Congressional Processes and Public Approval of New Laws

Abstract

Does how Congress makes a law affect public approval of that law? This question has been little studied, but the rising use of unorthodox processes in Congress raises concerns about the perceived legitimacy of congressional action among the public. Utilizing two unique survey experiments, I present evidence that when people are aware of the use of unorthodox legislative processes they express lower levels of approval for new laws. This effect is especially pronounced among partisans already inclined to be in opposition to the law, further solidifying their opposition. These findings have important implications for a Congress that in recent years has increasingly turned to unorthodox legislative processes to pass legislation.

Keywords

Congress unorthodox lawmaking public approval

Voters generally care about ends, not means; they judge government by results and are generally ignorant of or indifferent about the methods by which the results are achieved.

—Samuel Popkin (1994, 99).

I don’t think procedural stuff really resonates with most Americans. It may add generally to their cynicism, but it is accomplishment—or lack of it—that matters much more.

—Tom Daschle, former Senate majority leader.¹

Laws, like sausages, cease to inspire respect in proportion as we know how they are made.

—John Godfrey Saxe.²

Does how Congress makes a law influence approval of that law? Since the 1970s, Congress has increasingly employed unorthodox legislative processes to pass legislation. Once characterized as a decentralized and norm-driven institution that typically adhered to “regular order” legislative procedures, the contemporary Congress frequently bypasses traditional processes when considering legislation, and today’s congressional leaders are willing to use all procedural tools at their disposal to achieve legislative goals (Hanson 2014; Sinclair 2016; Smith 2014).

The public expresses a general preference for civil and bipartisan policy making, and there is ample empirical evidence that legislative and public politicking can damage approval of and faith in Congress as an institution (Harbridge and Malhotra 2011; Jones 2013; Mutz 2015; Ramirez 2009). But does procedural wrangling influence public approval of the laws being wrangled, too? This question has been little studied³ but may have important implications, as citizen skepticism of government processes can reduce public compliance with the law (Marien and Hooghe 2011; Tyler 2006), participation in political processes (Cox 2003; Grönlund and Setälä 2007; cf. Hetherington 1999), and faith in political leaders (Hetherington 1998).

Information about the use of unorthodox tactics may reduce approval for new laws in large part because most citizens have “process preferences” that engender skepticism of legislative politicking (Hibbing and Theiss-Morse 2002), and a sense of “procedural justice” which leads them to view some governmental processes as inherently more, or less, fair (Tyler 1994, 2006). Moreover, information about the use of unorthodox processes may exacerbate partisan motivated reasoning (Druckman, Peterson, and Slothuus 2013) among citizens deciding whether to approve or disapprove of a policy. Reading that Congress bypassed traditional steps of the legislative process is likely to further reduce approval for the policy enacted among those already inclined to be opposed based on policy preferences or partisan-leanings.

This article assesses the impact of public awareness of the use of certain unorthodox processes on approval of new laws. Specifically, it analyzes how procedural hardball tactics—tactics with which congressional leaders strain the rules and bypass traditional legislative processes to win legislative battles—affect levels of public support for the policies enacted. To do this, I draw on two survey experiments, the first embedded in a module of the 2014 Cooperative Congressional Election Study (CCES), and the second fielded using Amazon’s Mechanical Turk (MTurk) in 2016. Both experiments asked respondents to read descriptions of hypothetical new policies passed by Congress, modeled on the language used in newspaper accounts of congressional action. Respondents in control groups just read about the law, while those in the experimental groups also read about processes used to enact the law. The results show that reading about the use of hardball processes reduces approval for the laws, with the sharpest effects among partisans who might already disapprove. In the conclusions, I discuss the implications of these findings for a contemporary era in which Congress is frequently relying on unorthodox tactics to make laws.

Congressional Unorthodoxy

Once characterized as a legislature governed by institutional norms and an adherence to traditional, regular order legislative processes, the contemporary Congress frequently bypasses traditional processes, and its members are more willing to employ all of the procedural tools at their disposal to achieve legislative goals. Barbara Sinclair (2016, 5) termed this new approach unorthodox lawmaking, as “the legislative process on major legislation is now regularly characterized by a variety of what were once unorthodox practices and procedures.”

What does unorthodox lawmaking look like? It includes bypassing the traditional committee stages of the legislative process ahead of floor consideration (Bendix 2016a), with fewer bills subject to committee hearings and testimony (Lewallen, Theriault, and Jones 2016). It also includes closed-down consideration of legislation on the House and Senate floors, with strict limits on debate and amendment (Bach and Smith 1988; Finocchiaro and Rohde 2008; Wallner 2013). Likewise, it includes secretive and behind-the-scenes decision making (Curry 2015), with party leaders assuming more responsibility for cutting deals and constructing legislative proposals (Aldrich and Rohde 2000; Hanson 2014; Rohde 1991; Sinclair 2016).

Most major lawmaking efforts of the last several years have relied on unorthodox processes. Most major legislative drives of the 115th Congress (2017–2018) relied on unorthodox tactics. Both the Republicans’ Affordable Care Act (ACA) repeal and tax reform efforts used special “budget reconciliation” rules that allow Congress to sidestep filibusters and limit debate (Reynolds 2017). The ACA repeal also featured highly secretive processes in which rank-and-file legislators were kept in the dark about deals made behind the scenes.⁴ Several omnibus spending packages reflected negotiations conducted at the leadership table, with committee processes bypassed almost entirely.⁵ These highly unorthodox legislative processes have received considerable attention in the media and among political observers.⁶

Although this approach helps Congress pass legislation (Curry 2015; Sinclair 2016), many scholars and observers view unorthodox lawmaking processes as antideliberative, resulting in dysfunction (Lewallen, Theriault, and Jones 2016; Mann and Ornstein 2006, 2012), the development of poor-quality laws (Bendix 2016b; Drutman 2016; Lewallen 2016), and an erosion of Congress’s public esteem (Ramirez 2009). Do such attitudes affect how the broader public responds to congressional action?

