition even if they cannot engage in more the costly efforts of persuasion and providing legislative subsidies. 17

However, the models of bill passage place more emphasis on group advocacy efforts. The models revealed the significant effects of spending on lobbying and hours spend in direct communication with legislators and their staff. Though the opposition remained relatively advantaged in these efforts, both sides could influence the probability of a bill ultimately passing. This implies that to influence the passage (or defeat) of a bill, unlike just moving forward in the legislative process, requires more costly efforts by interest groups beyond simple signals of support or opposition. Thus, resources like money and staff are critical for groups to ultimately influence bill passage, providing an advantage to those interests who are most organized. Furthermore, these models reveal that campaign contributions did affect the probability of a bill passing. Again, these findings of a significant effect on bill progress but no effect on bill passage are consistent with arguments that campaign contributions can enhance a group s access to the legislature but cannot buy votes or legislators. Though this finding runs counter to popular attitudes about the negative and corrupting role of money in politics, it still has some normatively negative implications. Groups that can afford to engage in electoral politics seem to be advantaged at critical agenda setting stages and in committees. While the analyses do find a significant impact of organized interests on the legislative process, it is important not to overemphasize these effects. The results all show very strong contextual factors party, status in the legislature and timing all have substantively large impacts on the progress a bill is likely to make. The analyses also found a very strong defensive advantage. This finding mirrors Baumgartner et al. (2009) arguments as to the power of the status quo. Though the impact of status quo advocacy seems to be much larger than advocacy for change, this difference is driven by institutional difficulty of enacting change rather than a bias towards any particular interest. 18

References American National Election Studies (2008) The ANES Guide to Public Opinion and Electoral Behavior. Austen-Smith, D. & Wright, J. R. (1994) Counteractive Lobbying. American Journal of Political Science 38(1): 25-44. Bauer, R. A., Pool, I. D. S. & Dexter, L. A. (1963) American Business & Public Policy; the Politics of Foreign Trade, New York: Atherton Press. Baumgartner, F. R., Berry, J. M., Hojnacki, M., Kimball, D. C. & Leech, B. L. (2009) Lobbying and Policy Change: Who Wins, Who Loses, and Why, Chicago, IL: University of Chicago Press. Baumgartner, F. R. & Leech, B. L. (1998) Basic Interests: The Importance of Groups in Politics and in Political Science, Princeton, N.J.: Princeton University Press. Cox, G. W. & McCubbins, M. D. (2007) Legislative Leviathan: Party Government in the House, Cambridge; New York: Cambridge University Press. Denzau, A. T. & Munger, M. C. (1986) Legislators and Interest Groups: How Unorganized Interests Get Represented. The American Political Science Review 80(1): 89-106. Government Accountability Board (2010) Lobbying Registration. Grenzke, J. M. (1989) PACs and the Congressional Supermarket: The Currency Is Complex. American Journal of Political Science 33(1): 1. Hall, R. L. & Deardorff, A. V. (2006) Lobbying as Legislative Subsidy. American Political Science Review 100(01): 69-84. Hall, R. L. & Wayman, F. W. (1990) Buying Time: Moneyed Interests and the Mobilization of Bias in Congressional Committees. The American Political Science Review 84(3): 797. 19

Hansen, J. M. (1991) Gaining Access: Congress and the Farm Lobby, 1919-1981, Chicago: University of Chicago Press. Heinz, J. P., Laumann, E. A., Nelson, R. L. & Salisbury, R. H. (1993) The Hollow Core: Private Interests in National Policy Making, Cambridge, Mass.: Harvard University Press. Hojnacki, M. & Kimball, D. C. (1998) Organized Interests and the Decision of Whom to Lobby in Congress. The American Political Science Review 92(4): 775-790. Kingdon, J. W. (1984) Agendas, Alternatives, and Public Policies, Boston: Little, Brown. Kollman, K. (1998) Outside Lobbying: Public Opinion and Interest Group Strategies, Princeton, N.J.: Princeton University Press. Langbein, L. I. (1986) Money and Access: Some Empirical Evidence. The Journal of Politics 48(4): 1052-1062. Lewis, D. C., Ball, A. R. & Pisaneschi, M. L. (2011) Gauging Influence: Legislative Lobbying in Wisconsin. Annual Meeting of the Southern Political Science Association. New Orleans, LA. Lowery, D. & Brasher, H. (2004) Organized Interests and American Government, New York: McGraw-Hill. Lowery, D. & Gray, V. (2004) A Neopluralist Perspective on Research on Organized Interests. Political Research Quarterly 57(1): 163-175. Olson, M. (1965) The Logic of Collective Action; Public Goods and the Theory of Groups, Cambridge, MA: Harvard University Press. Olson, M. (1982) The Rise and Decline of Nations: Economic Growth, Stagflation, and Social Rigidities, New Haven: Yale University Press. 20

