Do legislators and lobbyists trade favors? This study uses uncommon data sources and plagiarism software to detect a rarely observed relationship between interest group lobbyists and sitting Members of Congress. Comparison of letters to a Senate committee written by lobby groups to legislative amendments introduced by committee members reveals similar and even identical language, providing compelling evidence that groups persuaded legislators to introduce amendments valued by the group. Moreover, the analysis suggests that these language matches are more likely when the requesting lobby group hosts a fundraising event for the senator. The results hold while controlling for ideological agreement between the senator and the group, the group’s campaign contributions to the senator, and the group’s lobbying expenditures, annual revenue, and home-state connections.

More than a hundred campaign fundraisers occur in an average week in Washington.1 Political fundraising in Washington is a thriving industry, with many firms dedicated to hosting fundraisers, inviting people to attend, and soliciting contributions. Journalistic accounts describe professional fundraisers and fundraising firms that collect and exploit lists of willing donors, leadership political action committees (PACs)2 that allow double contributions to Members of Congress, and privileges (such as listening in on a conference call of high-ranking Members) that are exchanged for large contributions (in this example, $250,000 to the party) (Birnbaum 2000). The concerned citizen asks, “Who is providing all of this fundraising assistance, and what are they getting in return?”

Good governance groups and the government itself express concern about fundraising practices and the lobbyists who provide them. Yet fundraising events, unlike lobbying activities and contributions, are not publicly reported. As a result, previous scholars have not had access to data that allow examination of whether fundraising events—and the lobbyists who typically host them—have any effect on the benefitting legislators. This study uses for the first time data containing instances of fundraising by specific interest group lobbyists on behalf of specific incumbent Members of Congress. It then links these fundraising events to activities by senators in pursuit of the interest group’s legislative requests on a bill of major public importance. I show that senators are more likely to perform legislative favors for lobbyists who fundraise for them than for lobbyists and groups that do not. While no study of money in politics can prove a causal link, in a literature replete with null findings (Lowery 2013), the observed relationship between hosting fundraisers and securing desired policy provisions is provocative and robust.