Why Process Might Affect Approval of New Policies

Most scholarship finds people approve or disapprove of a new policy based on its congruence with their policy preferences (Burden 1997; Coughlin 1992; Downs 1957; Enelow and Hinich 1984; Page and Shapiro 2010; Wlezien 1995), its relationship to their partisan attachments (Bartels 2002; Henderson and Hillygus 2011; Layman and Carsey 2002; Miller and Shanks 1996; Shanks and Miller 1991), and their perceptions of the policy’s effects or consequences (Fiorina 1981; Gomez and Wilson 2001; Healy and Malhotra 2013; Kinder and Kiewiet 1979; Nadeau and Lewis-Beck 2001; Tufte 1975). However, there are reasons to suspect processes may influence approval of new policies, as well. Specifically, because citizens: (1) have “process preferences,” (2) have a sense of procedural justice, and (3) often evaluate political events on the basis of partisan motivated reasoning.

First, Hibbing and Theiss-Morse (2001, 2002) find that people’s attitudes about their government and its actions reflect more than policy preferences, but process preferences as well. These preferences capture citizen’s attitudes about how they believe government should and should not work. The individuals in Hibbing and Theiss-Morse’s focus groups saw political conflict as driven by the influence of special interests, evidence of a disconnect between lawmakers and ordinary Americans, and a consequence of corruption in Washington. In their view, abstruse legislative processes should be unnecessary and the conflict driving their use would not exist were the government more responsive to ordinary citizens. This is in part why the public prefers decisive legislative action to prolonged deliberation, and rewards parties for achieving legislative victories (Lebo and Green 2011; Lebo, McGlynn, and Koger 2007).

A consequence of these attitudes is that Americans are likely to be suspicious when they read or hear about Congress resorting to unusual processes to pass laws, especially procedural hardball tactics. For many rationally ignorant citizens (Lau and Redlawsk 2001; Lupia and McCubbins 1998), the use of such tactics likely serves as a heuristic, indicating that something is amiss—that legislators are trying to hide something unpalatable about a bill, or indicating that the policy is too extreme to pass through a “normal” process. As a result, the public may be less inclined to support the resulting policies.

Second, Americans have a sense of procedural justice, viewing some governmental processes as inherently more or less fair, and this may color their reactions to government action. Tyler (1994, 2006) finds citizen’s evaluations of the fairness of processes affects their trust of and compliance with the criminal justice system. Others have extended the logic of procedural justice to other governmental realms, including legislative processes (Gangl 2003) and the processes of the Supreme Court (Gibson 1991). In short, when people believe the government to have violated the rules or proceeded in an unfair manner, public support for political institutions declines, and the legitimacy of decisions made by these institutions is viewed with more suspicion. Over the long run, processes seen as unfair may drive down support for governmental systems as a whole and increase support for reforms (Banducci and Karp 1999; Rose and Mishler 2009). Doherty and Wolak (2012) find the effects of perceived procedural fairness are sharpest when processes are seen as unambiguously fair or unfair, but even ambiguous processes can serve to reinforce people’s biases as they make evaluations. The logic of these studies may apply to congressional enactments—the public may be more skeptical of policies produced via seemingly “unfair” means.⁷

Third, we know from a substantial body of research that Americans are motivated reasoners, not broadly seeking information when making political evaluations, but focusing on information that reinforces their existing beliefs and loyalties (e.g., Taber and Lodge 2006; Zaller 1992). In particular, citizens are partisan motivated reasoners (Druckman, Peterson and Slothuus 2013) who respond to cues and frames coming from their party’s leaders (Slothuus and de Vreese 2010). Consequently, partisans may approve of hardball procedural tactics used by their party, but use by the other party may raise concern, skepticism, and stronger disapproval of the policies they are used to enact.

Process-based messaging by partisan elites to attack and discredit the other party likely reinforces any such effect. Congressional minority parties, while not always able to stop a bill from passing, can always complain that the majority is not acting in good faith by ramming the legislation through, writing it in a shoddy way, stifling debate, advancing it in an unfair manner, and maybe even “cheating” to get it passed. In the U.S. two-party system, out-parties frequently lob partisan attacks against the majority on valence issues—such as process fairness—to try to give their party an edge in the next election (Lee 2009).

Indeed, process-based political messaging has been widespread in recent years, including on high-profile issues. During consideration of the ACA in 2009-2010, conservative commentators and congressional Republicans expressed outrage about the processes Democrats employed. Brian Darling of the Heritage Foundation argued that the use of the budget reconciliation process constituted “cheating.”⁸ Michael Barone of the American Enterprise Institute argued that if the Democrats had constructed the bill through more “careful deliberation” it would probably have had more Republican support.⁹ David Bernstein argued that implementation of the law went poorly because of how the Democrats passed it.¹⁰ During the ACA’s consideration in the House, Republican Paul Ryan (R-WI) joined the chorus:

Congress is moving fast to rush through a health care overhaul that lacks a key ingredient: the full participation of you, the American people . . . Before members even had time to read the 1,000-page bill, it already has cleared two major House committees and is set to be fast-tracked through Congress in the days and weeks ahead. Those members of Congress who voted for this bill already in their committees did so without knowing what the legislation costs.¹¹

A similar line of arguments emerged during the Republican’s efforts to repeal the ACA in 2017, with observers on both sides of the aisle lamenting the process by which it was considered, and Democrats attacking Republicans for their tactics.¹² Although hardball procedural tactics are used to advance both bipartisan and partisan laws (Curry and Lee forthcoming), partisan messaging around their use can be used to score easy political points.