Powell, L. W. (2012) The Influence of Campaign Contributions in State Legislatures: The Effects of Institutions and Politics, Ann Arbor: University of Michigan Press. Rothenberg, L. S. (1992) Linking Citizens to Government: Interest Group Politics at Common Cause, Cambridge ; New York: Cambridge University Press. Schattschneider, E. E. (1960) The Semisovereign People; a Realist's View of Democracy in America, New York: Holt. Stratmann, T. (1991) What Do Campaign Contributions Buy? Deciphering Causal Effects of Money and Votes. Southern Economic Journal 57(3): 606-620. Stratmann, T. (2005) Some Talk: Money in Politics. A (Partial) Review of the Literature. Public Choice 124(135-156. Truman, D. B. (1951) The Governmental Process; Political Interests and Public Opinion, New York: Knopf. Wawro, G. (2001) A Panel Probit Analysis of Campaign Contributions and Roll-Call Votes. American Journal of Political Science 45(3): 563-579. Webb Yackee, J. & Webb Yackee, S. (2006) A Bias Towards Business? Assessing Interest Group Influence on the U.S. Bureaucracy. The Journal of Politics 68(1): 128-139. Wright, J. R. (1996) Interest Groups and Congress: Lobbying, Contributions, and Influence, Boston: Allyn and Bacon. 21

Table 1. Lobbying Activity & Campaign Contributions: Descriptive Statistics Variable Mean St. Dev. Minimum Maximum Number of Groups 5.707 6.049 0 32 Groups For 2.600 3.203 0 17 Groups Against 1.137 2.461 0 20 Groups No Position 1.977 2.821 0 21 Number of Hours 48.373 115.802 0 1,045 Hours For 29.240 82.714 0 685 Hours Against 9.293 33.085 0 287 Hours No Position 10.153 44.601 0 637 Expenditures ($k) 6.519 17.492 0 177.292 Expenditures For ($k) 3.498 9.768 0 66.431 Expenditures Against ($k) 1.581 7.185 0 86.428 Expenditures No Position ($k) 1.439 7.433 0 110.861 Campaign Contributions For ($k) 25.382 52.794 0 292.252 Campaign Contributions Against ($k) 14.473 48.548 0 316.152 Campaign Contributions No Position ($k) 26.899 59.359 0 389.462 Note: The sample includes 300 bills covering 19 topics: agriculture, budget, business & finance, consumer protection, criminal justice, K-12 education, elections, environment, family law, health, higher education, housing, labor, state government, taxation, tourism & recreation, transportation, urban affairs, and veterans. 22

Table 2. Ordered Probit Models of Bill Outcomes Model 1 Model 2 Model 3 Variable Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. Groups For [+] 0.003 0.032 0.006 0.030 ----- ----- Groups Against [-] -0.027 0.048-0.035 0.062 ----- ----- Groups No Position -0.006 0.033-0.003 0.035 ----- ----- Spending For (k) [+} 0.005 0.008 ----- ----- ----- ----- Spending Against (k) [-] -0.001 0.008 ----- ----- ----- ----- Spending No Position (k) 0.002 0.010 ----- ----- ----- ----- Hours For [+] ----- ----- 0.000 0.001 ----- ----- Hours Against [-] ----- ----- 0.001 0.003 ----- ----- Hours No Position ----- ----- 0.000 0.001 ----- ----- Effort For [+] ----- ----- ----- ----- 0.035 0.066 Effort Against [-] ----- ----- ----- ----- -0.031 0.038 Effort No Position ----- ----- ----- ----- 0.005 0.041 Cont. For (log) [+] 0.037* 0.020 0.037* 0.020 0.037* 0.017 Cont. Against (log) [+] -0.054** 0.022-0.055** 0.023-0.062** 0.018 Cont. No Position (log) -0.002 0.016-0.003 0.016-0.004 0.012 Senate Bill 0.132 0.116 0.138 0.114 0.137 0.111 Maj. Party Sponsor [+] 0.942** 0.283 0.946** 0.282 0.948** 0.282 Com. Chair Sponsor [+] 0.669** 0.180 0.675** 0.176 0.673** 0.179 No. of Cosponsors [+] -0.003 0.008-0.002 0.008-0.003 0.008 Bipartisan Cosponsor [+] 0.148 0.132 0.160 0.134 0.160 0.131 Bi-Chamber Cosponsor [+] -0.273 0.260-0.295 0.261-0.277 0.261 Date of Introduction [-] -0.001* 0.001-0.001* 0.001-0.001* 0.001 cut1-17.980 9.438-17.652 9.353-17.205 9.210 cut2-17.359 9.450-17.032 9.365-16.585 9.220 cut3-16.753 9.438-16.428 9.355-15.980 9.210 cut4-16.594 9.436-16.270 9.354-15.822 9.209 Log pseudolikelihood -350.637-350.850-350.856 McKelvey & Zavoina s R 2 0.368 0.367 0.369 Notes: Fixed effects for the 19 bill topics are included in all models, but are not presented here; 300 observations; Standard errors are clustered on 51 committees of original referral; Directional tests of significance are used as indicated by the bracketed signs following the variable names. ** p<0.01; *p<0.05 23