Data and Variables The creation and negotiation of American health reform legislation in 2009 under President Obama offers an ideal opportunity to detect the influence of interest groups’ money and efforts in a way that most research designs cannot. In particular, the case provides us with three sources of data that have not been used in this way before. First, the committee solicited public comments about health reform legislation, which it provided to me. Most of these were never published (a handful of groups put their letters online). Interest group scholars rarely have access to substantive details about exactly what groups want (de Figueiredo and Richter 2014, 170; but see Nelson and Yackee 2012; Yackee and Yackee 2006)—which is key to determining whether they are successful. Second, the Senate Finance Committee released on its website all of the 564 amendments to the legislation submitted by committee members, an act of transparency that the committee had never done before.6 Comparing the text of interest group preferences to the language of legislative proposals is a more direct means of matching advocacy to policy outcomes than is typical in the literature (Burstein 2014, chap. 6). As such, it reveals similarities that are difficult to dismiss as mere coincidence. For example, a letter from a company that makes the first two-hour blood test for Methicillin-resistant Staphylococcus aureus (MRSA) and a device that can simultaneously test multiple specimens for multiple infections requested a change that was inserted into the bill after committee markup had ended. Both the letter and the amendment contain the phrase “healthcare-associated infection[s, as measured by the] preventions metrics and targets [as] established in the Department of Health and Human Services’ HHS Action Plan to Prevent Healthcare-Associated Infections or any successor plan.” This language—which has now become law—incentivizes hospitals to test every Medicare patient for an array of infections before discharging them, and thus encourages hospitals to buy the products sold by the company doing the lobbying—a company headquartered in the state represented by the senator that introduced it. Third, data about fundraising have not been used in previous research, since there is no obligation to report details about fundraisers. Even with the Sunlight Foundation’s database of fundraiser invitations (described in the following), it took careful, specialized matching techniques to link fundraiser hosts to specific lobbyists and interest groups. Dependent Variable: Amendment Offering If a legislator offers an amendment in committee that is requested by an interest group, this is an indicator that the senator is making an effort on the group’s behalf. No previous study has focused exclusively on legislators’ decisions to offer amendments in committee, though it is one of numerous actions Hall and Wayman (1990) and Evans (1996) examine. To capture such instances of legislative effort, I compare language in the amendments to language in public comments submitted to the committee by health care lobbying groups. Interest groups submitted comments in response to a series of three sets of “Options for Health Reform” released by the committee in the spring of 2009. In these letters, groups stated their support of or opposition to an array of provisions in the Options. Groups did not explicitly request amendments, because the draft that would be marked up by those amendments had not yet been released. Many letters writers did, however, request additional provisions not found in the Options or asked for alterations to provisions that were in the Options. These are the kinds of requests that appear in senators’ amendments. Thus, while not every group submitted additional requests (i.e., requests not in the Options), every group had an opportunity to do so. Furthermore, it seems likely that groups that fundraise might be more likely to make additional requests than groups not involved in fundraising. To avoid selecting on the dependent variable in this way, the universe is all groups that submitted letters to the committee at the email address it created for this purpose after the release of the Options for Health Reform (not just those groups that made additional requests). Because of the high probability that amendment writers varied—probably intentionally—the language of the amendment somewhat from the language used in the letters, I made multiple attempts to identify matches. I first performed a broad sweep to capture as many matches as I could reasonably make, resulting in some three hundred potential matches. A second, narrow sweep winnowed down that list to just those that were almost certainly describing the same proposal, resulting in about a hundred matches (these sweeps are described in the following). When an amendment was consistent with a letter’s request but the two were not clearly asking for the same legislative act, I did not count this as a match, nor were amendments that did not go as far as the requester would have liked.7 These decisions required my firm understanding of the legislation, and as such, I did not employ anyone else to make coding decisions. (For example, it required knowing the difference between Medicare Advantage Part D and ordinary Medicare Part D.) In robustness checks, I adjusted the threshold for definite match to be more or less generous; these alternatives still produced a significant relationship between amendment-offering by the senator in the dyad and fundraising events hosted for the senator by the group in the dyad or its lobbyists. To perform the broad sweep, as has also been done by a number of scholars recently (Corley 2008; Kroeger 2016; Wilkerson, Smith, and Stramp 2015), I used plagiarism-detection software, in this case WcopyFind, to identify instances of word matches between the amendments and the comments. I started by setting the program to identify in the amendments and in the full set of letters any common phrases of six words, allowing up to four imperfections, and ignoring punctuation and letter case. I then read through the matches to determine whether the amendment and the letter might be describing the same policy change. I varied the phrase length and number of imperfections to capture all meaningful matches. Second, I identified in the letters specific requests that were not provisions suggested by the committee in its draft Options for Health Care Reform. I then chose key words from each request and searched all the amendments for those key words, and determined whether these matches were substantive or coincidental (e.g., references to the Department of Health and Human Services). Third, I created key words from each amendment, and again used WCopyFind to identify these key words in any request, and then manually distinguished true matches from mere similar language. To conduct the narrow sweep, I compared the letter and the amendment it was matched with directly. If it existed, I extracted the language that indicates that the amendment is based on, at least in part, the request made in the letter. The dependent variable is coded as 1 when there is a substantive match between a request made by an interest group and an amendment offered by a senator and 0 otherwise. Each organization that submits comments, and each organization listed on the letterhead of a coalition, is included in the sample, for a total of 864 organizations. Key Explanatory Variable: Fundraiser Hosting Information about fundraising events comes from the Sunlight Foundation, a government watchdog group that has for years solicited from the public the invitations to political fundraisers that lobbyists and previous congressional donors routinely receive. To date, it has collected invitations to more than twenty-two thousand distinct congressional fundraising events over the last ten years. The Foundation records the information from these invitations in a database available to the public at http://politicalpartytime.org. Given that these data are “crowd-sourced,” we