In his influential book on the US Congress, David R. Mayhew (Reference Mayhew1974) observed a simple yet important feature of the national legislature: ‘the organization of Congress meets remarkably well the electoral needs of its members.’ Going even further, he argued that ‘if a group of planners sat down and tried to design a pair of national assemblies with the goal of serving members’ electoral needs year in and year out, they would be hard pressed to improve on what exists’ (81). But members’ electoral needs are only rarely so aligned as to facilitate national policy change or effective oversight of the executive branch: polarization, gridlock, and party gatekeeping can stall legislative activity even on issues where a majority of legislators and voters might prefer revision of the status quo. Despite the apparent ingenuity of US legislative design for members’ electoral needs, collective action problems plague the institution, often rendering it incapable of responding to the popular will or overseeing the executive branch.
Legislating in the American system requires Herculean efforts. Once introduced, bills must pass through at least two committees controlled by the majority party to make it to the floor of each chamber. Once on the floor, the House of Representatives must pass the bill by a simple majority vote, but a minority of senators in the upper chamber can halt the legislative process indefinitely. Even if the bill passes both chambers, the president may veto it, which can only be overridden by supermajorities in both chambers.Footnote 1
So great are congressional collective action problems, in fact, that Congress has not infrequently bestowed (or perhaps foisted) its authority to make policy upon the Executive Branch. Unlike Congress, executive agencies are hierarchical and centralized organizations usually headed by a single secretary or administrator at the top and filled with layers of careerists underneath. Although the bureaucratic policymaking process is neither unilateral nor without cost, agencies do not suffer from the same collective action problems or transaction costs that Congress does. Therefore, when congressional collective action problems or transaction costs become too much to bear, Congress delegates to the Executive Branch (Epstein and O’Halloran Reference Epstein and O’Halloran1999). Over the last century or so, the Executive Branch has become responsible for such constitutionally legislative duties as budgeting, apportionment, tariffs, and military engagement (see, for example, Dearborn Reference Dearborn2021). But delegation as such does not always resolve Congress’s collective action problems or high transaction costs; it may only postpone them.
After delegation, bicameralism, separation of powers, and the committee system continue to limit legislative responses to the administrative state. Congress is not the only institution responsible for overseeing the bureaucracy: the president and the courts also play an important role in overseeing federal agencies. These multiple principals, or overseers, create multiple veto points and collective action problems in the post-delegation stage of bureaucratic oversight. Even if majorities in each chamber of Congress support punishing an agency for its decisions, the president can veto whatever sanction that legislative coalition supports, or a court can nullify the law. The more disagreement among those principals, the more likely it is that agencies will be able to act with impunity since all veto players must agree to punish an agency for such a punishment to be doled out (see, for example, Boushey and McGrath Reference Boushey and McGrath2020; Hammond and Knott Reference Hammond and Knott1996; Reference Hammond and Knott1999; MacDonald Reference MacDonald2007; McCubbins, Noll and Weingast Reference McCubbins, Noll and Weingast1989).
Even just within Congress, agencies are subjected to (or enjoy) oversight by multiple principals. Both chambers of the US Congress have organized themselves into several committees, each with a specific policy jurisdiction that members guard jealously (see, for example, Weingast and Marshall Reference Weingast and Marshall1988). For example, both the House and Senate have an Agriculture Committee, an Armed Forces Committee, and a committee handling education and labour policy. When Congress delegates the power to make policy to the Department of Agriculture, for example, both representatives in the House Agriculture Committee and senators in the Senate Agriculture Committee are responsible for overseeing the Department’s activity. This duplication leads to yet another collective action problem since each committee may free ride off the other’s supervisory activity, and each committee must agree to any legislative action curbing the agencies (Clinton, Lewis and Selin Reference Clinton, Lewis and Selin2014; Gailmard Reference Gailmard2009; Rezaee, Gailmard and Wood Reference Rezaee, Gailmard and Woodn.d.; Shipan Reference Shipan2004; Woolley Reference Woolley1993). Multiple veto points, collective action problems, and high transaction costs in Congress, in short, benefit agencies because legislative sclerosis limits legislative responses to agency actions.Footnote 2
The politically astute bureaucrat recognizes congressional collective action problems and high transaction costs at both the policy making and oversight stages and exploits them to their benefit, gridlock and freeriding, respectively. This article considers how executive policy-making coalitions – federal rules promulgated jointly by more than one agency (Napolio 2023) – offer bureaucrats a tool to activate veto players and exploit congressional collective action problems. I argue that one of the key political functions of contemporary executive coalition building is to activate veto players and induce collective action problems among congressional overseers. In so doing, bureaucrats can promulgate policies that overseers cannot repeal by increasing the number of overseers (and therefore veto players), compounding both the free-rider and collective action problems endemic to collective choice institutions like legislatures. In short, bureaucrats understand how the legislative process and legislative organization limit congressional responses to agency actions and how to manipulate the legislative process in order to further limit Congress’s ability to curb agency behaviour.