Figure 1. Predicted Probabilities of Bill Outcomes over Campaign Contributions, Model 3.25.2.15.1.05 0 5000 10000 15000 20000 Campaign Contributions For Passage Passes Committee Passes 2nd Chamber Committee Passes 1st Chamber Passes.25.2.15.1.05 0 0 5000 10000 15000 20000 Campaign Contributions Against Passage Passes Committee Passes 2nd Chamber Committee Passes 1st Chamber Passes 24

Table 3. Ordered Probit Models of Bill Outcomes, Alternative Specifications Model 4 Model 5 Model 6 Variable Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. Number of Groups [-] -0.023# 0.016-0.027# 0.016 ----- ----- Group Advantage [+] 0.045* 0.023 0.056* 0.022 ----- ----- Total Spending (k) [-] 0.004 0.004 ----- ----- ----- ----- Spending Advantage (k) [+] 0.003 0.006 ----- ----- ----- ----- Total Hours [-] ----- ----- 0.001 0.001 ----- ----- Hours Advantage [+] ----- ----- -0.001 0.001 ----- ----- Effort Advantage [+] ----- ----- ----- ----- 0.067* 0.037 Cont. Advantage (logged) [+] 0.015# 0.011 0.016# 0.011 0.023* 0.010 Senate Bill 0.131 0.112 0.143 0.114 0.144 0.113 Majority Party Sponsor [+] 0.919** 0.284 0.919** 0.281 0.936** 0.287 Committee Chair Sponsor [+] 0.638** 0.178 0.651** 0.173 0.642** 0.175 Number of Cosponsors [+] 0.000 0.008 0.000 0.008-0.003 0.007 Bipartisan Cosponsor [+] 0.165 0.135 0.179# 0.137 0.203# 0.127 Bi-Chamber Cosponsor [+] -0.301 0.261-0.329 0.261-0.292 0.265 Date of Introduction [-] -0.001* 0.001-0.001* 0.001-0.001# 0.001 cut1-17.030 9.431-17.024 9.121-13.908 9.230 cut2-16.420 9.441-16.414 9.131-13.302 9.233 cut3-15.818 9.426-15.814 9.120-12.703 9.217 cut4-15.659 9.428-15.656 9.122-12.547 9.214 Log pseudolikelihood -354.001-354.177-355.395 McKelvey & Zavoina s R 2 0.342 0.342 0.337 Notes: Fixed effects for the 19 bill topics are included in all models, but are not presented here; 300 observations; Standard errors are clustered on 51 committees of original referral; Directional tests of significance are used as indicated by the bracketed signs following the variable names. ** p<0.01; *p<0.05; #p<0.1 25

Figure 2. Predicted Probabilities of Bill Outcomes over Lobby Effort Advantage, Model 6.4.3.2.1 0-10 -5 0 5 10 Lobbying Effort Advantage Passes Committee Passes 2nd Chamber Committee Passes 1st Chamber Passes 26

Figure 3. Predicted Probabilities of Bill Outcomes over Contributions Advantage, Model 6.25.2.15.1.05-20000 -10000 0 10000 20000 Campaign Contribution Advantage Passes Committee Passes 2nd Chamber Committee Passes 1st Chamber Passes 27