The media likely reinforces this kind of messaging with the public. The news media is inclined to cover conflict and combat, rather than cooperation (Atkinson 2017), and Bennett (2012) finds that controversial action generally spurs more media attention. Moreover, Lawrence (2000) finds the media is inclined to present congressional action as a game, focusing on strategy over issue substance. Hardball tactics play right into this media focus, with the news articles likely to cover not only the use of unusual processes but also any partisan outrage that erupts over their use.

Consequently, party messaging and media coverage may serve to reinforce and shape public reactions to the use of hardball tactics. As Harbridge, Malhotra, and Harrison (2014) find, partisans are willing to set aside their general preferences for bipartisan lawmaking if it means their party gets a policy win, but not the other way around. Smith and Park (2013) find the public dislikes at least one congressional process—the filibuster—when it obstructs their party’s goals, but like it just fine when it helps. The same, partisan-conditioned effects may be found in the public’s subsequent approval of new laws.

Research Design and Measurement

I conducted two survey experiments to assess the influence of hardball congressional processes on public support for new laws. Each asks respondents to read a description of a hypothetical new policy passed by Congress and indicate their approval or disapproval. Additional information about partisan conflict present during consideration of the law, or the use of procedural tactics, is provided to those randomly assigned to treatment groups.¹³

I took several steps to bolster external validity. First, the experiments had respondents read about the passage of laws across five different policy areas—transportation, energy, defense, abortion, and tax policy. This helped ensure the results were not a function of selecting a single policy for analysis. It also allowed me to assess if the effects of the treatments varied by policy area. Second, I loosely based the description of each policy on actual bills considered or passed by at least one chamber of Congress during the last two decades, providing a dose of realism to the policy descriptions. However, I was careful to draw on policy proposals that were not particularly prominent to minimize concerns of pretreatment bias (Druckman and Leeper 2012). Third, I based the language used for the descriptions on that used in major newspaper reports of congressional action. This placed the experiments within in a realm of realism, as the information respondents read is similar to the information in a short newspaper article. The supplemental appendix contains all language used for both experiments.

It is also important that the portrayal of hardball processes closely reflected real media coverage for the experiments to be valid. Portrayals of congressional process that differ considerably from media descriptions would not help us understand how information about the use of these processes affects public reactions to new policies. This effort influenced both the processes selected for the treatments and how they were described. First, the two processes selected for the treatments—“budget reconciliation” and “self-execution”—are processes that are covered in the media from time to time and that can be understood by the public. Budget reconciliation is, as noted above regarding the ACA and ACA repeal and replace efforts, sometimes covered in by the media when employed in Congress. It is also a relatively understandable effect in that it side-steps filibusters (Reynolds 2017). Self-execution is less well known, but is used to execute a legislative tactic also often used and easy to understand. Self-executing special rules change the contents of an underlying bill as the rules for floor debate are set in the House of Representatives. Congressional leaders frequently used this process to make last minute changes to legislation or advance a brand-new version of bill immediately before a vote and to avoid public and legislative scrutiny of those changes (see Curry 2015). Such last minute changes are common and easy to explain in a news article.

Second, the language used to describe these processes in the treatments reflects how they are described in journalistic coverage. Generally, the hardball tactics are described with something of a negative, normative tinge. They are described as “arcane,” “rarely used,” or otherwise unusual, and employed to sidestep traditional processes or the opposition of certain lawmakers. For whatever reason, this softly negative portrayal is ubiquitous in media coverage of congressional process innovation. Although positively framed treatments would allow us to understand if the use processes could hypothetically have different effects on public approval if framed differently, unorthodox processes are so rarely presented in a positive light that this would undermine the validity of the study for the current state of reality.¹⁴

The first experiment was embedded in a module of the 2014 CCES with 1,000 respondents. The experiment asked respondents to read about and register their approval or disapproval for a hypothetical transportation policy on a 4-point scale (How would you describe your level of approval or disapproval of this policy? Options: strongly disapprove, disapprove, approve, and strongly approve). Respondents were randomly assigned either to a control group or one of three treatment groups, each provided with a slightly altered description of the policy. The first group (policy only) was the control group. These respondents were provided a straightforward description of the policy. The second group (partisan) was provided the same description but was also told about party-line votes in the House and the Senate and unified opposition from congressional Republicans. The third group (process) was not only given the same policy description but also told about the use of budget reconciliation to avoid filibusters from the bill’s opponents. Untold is the partisan nature of any opposition to the policy and which party used the procedure. The fourth group (combined) was provided with the policy description as well as the details about both partisan conflict and the use of budget reconciliation. Separate partisan and process treatments allowed me to assess the relative impact of each and find out if the information about the hardball processes had an effect independent of partisan conflict. The combined treatment allowed the analyses to assess if the effect of process is conditioned by an explicit reference to party conflict. Table 1 provides an overview of the language used in this experiment.

Table 1.

Sample of Language Used in the CCES and MTurk Experiments.