This article is structured as follows. First, I explain my theory of strategic agency collaboration, veto activation, and collective action problems. I derive precise empirical implications from a simple spatial policymaking model. Next, I describe the data I use to test the theory. I leverage a novel dataset of thirty-two agencies forming 496 dyads over six presidential administrations. I then describe my empirical approach and present results consistent with my strategic theory of agency collaboration. Finally, I conclude with a discussion of the implications of my theory and results.
Veto Activation and Exploitation of Collective Action Problems
Agencies are not passive actors in the American political system. They recognize opportunities to achieve their policy goals in the face of political opposition. They may leverage their superior knowledge of the regulatory process to get what they want, wait to produce certain policies until congressional, presidential, or judicial conditions are more favourable (Potter Reference Potter2017, Reference Potter2019), or activate diverse networks of support to lobby or otherwise convince overseers to defer to agency desires (Carpenter Reference Carpenter2001). To this, I add that agencies collaborate strategically to activate veto players and induce collective action problems in Congress. Previous scholarship has highlighted how strategic collaborations are helpful for agencies to get what they want in the face of presidential opposition (Napolio Reference Napolio2023), but scholarship has yet to consider how strategic collaborations are helpful for agencies to get what they want in the face of congressional opposition.
Much of the work on multiple principals studies either congressional outcomes like hearings held (McGrath Reference McGrath2013; Rezaee, Wood and Gailmard Reference Rezaee, Gailmard and Woodn.d.), individual forms of oversight that do not require collective action (Bolton Reference Bolton2021; Lowande Reference Lowande2018a; Lowande and Potter Reference Lowande and Potter2020), or regulatory output from individual agencies given different partisan or ideological arrangements among principals (Boushey and McGrath Reference Boushey and McGrath2020; Lowande Reference Lowande2018b; Palus and Yackee Reference Palus and Yackee2020; Shipan Reference Shipan2004). But all of these previous studies overlook the ability of agencies to induce collective action problems and raise transaction costs among their multiple principals. Agencies do not simply observe whether their principals are divided and choose to act – although waiting until political conditions among overseers are friendlier to agency action is a strategy agencies use (Potter Reference Potter2017, Reference Potter2019) – they also work to amplify political divisions among their overseers, activating additional oversight committees by collaborating in the administrative policy-making process with other agencies with different oversight committees. In the language of positive political theory, agencies can increase the size of the core, or the set of undominated policies, such that they can move policy closer to their ideal points and into an ideological space that majorities in Congress cannot agree to change (see, for example, McCubbins, Noll and Weingast Reference McCubbins, Noll and Weingast1989).
Consider a simple spatial model in one dimension with three actors: an agency with ideal point A, a House committee whose median’s ideal point is C H , and a Senate committee whose median’s ideal point is C S, represented in Figure 1.Footnote 3 The agency first promulgates a policy, A, pursuant to some grant of authority. Then, a member of Congress can introduce a bill revising the agency action, which will be assigned to committee C H in the House and C S in the Senate. Either committee can kill the bill, reverting the policy to whatever the agency did in the first place. If a committee kills the bill, then the policy outcome is the agency’s action. If both committees pass the bill, then the policy outcome is the bill introduced in Congress. (This is a simplified version of the model presented in Shipan (Reference Shipan2004).
Figure 1. Spatial Model with Two Committees.
Under standard assumptions, each player has a single-peaked ideal point such that each actor’s most preferred policy is represented by their ideal point and their utility decreases symmetrically as policy outcomes diverge from their ideal point. Since preferences are fixed in (at least) the short run, agencies can only manipulate outcomes by bringing in more veto players such that at least one prefers a policy closer to the agency’s ideal point than any proposed bill that the other veto players could agree to pass.
To see why, suppose two committees in the Senate are responsible for a bill to revise the agency’s policy, leading to the preference configuration represented in Figure 2. As before, A represents the agency’s ideal point, and C H represents the ideal point of the House committee’s median. Now, however, C S 1 represents one of the Senate committee median’s ideal points, and C S 2 represents the second’s. Under this preference configuration, the agency can set policy at exactly its ideal point. Even if the first Senate committee median would set policy at C S 1 instead of A, a move that CH would approve of, the second Senate committee median prefers A to C S 1 so it will block the bill, reverting policy to A. As a general matter, if agencies can expand the scope of conflict to include at least one veto player closer to its ideal point than existing veto players, the agency can be no worse off and may often fare better.
