BALANCING THE LEGISLATIVE AGENDA: SCHEDULING IN THE UNITED STATES HOUSE OF REPRESENTATIVES
DISSERTATION
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University
By
Edward Brooke Hasecke, M.A.
*****
The Ohio State University 2002
Dissertation Committee: Approved by Professor John Wright, Adviser
Professor Herbert Weisberg Adviser Professor Jan Box-Steffensmeier Department of Political Science UMI Number: 3081924
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ProQuest Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, Ml 48106-1346 ABSTRACT
The Speaker of the House has tremendous procedural authority over the
legislative schedule. He is able to defme which bills will be considered and when they
will be considered. This gives him an effective veto over the schedule and allows him to
define the legislative agenda. The concentration of agenda control in the hands of the
Speaker and the increased partisanship in the House has led scholars to argue that the
Speaker uses his scheduling authority to create a legislative agenda that is biased towards
the majority party’s interests. In this dissertation, I challenge this portrait of the Speaker.
I argue that the Speaker is an agent of the chamber and the majority party and to satisfy
these competing principals, he must balance the chamber’s institutional demand for
fairness and the majority party’s demand for partisan benefits.
The partisan theory of scheduling and my balancing theory lead to different
expectations about scheduling, which are the basis for the empirical analysis. First, partisan theories argue that the Speaker will frequently change the regular order of business to optimize a bill’s partisan benefits. I expect, however, that the Speaker will
rarely deviate from the calendar order. Using data from the 100**’ and 105**’ Congresses, I
compare the actual schedule for each legislative day to the calendar schedule. I frnd that
the Speaker rarely deviates from the regular order of business.
ii Second, partisan theories argue that committees will anticipate the Speaker’s partisan preferences and show a strong partisan bias when reporting bills. I, on the other
hand, argue that committees are designed to provide different benefits and that partisan benefits will not always be dominant. Using original data on all bills and resolutions sent
to committee, I find that in the 100**’ Congress committees were biased towards securing
gains-tfom-exchange. In the 105**’ Congress, committees were biased towards partisan benefits.
Third, partisan theories argue that the Speaker will use his scheduling authority to
advance partisan goals. I argue that the Speaker will first facilitate the committee agenda
(whatever the legislative bias) and second schedule unreported bills that provide benefits undersupplied by the committee system so as to balance the schedule and satisfy
institutional and partisan demands. I find that Speaker Wright in the 100**’ Congress
showed the same gains-ffom-exchange bias of the committee system when scheduling
reported bills and brought balance to the agenda by scheduling partisan bills that were not
reported. In the 105**’ Congress, Speaker Gingrich facilitated the partisan bias of the
committee system when scheduling reported bills, but balanced the schedule by providing
gains-ffom-exchange benefits in the unreported bills he scheduled.
Ill TO CATHY AND EMILY
IV ACKNOWLEDGMENTS
Over the eourse of this projeet, I have benefited tfom the intelleetual support,
eneouragement, and eonstruetive eritieism of many people. Yet no single person has pushed me more than my advisor, Jaek Wright. I am indebted to his investment of time,
his stylistie and seientifie adviee, and his willingness to ask the “tough” questions. He
has ehallenged my thinking in ways that have both benefited this projeet and helped me
grow as a seholar.
I would like to thank Herb Weisberg for taking me under his wing early in my
graduate eareer. He has frequently asked questions that ehallenge my assumptions and push me to think out of the box. He also has provided emotional support during the ups
and downs of graduate life.
I am grateful to Jan Box-Steffensmeier for her substantive and methodologieal
help. She read the first paper I wrote on agenda setting proeedures and helped me see the
larger pieture. In addition, her methodologieal help erystallized my way of thinking
about seheduling and informs both my eurrent and future work in this area.
I am indebted to Jim Eudwig for writing the eomputer program that turned
thousands of HTME pages from THOMAS into text data that I eould use. He saved me
hundreds of hours of work. I also want to thank Paul Beek, Dean Eaey, Rieh Timpone, and participants in the Research in American Politics group at Ohio State for their
comments and suggestions.
Financial support for this research came tfom The Ohio State University through
the Presidential Fellowship and tfom the Department of Political Science through the
PEGS Dissertation Grant.
This project would not he where it is without the consistent tfiendship of my
graduate colleagues Scott Meinke, William Anderson, and J. Tobin Grant. They not only
read numerous drafts, hut also consumed more cotfee than is healthy as we discussed politics, research questions, statistical models, and life in general. I will always be
grateful to them for making graduate school fun and challenging.
Finally, my greatest debt is to my wife Cathy. The importance of her love and
support cannot be expressed in words. She has listened endlessly to my struggles and
helped me work through the conceptual and organizational work of writing. No one
gives me greater confidence and provides a safer place to fall than she. This project
would not have been possible without her constant love and reassuring words.
VI VITA
November 25, 1974 ...... Born - Pittsburgh, PA
1997 ...... B.A. - Politieal Seienee, Wittenberg University.
1997 -2000 ...... Graduate Teaebing Assistant and Researeb Assistant, The Ohio State University
2000 ...... M.A. - Politieal Seienee, The Ohio State University
2000 - present...... Graduate Teaehing, The Ohio State University
PUBLICATIONS
1. Meinke, Seott R. and Edward B. Haseeke. “Professionalization, Term Limits, and Partisan Control in U.S. State Legislatures.”Journal o f Politics, fortheoming.
LIELDS OP STUDY
Major Pield: Politieal Seienee Coneentration: Ameriean Polities Politieal Eeonomy
VII TABLE OF CONTENTS
Page
A bstract...... ii
Dedication...... iv
Acknowledgments...... v
V ita ...... vii
Eist of Figures...... x
Chapters:
1. Introduction...... 1
1.1 The Scheduling Decision and Agenda Control...... 3 1.2 D a ta ...... 9 1.3 Outline of Dissertation...... 12
2. The Scheduling D ecision...... 16 2.1 The Partisan Speaker...... 17 2.2 An Alternative View: The Balancing Speaker...... 26 2.2.1 Competing Principals...... 27 2.2.2 Agenda-Setting...... 32 2.2.3 Influencing the Committee Agenda...... 36 2.3 Empirical Predictions...... 38 2.4 Conclusion...... 41
3. Following the Calendar...... 42 3.1 The Scheduling Process: Rules and Procedures...... 43 3.1.1 Circumventing the Regular Order of Business...... 49 3.2 Comparing the Actual Schedule and Calendar Order...... 53 3.2.1 D a ta ...... 57 viii 3.3 R esults...... 59 3.4 Scheduling with Bypass Procedures...... 61 3.5 Conclusion...... 66
The Committee Agenda...... 68 4.1 Delivering Legislative Benefits: Theoretical Predictions...... 70 4.1.1 Gains from Exchange...... 70 4.1.2 Information...... 73 4.1.3 Party Organization...... 76 4.2 The Committee Agenda...... 79 4.2.1 Independent Variables...... 81 4.2.2 Results...... 87 4.3 Im plications...... 100 4.4 Conclusion...... 104
Balancing the Legislative A genda...... 106 5.1 Information Variables...... 108 5.2 Scheduling Reported Bills...... 117 5.2.1 R esults...... 118 5.3 Scheduling Unreported Bills...... 127 5.3.1 R esults...... 130 5.4 Conclusion...... 139
Conclusion...... 141 6.1 Summary of Argument...... 142 6.2 Im plications...... 145
Appendices:
A. Data Collection...... 150
B. Alternative Models for Analysis in Chapter 5...... 153
Bibliography ...... 162
IX LIST OF FIGURES
Figure Page
3.1 Scheduling Paths to the Floor of the House of Representatives...... 45
3.2 Identifying Bills that are “Skipped”...... 54
3.3 Actual Method Used to Count Skipped Bills...... 55
3.4 Percentage of Legislative Days Where the Actual Schedule Follows the Calendar Order Exactly...... 59
3.5 Legislative Day Where Non-eontroversial Bills are Scheduled in Order But Skip Controversial Bills (June 3, 1997)...... 63
3.6 Percentage of Days Where Calendar Order is Followed Exactly Controlling for Type of B ill ...... 65
4.1 Summary Statistics for Theoretically Derived Variables...... 82
4.2 Logistic Regression Predicting Wliieh Bills are Reported from Committee in the 100**’ Congress...... 90
4.3 Logistic Regression Predicting Wliieh Bills are Reported from Committee in the 105**’ Congress...... 92
4.4 Net Effects of Theoretically Important Variables on a Bill’s Probability of Being Reported...... 96
4.5 Change in the Odds of a Bill Being Reported for a Standard Deviation Increase in Theoretically Derived Variables...... 98
4.6 Net Effects of Legislative Benefits on a Bill’s Probability of Being Reported...... 100
X 5.1 Committee Composition and Informational Efficiency...... 112
5.2 The Party Contingent Median for Each Committee...... 113
5.3 Relationship between Committee Party Medians and the Full Committee Standard Deviation...... 114
5.4 Relationship between Committee Party Medians and Full Committee Median...... 116
5.5 Fogistic Regression Predicting Which Reported Bills are Scheduled in the 100*'’ Congress...... 120
5.6 Fogistic Regression Predicting Which Reported Bills are Scheduled in the 105*'’ Congress...... 122
5.7 Predicted Probability of Being Scheduled By Committee Party Medians...... 126
5.8 Fogistic Regression Predicting Wfiich Unreported Bills are Scheduled in the lOO"’ Congress...... 131
5.9 Fogistic Regression Predicting Which Unreported Bills are Scheduled in the 105*'’ Congress...... 133
5.10 Predicted Probability of Being Scheduled By Committee Party M edians...... 136
B. 1 Fogistic Regression Predicting Which Reported Bills are Scheduled in the lOO"’ Congress...... 154
B.2 Fogistic Regression Predicting Which Reported Bills are Scheduled in the 105*'’ Congress...... 156
B.3 Fogistic Regression Predicting Wfiich Unreported Bills are Scheduled in the lOO"’ Congress...... 158
B.4 Fogistic Regression Predicting Which Unreported Bills are Scheduled in the 105*'’ Congress...... 160
XI CHAPTER 1
INTRODUCTION
Political scientists have come to accept a portrait of the modern-day Speaker as a
leader of the majority party who uses his procedural rights to advance the party agenda.
The dominance of the Speaker over the agenda is a relatively recent phenomenon,
growing out of the reforms of the 1970s that changed both chamber and party rules. The
reforms led to a “remarkable resurgence of partisanship” (Rhode 1991, 14) in the House
which shifted the balance of power away from committee chairs and placed control over
the agenda in the hands of majority party leaders (Dodd and Oppenheimer 1977; Sinclair
1983; Smith 1989). The Speaker, in particular, was given greater control over the referral
of bills, committee assignments, and most importantly the power to appoint the majority party members of the rules committee (Sinclair 2000). The increased authority of the
Speaker has led some scholars to claim that the Speaker today has been “granted powers
greater than those granted at any time since early in the twentieth century” (Aldrich and
Rohde 2001, 269).