CCES 2014 language	2016 MTurk language (tax policy example)
[italics] = Added for the “partisan” treatment [bold] = Added for the “process” treatment [underline] = Added in the “combined” treatment After months of negotiation, Congress passed a major transportation bill on Wednesday. The bill [ which cleared the House by a close party line vote, 217–202, and was unanimously opposed by House Republicans ] allots $286 billion for roads, bridges, mass transportation, and safety projects over the next six years, and is expected to create thousands of new jobs [and was opposed by numerous lawmakers dissatisfied with many of the underlying policies. House and Senate leaders had to rely on a rarely used process known as “budget reconciliation” to push the bill through the floor of each chamber. This arcane process allowed the Senate to sidestep any filibusters and pass the bill by a simple majority.] According to the House Committee on Transportation and Infrastructure, 80 percent of the money will go to road projects, 18 percent to mass transit, and the remainder to road safety and other projects. In addition, the bill imposes sweeping new auto safety standards, including provisions that raise rollover standards on minivans and other large vehicles, and a provision that requires the crash test ratings of cars and trucks to be posted on window stickers visible to consumers. Perhaps most sweeping are new rules that would withhold federal transportation funds from states that do not pass laws allowing police officers to pull over drivers for not wearing their seatbelts. [Senate Republicans strenuously opposed this policy arguing it violated state sovereignty and represented an overreach by the federal government. The bill passed the Senate by a close party-line vote last month.] [However, the budget reconciliation process restricted Republicans from mounting a filibuster and the bill ultimately passed by a close party-line vote.] [Several senators threatened to filibuster the bill over these rules, but due to the reconciliation process were unable to mount an effective opposition.] The bill is expected to be signed by the President by the weekend.	[italics] = Added for the “partisan” treatment [bold] = Added for “process” treatment option 1 [underline] = Added for “process” treatment option 2 Congress passed new tax legislation on Wednesday [ after prolonged debate and strenuous opposition from numerous lawmakers ]. The bill, which [cleared the House by a close party line vote, 217–202, and was unanimously opposed by House Republicans,] cuts taxes modestly for low- and middle-income families while boosting taxes on high-income individuals and businesses, is expected to increase government revenues by $3 trillion over the next decade. Nearly $1 trillion of that total will be achieved by closing tax loopholes for wealthy Americans, including one loophole that allows households making more than $250,000 a year to avoid some taxes by passing investment income through partnerships or businesses. Other revenue boosters include restoring estate tax rates and thresholds to 2009 levels, imposing new fees on financial institutions, and setting a new minimum tax rate of 30 percent on people who earn more than $1 million. [Senate Republicans strenuously opposed these provisions, arguing that the new taxes were job killers, and another example of Democrats trying to grow the size of the government on the backs of American tax payers.] In addition, several proposals aim to ease the tax burden on lower- and middle-income Americans, including a provision that triples the maximum allowable child care tax credit, and another that strengthens the earned-income tax credit for workers not raising children. [House and Senate leaders had to rely on a rarely used process known as “budget reconciliation” to push the bill through each chamber. This arcane process allowed Senate leaders to sidestep attempts by numerous senators to filibuster the bill.] [Congressional leaders used a process known as “self-execution” to ease the passage of the bill. This process made various changes to the bill without any debate, and immediately before passage. As a result lawmakers opposed to these new provisions were unable to voice their concerns.] The bill is expected to be signed by the President over the weekend.

CCES 2014 language

2016 MTurk language (tax policy example)

[italics] = Added for the “partisan” treatment
[bold] = Added for the “process” treatment
[underline] = Added in the “combined” treatment
After months of negotiation, Congress passed a major transportation bill on Wednesday. The bill [ which cleared the House by a close party line vote, 217–202, and was unanimously opposed by House Republicans ] allots $286 billion for roads, bridges, mass transportation, and safety projects over the next six years, and is expected to create thousands of new jobs [and was opposed by numerous lawmakers dissatisfied with many of the underlying policies. House and Senate leaders had to rely on a rarely used process known as “budget reconciliation” to push the bill through the floor of each chamber. This arcane process allowed the Senate to sidestep any filibusters and pass the bill by a simple majority.]
According to the House Committee on Transportation and Infrastructure, 80 percent of the money will go to road projects, 18 percent to mass transit, and the remainder to road safety and other projects. In addition, the bill imposes sweeping new auto safety standards, including provisions that raise rollover standards on minivans and other large vehicles, and a provision that requires the crash test ratings of cars and trucks to be posted on window stickers visible to consumers.
Perhaps most sweeping are new rules that would withhold federal transportation funds from states that do not pass laws allowing police officers to pull over drivers for not wearing their seatbelts. [Senate Republicans strenuously opposed this policy arguing it violated state sovereignty and represented an overreach by the federal government. The bill passed the Senate by a close party-line vote last month.] [However, the budget reconciliation process restricted Republicans from mounting a filibuster and the bill ultimately passed by a close party-line vote.] [Several senators threatened to filibuster the bill over these rules, but due to the reconciliation process were unable to mount an effective opposition.] The bill is expected to be signed by the President by the weekend.