cannot be sure what portion of the population of fundraisers it captures. Therefore, it underreports (but does not overreport) the incidence of lobbying events.8 Still, these are the best data available on fundraising events.9 I identified in the database those fundraisers that list as “beneficiaries” or “honorees” any of the members of the Senate finance committee as it wrote health reform legislation in 2009. I define the health reform period as starting with President Obama’s election in November of 2008 and ending when he signed the Affordable Care Act in March of 2010. The time period over which fundraiser data are collected extends from the beginning of 2008 to the end of 2010: this allows for the possibility that a health lobbyist hosts a fundraiser for a senator after the bill is passed, or that a senator remembers a fundraiser held before consideration of the legislation began. (Whether the fundraiser or the amendment occurs first makes no difference to my argument. Especially when both sides endeavor to conceal any quid pro quo relationship, it seems just as likely that a senator would offer an amendment in anticipation of a future fundraiser as that the senator would offer an amendment in response to a fundraiser that has already occurred.) A lobbyist is linked to a fundraiser if, for the lobby group that writes the letter, any of the following is true: (1) the group is listed as hosting a fundraiser benefitting a senator, (2) an in-house lobbyist for the group hosts a fundraiser for a senator, or (3) a contract lobbyist whose client is the group hosts a fundraiser for a senator. The decision to treat all fundraiser hosts equivalently biases somewhat toward a null finding, since contract lobbyists have many clients, and any legislative benefit a contract lobbyist gets from fundraising may go to another of the lobbyist’s clients that does not submit a letter to the committee. Using the methods just described, of the 864 groups that submit comments to the committee, I identified fifty-nine groups whose requests appear in any of the 564 amendments offered by a Finance committee member during the committee’s consideration of the America’s Healthy Future Act. A total of forty-two amendments were linked to specific interest group requests. Since amendments were often sponsored jointly by more than one senator, and some dyads contained more than one amendment, in all there were ninety-eight dyads in which the senator offered an amendment requested by the group. Control Variables Member-group agreement To determine whether a senator’s decision to offer an amendment requested by a group is related to the willingness of the group or its lobbyists to host a fundraiser for the senator, we must address the possibility that the senator is inclined to do what the group requests in the absence of any fundraising assistance. While we have no measure of a senator’s predisposition to offer a particular amendment, researchers have established methods for estimating general ideological agreement between Members and groups. In particular, McKay (2008) and Bonica (2013) scale interest groups using as their basis Poole and Rosenthal’s (2007) ideal point estimates for Members of Congress. Only a minority of the groups in these data give any contributions to federal candidates (required for Bonica’s method), and even fewer generate score cards for Members (necessary for McKay’s method). But for those 132 groups in the data that do make political contributions, we can use Bonica’s (2016) Campaign Finance (CF) scores, which are inferred from the ideologies of the federal candidates to whom groups donate.10 To simplify the results and to mitigate any problems of inference associated with applying CF scores to these data, I create a dichotomous variable of whether or not the group’s CF score and the senator’s DW-NOMINATE (Poole and Rosenthal 2007) score have the same sign (i.e., both liberal or both conservative).11 This method produces a measure of member-group agreement that can heuristically be thought of as an indicator of whether the group and senator are of the same party (acknowledging that federal lobby groups are independent of political parties). Member-group agreement interacted with hosting fundraisers The incentives to fundraise and to secure amendments encourage both senator and group to trade favors. As such, it might be the case that fundraising activity is more important in a senator-group relationship when the group and the senator’s ideologies do not coincide. When a senator favors a free-market approach to governance, he or she may already be inclined to fulfill a trade association’s deregulatory amendment request. But when the senator prefers to minimize government expenditures while the group wants to increase Medicare reimbursements, hosting a fundraiser may tip the balance in the lobbyist’s favor. This senator may be persuaded to offer an amendment regarding the issue the group cares about even if it is not an issue the senator cares about. This possibility makes it important to include this interaction term where possible (i.e., for groups that make campaign contributions). Contributions Legislators may be incentivized by campaign contributions to offer amendments groups want. The theory suggests that hosting a fundraiser may offer legislators a greater benefit—literally, more money—toward their perpetual reelection goals than campaign contributions provide. I, therefore, expect contributions to be significantly related to amendment success but not to be as important as fundraising. To capture contributions, for each dyad, I combine the amounts of money that the lobby group gave to the senator’s campaign or leadership PAC, any personal contributions from an in-house lobbyist to the senator, and any contributions made from employees of the group to the senator’s campaign. These data come from the Federal Elections Commission, the Senate Office of Public Records, and the Center for Responsive Politics (CRP), respectively. Lobbying expenditures Controlling for lobbying expenditures helps us identify whether it is the lobby group’s fundraising activity, rather than its lobbying activities alone, that influences groups’ success in getting a desired amendment offered. It also helps us evaluate the lobbying subsidy argument (Hall and Deardorff 2006), which suggests that greater lobbying effort by interest groups should produce greater amendment success for the group. Lobbying expenditures are summed across the four quarters of 2009 (coinciding with the start of the 111th congress in January to the final Senate vote in late December) and come from the Senate Office of Public Records. Home state Given the importance in the literature of Members’ ties to constituents and their employers (e.g., Arnold 1990; Hall and Wayman 1990; Schiller 1995), I consider whether the interest group is headquartered in the senator’s state.12 Importantly, this variable also serves as an indication that the group likely supports the amendment. Revenue Some groups represent more individuals or a broader segment of the economy, and therefore, these groups may be more likely to have their requests entertained by senators. To estimate group size or importance, I use the natural log of the organization’s most recently available (at the time the information was collected) annual revenue amount. In most cases, these data come from manual look-up of organizations’ tax returns or Securities and Exchange Commission reports. Unavailable revenue numbers (e.g., for private companies or unofficial organizations) were imputed using regression of collinear variables (about 9%).13 Number of requests Finally, I include a variable that counts the number of distinct requests made by the group, plus the number of requests made by any of its coalition partners (for those groups that sent in their own letters and also signed a coalition-written letter). This variable is included following the logic that the more a group asks for, the greater the chances that at least one of its requests will be granted.14