The Speaker’s ability to define the agenda is based on his control over the
scheduling decision. Former Speaker Newt Gingrich once said that “when you are
1 speaker you get to set the agenda . . . you get to decide what legislation is up.”
Anecdotal evidence abounds illustrating the ways that past Speakers have used
scheduling to advance partisan goals (see Sinclair 1983). Davidson and Oleszek (2002)
argue that scheduling gives the majority party the ability to “mold policy.” Sinclair
(1983, 1995, 2000) argues that scheduling decisions are made according to a host of policy and political considerations, which makes scheduling “one of the most significant powers of the majority leadership” (Sinclair 1983, 42).
The partisan view of the Speaker has created a fundamental shift in the understanding of leadership in the House. Leaders were once assumed to be
inconsequential in shaping the agenda; committees were the dominant force in the House
and “the term ‘House leadership’ was considered by many as an oxymoron” (Davidson
1995, 159). Today, leaders are often characterized as more important than committees in
deciding which bills will be considered and when. In textbooks, it has become uncontroversial to assert that the Speaker freely changes the order in which bills are
scheduled and routinely disregards the priorities set by committees in favor of strategic
considerations (see Davidson and Oleszek 2002, 238-46). In fact, one theory posits that
the absolute control of the Speaker over the legislative schedule causes committees to
adjust their agenda so that the bills they report match the preferences of the Speaker (Cox
and McCubbins 1993). In short, the conventional wisdom is that the Speaker is a powerful figure in the House who uses his scheduling authority to advance a partisan
agenda. In this dissertation, I call into question the conventional portrait of a strong, partisan Speaker. In contrast, I suggest that agenda-setting in the House is still primarily
the role of the committee system. Instead of using scheduling to change the priorities of
the committee system, I argue that the Speaker generally follows the committee agenda.
This is not to say that the Speaker does not adjust the schedule. The Speaker uses his
authority to schedule bills that have not been reported. But instead of using bis authority
to pursue a partisan agenda, tbe Speaker uses his authority to balance tbe agenda set by
committees.
Scholars have identified different benefits tbat legislators bope to obtain through
institutional arrangements - gains-Ifom-exchange, informational, and partisan (Weingast
and Marshall 1988; Krehbiel 1991; Cox and McCubbins 1993). Committees can be
designed to provide tbese benefits, but there is a “fundamental tradeoff’ - producing one benefit comes at the cost of producing another (Gilligan and Krehbiel 1989, 483).
Because committees are imperfect instruments, the House must turn to different methods
for capturing all three benefits. Giving the Speaker scheduling authority to dip into
committee agendas allows the House to secure an agenda that provides all three benefits.
1.1: The Scheduling Decision and Agenda Controi
My thesis is that the Speaker defers to the agenda set by the committee system
and uses his scheduling authority, not to change the committee agenda, but ratber to bring
additional bills to tbe floor that provide benefits under-produced by tbe committee
system. Before developing tbis fiirtber, it is important to clarify wbat I mean by
“agenda” and “scbeduling.” Tbese are terms tbat are widely used in tbe literature, but are taken to mean different things. The Speaker’s seheduling deeision ean be widely
eonstrued. Setting the legislative sehedule
involves advanee planning of annual reeesses and adjournments, eoordinating eommittee and floor aetion, providing a steady and predietahle weekly agenda of business, antieipating legislative priorities during the end-game rush to adjourn, regulating the flow of hills to the floor during slaek or peak periods, and devising a workload that takes into aceount members’ family needs...’’(Oleszek 2001, 109).
While all aspeets of the seheduling deeision are interesting, I take a narrower view of
seheduling. Cox and MeCubhins (1993, 235) suggest that the seheduling deeision is best
“eneapsulated in the question. What next?” This is the basie definition adopted here.
Over the eourse of a Congress, the Speaker must deeide whieh hills to eonsider and when
to sehedule them. The seheduling deeision, then, is simply the deeision over whieh hills
to eonsider and when.
The seheduling deeision defines the legislative agenda. Roughly ten pereent of
the bills introdueed in Congress are seheduled and eonsidered on the floor. Agenda-
setting is the ability to deeide whieh bills reeeive eonsideration. Kingdon (1995, 3)
defines agenda-setting generieally as a proeess that “narrows this set of eoneeivable
subjeets to the set that aetually heeomes the foeus of attention.” In this way, the
seheduling deeision narrows the set of all introdueed bills into the set of hills that aetually
reeeive eonsideration on the floor.’ The set of seheduled bills is the House’s agenda.
This definition of agenda control can be extended to committees. Committees narrow down the list of bills in their jurisdiction that they want to consider. The bills that receive committee attention are part of the committee agenda. Control over the agenda through scheduling is based on the Speaker’s control
over the three bypass procedures, which circumvent the House’s regular order of business. The regular order of business is defined by the calendar system, which is a
first-in/first-out schedule determined by the order in which committees report hills to the
lull House. To overcome the rigidities of the regular order of business, three bypass procedures have evolved-unanimous consent, suspension of the rules, and special rules
(Bach 1990). Each of these procedures is controlled by the Speaker and can be used to
schedule any hill, even if it has not been reported from committee.^ The Speaker can
change the agenda, then, in two basic ways - he can change the regular order of business
or he can schedule hills that have not been reported. The conventional portrait of the
Speaker and my alternative picture have different expectations for both methods of
agenda control.
It is important to note that while the Speaker has the authority to set the schedule,
decisions are made by the House leadership. The Speaker works with the Majority
Leader and Majority Whip along with the Rules committee and other House leaders when
setting the schedule. In fact, the Speaker generally delegates the scheduling decision to
the Majority Leader (Sinclair 1983, 1995). In addition, since special rules are created by
the Rules committee, the Speaker is not directly involved in every rules decision. The
schedule, then, is the product of the leadership. However, the Speaker is recognized as
the leader of the party and he ultimately holds the procedural authority to implement the
^ Unanimous consent and suspension of the rules are controlled by the Speaker’s right of recognition. Special rules are indirectly controlled by the Speaker’s ability to appoint majority party members to the Rules committee. More details can be found in Chapter 3. leadership’s seheduling deeisions. Therefore, it makes sense to simplify the exposition
and subsume the deeisions by tbe Rules eommittee, tbe Majority Leader, and tbe full
leadership under the Speaker’s seheduling deeision.
The partisan theory of seheduling expeets the Speaker to aetively ehange the
regular order of business. The regular order is the produet of a deeentralized proeess.
Eaeh eommittee has jurisdietion over a poliey area and there is not neeessarily
eoordination between eommittee ehairs over whieh bills to report and when. Even if
eommittees report the bills that are the most preferred by the Speaker (see Cox and
MeCubbins 1993), it is improbable tbat they will be in an order that gives the majority party the most benefits. Therefore, the partisan view expeets the Speaker to use bypass proeedures and rearrange the regular order to optimize the party’s advantage.
In eontrast, I argue that agenda eontrol remains with the eommittee system. Over
a eentury ago, Wilson eharaeterized the House as “government by tbe ebairmen of the
standing committees of Congress” ([1885] 1956, 102). While the reforms of the 1970s
increased the Speaker’s ability to set tbe legislative agenda, all we have is anecdotal and
indirect evidence that the Speaker uses his authority to ehange the agenda set by the
eommittee system.^ Krehbiel and Rivers (1990) remind us tbat “institutional possibilities
are one thing while incentives to exploit them are quite another” (554). It is possible.
^ For anecdotal evidence of agenda control see Sinclair 1983 and 1995, Rohde 1991, and Pitney and Connelly 1995. Indirect evidence is given by the dominance of bypass procedures in scheduling legislation. Generally, scholars emphasize the partisan advantages that can be gained by using bypass procedures (Bach 1990; Bach and Smith 1988). However, there is no evidence that bypass procedures are used tochange the agenda set by committees. As I show in Chapter 3, bypass procedures rarely change the regular order of business. then, that the Speaker follows the eommittee agenda despite his ability to ehange it. The
Speaker is an eleeted leader of the House and has institutional, as well as partisan,
responsibilities (Peters 1995a). Sinee the eommittee agenda refleets the priorities of
members within individual jurisdietions, tampering with the eommittee agenda ean have politieal costs for the Speaker - members may view the Speaker’s deeision as violating
their institutional demand for fairness. Perhaps the best strategy for the Speaker is to
follow the agenda set by the eommittees.
I argue that the Speaker follows the regular order of business set by the eommittee
system. Further, I suggest that this is independent of the types of benefits produced by
committees. Cox and MeCubbins (1993) suggest differently. They argue that
committees ean anticipate the Speaker’s partisan preferences and so there may not be a
need for “active” eontrol of the agenda. Their argument has two implications. First,
eommittees must show a preference for partisan benefits over other benefits. Second, the
Speaker will only follow the agenda when eommittees produce partisan benefits
(“automatic pilot”) and will ehange the agenda if eommittees produce different benefits
(“active eontrol”). My claim is that the Speaker will follow the eommittee agenda
regardless of whether or not eommittees show a partisan preference.
Following the eommittee agenda, however, does not preclude the Speaker from
affecting the final agenda. Bypass proeedures ean he used to sehedule bills that have not been reported from eommittee. In fact, roughly half of the bills seheduled in the House are not reported."^ Since the Speaker is responsible for bringing tbese bills to tbe floor,
tbe Speaker is responsible for defining a large part of the agenda. The difference between
tbe partisan picture of the Speaker and my thesis lies in the types of bills the Speaker
adds to the agenda.
The literature is virtually silent on how bypass proeedures are used to circumvent
eommittees. When textbooks discuss bypassing a eommittee they outline the discharge procedure, whieh requires a majority of members to sign a petition that extracts a bill
from committee.^ Empirical studies and theoretical models almost unanimously assume
that bills are reported from eommittee. The datasets either exclusively include bills tbat
are reported or the models assume that the traditional textbook proeess is followed.^
However, despite no explicit claims about seheduling unreported bills, the spirit o f the
argument implies that the Speaker will use his authority to supplement the agenda with partisan gains.
In eontrast, I argue that the Speaker’s role is not to advanee a party agenda, but
rather to create a legislative agenda that provides gains-from-exchange, informational,
and partisan benefits. The literature on legislative organization has emphasized the
This estimate comes from the data I collected on the 100*'’ and 105"’ Congresses. See Chapter 3, Figure 1 for details.
^ It is a little more complex than this. See Chapter 3 for more details.
" Datasets typically include a subset of the bills scheduled. Sinclair (1994) analyzes billsCongressional on Quarterly'?, list of important legislation and key votes. Krehbiel (1991) analyzes all bills where a special order was requested or granted. Cox and McCubbins (1993) exclude bills considered under suspension and assume that bills follow the textbook path of report, special rule, floor consideration.
8 tradeoff between securing these benefits (see Sinclair 1994). Committees can be
designed to produce particular benefits, but it often comes at the expense of other benefits. Recognizing that committees will not fiilly supply all three benefits, committee
members are willing to give up some jurisdictional control so that the Speaker can balance the agenda. I expect, then, that the Speaker will use his authority to schedule unreported bills that complement the set of bills in the regular order of business.