[italics] = Added for the “partisan” treatment
[bold] = Added for “process” treatment option 1
[underline] = Added for “process” treatment option 2
Congress passed new tax legislation on Wednesday [ after prolonged debate and strenuous opposition from numerous lawmakers ]. The bill, which [cleared the House by a close party line vote, 217–202, and was unanimously opposed by House Republicans,] cuts taxes modestly for low- and middle-income families while boosting taxes on high-income individuals and businesses, is expected to increase government revenues by $3 trillion over the next decade. Nearly $1 trillion of that total will be achieved by closing tax loopholes for wealthy Americans, including one loophole that allows households making more than $250,000 a year to avoid some taxes by passing investment income through partnerships or businesses. Other revenue boosters include restoring estate tax rates and thresholds to 2009 levels, imposing new fees on financial institutions, and setting a new minimum tax rate of 30 percent on people who earn more than $1 million. [Senate Republicans strenuously opposed these provisions, arguing that the new taxes were job killers, and another example of Democrats trying to grow the size of the government on the backs of American tax payers.] In addition, several proposals aim to ease the tax burden on lower- and middle-income Americans, including a provision that triples the maximum allowable child care tax credit, and another that strengthens the earned-income tax credit for workers not raising children. [House and Senate leaders had to rely on a rarely used process known as “budget reconciliation” to push the bill through each chamber. This arcane process allowed Senate leaders to sidestep attempts by numerous senators to filibuster the bill.] [Congressional leaders used a process known as “self-execution” to ease the passage of the bill. This process made various changes to the bill without any debate, and immediately before passage. As a result lawmakers opposed to these new provisions were unable to voice their concerns.] The bill is expected to be signed by the President over the weekend.

CCES = Cooperative Congressional Election Study; MTurk = Amazon’s Mechanical Turk.

The second survey experiment used a sample of 2,009 adult Americans recruited in October 2016 using MTurk. Table 2 provides details on the MTurk sample alongside the CCES sample. Consistent with most MTurk samples, the respondents are generally younger, more democratic-leaning, more liberal, and better educated than the more nationally representative CCES. Nonetheless, Berinsky, Huber, and Lenz (2012) find that MTurk samples are more representative than the convenience samples used for most experimental studies and provide for valid analyses.

Table 2.

Comparison of CCES and MTurk Samples.

	CCES (2014)	MTurk (2016)
N	1,000	2,009
Democrats (including leaners)	48.2%	55.1%
Republicans (including leaders)	34.9%	28.7%
Liberal (moderately to very)	29.6%	48.4%
Conservative (moderately to very)	37.3%	24.2%
Median age	53	33
Median education level	Some college	4-year college degree
In control group	22.9%	25.1%
In partisan treatment group	26.1%	24.9%
In process treatment group	26.2%	49.9%
In combined treatment group	24.8%	—

CCES = Cooperative Congressional Election Study; MTurk = Amazon’s Mechanical Turk.

The experiment itself was a three-by-four factorial design. Respondents were randomly assigned either into a control group or one of two treatment groups, but they were also randomly assigned to read about one of four different hypothetical policies—an energy policy, a defense policy, an abortion policy, or a tax policy. The treatments groups are slightly different from the CCES experiment. Again, the control group (policy only) was only provided a description of the policy. The second group (partisan) added language about explicit conflict between the parties and opposition from one party or the other, varying by policy. Republicans were described as “unanimously opposed” to the energy and tax policies, and Democrats as “unanimously opposed” to the abortion and the defense policies. About half of the respondents were assigned to a process group, and respondents within this group were provided a description of the policy along with information about the use of one of two unorthodox processes used to pass the law—either budget reconciliation or self-execution. These two process “subgroups” are combined for the analyses.¹⁵ All respondents were asked the same question as in the CCES to register their approval or disapproval for the policy. Table 1 provides an example of the language added for each treatment group.¹⁶

The five policies used across the two studies provide some variety to the setting of the experiment. These policies include a distributive policy (transportation), a regulatory policy (energy), a social/cultural policy (abortion), policies that divide the parties along traditional lines (tax, energy, abortion), and those that are sometimes partisan and sometimes bipartisan (transportation and defense). Each policy was written to be more favorable to the preferences of one side of the aisle or the other. Specifically, the tax and energy policies were written to be viewed favorably by Democrats, and the defense and abortion policies were written to be viewed favorably by Republicans. The transportation policy in the CCES survey was written to be as neutral as possible and serves as a comparison. These partisan differences across issues allow the analyses to assess if the effect of information about the use of unorthodox processes is conditioned by partisanship. Partisans inclined to dislike a policy may be more upset by the use of unorthodox or “unfair” processes than those inclined to support it.

In both the CCES and MTurk surveys, several other measures serve as controls in multivariate analyses. These include a traditional party identification measure that includes partisan leaners, and a measure of each respondent’s self-reported ideology (collapsed into an ideological extremity measure).¹⁷ These measures control for respondents’ political predispositions. Also included is a 5-point measure of each respondent’s presidential job approval for President Obama. In addition, each respondent’s self-reported age, gender (female), annual income, level of education, and race/ethnicity (nonwhite) were measured. More details on these variables are found in the supplemental appendix.

Expectations

What are the specific expectations for the analyses? One is simply that the process treatment will decrease likelihoods that individuals approve of any new policy. Because Americans’ process preferences and sense of procedural justice predispose them to dislike legislative maneuvering and politicking, information about the use of hardball processes may generally reduce support for the policies described:

Hypothesis 1: The process treatment will reduce the likelihood a respondent approves of the policy.

Another possibility is that process effects are conditioned by partisanship. As noted above, partisan elites sometimes leverage complaints about congressional processes to score points off the majority, building and reinforcing opposition among their supporters in the public. Furthermore, prior research suggests the public might care more about process when their party is set to lose, compared with when it benefits their party (see Smith and Park 2013):

Hypothesis 2: The process treatment will reduce likelihoods of approval among partisans inclined to oppose the policy, but not among partisans inclined to support the policy.