Figure 2. Spatial Model with Three Committees.
But agencies do not refer bills to committees: Congress does. House rules enacted in the 1970s prescribe that each bill introduced in the House must be referred to all committees with jurisdiction over the subject matter of the bill.Footnote 4 For example, the Department of Homeland Security Blue Campaign Authorization Act, designed to aid the Department of Homeland Security in addressing human trafficking and signed into law by President Trump in 2018, was referred in the House to both the Homeland Security and Judiciary committees as it dealt with both homeland security and law enforcement.Footnote 5 The United States Parole Commission Extension Act of 2018, extending the authority of the US Parole Commission by two years, and also signed into law by President Trump in 2018, however, was referred only to the House Judiciary Committee as it dealt solely with law enforcement.Footnote 6 The Senate has a longer history of multiple referrals (Davidson Reference Davidson1989; Sinclair Reference Sinclair2016). Unsurprisingly, research indicates that multiply referred bills are less likely to be reported to the floor of the House than singly referred bills due to the increasing number of veto players created by multiple referrals (Davidson, Oleszek and Kephart Reference Davidson, Oleszek and Kephart1988; Krutz and Cullison Reference Krutz and Cullison2008; Young Reference Young1996).
Since bills must be referred to all committees with reasonable claims to jurisdiction over the issue, any bill that affects agencies with disparate jurisdictions should be referred to all committees with those same jurisdictions. For example, if Congress wishes to address a recent action by the Department of Homeland Security, a member can introduce a bill which will be referred to the Homeland Security committees in the House and Senate. But if Congress wishes to address a recent action by both the Department of Homeland Security and the Department of Energy, the bill will likely be referred to four committees: Homeland Security in the House and Senate, and Energy and Commerce in the House and Senate. Therefore, by forming a coalition, the Departments of Homeland Security and Energy can increase the number of veto players required to overturn their action.
To generalize, if agencies work together and increase the number of veto players with authority over whether a bill punishing those agencies or setting policy far from the agencies’ ideal policies can move through the legislative process, those agencies can foreclose legislative action. If agencies use such a strategy, then we should observe agencies forming coalitions with other agencies when doing so increases the ideological disagreement among the committees responsible for legislating in the agencies’ policy areas.
Oversight committee medians for pairs of agencies may be arranged in three possible ways. First, two agencies can have the same oversight committees. For example, the Equal Employment Opportunity Commission and the Department of Labor are both overseen by the same agencies in the House (House Committee on Education and Labor) and the Senate (Senate Committee on Health, Education, Labor, and Pensions).Footnote 7 For agencies with oversight committees arranged in this way, collaborating will make no difference in the ideological disagreement or gridlock between committees, since no additional veto players are brought in. This regime is represented in Figure 3 in the first panel: (a) Same Oversight Committees. Agency 1 is overseen by C S 1 and C H 1, and agency 2 is overseen by C S 2 and C H 2 in each regime.
Figure 3. Three Oversight Regimes. Numbers in superscripts indicate which agency each committee oversees, and letters in each subscript indicate each committee’s chamber. Brackets indicate the ideological distance between each agency’s oversight committees.
Second, two agencies can have different oversight committees, but the ideological distance between the most liberal and most conservative of the four committees jointly responsible for overseeing those two agencies is only larger than the ideological distance between the most liberal and most conservative of each pair of committees for one agency. This occurs when the ideal points of both House and Senate committee medians for one agency lie between the ideal points of the other agency. For agencies with oversight committees arranged in this way, the agency with less ideologically diverse committees benefits from coalition building, but the agency with more distant oversight committee medians may not. This regime is represented in Figure 3 in the second panel: (b) Larger for One.
Finally, two agencies can have different oversight committees, and the ideological distance between the most liberal and most conservative of the four committees jointly responsible for overseeing those two agencies is larger than the ideological distance between the most liberal and most conservative of each pair of committees for both agencies. This occurs when the interval between the House and Senate committee medians for each agency overlaps, but neither is wholly contained in the other.Footnote 8 For pairs of agencies with oversight committees arranged in this way, both agencies benefit from collaboration by guaranteeing more committee gridlock if Congress attempts to overturn their policy. This regime is represented in Figure 3 in the final panel: (c) Larger for Both.