Method From the fundraising data, I extracted the names of each host and beneficiary so that individual and group fundraisers were linked to all of the senators who benefitted from a given fundraising event. To match fundraisers to lobbyists, I used data from the lobbying disclosure database, maintained by the Senate Office of Public Records, which links individual lobbyists to their registered lobbying organizations and/or their individual lobbying clients each quarter. Using regular expressions in Stata, I matched lobbyist to group using simplified versions of each group or individual’s name, then re-matched the leftovers by nicknames and alternate spellings. The CRP subsequently released cleaned data derived from the Lobbying Disclosure Act database, which I used to verify and supplement my own work. In particular, data from CRP (available at www.opensecrets.org) allowed me to disambiguate lobbyists with similar or common names. To analyze the relationship between hosting a fundraising event and the benefitting senator as the senator considers a bill on which the interest group is currently working, each interest group was paired with each senator on the Finance committee to create a dyadic data set. I use the 864 groups that submitted comments to the committee, multiplied by the twenty-two senators who offered amendments in committee, to create 19,008 possible lobby group-senator dyads. As the universe contains only one committee, the variation among senators is too small to be explained by senator-specific traits such as party, ideology, reelection, or membership on other committees. So instead of controlling explicitly for these variables, I employ a conditional logit model with fixed effects for senators.15 Fixed-effects models allow us to analyze differences over time or across dyad partners within a unit—in this case the senator. In addition, I cluster errors on the individual group, to more accurately provide the significance of group-specific variables (i.e., lobbying expenditures, annual revenue, and the number of requests made in the group’s letter). Descriptive statistics appear as supplemental materials (Table S1).