The MTurk experiments are set up nicely to test hypothesis 2 with different policies written to appeal to different partisan groups. Specifically, if hypothesis 2 is supported, the process treatment will reduce support among Democrats for the abortion and defense policies and reduce support among Republicans for the tax and energy policies. In the CCES experiment, the combined treatment group will provide insight. Respondents in this group are told Republicans opposed the policy and Democrats used unorthodox tactics to pass it. If process effects are conditioned by partisanship the combined treatment will reduce support among Republicans but not Democrats, and the combined effect will be larger than the process effect among Republican respondents.¹⁸

Results

Figure 1 presents bivariate results from each survey experiment, showing the combined percent of respondents who indicated they approved or strongly approved of the hypothetical policy. Across issues, those exposed to the treatments registered less support than those in the policy only control groups. Specifically, every process treatment and the combined treatment had a statistically significant and negative effect on approval. The top-right panel in the figure shows this for all four issues combined in the MTurk survey: 65 percent of respondents in the policy-only group were supportive of the policy, on average. Among those exposed to the partisan treatment, 60 percent indicated approval, a 5-percentage-point drop. Among those exposed to the process treatment, 59 percent indicated approval, a 6-percentage-point drop.

Figure 1.

Raw support for new laws by treatment groups (CCES 2014 and MTurk 2016).

Across the different issues, the results are generally similar, though overall levels of support and the size of the effects vary. For instance, the Republican-leaning policies in the MTurk survey (abortion and defense) were generally less popular than the Democratic-leaning policies (energy and taxes), likely reflecting the larger number of Democrats in the sample, but the process treatment had similarly sized effects on both, reducing rates of approval by 6-percentage-points and 5-percentage-points, respectively. The partisan treatment had a similar-size effect for the Republican-leaning policies (about 6-percentage-points), but a smaller and insignificant effect among Democratic policies (about 3-percentage-points). The neutral transportation policy in the CCES survey was also broadly supported (69% approval in the policy only group), but treatment group respondents were less approving. Specifically, the process group was about 9-percentage-points less approving, and the partisan and combined groups were about 8-percentage-points less approving. Altogether, the bivariate results in Figure 1 support hypothesis 1. The process treatment broadly reduced approval of hypothetical new laws passed by Congress. Notably, the size of the effects was roughly similar to or larger than the effects of the partisan treatments, which have a well-established effect on public opinion.

Figure 2 looks for partisan conditioning of the process treatment (hypothesis 2), showing bivariate results separately for Democrats and Republicans (including partisan leaners in each group). The results generally provide support for hypothesis 2—the use of hardball legislative tactics reduces approval among partisans who should be inclined to oppose the policy, but not among partisans inclined to be in support. For instance, the process treatment strongly reduces approval for the Republican-leaning policies among Democrats. Although about 46 percent of Democrats in the policy only group supported these policies, only 34 percent in the process group indicated approval—a 12-percentage-point drop. By comparison, Republican respondents in the policy only and process group had similar levels of approval. Among the Democratic-leaning policies, the results are reversed. Roughly 61 percent of Republican respondents in the policy only group supported the Democratic-leaning policies, compared with just 47 percent in the process group. Among Democratic respondents, approval for these policies is around 91 percent regardless of the treatment.

Figure 2.

Raw support for new laws by party identification and treatment groups (CCES 2014 and MTurk 2016).

The treatment effects for the CCES transportation policy provide support for hypothesis 2 as well. The combined treatment, which told respondents that Republican members of Congress opposed the law and that Democrats used unorthodox tactics to pass it, only reduced approval among Republican respondents. Specifically, while roughly 52 percent of Republicans in the policy only group approved of the policy, just 30 percent in the combined group indicated approval. By comparison, Democratic support for the policy is actually higher among those in the combined group, though the difference is not statistically significant. Combined, the bivariate results in Figures 1 and 2 provide strong support for both hypotheses.

Tables 3 and 4 begin to assess these hypotheses with multivariate tests. First, Table 3 presents the results of logistic and ordered logistic regression analyses for the CCES survey experiment. The dependent variable for the logistic regressions combines approve and strongly approve, and disapprove and strongly disapprove, responses to create a dichotomous measure of approval. The dependent variable for the ordered logistic regression is the 4-point measure of approval, ranging from strongly disapprove (0) to strongly approve (3). This second measure can be thought of as the intensity of approval/disapproval expressed by the respondents.

Table 3.

CCES Survey Experiments (2014)—Transportation.

	Dichotomous approval (logit)		Intensity of approval (ordered logit)
	(1)	(2)	(3)	(4)
Partisan group	−0.328* (0.192)	−0.312 (0.219)	−0.244 (0.168)	−0.203 (0.177)
Process group	−0.402** (0.191)	−0.411* (0.218)	−0.285* (0.169)	−0.304* (0.178)
Combined group	−0.310 (0.194)	−0.390* (0.224)	−0.240 (0.171)	−0.312* (0.180)
Democrats		0.656*** (0.242)		0.714*** (0.207)
Republicans		−0.424* (0.220)		−0.362* (0.196)
Ideological extremity		−0.188*** (0.071)		−0.198*** (0.059)
Presidential approval		0.351*** (0.070)		0.358*** (0.060)
Age		0.001(0.005)		0.003(0.004)
Female		0.459*** (0.152)		0.309** (0.125)
Education		0.014(0.056)		0.014(0.046)
Income		−0.028(0.027)		−0.008(0.022)
Nonwhite		−0.137(0.194)		−0.339** (0.154)
Constant	0.820*** (0.143)	1.049** (0.409)
Cut 1, constant			−2.121*** (0.146)	−2.400*** (0.349)
Cut 2, constant			−0.748*** –0.127	−0.810** –0.336
Cut 3, constant			1.582*** –0.137	1.914*** –0.346
N	1,000	952	1,000	952

CCES = Cooperative Congressional Election Study.

p < .10. **p < .05. ***p < .01.