My theory of scheduling paints a dramatically different picture of legislative politics than the partisan view. The Speaker is not a strong leader who uses his authority
to advance partisan goals. Rather, the Speaker is restrained. While the conventional
wisdom is that the Speaker has used his post-reform scheduling power to usurp the
agenda setting power of the House, I argue that committees remain the driving force of
the agenda in the House. Instead, the Speaker uses his scheduling power to balance the
final agenda so that the set of bills considered provide gains-ffom-exchange,
informational, and partisan benefits.
1.2: Data
My theory of scheduling is general in the sense that it is intended to explain
scheduling decisions over all bills. This approach differs from other studies of Congress
in two important, although related, ways. First, I do not make a theoretical distinction between controversial and non-eontroversial bills. Generally, research on Congress
excludes non-eontroversial bills because they are considered “trivial” and of little
importance or interest. However, non-eontroversial bills make up the majority of
legislation passed in the House. If these bills are truly of little importance, then why does the House bother with them? The reason is that they are important to individual
members. A hill that renames a post ofFiee may not he important in terms of the national
agenda, hut it is important for the member who is able to unveil the new name in a publie
eeremony and “elaim eredit” for honoring a loeal or national hero (Mayhew 1974). If the
Speaker’s seheduling deeision is a funetion of the interests of the members of the House,
then it is important to inelude in the analysis all bills that matter to individual members.
Seeond, I do not limit the analysis to House hills (H.R.). Instead, I inelude all hills that have the potential to he seheduled in the House. This means all types of House hills and resolutions (House, Joint, and Coneurrent). As well as Senate hills and
resolutions (Joint and Coneurrent) that have passed the Senate.’ I inelude these for the
same reason I inelude non-eontroversial bills. Resolutions deal with a different type of
legislation, hut they are no less important for members. Coneurrent Resolutions that
“express the sense of Congress” are politieal statements that have real-world
implieations. Joint Resolutions that propose eonstitutional amendments or eommemorate
eertain individuals mean something to the members that introduee them. Ineluding these hills in the analysis is essential for understanding the seheduling deeision.
To test my seheduling theory, I have eolleeted original data from the 100**’ and
105**’ Congresses. The dataset ineludes every bill and resolution proposed in the House
and every bill and resolution (joint and eoneurrent) that passed the Senate. This ereates
an original dataset with over 19,500 bills. The 100**’ and 105**’ Congresses provide a
’ This excludes Senate Resolutions. House and Senate Resolutions only apply to the chamber that passed them. They are not law; rather they are used to deal with internal matters. As a result, they are not brought up in the other chamber for consideration.
10 stringent test of my theory beeause these two eongresses were led by notoriously strong and partisan Speakers. Jim Wright (D-TX) heeame Speaker at the beginning of the 100**’
Congress (1987-88). He was known for making “minority status more painful” by using the authority of his offiee to partisan advantage. He inereased the use of restrietive rules and made eontroversial rulings, even adjourning the House and deelaring a new legislative day to pass a Demoeratie welfare reform paekage (Pitney and Connelly 1995).
Wright’s use of power led Minority Leader Miehel to exelaim “You’re getting right on the rim where the Speaker himself is getting mighty damned autoeratie” (quoted in Pitney and Connelly 1995, 73). In an effort to stop Wright’s eonsolidation of power,
Representative Gingrieh raised ethieal eharges the lOL* Congress that led to Wright leaving the House in June 1989 (Davidson and Oleszek 2002, 164).
In the 105**’ Congress (1997-98), it was Gingrieh who was Speaker. Gingrieh had transformed the speakership during the 104**’ Congress implementing the Contraet with
Ameriea and taking a puhliely eonfrontational strategy with the White House. The 105***
Congress was more subdued after Gingrieh was formally diseiplined by the House for ethieal wrongdoing. However, he pushed an agenda of “hot-hutton” issues and in the last few days of the Congress the House impeaehed President Clinton (Davidson and Oleszek
2002, 166). After a poor showing by the GOP in the 1998 eleetion, Gingrieh withdrew from the raee for Speaker and resigned from the House.
These two Speakers are eonsidered by seholars to he the most partisan of the modern House (Peters 1995a, 1995h). They are notorious for exploiting their power to advanee partisan goals. If seheduling is used as a partisan tool to ehange eommittee
11 incentives, alter the agenda for partisan gain, and provide partisan benefits, then these
two Speakers should be extreme examples. However, I demonstrate that both of these
Speakers follow the eommittee agenda and use their authority to sehedule hills that halanee the eommittee agenda. Instead of being pure partisans, both Speakers produee an
agenda that provides gains-Irom-exehange, informational, and partisan benefits.
1.3: Outline of the Dissertation
The ohjeetive of this dissertation is largely empirieal. I intend to show that the
strong, partisan portrait of the Speaker does not fit even the most partisan Speakers in the post-reform House. However, before laying out empirieal analysis, it necessaryis to
develop in greater detail the expectations surrounding both the partisan view of the
Speaker and my balancing perspective. I begin Chapter 2 by summarizing the partisan
literature on the Speaker and drawing empirieal expectations about how the Speaker will use his seheduling authority. I then develop my balancing theory. I present a principal
agent perspective of the Speaker and argue that it is in the interest of the Speaker to
facilitate the eommittee agenda and balance the final agenda by seheduling unreported hills. The empirieal predictions from my theory pose alternative hypotheses that ean he
tested.
The first step in testing my theory is to examine the extent to which the Speaker
follows the eommittee agenda. The House rules define the order in whieh bills will he
eonsidered according to the calendar system. In Chapter 3 ,1 outline these rules and
compare the regular order of business to the actual sehedule set by the Speaker. Beeause
different rules apply on different days, I examine the percentage of legislative days where
12 the Speaker seheduled bills in their “regular” order. I find that in the strictest test the
Speaker follows the calendar order on some days, but is more likely to ehange the order
than follow it.
Upon further analysis, however, I find that there is a general distinction between
seheduling eontroversial and noneontroversial bills. Controversial bills are reserved for
the later half of the week and noneontroversial bills are eonsidered at the beginning.
Once this basie organization of the work week is controlled for, I find that the Speaker
frequently follows the calendar. Thus, eontroversial bills are taken in their calendar order
and non-eontroversial bills are seheduled in their calendar order. This implies a further
rationale for using bypass proeedures as the primary method for bringing bills to the floor
- bypass proeedures allow the Speaker to organize the work week. Thus, even though bypass proeedures are the primary method for bringing bills to the floor, the eommittee
agenda is preserved.
While the calendar order is generally followed, it is also the ease that the Speaker
exercises discretion over the sehedule. The theoretical expectations of how the Speaker uses his seheduling authority are based on the nature of the eommittee agenda. The partisan theory predicts that if eommittees favor partisan benefits, then the Speaker will
generally follow the agenda. However, if eommittees do not favor partisan benefits, then
the Speaker will ehange the agenda to match partisan preferences. My theory predicts
that the Speaker facilitates the eommittee agenda and thus will reinforce the priorities of
the eommittee system. For example, if eommittees have a distributive bias, then the
Speaker will sehedule bills with the highest distributive content. In Chapter 4 ,1 examine
13 the nature of the eommittee bias in eaeh Congress. Using multivariate logit models, I
find that committees in the 100**’ Congress favored distributive benefits over partisan benefits; and, in the 105**’ Congress eommittees favored partisan over distributive benefits. The shift in eommittee tendencies is important because it suggests that the bias
in eommittees is the result of changes in the structure of the eommittee system (which
happened during the 104**’ Congress) rather than eommittees eonforming to the Speaker’s partisan expectations.
In Chapter 5 ,1 examine how the Speaker uses his scheduling discretion. The
variation in eommittee bias between the 100**’ and 105**’ Congresses provides a rich test of
the two theories. In both Congresses, I find that the Speaker reinforces the eommittee bias when scheduling reported hills. Speaker Wright reinforced the gains-ftom-exehange bias in the 100**’ Congress and Speaker Gingrich reinforced the partisan bias in the 105**’.
The scheduling behavior of the Speaker raises questions about the partisan view of the
Speaker. Instead of changing the eommittee agenda to ensure that it supplied partisan benefits, both Speakers followed the priorities of the eommittees, regardless of the benefits provided. In addition, I find support for the balancing thesis. In the 100**’
Congress, Speaker Wright displayed a partisan bias when scheduling unreported bills.
This balanced the distributive tendency of the eommittees. In the 105**’ Congress,
Speaker Gingrich showed a distributive bias that balanced the partisan tendency of the
eommittees.
Taken together, the empirical evidence supports a fundamentally different view of
the Speaker than the conventional notion of a strong, partisan leader. Speeifieally, it
14 supports my thesis that the Speaker faeilitates the eommittee agenda and uses his seheduling authority, not to ehange eommittee ineentives, hut rather to halanee the eommittee agenda by seheduling unreported hills. This has important eonsequenees for our understanding of the House and the legislative reforms of the mid-1970s. The post reform Speaker has greater authority to eontrol the sehedule than any Speaker sinee
Cannon. However, this authority does not have the absolute partisan implieations that most seholars draw. Instead of using this authority to usurp the power of eommittees, the
Speaker leaves agenda-setting primarily in the hands of the eommittee system. The
Speaker, then, is not the dominant agenda-setting three assumed by partisan theories.
Rather, the Speaker is a eonstrained leader whose top priorities are to faeilitate the eommittee agenda and halanee the final agenda.
15 CHAPTER 2
THE SCHEDUEING DECISION
At the beginning of the 20**’ century, Speaker Cannon had more scheduling authority than at any other time in the House’s history. The Speaker’s right of recognition extended direct control over the two most common methods for bypassing the regular order of business and bringing legislation to the floor - suspension of the rules and unanimous consent. In addition, the Speaker was the chair of the Rules committee.
This gave him control over the newest procedure to bypass the regular order of business - special rules. Cannon has reached legendary status among congressional scholars for his dominance over the House agenda and his dramatic partisan bias.
In 1910, the House revolted against “Cannonism” and stripped the speakership of many agenda-setting rights. What followed was a period of decentralized agenda control where committee chairs dictated the agendas in their individual policy domains. By the end of the 20**’ century, however, the Speaker’s office had regained much of the authority it had lost. Reforms in the 1970s caused dramatic changes in the Speaker’s authority giving the Speaker control over the agenda that has not been seen since the days of
“Czar” Cannon. Eike Cannon, the modern Speaker has control over suspension of the
16 rules and unanimous consent through his power of recognition (Oleszek 2002). And,
while no longer a member of the Rules eommittee, the Speaker controls the use of special
rules by appointing loyal majority party members to the Rules eommittee (Oppenheimer
1977; Rohde 1991).