Table 4. Probit Models of Bill Passage Model 7 Model 8 Model 9 Variable Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. Groups For [+] -0.127 0.092-0.104 0.087 ----- ----- Groups Against [-] -1.497** 0.385-1.706** 0.394 ----- ----- Groups No Position -0.004 0.077 0.003 0.082 ----- ----- Spending For (k) [+} 0.037** 0.013 ----- ----- ----- ----- Spending Against (k) [-] -0.075# 0.056 ----- ----- ----- ----- Spending No Position (k) -0.016 0.013 ----- ----- ----- ----- Hours For [+] ----- ----- 0.003 0.002 ----- ----- Hours Against [-] ----- ----- 0.000 0.012 ----- ----- Hours No Position ----- ----- -0.001 0.003 ----- ----- Effort For [+] ----- ----- ----- ----- 0.115 0.131 Effort Against [-] ----- ----- ----- ----- -3.897** 1.404 Effort No Position ----- ----- ----- ----- -0.076 0.077 Cont. For (log) [+] 0.033 0.030 0.034 0.028-0.004 0.023 Cont. Against (log) [+] ----- ----- ----- ----- ----- ----- Cont. No Position (log) -0.008 0.032-0.008 0.034-0.003 0.025 Senate Bill 0.325 0.204 0.349# 0.199 0.391* 0.196 Maj. Party Sponsor [+] 0.175 0.376 0.215 0.378 0.134 0.361 Com. Chair Sponsor [+] 0.338 0.333 0.316 0.335 0.354 0.317 No. of Cosponsors [+] 0.001 0.013 0.005 0.014 0.003 0.014 Bipartisan Cosponsor [+] 0.581* 0.277 0.634* 0.287 0.574* 0.276 Bi-Chamber Cosponsor [+] -0.612 0.477-0.715# 0.491-0.709# 0.487 Date of Introduction [-] -0.002* 0.001-0.002* 0.001-0.002* 0.001 Log pseudolikelihood -82.243-82.243-86.184 Count R 2 0.855 0.855 0.864 Notes: Fixed effects for the 19 bill topics are included in all models, but are not presented here; Contributions Against > 0 perfectly predicts failure to pass and is omitted from the model along with those bills; 242 observations; Standard errors are clustered on 51 committees of original referral; Directional tests of significance are used as indicated by the bracketed signs following the variable names. ** p<0.01; *p<0.05; #p<0.1 28

Figure 4. Predicted Probabilities of Bill Passage over Spending, Model 7.8.6.4.2 0 0 10 20 30 40 50 60 70 Spending For (k) Spending Against 0 (mode) 1 (low) 7.651 (mean) 30 (high).8.6.4.2 0 0 10 20 30 40 50 60 70 Spending Against (k) Spending For (k) 0 (mode) 1 (low) 8.603 (mean) 30 (high) 29

Table 5. Probit Models of Bill Passage, Alternative Specifications Model 10 Model 11 Model 12 Variable Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. Number of Groups [-] -0.154** 0.045-0.149** 0.045 ----- ----- Group Advantage [+] 0.076 0.065 0.093# 0.065 ----- ----- Total Spending (k) [-] -0.024* 0.011 ----- ----- ----- ----- Spending Advantage (k) [+] 0.065** 0.021 ----- ----- ----- ----- Total Hours [-] ----- ----- -0.003* 0.002 ----- ----- Hours Advantage [+] ----- ----- 0.006* 0.003 ----- ----- Effort Advantage [+] ----- ----- ----- ----- 0.105* 0.055 Cont. Advantage (logged) [+] 0.018 0.020 0.020 0.019 0.016 0.014 Senate Bill 0.384# 0.200 0.395# 0.193 0.387* 0.196 Majority Party Sponsor [+] 0.114 0.331 0.154 0.328 0.223 0.330 Committee Chair Sponsor [+] 0.390 0.311 0.377 0.311 0.241 0.309 Number of Cosponsors [+] 0.004 0.013 0.007 0.013-0.006 0.012 Bipartisan Cosponsor [+] 0.429* 0.196 0.492** 0.198 0.555** 0.182 Bi-Chamber Cosponsor [+] -0.484 0.377-0.582 0.377-0.486 0.356 Date of Introduction [-] -0.002** 0.001-0.002** 0.001-0.001# 0.001 Log pseudolikelihood -88.709-91.295-100.318 Count R 2 0.887 0.890 0.870 Notes: 300 observations; Standard errors are clustered on 51 committees of original referral; Directional tests of significance are used as indicated by the bracketed signs following the variable names. ** p<0.01; *p<0.05; #p<0.1 30

Figure 5. Predicted Probabilities of Bill Passage over Spending Advantage, by Total Spending, Model 10.3.2.1 0-30 -20-10 0 10 20 30 Spending Difference (k) Total Spending (k) 4 (median) 12 (mean) 30 (high) 31

Figure 6. Predicted Probabilities of Bill Passage over Hours Advantage, by Total Hours, Model 11.1.08.06.04.02 0-150 -100-50 0 50 100 150 Lobbying Hours Advantage Total Lobbying Hours 40 (median) 90 (mean) 150 (high) 32