Agencies have the most to gain in the third regime since they can activate sympathetic veto players, forcing greater disagreement among legislative overseers, and induce a collective action problem, or raise transaction costs in Congress by activating multiple committees that have incentives to freeride off each other’s oversight activity. Both veto activation and freeriding are likely to stymie legislative efforts at oversight in the third regime. Therefore, the first empirical implication of my theory of executive coalitions vis-à-vis Congress is:
Hypothesis 1 (Veto Activation + Freeriding): When the ideological distance between the most liberal and most conservative committee medians of the four committees overseeing two agencies is larger than the ideological distance between the most liberal and most conservative committee medians for each individual agency’s oversight committees (regime c), those agencies are most likely to collaborate.
But legislative control of the administrative state is not only achieved through legislation. Committees also serve an important role in overseeing agency implementation of legislative policy. And just like in the legislative process, collective action problems plague congressional oversight. Bicameralism again limits the responsiveness of committees to agency behaviour since committees have incentives to free ride off their counterparts (Gailmard Reference Gailmard2009; Rezaee, Gailmard and Wood Reference Rezaee, Gailmard and Woodn.d.). In fact, agencies report less congressional influence in their affairs when they are subject to oversight by multiple committees (Clinton, Lewis and Selin Reference Clinton, Lewis and Selin2014).
Policing the administrative state is costly for members of Congress. The committee system helps cut down on information-seeking costs since each committee is only responsible for a subset of federal agencies, but committees still oversee multiple agencies responsible for regulating activity in many policy areas. If members of Congress had to actively monitor every agency under their committees’ jurisdictions, there would be no time for any of the many other activities members of Congress must do, like legislating, case work, and campaigning. Therefore, Congress, with the Administrative Procedure Act and other statutes regulating the administrative state, has installed procedural technologies that allow interested parties, like interest groups, to alert Congress if an agency engages in undesirable behaviour. These ‘fire alarms’ reduce oversight costs for Congress, thereby providing a more efficient means of oversight (McCubbins and Schwartz Reference McCubbins and Schwartz1984; but see Lowande Reference Lowande2018a for evidence that members of Congress do engage in some unprompted monitoring).
Relying on fire alarms, however, means that committees only receive allegations of agency malfeasance, but the members sitting on committees do not directly observe agency behaviour unless they call for a hearing with agency witnesses or subpoena agency records. Calling a hearing, subpoenaing agency records, or otherwise seeking to audit agency actions, however, is costly. The benefits of such an audit are informational: the committees can learn whether and to what extent an agency has misbehaved. Because once that information is public, all members of Congress can access it, committees have incentives to free ride off the auditing activity of other committees in order to learn the information they seek without taking costly action themselves (Gailmard Reference Gailmard2009). Since each agency is overseen by a committee in the House and the Senate, each committee can theoretically free ride off the auditing activity of at least one other. Critically, even if both committees agree perfectly that the agency should be audited, oversight may be underprovided due to the free riding problem. Therefore, the institutional design of bicameralism is sufficient to lead to inefficient oversight. But crafty agencies can compound the problem.
Executive coalition building helps agencies avoid oversight. Agencies can induce an even larger collective action problem in oversight by collaborating with each other. If two agencies have different oversight committees, then by collaborating, agencies can expand the number of principals responsible for oversight from two to four. With four instead of two oversight committees, free riding should increase since each committee may anticipate any of the three – rather than only one – other committees may audit the agencies. This argument stands in contrast to a more mechanistic explanation for collaboration: that coalition formation is simply a function of overlapping jurisdictions and therefore increased opportunities for collaboration. By contrast, this strategic theory of coalition formation argues that having different jurisdictions, and therefore fewer natural opportunities for collaboration, is an important predictor of collaboration.
Mapping this theory onto the three regimes in Figure 3 yields the second hypothesis. Pairs of agencies with the same oversight committees (regime a) do not stand to gain from collaborating since acting on their own or as a pair would result in the same number of committees responsible for overseeing them. However, pairs of agencies with different sets of oversight committees (regimes b and c) can make freeriding among oversight committees more likely by collaborating and increasing the number of committees responsible for oversight. In regime b, gridlock may not be as much of a problem, but freeriding certainly is. Therefore:
Hypothesis 2 (Freeriding): Pairs of agencies with different sets of oversight committees (regimes b and c) are more likely to collaborate than pairs of agencies with the same oversight committees (regime a).
This hypothesis is counterintuitive without theory. Agencies with the same oversight committees inhabit similar policy areas and, therefore, might naively be expected to collaborate more frequently than those with different policy areas. If agency coalitions serve only technocratic purposes, that might be the case. However, if agency coalitions are intended to induce collective action problems in Congress so agencies can achieve their desired policy outcomes, we should observe agencies collaborating when they have different oversight committees.