The increased authority of the Speaker over the sehedule, combined with an
increase in partisanship over the past twenty years, has led many seholars to accept a partisan portrait of the modern Speaker and a “top-down” understanding of agenda-
setting the House. In this chapter, I summarize the rationale and data used to support this
approach. I also present an alternative portrait that presents the Speaker’s seheduling
decision as a balancing act. I argue that seheduling is not used to bias the agenda towards
the majority party; rather, it is used to create an agenda that provides multiple legislative benefits. Further, agenda-setting is a “bottom-up” process that flows from eommittees.
The contrasting expectations that arise between the partisan view and my balancing portrait are the basis for the empirical analysis in this dissertation.
2.1: The Partisan Speaker
After the revolt against Cannon, agenda eontrol in the House shifted from the
Speaker to the eommittees. The Speaker was removed from the Rules eommittee and lost
eontrol over eommittee assignments. Over the next few decades, eommittee chairs became less responsive to the policy interests of the majority party. This was especially
the ease in the Rules eommittee where the “conservative coalition” - Republicans and
southern Democrats - effectively controlled legislative outcomes (Manley 1973; Brady
and Bullock 1980, 1981; Robinson 1963; Bolling 1966; Jones1968 ). By the 1960s, the
17 party was virtually inconsequential. “The majority party leadership was not without
resources, but it generally lacked the institutional tools, the numerical support, and the personal inclination to confront and defeat the committee leadership” (Rohde 1991, 7).
During the 1960s, the House experienced an influx of liberal northern Democrats.
The control exercised over the agenda by the “conservative coalition” frustrated the junior members of the party who felt their policies were supported by a majority. In the
1970s a series of reforms were implemented that restricted the power of committee chairs
and enhanced the power of the Speaker and the party leadership. The general view is that
through these reforms, “the liberals sought to reduce the power of committee chairmen,
to strengthen the party leadership, and to guarantee that the will of the majority of
Democrats was not overridden” (Rohde 1991, 14).
At first, the strengthened leadership did not achieve partisan goals. In fact, the
initial reactions by scholars suggested that on the whole the reforms weakened the control
of parties. In addition to increasing the Speaker’s authority, subcommittees were given
greater autonomy that Davidson (1981) argued shifted the House from “committee
government” to “subcommittee government.” The power given to the leadership was not
significant enough to counterbalance “the trend toward fragmentation and dispersal of power” (Collie and Brady 1985, 275).
The weakness of the party, however, did not last long. Rohde (1991, 14) argues
that by the end of the 1970s and through the 1980s there was a “remarkable resurgence of partisanship in the House, in floor voting and other areas.” The initial weakness of the party was due to a divided Democratic party. However, as new issues emerged the
18 parties became more homogenous and the Democratic leadership began to exercise
greater eontrol over the agenda. “The combined effects of increased Democratic
consensus, new institutional powers for the party leadership, and a greater willingness by
leaders to use the tools at their disposal reached their maximum when Jim Wright became
Speaker in the One Hundredth Congress” (Rohde 1991, 105). Wright proposed a
legislative agenda and used his authority to push it through the House.
While his successor, Thomas Foley, was less disposed to such partisanship, the
Republican takeover in 1994 built on the concentration of power in the hands of the
Speaker and the general trend towards greater partisan eontrol. The Republicans
reorganized the eommittee system reducing the power of subcommittees and giving
greater authority back to eommittee chairs (Aldrich and Rohde 2001). At the same time
they enhanced the Speaker’s eontrol over the committee chairs. Given that the Speaker’s
authority was initially expanded to advance a liberal Democratic agenda, “it is ironic that
the pinnacle in party leadership power was achieved by a Republican - Speaker Newt
Gingrich in 1995” (Beck 1997, 311).
The Speaker’s eontrol over the sehedule is based on three key changes in
Speaker’s authority.* First, in 1973, and again in 1977, the number of days available for
the use of suspension of the rules was increased. Bills considered under suspension are
The three changes outlined here are not the only changes that impact agenda control. The Speaker was given greater authority over the referral process. He could refer bills to multiple committees. Joint referrals were used to send a bill to different committees simultaneously. Sequential referrals sent bills to one committee and then to another. In 1977 the Speaker was given the authority to set time limits on the first committee in a sequential referral. Multiple referral has increased the Speaker’s ability to control the agenda. However, the control does not derive from the scheduling decision, which is the focus of this study. The three changes outlined here apply to the scheduling decision.
19 not allowed amendments and must pass with a two-thirds vote. While this generally
restriets the use of suspension to non-eontroversial hills, the proeedure has heen
eontrolled hy the Speaker sinee the turn of the eentury (Baeh 1990). Thus, it is an
important “instrument hy whieh the majority party leadership eould arrange the House’s
legislative agenda” (Baeh 1990, 58). The expansion in the number of days from the first
and third Monday of eaeh month to every Monday and Tuesday ereated a greater
opportunity for the Speaker to rearrange the sehedule. In addition, it opened the door for using suspension to eonsider more eontroversial bills (Baeh 1990; Rohde 1991).
Suspension has beeome a dominant part of the seheduling proeess. Sinelair
(1994) reports that 38 pereent of the hills passed in the 95**’ Congress were eonsidered under suspension. This inereased to 52 pereent in the 102"'* Congress. The data I have
eolleeted show that 42 pereent and 49 pereent of the hills eonsidered in the 100**’ and
105**’ Congresses, respeetively, were eonsidered under suspension. The pereentage is
higher if restrieted to the hills that aetually passed. In addition, the use of suspension is
more eontroversial. Rohde (1991) shows that suspension (at least through the 100**’
Congress) was inereasingly used to sehedule bills that reeeived divided party line votes.
Aneedotally, suspension eontinues to be used for more eontroversial and signifieant hills.
For example, the 1994 Teleeommunieations Reform Bill was passed in the House under
suspension. Thus, the inerease in the number of hills eonsidered under suspension and
the use of suspension for more eontroversial bills has made the Speaker’s eontrol over
suspension an important part of the party’s ability to dominate the agenda.
20 Second, in 1975 the Speaker was given the power to appoint the majority party members of the Rules committees. This gave the Speaker control over the use of special rules. Special rules are resolutions reported from the Rules committee that set the terms of debate for a bill. Because special rules only require a majority vote to pass, most controversial legislation require a special rule to bypass the regular order of business.
Control of the Rules committee gave the “conservative coalition” tremendous control over the agenda during the 1960s. After the reforms, the Speaker’s ability to appoint members to the committee ensured that only members loyal to the Speaker and supportive of the leadership’s agenda would be given Rules assignments. If effect, the
Rules committee became an “arm of the leadership” (Oppenheimer 1977, 114). Ruhin
(1993, 3050) goes so far as to say that “the role of Rules is to exert the power of the
Democratic House leadership on legislation to ensurethat... the final product is a hill reflecting the leadership’s agenda”.
Special rules have changed in nature since the 1970s reforms. Originally, special rules were open rules that did not restrict amendments. These rules had advantages over suspension because they only required a majority to pass and could he used anytime
(Bach 1990). However, this changed after the reforms. Special rules today are often restrictive, limiting the number of amendments that can be offered on the floor. Control over the Rules committee has given the party control over how debate is structured and which amendments are in order. These decisions are “crucial to the hill’s success” and give the party the ability to affect outcomes (Sinclair 2000, 22). For this reason, control
21 over the Rules eommittee was the “most important expansion of the Demoeratie
leadership’s power over the agenda” (Rohde 1991, 98).
The third ehange whieh solidified the Speaker’s eontrol did not eome direetly
from the reforms. Unanimous eonsent is the oldest proeedure for bypassing the regular
order of business (Baeh 1990). Any member ean rise at almost any time and ask unanimous eonsent that a bill he eonsidered or passed. In 1984, however, the Speaker
established eontrol over unanimous eonsent by invoking his right of reeognition. “The
Speaker’s power of reeognition . .. is an unehallengeahle prerogative of the ehair”
(Oleszek 1996, 127). Requiring members to he reeognized for a unanimous eonsent
request brought the proeedure under the Speaker’s eontrol. In effeet, the Speaker deeides
who is allowed to ask unanimous eonsent and who is denied.
Taken together, the three bypass proeedures give the Speaker almost absolute
eontrol over the seheduling proeess. Beeausebypass proeedures ean be used to ehange
the regular order of business, the Speaker ean use these proeedures to set his own
sehedule. In the post-reform House, over ninety pereent of the unprivileged bills
seheduled eome to the floor through bypass proeedures.^ This means that “seheduling
floor aetivities in the House is fundamentally the prerogative of the Speaker and the
majority party leadership” (Oleszek 1996, 125). In effeet, eontrol over the sehedule gives
^ Privileged bills automatically have access to the floor and do not need bypass procedures to be scheduled out of order. See Chapter 3 for more details. The percentage is based on the data I collected for the 100*'’ and 105"’ Congresses. See Chapter 3, Figure 1 for a complete breakdown of the various routes to the floor. The ninety percent referred to in the text is the percentage of bills that are scheduled with bypass procedures out of the bills scheduled through bypass and the regular order of business.
22 the Speaker a final veto over the bills that are eonsidered. He makes the final “go/no go” deeision over whether a hill will he part of the agenda or not (Sinelair 1995).
The resurgenee of partisanship in the House has motivated seholars to theorize about the role that seheduling plays in strueturing the agenda and influencing the political dynamics of the House. Many have argued that the modem Speaker is a partisan leader who uses his seheduling authority to advance a party agenda and bias outcomes in favor of the majority party (Rohde 1991; Aldrich 1995; Sinelair 1983, 1995). The partisan approach to understanding seheduling is exemplified by the “party cartel” theory developed hy Cox and MeCubhins (1993). They argue that the majority party acts like a
“species of legislative cartel” that “usurp [s] the mle-making power of the House in order to endow [its] members with differential power. . . . Most of the cartel’s efforts are centered on securing eontrol of the legislative agenda for its members” (1993, 278). The
Speaker’s seheduling authority is an essential component for securing eontrol of the agenda.
The partisan view of the Speaker is based on the assumption that members are motivated by their desire for réélection and that, at least in part, their success depends on their “party label” (Rohde 1991) or “party record” (Cox and MeCubhins 1993). Sinee lawmaking involves a host of eolleetive action and coordination issues (Sinelair 1995), leaders ean be understood as agents, hired to overcome these problems (Alehian and
Demsetz 1972; Frohlieh and Oppenheimer 1978; Kiewiet and MeCubhins 1991;
Salisbury 1969). Speeifleally, the Speaker is hired by the majority party to use his scheduling authority to maximize the heneflts for the majority party. Cox and
23 McCubbins (1993, 128) describe the speaker as “faced with a mixture of three
motivations: increasing their personal probability of réélection; increasing the probability
that their party secures a majority; and increasing the probability that they are reelected as
leader of their party.” In short, for his own electoral security, the Speaker uses his
authority to advantage the majority party.