Table 4.

MTurk Survey Experiments (2016)—All Issues.

	Dichotomous support (logit)		Intensity of support (ordered logit)
	(1)	(2)	(3)	(4)
Partisan group	−0.233* (0.138)	−0.198(0.141)	−0.151(0.119)	−0.144(0.121)
Process group	−0.272** (0.120)	−0.264** (0.122)	−0.177* (0.102)	−0.173* (0.104)
Democrats		0.346** (0.162)		0.340** (0.138)
Republicans		0.689*** (0.164)		0.512*** (0.140)
Ideological extremity		−0.169** (0.078)		−0.113* (0.068)
Presidential approval		0.196*** (0.048)		0.173*** (0.041)
Age		0.002(0.004)		−0.002(0.004)
Female		0.136(0.101)		0.124(0.087)
Education		−0.042(0.042)		−0.040(0.036)
Income		0.023(0.015)		0.009(0.013)
Nonwhite		0.012(0.122)		−0.038(0.103)
Issue group dummies	✓	✓	✓	✓
Constant	0.109(0.123)	−0.729** (0.308)
Cut 1, constant			−1.790*** (0.119)	−1.267*** (0.268)
Cut 2, constant			−0.119(0.107)	0.408(0.264)
Cut 3, constant			2.361*** (0.124)	2.923*** (0.275)
N	2,009	1,961	2,009	1,961

MTurk = Amazon’s Mechanical Turk.

p < .10. **p < .05. ***p < .01.

Columns 1 and 2 in Table 3 show the results of the logit regressions, and the results confirm that the treatments reduce the likelihood that a respondent will support the described policy. Columns 3 and 4 show the ordered logit regressions assessing the impact of the treatments on the intensity of support or opposition. In both sets of analyses, the process treatment has a negative and statistically significant effect on respondent approval. In the models with control variables, the combined treatment also has a negative and statistically significant effect. Generally, the results support hypothesis 1.

The left panel in Figure 3 presents predicted effects from analyses in Table 3 (column 2), showing the substantive size of the treatment effects controlling for other important variables. All three treatments reduced the likelihood an individual will support the policy by about 10-percentage-points. Specifically, while respondents in the policy only group are predicted to have, on average, a 68 percent likelihood of approving of the policy, those in the combined group are predicted to have just a 58 percent likelihood of approval, on average, and those in the process group are predicted to have a 59 percent likelihood of approval, on average.

Figure 3.

Predicted likelihoods of approval among treatment groups from the analyses in Tables 3 and 4.

Table 4 shows the regression results for the MTurk survey experiments, combining the results across issues. Again, both logistic and ordered logistic results are shown. In all four analyses, the process treatment had a negative and statistically significant effect on the likelihood of approval. Notably, while the process treatment had a consistent effect, the partisan treatment did not. The right panel in Figure 3 shows the substantive effects (from column 2). Respondents in the policy only group are predicted to have a 65 percent likelihood of approval, while those in the process group are predicted to have a 58 percent likelihood of approval.

The results in Tables 3 and 4 provide strong support for hypothesis 1 controlling for several variables that help predict respondents’ likelihoods of approval, including their partisanship, their ideology, and their approval of President Obama. These variables had large effects on respondents’ levels of the support for the policies. Other demographic controls including age, gender, race, education, and income, did not have consistent effects. Importantly, across these tests, the effects of the process treatment is always similar in size or larger than the effect of the partisan treatment. In addition, process effects were more consistently significant than the effects of the partisan treatment.

The results in Table 5 assess the conditional partisan effects of the process treatments. In each analysis, each treatment dummy is interacted with dummy variables for Democratic and Republican respondents. Each analysis is a logistic regression, with the dichotomous measure of approval as the dependent variable. As interpreting the significance of interaction effects from coefficients is difficult, the predicted effects by party and treatment are presented in Figure 4.

Table 5.

All Survey Experiments (CCES 2014 and MTurk 2016) by Issue with Party Interactions.

	Transportation (neutral)	Democratic-leaning (energy and taxes)	Republican-leaning (abortion and defense)
Partisan group (both CCES and MTurk)	0.542(0.483)	−0.531(0.482)	0.702(0.471)
Process group (both CCES and MTurk)	0.233(0.480)	−0.388(0.422)	0.025(0.411)
Combined group (CCES, only)	−0.117(0.489)	—	—
Democrats	1.057** (0.459)	0.730(0.477)	0.597(0.391)
Republicans	0.335(0.436)		1.461*** (0.425)
Partisan Group × Democrats (both CCES and MTurk)	−0.602(0.611)	0.779(0.654)	−1.528*** (0.540)
Partisan Group × Republicans (both CCES and MTurk)	−1.469** (0.589)	0.155(0.608)	−0.341(0.600)
Process Group × Democrats (both CCES and MTurk)	−0.974* (0.588)	0.394(0.566)	−0.456(0.466)
Process Group × Republicans (both CCES and MTurk)	−0.581(0.580)	−0.141(0.525)	−0.039(0.515)
Combined Group × Democrats (CCES, only)	0.295(0.627)	—	—
Combined Group × Republicans (CCES, only)	−0.880(0.600)	—	—
Ideological extremity	−0.205*** (0.073)	−0.084(0.137)	−0.269** (0.109)
Presidential approval	0.353*** (0.071)	0.498*** (0.074)	−0.024(0.069)
Age	0.001(0.005)	−0.007(0.008)	0.009(0.006)
Female	0.493*** (0.155)	−0.120(0.175)	0.258* (0.140)
Education	0.011(0.056)	−0.044(0.073)	−0.007(0.058)
Income	−0.029(0.027)	−0.008(0.026)	0.034(0.021)
Nonwhite	−0.185(0.198)	−0.392* (0.217)	0.347** (0.165)
Constant	0.624(0.494)	0.820(0.536)	−1.219** (0.503)
N	952	984	977