To summarize, the strategic theory of coalition formation implies that agencies should form coalitions the least under regime a, more under regime b, and the most under regime c. This is because the strategic theory implies no incentive to form coalitions in regime a, incentives related to anticipated freeriding in regime b, and incentives related both to anticipating freeriding and gridlock in regime c. This does not imply that there are no reasons to collaborate in regime a. Rather, those incentives are orthogonal to the strategic argument. For example, an agency may want to collaborate with another for informational purposes. However, that incentive exists regardless of the configuration of oversight committees and therefore would not make a difference on the margins of oversight regime type. That incentive is constant; the strategic incentives vary with the oversight regime.
Take, for example, the Environmental Protection Agency and Department of Transportation efforts to regulate greenhouse gas emissions during the Obama administration. In 2010, the agencies jointly promulgated a rule establishing new standards for vehicles to reduce greenhouse gas emissions. At the time, the agencies fell into regime c, Larger for Both, indicating that the ideological space between the two most distant committee medians was larger than the distance between each agency’s individual pair of oversight committee medians. A few years later, that changed. The distance between the two committees overseeing the Environmental Protection Agency expanded such that it fully engulfed the distance between the two committees overseeing the Department of Transportation, shifting the dyad into regime b, Larger for One. That year, the Environmental Protection Agency published a rule on its own, without the Department of Transportation, establishing more stringent regulations on emissions for a wider range of vehicle types. The Environmental Protection Agency could not create further gridlock or activate more sympathetic overseers by collaborating with Transportation, so it acted alone.
It is, of course, possible that some coalitions are induced by or preferred by Congress. I do not claim that my theory explains every coalition ever formed, rather that when the conditions of my theory are met, coalitions are more likely on average. Some of the observed coalitions may be preferred by or induced by Congress, but if a large proportion of coalitions were congressionally induced, the empirical patterns I uncover below would not be present. In other words, the alternative explanation, that coalitions are congressional-induced, is part of the null hypothesis. Additionally, it is possible that agencies collaborate when doing so allows them to do more than they could do if they went at it alone, that agencies collaborate purely for technocratic reasons related to their capacity. Again, however, if that were true for a large proportion of coalitions, then the specific predictions from my strategic theory would not be borne out in the data. Future work may explore these two alternative explanations more, but the predictions from each are not observationally equivalent to the predictions from my strategic theory, and I can therefore be confident that the results I share below are supportive of my strategic theory.Footnote 9
Data and Empirical Strategy
To test these hypotheses, I leverage a novel dataset of agency coalitions, jointly promulgated policies, from thirty-two agencies during 1995-2018.Footnote 10 I created this dataset from the Federal Register. Each observation is an agency dyad-year since committee compositions change each Congress and occasionally within the same Congress. The dependent variable is a binary indicator for whether each agency dyad in each year formed a coalition or not. I then matched agencies to oversight committees in the Senate by selecting the committee responsible for first considering nominees to that agency, and in the House by selecting the committee analogous to the Senate oversight committee.Footnote 11 Next, I calculated the absolute value of the difference in the DW-NOMINATE estimate of each agency’s two oversight committees’ median member’s ideal point. Then, I calculated the absolute value of the difference in the DW-NOMINATE estimate for the most liberal and most conservative of each of the four committees overseeing the two agencies forming the dyad. Finally, I created a variable that can take one of three values corresponding to the regimes in Figure 3. This variable takes the value Same Oversight Committee if the two agencies forming each dyad have the same oversight committee; it takes the value Larger for One if the absolute value of the difference in the DW-NOMINATE estimate for the most liberal and most conservative of each of the four committees overseeing the two agencies is larger than only one of the absolute values of the differences of the pairs of committees overseeing each individual agency; last, it takes the value Larger for Both if the absolute value of the difference in the DW-NOMINATE estimate for the most liberal and most conservative of each of the four committees overseeing the two agencies is larger than both of the absolute values of the differences of the pairs of committees overseeing each individual agency. Across the entire dataset, five per cent of dyad-years fall into the Same Oversight Committee regime, 40 per cent fall into the Larger for One regime, and the remaining fifty-five per cent fall into the Larger for Both regime.Footnote 12
The dataset contains information on 496 pairs of thirty-two agencies over six presidential administrations. I define coalitions as pairs of department-level agenciesFootnote 13 (for example, Department of Commerce, Department of Agriculture, Environmental Protection Agency) that promulgate at least one joint rule in a year.Footnote 14 In consultation with an attorney and expert in administrative law, I also took a random sample of one hundred jointly produced rules in my data and examined whether they were promulgated pursuant to laws that required joint rulemaking. Only five per cent of those one hundred rules were promulgated pursuant to laws that require coordination. Most laws did not require coordination, either omitting any requirements for coordination or including explicit clauses releasing agencies from coordination requirements. For example, the Departments of Agriculture and Transportation promulgated a joint rule in 1996 pursuant to the 42 U.S.C. 106, which explicitly states the ‘administrator [of the Federal Aviation Administration] … shall not be required to coordinate, submit for approval or concurrence, or seek the advice of views of the Secretary [of Transportation] or any other officer or employee.’