In setting the sehedule, the Speaker must choose whieh bills on the calendar
advantage the majority party members the most. This requires signifieant changes in the
regular order of business. “Considering legislation in the order it is listed on the calendar
would make little sense, sinee optimal floor seheduling dictates attention to a host of policy and political factors” (Sinelair 1995, 20). Therefore, the Speaker must use his
eontrol over bypass proeedures to redetine the sehedule. According to Cox and
MeCubhins (1993, 236) he will not sehedule bills that “worsen the status quo” for the
majority party and will “sehedule first those that will take less time, effeet a bigger
improvement over the status quo if passed, and have a better chance of passing.” In
short, the Speaker will rearrange the sehedule to advance partisan interests.
Perhaps the most important effeet of controlling the sehedule is not the Speaker’s
active manipulation of the sehedule, but rather the effeet this eontrol has over the
ineentives of the eommittee system. Cox and MeCubhins argue that the Speaker’s
eontrol over the seheduling deeision fundamentally changes the ineentives that
eommittees face when reporting bills. Controlling the three bypass proeedures gives the
Speaker a “unilateral and unchallengeable power to choose whieh bills reported from
eommittee will be slated for consideration on the floor” (Cox and MeCubhins 1993, 243).
24 The Speaker’s scheduling veto gives committees an incentive to report hills that benefit the Speaker the most. Since time on the floor is scarce, the Speaker has a “credible (if typically implicit) threat” to only schedule his most preferred bills. If committees want to have their hills reported, they must compete in producing bills that are most preferred by the Speaker. This competition among committees biases the set of bills reported towards the Speaker’s preferences. And, since the Speaker’s preferences are based on being reelected hy the majority party, the set of hills reported by the committee system will reflect the partisan bias of the Speaker.
In this view, the Speaker’s control over the schedule creates a fundamental shift in the political dynamics of the House. Before the reforms, committees controlled the agenda and “the term ‘House leadership’ was considered by many as an oxymoron”
(Davidson 1995, 159). After the reforms, the Speaker’s control over the schedule not only gave the Speaker a veto over the hills reported from committee hut fundamentally changed the committee system into an agent of the leadership. This creates a type of
“automatic pilot” control in the House. The Speaker and other party leaders determine the House’s agenda and committees follow this direction. The “party cartel” portrait of legislative politics implies a “top-down” model of agenda-setting. This is a complete reversal of the “committee government” model that dominated the pre-reform literature.
Today, the term “committee government” is considered hy many as an oxymoron.
Scholars contend that this period of party government is “conditional.” Party government can only occur if the parties are homogenous and distinct. Even Cox and
MeCubhins (2002) argue that “positive agenda control” is “conditional,” while “negative
25 agenda control” is “unconditional.” Yet while this era of party government may be
“conditional,” the conditions that support party government are expected to continue.
“The homogeneity and divergence that the parties have exhibited for the last two decades should continue, and in turn so should the willingness of members to empower their party leaders in order to advance their party’s policy agenda” (Aldrich and Rohde 2001, 289).
In sum, the post-reform Speaker is understood as an agent of the majority party and, given the party’s homogeneity, has used his authority to push a partisan agenda. The
Speaker’s increased scheduling authority has allowed the majority party to usurp the agenda setting power of the committee system and, like a leviathan, take control of the
House to serve its own ends. The result is a fundamental shift from “committee government” to “party government.” The agenda is dictated by the leadership from the top-down. The House at the end of the century is much like the House at the beginning - the Speaker has strong partisan goals, he controls the schedule, and the political dynamics of the House bias the agenda towards the majority party.
2.2: An Alternative View: The Baiancing Speaker
The portrait of a strong and partisan Speaker is attractive, especially since post reform speakers have become more visible and outspoken about legislative priorities
(Davidson and Oleszek 2002). However, in this section I outline an alternative picture of the Speaker and of agenda-setting in the House. My picture differs from the “cartel” model in three ways. First, I argue that the Speaker has more than partisan considerations. In fact, the goal of the Speaker is not to implement a partisan agenda, rather to ensure that the final agenda balances partisan and institutional goals. Second,
26 the enhanced scheduling authority of the Speaker has not usurped the committees’
agenda-setting power. Instead, the Speaker follows the eommittee agenda. To ensure a balanced agenda, the Speaker uses his authority to sehedule bills that have not heen
reported. In this way, the Speaker reacts to the agenda set hy the eommittees instead of
dictating the agenda. Third, any changes in the partisan bias of the eommittee agenda are
a result of structural changes in the eommittee system, rather than changed expectations
about the Speaker’s partisan priorities.
2.2.1: Competing Principals
The Speaker of the House of Representatives is a unique office beeause it has both institutional and partisan responsibilities. “As a constitutionally defined presiding
officer of the House, the Speaker has the obligation to ensure the fairness and effieieney
of the House’s deliberative proeess. As the leader of the House’s majority party, the
Speaker has the obligation to . . . [enact] party legislation” (Peters 1995a, 1-2). This
tension between judge and advocate is the primary struggle eaeh Speaker faces. The
institutional position of the Speaker creates a sense of responsibility to protect the
institution of the House. Speaker Albert (1995, 201) writes that the speakership
demands fairness before the members. It demands flexibility in the face of eireumstanees. It demands steadfastness to the Constitution. It demands love for the House and respect for its ways. It demanded that of forty-five people before me. It will demand that o f all who ever succeed me.
At the same time, the Speaker is the leader of the majority party. To be reelected as
Speaker, he must maintain the support of his party and make sure they remain in the
majority (Cox and MeCubhins 1993). Striking the right balance between partisan and
27 institutional demands is important because leaning too far in one direction or the other
can have electoral consequences for the Speaker.
Most commonly, Speaker’s face consequences for pursuing extreme partisan
agendas. One example is the revolt against “Cannonism” at the turn of the century. After
the Civil War, Speakers gradually moved towards advancing partisan agendas at the
expense of the institution. Party solidarity, relatively weak presidents, and the personality of many of the speakers of this time supported this shift which culminated under Speaker Cannon (R-IL) and his absolute control over tbe agenda (Peters 1995a, 4).
“Cannonism,” and the partisan trend it represented, was rejected in 1910 when the House
revolted against Cannon and stripped the Speaker of many procedural rights.
More recently. Speakers Wright (D-TX) and Gingrich (R-GA) have been accused
of being too partisan. Wright’s use of his procedural authority caused great concern
among the Republican minority and some members of bis party (Davidson 1995, 170).
Republicans, led by Gingricb, raised etbical charges against Wright, which led to his
resignation in 1989. Almost ten years later, Gingrich found himself charged with ethical
violations and after public political losses against tbe President and a poor Republican
showing in the 1998 elections, Gingrich withdrew himself from the race for Speaker and
resigned from the House (Davidson and Oleszek 2002).
The fall of Cannon, Wright, and Gingrich all illustrate the danger of downplaying
the need for institutional fairness. Peters (1990, 279) writes, “Members of tbe House will
always prefer a fair speaker to a powerful one and the speaker who forgets this places
himself in harm’s way.” Pushing entirely partisan goals threatens more than the minority
28 party. Partisan goals come at the expense of institutional fairness, whieh ean anger
members of both parties. Majority party members reeognize that a strong partisan
leadership ean be at odds with their personal goals and, while they may benefit from the party agenda passed, they are also hurt by having to saerifiee individual goals. For this
reason, the leadership must take eare to maintain institutional equality so that members
ean aehieve individual goals.
At the same time, ignoring partisan goals ean erode support within the party.
Speaker Longworth (R-OH), who used to eommute eaeh morning with Minority Leader
John Nanee Gamer (D-TX), was aeeused of being too fair to the Demoerats (Pitney and
Connelly 1995). Even Gingrieh, who was responsible for the Republiean takeover of the
House, faeed a eoup attempt in the summer of 1997 by top leaders and other junior
eonservatives who believed he was eompromising too mueh with the Demoerats
(Davidson and Oleszek 2002).
The deeisions of the Speaker, then, eannot be understood in purely partisan terms.
The Speaker is held to both an institutional and a partisan standard. One way to
eharaeterize the speakership is as an agent serving two different prineipals - the party and
the ehamber. Seheduling is a delieate task beeause the final agenda must halanee the
demands of two different prineipals. “Speakers are expeeted to strike an appropriate halanee between these eonflieting demands,” Peters (1995a, 9) writes. Leaning too far in
one direetion or the other ean have eonsequenees for the Speaker. “Speakers may find
themselves humiliated by junior members of the minority party, as were O’Neill and
Wright; defeated for reeleetion, as was Foley; or erippled by junior members of the
29 majority party, as was Gingrich” (Dodd and Oppenheimer 2002, 54). The need for balance is even echoed by one of the most partisan speakers in the post-reform House.
Speaker Wright (1995, 223) argues that “the Speaker must protect the minority from
intolerance or abuse by tbe majority while protecting the majority from the obstructive
actions of a minority.”
My thesis is that the primary goal of the Speaker, in setting the schedule, is to
ensure that there is an appropriate balance between tbe interests of tbe chamber and tbe
interests of tbe majority party. Tbis is not to say that the balance between these principals is constant. The appropriate balance can vary over time due to “contextual
factors that are unique to each speakership” (Peters 1995a, 9). Understanding these
factors is beyond the scope of this dissertation. The simple point is that the Speaker is
not driven solely by partisan motivations. Rather, the Speaker is driven by tbe need to balance partisan and institutional goals. While these two principals are often in conflict
with each other, the agenda that the leadership sets does not have to serve one principal at
the exclusion of the other.
What are the institutional benefits tbat tbe Speaker must provide in addition to partisan benefits? Tbe literature on institutional organization has focused on different
types of benefits that members of congress seek to achieve. The general argument is that
institutions are designed to provide a particular benefit. Three theories have become
dominant. Party theory, as outlined above, poses one such institutional arrangement. In
this view, members prefer policies that enhance the party image and improve the
reelection chances of members in tbe majority party. Gains-fiom-excbange (or
30 distributive) theory posits a different rationale for institutions; members are most
interested in securing benefits for tbeir constituents. Information theory presents a third
option arguing that members demand credible information about tbe consequences of
legislative proposals so tbat they can make educated policy decisions. Distributive and
information theories are both institutional benefits because all members enjoy tbe benefits provided - members receive benefits for tbeir districts and members enjoy
credible information to make informed choices.
My thesis implies that the Speaker is motivated to create a final agenda that provides distributive, informational, and partisan benefits. This is in line with an
increasing number of scholars who argue that “congress is a multifaceted organization,
one that is unlikely to be understood in terms of a single principle” (Shepsle and
Weingast 1995, 23). Maltzman (1998, 2), for example, argues that committees “attempt
to please all their potentially competing principals.” He finds that the responsiveness of
committees to their various principals varies over time with changes in the political
context. Hurwitz et al. (2001) argue that competing principals can be satisfied within the
context of a single bill. Examining the 1996 farm bill and tbe two agriculture
appropriations bills in the 104*'’ Congress, they find institutional and partisan dimensions
within each individual bill. When it comes to serving principals, tbe decision over
scheduling is no different than tbe decisions that affect committee composition or the
content of legislation - the schedule can serve multiple principals.