Analysis and Inference When a lobby group in a dyad fundraises for the Senate Finance committee member in the dyad, the odds that the senator offers an amendment requested by the group are nearly 3.5 times (3.465) the odds if no fundraiser occurs in the dyad, as shown in the first (main) model of Table 1. This estimation controls for other variables that may also matter, including campaign contributions in the dyad, lobbying expenditures by the group, and whether the senator is predisposed to advocate for the group (as proxied by sharing a state). The predicted probability that the dyad contains an amendment changes from .005 to .017 if the dyad contains a fundraiser. While amendment-offering on behalf of identifiable interest groups may be rare, it is significantly more likely for those groups that host fundraisers. Of the groups in the data that we know hosted fundraisers for senators, 17 percent could be linked to an amendment, and of the groups that got amendments, 36 percent could be linked to a known fundraising event. Table 1. Predicting the Probability That a Lobby Group Will Have One of Its Policy Requests Introduced as an Amendment to the Health Reform Bill by a Senator on the Finance Committee. View larger version Among those interest groups that make any federal campaign contributions, we can further evaluate whether fundraising matters when the group and the senator generally agree or disagree ideologically. As seen in the second model, among groups that have PACs, and controlling for all the other variables in the model, when the group in the dyad hosts a fundraiser for the senator in the dyad, the odds that the senator offers an amendment requested by the group are more than four times the odds when no fundraiser occurs in the dyad. Meanwhile, ideological agreement is not a significant predictor of the dependent variable. The second model shows a significant relationship between the dependent variable and the interaction of hosting fundraisers and ideological agreement, but analysis of margins indicates that ideological agreement is not statistically different from ideological disagreement—whether the group fundraises for the senator or not—in predicting whether the senator provides an amendment to the group. Regarding home-state advantages, the model indicates that the odds that a group gets an amendment from the senator are about 2.5 times greater in the main model, and about 1.7 times greater in the second model, when the group is from the senator’s state while also controlling for the other variables in each model—but this variable is not significant. This result suggests that fundraising assistance may be more valuable to the senator than constituent interests are. In both models, the relationship between fundraising and the dependent variable is also stronger than the relationship between contributions and the dependent variable. This finding provides compelling evidence that fundraisers may be more valued by senators than contribution dollars, at least to the extent that either are traded for requested legislation. People who fundraise tend also to make contributions, so fundraisers are correlated with the total dollars contributed ( ρ = .21). Even so, substituting either the natural log of contributions, or an indicator of whether any contributions were given in the dyad, for the dollar amount contributed still produces significant odds ratios for fundraising (see Supplemental Materials Table S2, models 1 and 2). This finding supports the exchange theory of Hall and Wayman (1990) by suggesting that the greater dollar value of fundraising events yields a higher benefit to lobby groups than contributions alone. In Table 1, when controlling for fundraising in a dyad, higher lobbying expenditures by the group in 2009 are not significant (even at p < .05) predictors that the senator offers an amendment requested by the group. If we substitute for the amount spent on lobbying either its natural log or an indicator that the group spent any money on lobbying (Table S2, models 3 and 4), lobbying expenditures is a significant predictor of the group’s amendment success—but fundraising remains significant. A group’s annual revenue has no apparent association with whether the senator in a dyad offers an amendment requested by the group in the dyad. This null relationship indicates that amendments are not more likely to be offered to organizations that represent a greater number of people (though revenue may not be a perfect indicator of group size). In robustness checks, a model that substitutes for revenue an indicator for business interests, as well as interacting the two variables, also does not reveal a significant coefficient for business or for the interaction term. Finally, as one would expect, the greater the number of requests made by the group or its coalition partners,16 the greater its chances of amendment success, at least in the main model. Among groups that make political contributions, the second model shows that the number of requests made is not a significant predictor of the dependent variable. The main model explains about 10 percent of the variance, the second model explains about 12 percent of the variance, and F tests indicate that both models are significantly different from zero. While there is no clear consensus on how to model dyadic data (Aronow, Samii, and Assenova 2015; Kenny, Kashy, and Cook 2006), the significance of fundraising is robust to alternative specifications as shown in Table S2, including random effects for the group instead of errors clustered on the group (Kenny, Kashy, and Cook 2006; see Table S2, model 6), two-way clustered errors (Cameron, Gelbach, and Miller 2011; Petersen 2009; Thompson 2011; Table S2, model 7), and fixed effects for groups as well as fixed effects for senators (Cameron and Miller 2015).17