Table 1 displays examples of dyads with the Department of Labor in the 112th Congress to clarify the measurement. The first row displays information on the Department of Labor. From left to right, the second and third columns display the committee in the Senate overseeing the Department of Labor and the DW-NOMINATE estimate of that Senate committee median’s ideal point. The fourth and fifth columns display the same information, but for the House committee overseeing the Department of Labor. The sixth column displays the distance between the Senate and House committee medians’ ideal points. The second through fourth rows display the same information but for three other agencies during the 112th Congress. For these rows, the seventh column displays the distance between the most liberal and most conservative of all the committees responsible for overseeing both that agency and the Department of Labor. For example, the Senate median for the Department of Labor is the most liberal of any, and the House median for the Department of Agriculture the most conservative. Therefore, the cell under joint distance for the Department of Agriculture shows the absolute value of the difference between the Senate median for the Department of Labor and the House median for the Department of Agriculture. Finally, the eighth column displays the regime each dyad belongs to by comparing the joint distance to the individual distances in columns six and seven.
Table 1. Example of Regimes with Department of Labor Dyads in the 112th Congress
Table 2 displays raw percentages of dyads forming coalitions in each regime during each presidential term. Agencies with the same oversight committees were consistently less likely to form coalitions than agencies with different coalitions. Aggregating across the entire timeframe, only 3.6 per cent of dyads with the same oversight committees formed coalitions, and about 11 per cent of dyads with different oversight committees formed coalitions, a difference of about seven percentage points, consistent with hypothesis 2. During Clinton’s two terms, agency pairs whose joint oversight committee ideological distance was larger for both individual agencies were most likely to collaborate, those whose joint oversight committee ideological distance was larger for only one agency were second most likely to collaborate, and those with the same oversight committees were the least likely. The numbers are particularly striking in Clinton’s second term, where 26.4 per cent of dyads for whom collaborating increased ideological disagreement among overseers for both committees formed coalitions, whereas only 17 per cent of dyads for whom collaborating increased ideological disagreement among overseers for only one committee formed coalitions, consistent with hypothesis 1. The differences between these last two regimes dissipate in the raw numbers from Bush onward, but it remains across all time periods that agencies with the same oversight committees are the least likely to form coalitions.
Table 2. Proportion of Dyads Forming Coalitions by Regime and Presidential Term
Note: Cell entries are percentages.
* Clinton I only includes the last two years of that term.
** Trump only includes the first two years of his term.
Figure 1 displays the proportion of dyads forming coalitions each Congress for agency pairs that share oversight committees and those that do not. In every Congress, agencies with different oversight committees were more likely to collaborate, consistent with hypothesis 2. Agencies with different oversight committees can compound the free rider problem that plagues committee oversight of agency actions by increasing the number of committees responsible for oversight, thereby making it more likely that each individual committee believes it can free ride off the other committees’ oversight activities. Figure 1 provides evidence that agencies do, in fact, behave in this way.
Figure 4. Coalitions by Congress and Oversight Committees.
However, these raw numbers are only suggestive given the repeated observations in the data, and dyad- and Congress-level confounders. Therefore, I estimate a series of linear probability models to estimate the effect of different regimes on agency coalition building more rigorously.Footnote 15 Specifically, to test hypothesis 1, I regress whether each dyad formed a coalition in each year on an indicator variable, Larger for One, which takes the value of one if collaborating increases gridlock for only one agency (regime b) and zero otherwise, on dyad and year fixed effects, and on a series of control variables. These models exclude agencies with the same oversight committees (regime a) due to the dyad fixed effects. To test hypothesis 2, I include all dyads and regress the same dependent variable on a binary variable, Same Oversight Committees, which takes the value of one if the dyads share the same oversight committees (regime a), year fixed effects, and the same control variables.Footnote 16 For both tests, the coefficients on the relevant independent variable should be negative.