31 2.2.2: Agenda-Setting
Woodrow Wilson ([1885] 1956, 69), writing over a century ago, observed that
“Congress in its eommittee-rooms is Congress at work.” Little has changed sinee then.
Committees are an indispensable part of the legislative proeess in the House of
Representatives. They are the workhorses of congress that serve as “little legislatures”
(Wilson [1885] 1956, 79) prioritizing hills, researching proposals, drafting and refining
legislation, and setting “the stage for legislating on the House or Senate floors”
(Groseelose and King 1998, 135).
The eommittee system serves “two broad purposes: individual and institutional”
(Davidson and Oleszek 2002, 199). On the one hand, eommittees give members of
congress the ability to serve their constituents. Sitting on a eommittee with jurisdiction
over policies that have direct implieations for their district gives members an opportunity
to influence policy and deliver benefits to their constituents. This has electoral benefits.
Members improve their chances of reeleetion hy “claiming credit” for obtaining
“particularized benefits” thus fulfilling the “traditional role of supplier of goods to the
home district” (Mayhew 1974, 52-55).
On the other hand, eommittees serve institutional functions through policy
making and federal oversight. The committee system allows for a division of labor that is
able to capture “gains from specialization” (Krehhiel 1991, 5). Committees allow the
House to work on multiple proposals at once, increasing the number of bills they ean
eonsider while enhancing the amount of information they ean use to make deeisions.
Without this specialization, the House eould not proeess the thousands of bills and
32 nominations that come before it. “Committees are the means by wbieb Congress sifts
through an otherwise impossible jumble of bills, proposals, and issues” (Davidson and
Oleszek 2002, 199).
The bills reported from eommittee ereate an agenda for tbe House tbat is exeeuted by following the regular order of business. Proeedures have been developed over the
history of the House to bypass the regular order of business. Tbe reforms of the 1970s
eoneentrated the eontrol over these bypass proeedures in tbe hands of the Speaker. The
standard interpretation has been tbat tbe Speaker has used tbis eontrol to usurp tbe
agenda-setting power of tbe eommittees to advanee partisan goals. Tbe reforms were
motivated by frustrated liberals in the Demoeratie Party who felt the “eonservative
eoalition,” whieh eontrolled the Rules eommittee, kept the majority party from aehieving
its legislative goals. Over time, the Speaker’s eontrol of the sehedule ehanged the
ineentives of the eommittee system so that the eommittee agenda itself refleeted the partisan hias of the Speaker.
My intention is not to eall into question the reason behind the reforms, although
see Wright (2000) for an alternative to the party explanation; rather, I pose a different pieture of how the Speaker uses his seheduling authority. My thesis is that the Speaker uses his authority to halanee partisan and institutional demands. Tbe tension between
institutional and partisan interests is eonsistent with the motivation for reforming the
agenda proeess in the House - the agenda did not supply the benefits tbat tbe majority party demanded. In response, the majority party gave the Speaker greater eontrol over
the agenda to ensure that its demands were met. This does not mean, however, that the
33 Speaker abandoned his institutional responsibilities. It simply means that he was given
the authority to make sure that partisan interests were ineluded.
Through the use of bypass proeedures, the Speaker is able to ehange the sehedule
in two basie ways. First, he ean ehange the order in whieh bills reported from eommittee
are eonsidered. The regular order of business defines a sehedule set by the eommittee
agenda and bypass proeedures ean be used to adjust tbat sehedule. Seeond, he ean
sehedule bills that have not been reported from eommittee. By bringing unreported bills
to the floor, the Speaker supplements the eommittee agenda with additional bills. This
seeond method for seheduling bills is often overlooked. Cox and MeCubbins (1993,
235n), for example, restriet their seheduling model to bills “tbat go through the textbook
sequenee of report, ealendar, speeial rule, and floor eonsideration.” However, it raises
tbe possibility that the Speaker ean halanee tbe sehedule without ehanging tbe eommittee
agenda. He simply balanees tbe eommittee agenda by adding additional bills to tbe
sehedule.
In my view, the agenda is still set by tbe eommittee system. Committees provide
individual members with benefits tbat are essential to reeleetion. Mayhew (1974, 81-2)
onee eommented that “the organization of Congress meets remarkably well tbe eleetoral
needs of its members. . . if a group of planners sat down and tried to design a pair of
Ameriean national assemblies with tbe goals of serving members’ eleetoral needs year in
and year out, they would be hard pressed to improve on what exists.” Individual
members benefit from serving on eommittees and having eontrol over polieies in their jurisdietion. Further, eommittees enhanee legislative produetivity. Usurping the agenda-
34 setting power of committees does not serve the institution or the individual members
well.
However, committees cannot do everything. Achieving gains-tfom-exchange,
informational, and partisan benefits requires that committees be designed in mutually
exclusive ways. For example, informational efficiency is improved by creating
committees that are heterogeneous and non-outlying. However, distributive efficiency
requires committees to be homogenous outliers. In designing committees, there are
“fundamental tradeoffs” between tbe three primary legislative benefits (Gilligan and
Krehbiel 1989, 483). If the House, acting through the Speaker, demands a balance between partisan, informational, and distributive benefits, then the committee system will
always fail. The reforms of the 1970s gave scheduling authority to the Speaker to
overcome the failure of the committee system to produce partisan benefits.
The Speaker’s use of his scheduling authority, however, has not been used to
change committee incentives or bias tbe agenda towards majority party interests, as party
theories claim. Instead, the Speaker uses his authority to balance the agenda produced by
tbe committee system. In the context of the reforms, the Speaker provided partisan benefits by circumventing committees. Committees continue to set the agenda in their
respective jurisdictions and in the process provide a mix of distributive, informational,
and partisan benefits. To ensure that the final agenda reflects a balance between these benefits, the Speaker uses his authority to schedule unreported bills. Thus, in contrast to
the top-down partisan model of agenda setting, the agenda is set from the bottom-up and
tbe Speaker reacts to tbe committee agenda.
35 2.2.3: Influencing the Committee Agenda
I have argued that the Speaker’s control over the schedule does not induce
committees to provide partisan benefits. The committee system is a massive institution
where each committee is influenced by a large set of environmental factors. Committees
face competing interest groups tbat are passionate about policies tbe committee controls.
Further, ideological differences create conflict and controversy. Committees are a part of
iron triangles, or sloppyhexagons, tbat bring federal departments, committees, and pressure groups together. In addition, committees are notoriously protective of their jurisdiction and resist challenges to their agenda-setting rights. Wilson ([1885] 1956,
102) characterized the legislature as “government by the chairmen of the standing
committees in Congress.” While committees do not have final say over the agenda in the
House, I agree that committees set their own agendas according to the internal dynamics
of the committee.
This does not mean, however, that the majority party is unable to influence the
committee agenda. At the beginning of each Congress the House defines the committee
system by setting the number of committees, defining their jurisdiction, setting the ratio
of majority to minority party members, and assigning members to eacb committee.
Through this process, the committee system can be set up to produce different types of benefits. In particular, tbe committee system can be biased towards partisan goals.
Members that are ideologically in line with the party leadership can be given committee
cbairs, important committees can have a greater proportion of majority party members,
and party contingents on each committee can be assigned to reflect the median party
36 member (Kiewiet and MeCubbins 1991; Cox and MeCubbins 1993). In this way, the
majority party ean “staek the deek” in its favor through struetural reforms.
The agenda-setting pieture that 1 present here does not eonfliet with partisan deek-
staeking. My argument, however, is that onee the eommittee system is set up, the
Speaker does not influenee its output through the use of seheduling. The eommittee
system ean be designed to favor gains-lfom-exehange, informational, or partisan benefits.
The nature of the eommittee system likely varies with eontextual faetors. Maltzman
(1998) argues that eommittees vary in their design aeeording to the salienee of the issues
in a eommittee’s jurisdietion and the relative strength of the majority party over time. I
expeet variation to oeeur in the types of benefits produeed by eommittees. Yet the
Speaker will not ehange the eommittee agenda to advanee partisan benefits. Rather, the
Speaker will use his authority to supplement the eommittee agenda and halanee the benefits delivered in the final agenda.
In sum, the portrait of a balaneing Speaker is neither strong nor partisan. The
agenda-setting power in the House still resides with eommittees. The Speaker, as an
agent of the ehamber, has ineentives to maintain fairness by faeilitating the eommittee
agenda. The eommittee agenda, however, is neeessarily limited. Committees eannot be
designed to provide all benefits fully beeause there are fundamental struetural tradeoffs between the three benefits. To ereate an agenda that provides eaeh benefit, the Speaker
supplements the sehedule with unreported bills. In short, the Speaker is a relatively weak
agenda-setter who eneourages the legislative agenda to be defined from the “bottom-up”
37 and reacts to the eommittee agenda so as to thltill both partisan and institutional
responsibilities.
2.3: Empirical Predictions
The seheduling deeision involves three different, yet interrelated choices. First,
the Speaker must decide whether or not to follow the regular order of business. If tbere
are eases where he does not follow the ealendar order, he must decide second whieh types
of bills to sebedule out of order. Finally, he must decide whieh unreported bills to bring
to the floor. In eaeh of these deeisions, the partisan theory of seheduling and my balaneing theory have different expectations. These differences are the basis for the
empirical analysis in the remaining chapters.
The regular order of business is defined by tbe eommittee agenda. Tbe Speaker’s
eontrol over bypass proeedures gives him the authority to ehange this order. The
widespread belief (even from critics of tbe party cartel model) is tbat the regular order of business does not influenee the actual sehedule followed in the House (Baeh and Smith
1988). The consensus is that, “the ‘regular order’ is irregularly used due to its
inflexibility or for other reasons currently not fully understood” (Krehbiel 1991, 153n).
In contrast, I argue that the Speaker generally follows the regular order of business.
Committees produce an agenda tbat is valuable to tbe individual members and tbe
Speaker faeilitates tbis agenda.
On the face, this prediction may seem untenable. After all, over 90 pereent of the
legislation seheduled in the House is eonsidered under a bypass proeedure. However, as
many bave pointed out, bypass proeedures serve many different functions. Speeial rules
38 can reduce uncertainty (Bach and Smith 1988), enhance informational efficiency
(Krehbiel 1991), and protect committee logrolls (Weingast and Marshall 1988). Bypass procedures, then, may not be used to change tbe regular order of business, but ratber to
secure other advantages.’® Thus it remains an open question whether or not the Speaker
alters the committee agenda.
This is not to say that the Speaker always follows the calendar. Not all the bills
reported from committee are scheduled by tbe end of tbe session and this fact alone
suggests that the Speaker deviates from the committee agenda. Party theories predict that
the Speaker uses his authority to advance partisan interests. Thus, if the committee
system produces bills that do not advantage the party, these bills will be vetoed. Even
with committees stacked in favor of parties, there are times when committees pursue
agendas of their own. Cox and McCubbins (1993, 259) write that “if there is uncertainty
about what can be got away with, then probings of the boundaries of acceptable behavior
can be expected, with consequent sanctions.” The sanction, in terms of scheduling, is
denying access to the floor.