CCES = Cooperative Congressional Election Study; MTurk = Amazon’s Mechanical Turk.

p < .10. **p < .05. ***p < .01.

Figure 4.

Interaction effects—Predicted likelihood of approval among party and treatment group (CCES 2014 and MTurk 2016).

Starting with the Democratic-leaning policies in the MTurk experiment (top left panel), the predictions show that the process treatment reduces likelihoods of approval only among Republican respondents. Specifically, the process treatment is predicted to reduce a Republican’s likelihood of approving a Democratic-leaning policy by about 10-percentage-points, on average. Among the Republican-leaning policies (top-right panel), the process treatment only reduces support among Democrats, reducing a Democrat’s likelihood of approving a Republican-leaning policy by 10-percentage-points, as well. These results provide clear support for hypothesis 2.

The bottom left panel shows the partisan-interactive effects for the process and combined treatments for the neutral transportation policy used in the CCES experiment. The results support hypothesis 2, as well. Among Republicans, the key effect is for the combined treatment, which has a negative and statistically significant effect. When Republican respondents are told their party in Congress opposed the policy and that Democrats used aggressive procedural tactics to pass it, their likelihoods of approving the policy dropped from about 64 percent (among the policy only group) to about 42 percent. Among Democrats, the process treatment significantly reduces likelihoods of approval, but the combined treatment erases any procedural effects. Democrats appear fine with the use of unorthodox processes when they are also told their party in Congress supported the measure. These combined effects strongly indicate that public reactions to the use of hardball processes can be conditioned by partisanship. Among policies their party supports, partisans are willing to accept the use of aggressive legislative tactics, but among policies their party opposes, procedural wrangling drives down support.

Generally, across the analyses presented here, there is substantial support for both hypotheses. In both bivariate and multivariate analyses, the process treatment reduces overall likelihoods of approval for hypothetical policies enacted by Congress (hypothesis 1). Upon closer investigation, likelihoods of approval appear to be reduced the most among partisans inclined to oppose the policy on substantive or partisan grounds, and among those prompted that their party in Congress was in opposition to the policy (hypothesis 2). Broadly, it appears public awareness of the details of unorthodox processes reduces approval for new policies.

Conclusion

What conclusions can be drawn? The evidence here suggests when the use of hardball procedural tactics is communicated to the public it is less approving of laws passed by Congress. This was true for respondents across two different survey experiments conducted in different years, drawing on different samples of Americans, presenting differently worded treatments, and using a variety of different policies. Polarizing effects of process were also found, as information about unorthodox legislating primarily reduced support among one group of partisans or the other, depending on the policy issue. This suggests that even when process does not have a uniform effect of reducing support for a law, it may polarize support for the law, further undercutting the legitimacy of a policy among a large subset of the public.

These findings are troubling because in recent years Congress has had to turn to unorthodox processes more frequently to pass laws. Indeed, it is difficult to find a major law passed in recent years that followed a “regular order” process from start to finish. The contemporary political environment is too contentious, with Congress facing small majorities, frequent divided government, and rampant partisanship as it tries to do its work. Unorthodox processes are a solution for congressional leaders to legislate in the face of these challenges (Sinclair 2016). However, if their use undermines the very laws Congress enacts, or polarizes support for these laws, then we should be concerned. Indeed, politicking and political conflict drive Americans’ disdain for their politics and both political parties (Klar and Krupnikov 2016). Apparently, it can drive down support for laws, too.

How much confidence should we have in these findings? Although experiments certainly have limitations, they have become increasingly common in political science in recent years and have helped political scientists gain insight into causal relationships on a number of topics (see Druckman et al. 2006). For this study, an observational approach is implausible. With many, or perhaps most, major laws passed using some form of unorthodox processes, and with so many other factors influencing an individual’s level of support for a law at any moment in time, an experimental approach makes it easier to identify a causal effect. Nonetheless, the experiments here were written to replicate reality as closely as possible, describing policies actually considered by Congress, and describing processes in the manner they are described in the media.

Ultimately, the results suggest that the manner by which Congress considers and passes laws can have important consequences. Those of us who educate Americans about policy making processes in Washington should keep this in mind as we teach our students about Congress and congressional action, and those of us who wish to reform Congress should keep these results in mind as recommendations are made for how congressional processes might be changed.

Supplemental Material

Supplemental_Appendix_(1) – Supplemental material for Congressional Processes and Public Approval of New Laws

Supplemental material, Supplemental_Appendix_(1) for Congressional Processes and Public Approval of New Laws by James M. Curry in Political Research Quarterly

Footnotes

Acknowledgements

The author thanks to Michael Brady, Chris Donnelly, and Thad Hall for their helpful advice and feedback.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Betty Glad Memorial Fund at the University of Utah.

Notes

Supplemental Material

The data used for the analyses in this articles can be found at the following for replication: .

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