Results
Tables 3 and 4 report the results of the linear probability models. Since all the covariates are only available from the 105th (1997-1998) to the 112th Congress (2011-2012), model 1 in each table presents results for the 104th (1995-1996) through 115th (2017-2018) Congresses without covariates – only with dyad and year fixed effects – and model 2 presents results using only those covariates available for the full timeframe, though not for all dyad-years.Footnote 17 No matter which way I cut the data, the results are substantively similar. Each model also includes Agency Alignment as an independent variable, which is the absolute value of the difference between each agency’s Chen and Johnson (Reference Chen and Johnson2015) ideal point estimate for the observation’s dyad-year.
Table 3. Coalition Building and Congressional Committee Gridlock
*p<0.1, **p<0.05, ***p<0.01
Note: The unit of analysis is the agency dyad-year. Standard errors clustered by dyad are reported in parentheses.
Table 4. Coalition Building and Compounding the Free-rider Problem
*p<0.1, **p<0.05, ***p<0.01
Note: The unit of analysis is the agency dyad-year. Standard errors clustered by dyad are reported in parentheses.
As expected, the coefficient on Larger for One across model specifications in Table 3 is negative, indicating that agencies are more likely to form coalitions when they can activate veto players and widen the ideological gap between oversight committees. Since these models include dyad fixed effects, the coefficient estimates the within-dyad change in probability of coalition formation when a dyad changes from regime c to regime b, and that change is negative, consistent with hypothesis 1. Also, as expected, the coefficient on Same Oversight Committees across most specifications in Table 4 is negative, indicating that agencies are more likely to form coalitions when they can compound the free rider problem among oversight committees by introducing additional overseers. These models include year fixed effects, so the coefficients estimate the difference in the probability of coalition formation within the same year among dyads with and without the same oversight committees, consistent with hypothesis 2.Footnote 18 Models 3 through 6 include the full suite of covariates and uncover similar results.
Substantively, the effects are sizable. The unconditional average rate of coalition formation for the full sample is about eleven per cent. Among agency dyads with different oversight committees, when collaborating guarantees increased gridlock among committees, they are about two to four percentage points more likely to form coalitions than when collaborating only increases gridlock for one agency forming the dyad, consistent with hypothesis 1. Among all agency dyads in a given year, those with different oversight committees are about four to eight percentage points more likely to collaborate than those with the same oversight committees, consistent with hypothesis 2.
The results provide evidence in favour of both hypotheses 1 and 2. First, dyads for whom collaborating increases ideological disagreement for both sets of oversight committees are most likely to form coalitions, consistent with hypothesis 1. Second, dyads with different sets of oversight committees are more likely to collaborate than those with the same oversight committees, consistent with hypothesis 2. These results are consistent with my theory that agencies form coalitions when doing so can induce collective action problems in Congress by introducing larger ideological cleavages among principals (hypothesis 1) and worse freeriding problems among oversight committees (hypothesis 2).
The previous analysis assumes that committee medians are decisive in advancing bills through the legislative process and that committee medians vote their sincere preferences without any pressure from party leaders. However, parties influence the rank-and-file by providing positive and negative incentives for members if they act in the interest of the party or not (Cox and McCubbins Reference Cox and McCubbins1993, Reference Cox and McCubbins2005). Parties exist partly to overcome the collective action problems inherent in legislative politics, and therefore might mitigate the effects of agency attempts to induce collective action problems and raise transaction costs (Aldrich Reference Aldrich2011). In addition, some argue that committee power in Congress has waned in the postreform era when the Democratic Party leadership consciously reduced the power of committee chairs and other senior members since they were dominated by the Southern wing of the Party that was out of step with party leadership on many issues. After the Republican Party gained control of the US House for the first time in forty years in 1995, committee power was further reduced, shifting agenda setting and legislative power from committees to centralized party leadership (see, for example, Deering and Smith Reference Deering and Smith1997; Rohde Reference Rodhe1991).
This view of power in Congress implies one of two potential observable phenomena. First, if committees are weak and the centralized party control is strong, then agencies should have trouble inducing collective action problems among committees since each committee’s majority party members should vote the party line and advance bills that satisfy their party’s median member. If that were the case, then there should be no difference in agency collaboration across the three regimes. The previous analysis shows that not to be the case. Instead, I provided evidence that agencies anticipate that they can induce collective action problems, meaning they act as if committee medians can vote sincerely and committee medians from different committees could vote differently on the same bill. Second, if parties structure their members’ behaviour but nevertheless allow some degree of freedom to their delegates on committees, then it is not committee medians that matter, but the median of each committee’s contingent of majority party members that does. If that were the case, then the regimes of overlapping oversight should be constructed by comparing majority party medians on committees, not general committee medians. This expectation is tested below.