Discussion and Conclusion It is almost common sense that politicians reward those who help them get into office and keep them there. Yet the nature of these rewards, as well as the cost, have been particularly difficult to identify. Low contribution limits mean that any real or imagined quid pro quo exchanges may be present but statistical needles in a haystack of small contributions. But by focusing on two little-studied, unregulated, and low-salience phenomena—lobbyist fundraising for senators and committee amendment-offering—this study identifies significant relationships between lobbyist fundraising and politicians’ efforts on behalf of the lobbyists who fundraise for them on an issue of lasting public importance. The analysis suggests that when an interest group hosts one or more fundraisers for a senator on the Finance committee, the odds that that very senator introduces one of the group’s written requests as an amendment to the health care bill are nearly 3.5 times the odds when the lobby group does no fundraising for the senator. The odds are even greater when we control for whether the group and the senator are predisposed to agree ideologically. From this, we can infer that members of Congress may be more inclined to do favors for groups that fundraise for them than for groups with whom they share a political ideology. And while senators might have offered their amendments in the absence of the fundraising event, the use of similar and often identical language between the request and the amendment suggests that, at a minimum, the senator’s amendment was influenced by the lobbying effort, even if it was not wholly caused by the money that went along with it. The demonstrated link between lobbyist-hosted fundraisers and senators’ amendment-offering has important public policy implications. The models suggest that groups whose lobbyists can raise meaningful campaign contributions for Members of Congress are more legislatively successful than other groups that lobby the same people at the same time on the same bill but do not fundraise for them. And fundraising lobbyists, in addition to being more successful in getting amendments offered, are more successful than other lobbyists in shaping the final law: the amendments that can be directly linked to requests by interest groups using the method described here are twice as likely as other amendments to be included in the committee version of the bill—which itself very closely resembles the signed and adopted Affordable Care Act. From this, we can conclude that interest-group-requested amendments have a real effect on policy outcomes in the form of seemingly minor details in Public Law 111–148. The models indicate that fundraising has a more powerful relationship with a senator’s decision to offer an amendment than other relevant factors. We see that being from the senator’s home state is not as helpful in getting a senator to offer a requested amendment as hosting a fundraiser for the senator is. By controlling for groups’ lobbying expenditures and the number of requests groups made, the models show that it is not merely the intensity of lobbying activity that motivates senators to offer requested amendments. For groups that make political contributions, by controlling for member-group ideological agreement, we see that the relationship between fundraising and amendment-offering persists when a senator’s predisposition is taken into account. And by controlling for campaign contributions to the senator from the group (and its in-house lobbyists), the models suggest that hosting fundraising events may be more valued by legislators than campaign dollars alone. Interestingly, these results suggest that federal contribution limits may be largely effective in preventing legislators from unduly favoring high donors, but that both lobbyists and legislators may use fundraising events as more valuable currency than campaign contributions. The broad-impact and controversial “Obamacare” health reform bill was and remains highly salient, as suggested by the abundance of political science studies of the subject (Dinan 2011; Joondeph 2011; Skocpol and Jacobs 2010; Wilkerson, Smith, and Stramp 2015). Its high visibility provides a strong test of the theory that legislative favors are being exchanged for fundraising assistance. On lower-salience issues, the literature suggests that groups and legislators are more willing to trade favors (Fellowes and Wolf 2004; Morton and Cameron 1992; Sorauf 1992; Wawro 2001), while for a high-salience issue, public opinion and visibility tend to play a much larger role in legislative decision making. Future researchers should go beyond this atypical bill and examine a broader array of policy proposals that vary in salience, so that we may evaluate the role of public visibility in explaining lobbyists’ capacity to secure policy favors and legislators’ willingness to provide them. The literature’s infrequent examples of specific lobbying influence of the sort seen in this study suggest that legislators and lobbyists may be more likely to “cover their tracks” when journalists and the public are paying closer attention. Additional research should continue to explore ways to examine text as a means of assessing interest group influence. Designs like this one that allow for direct comparison of groups’ attempts to influence and evidence of that influence are likely to uncover relationships that other studies cannot detect (Burstein 2014). While hand-coding written comments can be tedious (as done by Yackee and Yackee 2006 and others), automated text coding has been used as a promising and time-saving alternative (e.g., Klüver 2009, 2013). In any case, the written comments of interest groups provide the researcher with a necessary counterfactual to assess the influence of lobbying (Lowery 2013, 5). There are other plausible explanations of fundraising behavior that do not imply a suspect link to legislative effort. Hosting fundraisers may help interest groups achieve solidary goals of group maintenance (Gray and Lowery 2000; Olson 1965; Salisbury 1969). Fundraisers also give attending lobbyists opportunities to keep abreast of what other lobbyists are doing and working on, as well as to get face time with the politician and the politician’s staff—a benefit that may increase the lobbyist’s subsequent access to legislative offices. For these reasons and others, I stop short of arguing that fundraising lobbyists are buying legislation. Still, the analysis suggests that fundraising activity by lobbyists does seem to encourage legislators to perform narrow legislative favors for the lobbyists that are helpful to them.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article. Supplemental Materials