The balancing theory, on the other hand, does not imply that scheduling is solely used to advance the party agenda. In regards to the regular order of business, tbe Speaker
works to facilitate the committee agenda, whatever its bias. Some bills will be skipped,
Here it is important to stress that my definition of agenda control is different from that defined in formal theory models. In these models, agenda setting is defined as structuring the order of alternatives so that the final outcome is the agenda-setter’s most preferred outcome (see Riker 1982, 1986). Restrictive rules are important instruments under this definition of agenda setting because they can define which amendments are available and the order in which they will be voted on. This type of agenda setting is outside the parameters of this study. I am only interested in which bills are considered and when, not the method used to consider the bill.
39 but the bills tbat are skipped will be those that are out of syne with the larger bias of the
eommittee system. Thus, if the eommittees were designed to generate distributive benefits, the Speaker would sehedule bills high in distributive eontent. If bills bad to be
skipped, he would skip bills with little distributive benefit. In this way, the Speaker uses
his seheduling authority to advanee the benefits provided by eommittees.
Control over bypass proeedures also gives the Speaker the ability to sebedule bills
tbat bave not been reported from committee. Wbile this method of seheduling is
excluded from scheduling models and rarely referenced in the literature, there are no
explicit predictions in other work about bow tbe Speaker uses this authority. However,
the spirit of the partisan approach and certainly the notion that the party is a “legislative
leviathan” implies that the Speaker will use this scheduling approach to flood the agenda
with partisan benefits. By bringing unreported partisan bills to tbe floor tbe Speaker builds on tbe bias created by tbe eommittee system to further bias tbe agenda towards partisan ends.
My balancing thesis suggests something much different. The Speaker schedules unreported bills to balance tbe final agenda. Thus, the types of bills brought to the floor
depend on the bills reported from eommittee. If the eommittee agenda has a partisan bias
and under-produees distributive benefits, then he will see a need to add distributive bills
to the final agenda. If eommittees do not provide partisan benefits, the Speaker will use
his authority to bring partisan bills to the floor.
40 2.4: Conclusion
Scholars have come to accept a portrait of the modem Speaker as a strong partisan
that uses his scheduling authority to advanee a partisan agenda. Further, the Speaker’s
control over the sehedule has shifted the agenda-setting authority of the House from the
eommittee system to the Speaker and the party leadership. I present a different picture of
the Speaker. The Speaker is a unique leader in that he has institutional and partisan
responsihilities. History has shown that failing to balance these two demands has
electoral consequences. The Speaker’s seheduling goal, then, is not to bias the agenda
toward partisan interests, but rather to balance the institutional demands for distributive
and informational benefits and the majority party demands for partisan benefits.
Creating a balanced sehedule does not mean that the Speaker usurps the agenda-
setting power of the eommittee system. Instead, the Speaker facilitates the agenda set by
committees and supplements the eommittee agenda with unreported bills so as to provide
a balanced final agenda. The partisan and balancing theories of seheduling have different
empirical expectations about the Speaker’s seheduling decision. In the next chapter, I begin my empirical analysis by comparing the sehedule defined by the regular order of business to the actual sehedule followed in the House in order to determine the extent to
which the Speaker follows the eommittee agenda.
41 CHAPTER 3
FOLLOWING THE CALENDAR
Congressional scholars are virtually unanimous in stating that the central power of
the House leadership is the ability to sehedule legislation (Bach and Smith 1988; Cox and
MeCubbins 1993; Davidson and Oleszek 2000; Rhode 1991). By determining what is
considered on the House floor, the Speaker is able to set the agenda for the Congress. He
decides “when (if at all), what, how, and in which order measures are brought to the
floor” (Oleszek 1996, 125). The Speaker’s control over the sehedule has led most
scholars to conclude that the regular order of business, defined by the calendar system, is
no longer relevant to defining the legislative sehedule (Bach and Smith 1988; Krehbiel
1991). The strength of this conclusion rests on two facts. First, the Speaker controls the
three basic proeedures in the House for bypassing the regular order of business - unanimous consent, suspension of the rules, and special rules. Second, virtually all
legislation that is scheduled is considered using one of these proeedures.
The Speaker’s advantage in setting the sehedule is most often understood to be
the ability to achieve partisan goals. Sinclair (1995, 210) argues that “the leaders’ aim is
to sehedule major legislation for floor consideration when they have the requisite votes
42 and when the politieal benefits of passage are at their height.” While the bypass proeedures are not inherently partisan,” the party has inereased its eontrol over their use.
In the post-reform House, unanimous eonsent and suspension are eontrolled through the
Speaker’s right of reeognition. Speeial rules are eontrolled beeause the Speaker has the
authority to appoint all the majority party members on the Rules eommittee. The partisan
theory of seheduling, then, assumes that the Speaker freely sets the sehedule. In this
view, the Speaker will rarely follow the regular order of business. This states a null
hypothesis that ean he tested.
In eontrast, I argued in Chapter 2 that the Speaker has an ineentive to follow the
ealendar. The regular order is defined by the eommittee agenda and individual members
have a stake in seeing bills from their eommittee seheduled. The Speaker’s institutional
role as an impartial leader of the House gives him an ineentive to faeilitate the eommittee
agenda. Past Speakers have been punished for pursuing personal or partisan agendas that
deviate too mueh from the preferenees of the members. Thus, I expeet that the Speaker
will follow the regular order of business. Testing this hypothesis against the null is the
goal of this ehapter.
3.1: The Scheduling Process: Rules and Procedures
The House of Representatives has a eomplex set of rules that define the regular
order of business. When a hill is introdueed in the House it is sent to a eommittee.
At their creation, unanimous consent and suspension were not partisan tools (Bach 1990). Special rules were created to be partisan tools. The Speaker was the chairman of the Rules committee and under Cannon special rules were created for partisan reasons. After the revolt against Cannon, party control over the committee was not automatic. The classic case is the Howard Smith who, as Chaiman of the Rules committee, often frustrated the wishes of the majority (Oleszek 2001).
43 Committees gather information, debate various proposals, and ehoose the hills they want
to report for eonsideration hy the lull House. When a committee reports a bill it is placed
on a legislative calendar. A calendar is nothing more than a chronological listing of hills
in the order in which they were reported. According to the rules, hills are seheduled for
eonsideration in order, as they are listed on the calendar.
The only exception to this is hills that are privileged. Privileged hills are “matters
of special import to the House as an institution or to the federal government” (Oleszek
2002, 118). Five standing committees (Appropriations, Budget, House Administration,
Rules, and Standard of Official Conduct) have privileged access to the floor for specific
types of hills. Privileged bills are in order at any time, as long as there is no pending business. Privileged hills, then, do not have to wait in their calendar order. However,
they must wait for at least three days for members to he able to read the reports. There
are exceptions to this. For example, special rules only have to wait one day before they
ean be considered. Further, the House ean vote to dispense with the waiting time.
The regular order of business is defined hy two classes of legislation (see Figure
3.1). The first are bills that are privileged and ean he called up at any time (bottom path).
The second are hills that enter the calendar system; they are reported from eommittee.
The rules are not completely clear about whether bills will be considered in the order on the calendar. For example, bills on the House calendar can be considered through the call of the standing committees. There is no way to tell which bill each committee would call and thus the order that bills on the House calendar will be considered is unclear. Davidson and Oleszek (2000, 237) state, however, that “the House rules require bills to be taken up in the chronological order listed on the calendars.” In addition, Stewart (2001, 345) refers to the calendar as “the most basic queuing device for legislation.” This implies that the order on the calendars is important. In addition, following the order on the calendars was standard practice in the early nineteenth century (Oleszek 2001, 120). Because of this historical precedent, I adopt this as the proper interpretation of the calendar order.
44 Bypass Proeedures - Speeial Rules - Unanimous Consent - Suspension of the Rules
Calendar - Union - House - Private ScheduleCommittee - Diseharge - Consent/ Correetions
Privileged - Appropriations - Budget - House Administration - Rules - Standards of Offieial Conduet
Note: Pereentages are ealeulated as the pereent of all bills that are seheduled that pass through eaeh path.
Figure 3.1: Seheduling Paths to the Floor of the House of Representatives.
45 placed on a calendar, and wait in the eue for their time on the floor (center path). The
regular order of business, then, is basically a "first in, first out” system of seheduling that prioritizes bills based on the agenda set by the eommittee system.
While a ealendar is a simple ehronological ordering of bills, the ealendar system
is more eomplex. The ealendar system is made up of five legislative calendars. When a hill is reported from eommittee it is placed either on the Union, House, or Private
ealendar. Eaeh ealendar is used for specific types of legislation. The clerk of the House
automatically assigns bills to the appropriate ealendar based on the language of the bill.
The Union ealendar is for bills that involve raising or spending money. The House
ealendar is for non-money hills. The Private ealendar is for bills of a private nature.
These are bills that are only applicable to an individual or spécifié entity.
The two other calendars are different than the first three because the clerk does
not automatically place bills reported from eommittee on them. The Discharge Calendar
is the list of bills that have been sueeessfully discharged from eommittee. If a eommittee
does not act on a hill, members of the House ean sign a diseharge petition to bring it out
of committee. The petition requires 218 signatures. At this point, the hill is placed on the
diseharge ealendar.
The Correetions Calendar was created in 1995 to replace the Consent Calendar.
Both calendars are for non-eontroversial legislation. A bill on the House or Union
ealendar can be placed on the Consent Calendar at the request of any member of the
House. The Correetions Calendar is a little different. The Speaker has the power to
assign bills to the Correetions Calendar from either the House or Union Calendar.
46 Speaker Gingrieh explained that this ealendar was ereated to repeal “the dumbest things the federal government is eurrently doing” (quoted from Oleszek 2001, 112). Like the
Consent Calendar before it, the Correetions Calendar is rarely used.
These five ealendars form the basis for the ealendar sehedule. The House and
Union ealendars are the primary ealendars that are in order eaeh day. By Rule XIV, the
House Calendar is eonsidered before the Union Calendar. Rule XIV establishes the order of business for tbe House. After unfmisbed business, tbe “morning bour for the eonsideration of bills ealled up by eommittees” is in order. At this time, standing eommittees are ealled in order and have the option to eonsider bills on the House ealendar. This eontinues until a motion is offered that the House resolve into the
Committee of the Whole House on the state of the Union. At this point, bills on tbe
Union ealendar are in order. While the House Calendar is eonsidered before tbe Union
Calendar, it is not the ease that all bills on tbe House Calendar must be eonsidered before moving on. If the House votes to resolve into the Committee of the Whole, then the
Union Calendar is in order.
Unlike the House and Union ealendars, the other ealendars are not in order eaeh legislative day. The Private Calendar is in order on the first Tuesday of eaeh month. The
Speaker is required to eonsider the Private Calendar on the first Tuesday unless the
House agrees to waive eonsideration of the ealendar by a two-tbirds vote. The Private ealendar is also in order on the third Tuesday of the month. Consideration of the ealendar on this day, however, is solely at the diseretion of the Speaker.