Table 5 displays raw percentages of dyads forming coalitions in the two regimes for dyads that do not share oversight committees. If agencies share oversight committees, the position of the party or committee median is irrelevant, as collaborating cannot induce more ideological gridlock, so I decline to include those numbers in this table, as they are the same as in Table 2. Unlike the findings for general committee medians, Table 5 shows that dyads do not collaborate more frequently when collaboration would induce more ideological conflict among majority party medians on committees. During each presidential term, dyads that can increase gridlock among majority party medians on committees by collaborating were about as likely as those that could not, with the exception of the Trump presidency, where the differences in probabilities are large but in the opposite direction of hypothesis 1. This implies that agencies care about general committee medians (who belong to the majority party because of how committees are constituted) and not the majority party medians on committees.
Table 5. Proportion of Dyads Forming Coalitions by Regime and Presidential Term (Majority Party Committee Medians)
Note: Cell entries are percentages.
* Clinton I only includes the last two years of that term.
** Trump only includes the first two years of his term.
Table 6 reports results of the linear probability models analogous to those in Table 3 but using majority party medians on committees instead of general committee medians. The preliminary findings in Table 5 are borne out in the regression results. Although for some models the coefficient on Larger for One is negative and significant, the effects are much smaller than those in Table 3. These results imply that agencies consider general committee medians rather than the median of the majority party’s contingent on each committee. As a result, agencies collaborate when doing so amplifies gridlock among general committee medians.
Table 6. Coalition Building and Congressional Committee Gridlock within the Majority Party
*p<0.1, **p<0.05, ***p<0.01
Note: The Unit of analysis is the agency dyad-year. Standard errors clustered by dyad are reported in parentheses.
Discussion and Conclusion
Existing theories of multiple principals overseeing the bureaucracy have ignored strategies agencies can use to exploit legislative collective action problems. Bureaucrats do not always have to wait for gridlock in Congress resulting from biannual elections. Instead, they can amplify gridlock between electorally induced changes in partisan and ideological coalitions by collaborating with other agencies to create ideological divisions among existing overseers.Footnote 19
Examining agency collaboration from the 104th Congress (1995-96) to the 115th Congress (2017-18), I find that agencies collaborate when doing so increases ideological disagreement among overseers, frustrating attempts at legislatively addressing those agencies’ actions. Additionally, I find that agencies with different sets of oversight committees collaborate more frequently than those with the same set of oversight committees because those with different oversight committees can compound the free rider problem endemic to decentralized oversight of agencies by congressional committees. The arguments presented here acknowledge that agencies are experts not only in their subject matters and the procedures they can use to achieve their policy aims, but also demonstrate considerable knowledge of the legislative process, the members of Congress most responsible for oversight, and the set of other agencies with whom they can collaborate to amplify collective action problems among congressional overseers.
Taken together with existing work that finds agencies collaborate to achieve their policy goals in the face of opposition from the president and the Office of Information and Regulatory Affairs (Napolio Reference Napolio2023), these findings further demonstrate that agencies collaborate strategically and in explicitly political ways. Agencies form coalitions with each other strategically in order to sidestep oversight and political control by Congress. By collaborating, agencies induce collective action problems and raise transaction costs among overseers. Specifically, collaboration exacerbates the free rider problem among oversight committees and can increase ideological disagreement among overseers, making legislative responses less likely and amplifying gridlock by activating veto players. The results presented in this article imply that agencies do not collaborate for purely technocratic reasons like information sharing or the crafting of more efficient policy, but instead collaborate for political reasons, to achieve their policy goals, and increase their power within the American political system.
Future work ought to study congressional responses to executive coalitions. The theory presented here has specific predictions about congressional responses: there should be fewer audits related to joint rules, bills attempting to overturn joint agency actions should be multiply referred, and bills attempting to overturn joint agency actions should not make it as far in the legislative process as those attempting to overturn individual agency actions. Linking hearings and bills to agency actions is a time-consuming project, although not intractable, and would supplement the results shown here by examining the other side of executive coalition building: how Congress responds.
The US separation of powers system enables this sort of strategic action on the part of agencies. In Westminster-style systems where the heads of agencies are themselves part of the national legislature, such a strategy may not be as viable an option. However, in presidential systems and other institutional settings that separate executive and legislative power more fully, similar strategies may be available to administrators. Future work might test the generalizability of this theory – developed to explain the US case – at least to other presidential systems.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0007123425100793
Data availability statement
Replication data for this article can be found in Harvard Dataverse at: https://doi.org/10.7910/DVN/26LH3W
Financial support
This research received no specific grant from any funding agency, commercial or not-for-profit sectors.
Competing interests
None to disclose.
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