Supplemental materials for this article are available with the manuscript on the Political Research Quarterly (PRQ) website.

Notes 1.

This number applies to the weeks in which Congress is in session. It comes from data gathered by the Sunlight Foundation and described further below. 2.

Leadership PACs (political action committees) are campaign committees in the name of specific Members of Congress to solicit donations and then redistribute them to other candidates. 3.

We know this from the published schedules of numerous Members of Congress, formerly available from the Sunlight Foundation. 4.

This figure is produced by the Center for Responsive Politics and comes from its website, https://www.opensecrets.org/overview/index.php?cycle=2010&type=R&display=A 5.

While fundraising events do not have to be reported, the Honest Leadership and Open Government Act of 2008 requires that individual registered lobbyists who raise large amounts of money for a campaign (and are given documented credit for doing so) report these “bundled” contributions. But, there is a threshold below which bundles need not be disclosed ($17,600 in 2015), and fundraisers hosted by multiple lobbyists can divide the total raised among all of the hosts to avoid reaching this threshold amount. In addition, campaigns do not have to report the bundling unless the campaign credits the lobbyist by name for raising the money. As evidence that the bundling reporting requirement is not capturing many fundraising events, between 2009 and 2015, only 133 congressional campaign committees reported receiving any bundled contributions, while in the 2012 cycle alone, there were 3,151 campaign committees in operation. 6.

This is according to Chairman Max Baucus as recorded in the transcript. 7.

An example of an amendment that was consistent with a group’s request but was not the same proposal is found in a letter that notes, “We believe that this problem is attributable to the inaccuracy of Medicare’s formulas for reimbursing for physician work and practice expense, and Medicare’s geographic adjustment of these portions of Medicare payment” and an amendment that reads, “The proposal would direct the Secretary to adjust the practice expense GPCI [Geographic Pricing Cost Index] for 2010 to reflect 1/4 of the difference between the relative costs of employee wages and rents in each of the different fee schedule areas and the national averages (instead of the full difference under current law).” An example of an amendment that does not go as far as the requester would like is found in a letter that reads, “Plans should not be allowed to impose cost-sharing that discriminates against enrollees with greater health care needs; nor should they be allowed to buy-down the Part B and/or Part D premium” and an amendment that commissions a study on the issue: “the Medicare Payment Advisory Commission (MedPAC) shall report to Congress on various aspects of the Medicare Part D program, and to the greatest extent possible its interaction with beneficiary access to prescription drugs under Medicare Part B. This report should focus specifically on the existence of specialty tiers and their effect on access to care for Medicare beneficiaries and shall consider the following mechanisms in the context of the Medicare Part D Anti-Discrimination Clause.” 8.

While we cannot comment on unobserved fundraisers, the research design mitigates against possible bias in the fundraiser database in several ways. For example, by identifying all fundraisers for incumbent senators in the database, I found that about two-thirds are Republican—but the present study circumscribes just twenty-two senators, only ten of whom are Republican (and two of these are dropped from the main model because they introduced no group-requested amendments). Furthermore, fundraisers beyond the first are treated the same as just one fundraiser. Thus, even if the fundraiser database is disproportionately Republican, this would be unlikely to threaten the validity of the models. 9.

It is not a simple matter to infer that a contribution to a candidate occurs at a particular fundraising event, even knowing the date and amount of the contribution. Invitations to fundraising events typically suggest contribution amounts in two to four distinct levels, which are generally multiples of $100 and frequently match the legal limits for individuals and PACs. Contributions made independently of fundraising events also typically occur in these numbers. And incumbent Members of Congress receive thousands of contributions. As such, concluding that a particular fundraiser generates a certain amount of money would be highly suspect, and I do not make any such conclusions here. 10.

These measures come from Adam Bonica’s (2016) Database on Ideology, Money in Politics, and Elections: Public version 2.0 [Computer file]. Stanford, CA: Stanford University Libraries. https://data.stanford.edu/dime 11.

In the six cases in which Bonica’s method does not produce a score for a group but contributions data exist, I substitute a measure that reflects whether the majority of federal candidates to whom the group gave in the 2010 cycle are of the same party as the senator. 12.

I considered a more nuanced measure of shared state, such as the number of clients a lobbyist represents in the senator’s home state. But this measure applies only to contract lobbying, depends on the overall scale of lobbying in each state, and is correlated with two other variables in the model (lobbying expenditures and the number of requests made), so instead, I simply use the dichotomous measure of whether the group is headquartered in the senator’s state. 13.

An alternative measure—group membership—is not appropriate for use here because groups’ “members” may be other groups, firms, Internet lurkers, or simply unknown. 14.

The significance of fundraising in the models withstands omitting the number of requests. 15.

The relevant senator-specific variables were (1) membership on the other Senate committee working on health reform, the Health, Education, Labor, and Pensions committee (HELP), which was not significantly related to amendment-offering; (2) whether the senator was up for reelection in 2010, which was also not significant; and (3) the Members’ ideology score estimate (Poole and Rosenthal 2007), which was negative and significant (i.e., Republicans/conservatives were more likely to offer amendments). 16.

For groups that signed onto a coalition letter (with letterhead reading, for example, the “Stand for Quality” coalition or the “Access to Medical Imaging” coalition, and group names along-side or below the text), I summed these requests and the requests made in the group’s own letter, if any, counting each request only once. 17.

The model that calculates fixed effects for groups as well as for senators is not shown because it differs from all the others. It drops the number of explanatory variables to three and excludes groups that were unsuccessful in getting any amendments offered; as such, its N = 1,098. Still, fundraising remains significant (at p < .01) in this model.

ORCID iD

Amy Melissa McKay https://orcid.org/0000-0002-4497-2456