47 Petitions on the Discharge Calendar are in order on the second and fourth
Mondays of each month. On these days, any member who has signed the discharge petition may motion to discharge the bill. The motion is then debated for twenty minutes.
If tbe motion passes, tbe bill may be brought up for immediate consideration or placed on
tbe appropriate calendar. If the motion fails, the bill is not eligible to be discharged for
the rest of the session.
The Consent Calendar was in order on the first and third Mondays of the month.
Bills considered under the consent calendar were passed without amendment. If one
member objected to passage, tbe bill was postponed until the next time the consent
calendar is considered. If, at this time, three or more members object to passing the bill,
it is removed from the calendar and may not be placed on the calendar again during the
same session of Congress.
The Corrections Calendar is in order on the second and fourth Tuesdays of the
month. The corrections calendar is completely under the control of the Speaker. He can
decide which bills are placed on the corrections calendar, if the calendar is in order on the
days it is available, and wbich bills on the calendar will be considered. When bills are
considered under tbe corrections calendar, tbe time for debate is limited to one bour, there
are restrictions on which amendments can be offered, and it takes three-fifrbs of tbose
voting to pass.
On days wben tbese calendars are in order, tbey bave privilege over tbe House
and Union calendars. Tbis means that they are considered first. In addition, two other
days give privilege to bills over tbe House and Union calendars. On Wednesday, the
48 speaker is to eall the roll of the standing eommittees in alphahetieal order. The
eommittee, when ealled, ean hring a bill that they have reported for eonsideration.
Today, the House generally votes to dispense with Calendar Wednesday. Distriet of
Columbia legislation is the other set of hills that are given privilege on speeifie days. On
the seeond and fourth Mondays of eaeh month, bills reported from the Government
Reform Committee pertaining to the Distriet are in order.
The “regular order of business,” then, is determined hy privileged hills and the
ealendar system. The ealendar system is struetured so that hills on the three speeial
ealendars are eonsidered first, followed hy the House Calendar whieh is then followed hy
the Union Calendar. Other rules of privilege ean intervene on eertain days (Calendar
Wednesday and Distriet of Columbia bills), but these rules are often dispensed with. The
result is a eomplex sehedule that is largely defined by the order in whieh bills are
reported from eommittee.
3.1.1: Circumventing the Regular Order of Business
While the regular order of business is elearly laid out in the House rules, the
aetual sehedule does not have to follow this order. Over the years, the House has found it
in its interest to ereate proeedures that eireumvent the regular order of business (see
Figure 3.1, top path). Today, the three bypass proeedures - unanimous eonsent,
suspension of the rules, and speeial rules - are eontrolled hy the House leadership
through the proeedural prerogatives of the Speaker.
Unanimous eonsent is one of the oldest proeedures in the House. It was the first proeedure used to bypass the regular order of the day (Baeh 1990). Members may ask for
49 unanimous consent to pass or consider legislation at almost any time the House is in
session; however, the Speaker must recognize a member for this purpose. In 1984, the
Speaker established a policy to confer reeognition for unanimous eonsent to members
after establisbing that key members do not object (Oleszek 2001). Tbe power of
reeognition gives the Speaker eontrol over whether bills will be eonsidered under tbis proeedure. Since unanimous eonsent requires tbe entire House to agree to tbe bill, it is
only useful for considering non-eontroversial measures. In fact, tbe restrietiveness of unanimity as a requirement led the House to develop a less restrictive proeedure -
suspension of the rules (Baeh 1990).
Suspension of the Rules requires the support of two-thirds of the House to pass.
This protected the regular order from being changed by a mere majority, but also prevented one member from obstructing tbe wishes of the House (Baeh 1990, 51). A
motion to suspend the rules is simultaneously a motion to pass the bill. On eaeb Monday
and Tuesday, and tbe lastsix days of tbe session, members ean motion to suspend the
rules and pass a bill. Debate is limited to 40 minutes and amendments not mentioned in
tbe motion are not allowed. As with unanimous eonsent, the Speaker has eontrol over
suspension through his power of reeognition. This power was established by Speaker
Randall at the end of the 19**’ century and eontinues today. Generally, committees or
individual members petition tbe Speaker in advanee for eonsideration of a bill under
suspension. The Speaker ean decide whieh motions will be recognized.
Suspension has limits in the bills that it ean be used for. Tbere is no restriction on
tbe substantive eontent of tbe bills; however, under tbe current GOP Conference rules,
50 the Speaker “shall not schedule any bill or resolution for consideration under suspension
of the Rules which fails to include a cost estimate, has not been cleared by the minority,
was opposed by more than one-third of the committee members [who] reported the bill,
and exceeds $100,000,000” (Oleszek 1996, 32). Furthermore, the limits on debate,
restrictions on amendments, and supermajority requirement for passage make suspension,
in general, useful for “non-eontroversial” hills only. For these types of hills, however,
suspension is a fast and efficient way for bills to be considered.
In contrast to unanimous consent and suspension, special rules are not motions by
individual members that must he recognized. Special rules are House Resolutions written hy the Rules committee which are considered as privileged matters. This means that they
can be called up at any time and debated for one hour without amendments. If the rule is passed, the hill it refers to is immediately considered. Since they are privileged, special
rules can he used to change the regular order of business. They also set the length of
debate for considering the bill and may limit the number of amendments that can he
offered. They also dispense with time consuming practices like the first reading of the hill and the reading of amendments.
Since the Rules committee and not the Speaker write rules, the control of the
leadership over this procedure depends on how cooperative the Rules committee is.
Originally, the Speaker served as the chair of the Rules committee. However, in the
revolt against Cannon, the Speaker was removed and the Rules committee had more
autonomy. In 1975, the Democratic Party caucus gave power to the Speaker (with
Democratic caucus approval) to appoint the majority party members of the committee.
51 The Republican Party did the same for its speaker when they took over eontrol in 1994.
This gives the Speaker more eontrol over the eommittee. By handpieking the eommittee
members, the Speaker is able to put members in place that are willing to follow his lead.
For this reason, the Rules eommittee today is seen as an extension of the leadership
(Kiewiet and MeCuhhins 1991; Oppenheimer 1977; Rhode 1991).
Bypass proeedures are the dominant way that hills are brought to the floor for
eonsideration. To show how often bypass proeedures are used, I eolleeted data on all hills and resolutions from both the Flouse and Senate that were eonsidered on the floor of
the House during the 100**’ and 105**’ Congress.*^ Figure 1 shows the percentage of all hills and resolutions that were seheduled at various stages in the legislative process by
eaeh method.*"* The first thing to note is that over 75 pereent of the bills seheduled were brought to the floor under a bypass proeedure. This percentage increases if we ignore privileged bills. The Speaker does not have formal eontrol over when privileged hills are
seheduled. While timing may he worked out between the eommittee chairs and the
Speaker, the Speaker cannot stop a eommittee chair from bringing a privileged bill to the
floor. Of the non-privileged hills that the Speaker has more absolute eontrol over, at least
92 pereent are eonsidered under bypass proeedures.
The eontrol of the Speaker over seheduling proeedures and the frequency with
whieh they are used hints at support for the null hypothesis that the aetual sehedule will
This includes House Resolutions, House Joint Resolutions, House Concurrent Resolutions, House Bills, Senate Joint Resolutions, Senate Concurrent Resolutions, and Senate Bills. Senate Resolutions were not included because they are not considered in the House.
The method used to consider each bill was collected from THOMAS (http://thomas.loc.gov).
52 differ from the ealendar sehedule. However, the use of bypass proeedures does not
neeessarily mean that the ealendar order has been ehanged. It is possible that the proeedures used to set the sehedule still follow the ealendar order. As outlined above,
eaeh of these proeedures have rules regarding amendments and plaee limits on the time
for debate. This ean have advantages even if the order defined by the ealendars is unchanged. For example, speeial rules vary in the degree to whieh they restriet
amendments. The ehoiee over rules ean have an impaet on eommittee incentives and the
final outeome of the bill (Dion and Huber 1996; Krehbiel 1997). In addition, restrietive
rules ean reduee uneertainty (Baeh and Smith 1988) and enforee logrolling agreements
(Weingast and Marshall 1988). To test the null hypothesis, the order in whieh bills are
aetually eonsidered must be eompared to the order in whieh they would be eonsidered under the ealendar.
3.2: Comparing the Actual Schedule and Calendar Order
The ealendar order is in eonstant flux. Eaeh day a different set of ealendars is
available, different rules of privilege are in order, and new bills are plaeed on the
ealendar. In short, eaeh legislative day has a unique ealendar order. To compare the
aetual sehedule and the ealendar sehedule, then, requires a method that identifies, for
eaeh legislative day, whether or not the ealendar order is followed. Determining the pereentage of days in the session where the ealendar order was followed will give insight
into the extent to whieh the Speaker follows the regular order of business.
To eompare the two sehedules, I eount the number of bills on the ealendar
sehedule that were “skipped” by bills that were aetually seheduled. If a hill is seheduled
53 when other hills higher in the ealendar order are not, then those bills not seheduled are
skipped. If hills are skipped, then the ealendar order is not followed. For example,
Figure 3.2 shows a hypothetieal legislative day with six hills on the ealendar sehedule. If
the first three hills on the ealendar are seheduled (as shown in the seeond eolumn), then
the ealendar order is followed. However, if Bills 2, 3, and 4 are the bills seheduled (as
shown in the third eolumn) the ealendar order is not followed beeause Bill 1 is “skipped.”
Calendar Sehedule Aetual Sehedule
Bill 1 Follows Deviates from Bill 2 Calendar Calendar Bill 3 Bill 4 Bill 1 Bill 2 B ills Bill 2 Bill 3 Bill 6 Bill 3 Bill 4
Figure 3.2: Identifying Bills that are “Skipped.
While this method is very intuitive, it runs into a problem when we eonsider how hills are skipped in praetiee. Some hills are reported from eommittee and never
seheduled. This means that they are skipped day after day. In the above example, if Bill
1 is never seheduled, then the ealendar order ean never be followed beeause Bill 1 will
54 always be skipped. This can give a distorted picture of how often the leadership deviates
from the calendar. Consider the example in Figure 3.3. The calendar order is the same as before, but Bill 1 is never scheduled during tbe Congress. In this case, Bill 1 is always
skipped and the calendar order is never followed. Flowever, it is possible, as in tbe
second column, that bills are scheduled in their calendar order after skipping Bill 1.
Since Bill 1 is skipped day after day, counting skipped bills can give a distorted picture of
bow often tbe calendar is followed. To put this more concretely, in the 105**’ Congress
the first reported bill wbich was not scheduled was reported on March 17, 1997. This
was only the 23*** day of the session. Therefore, by tbis method the calendar schedule
was automatically not followed for the other 228 days, regardless of the order in which
the remaining bills were considered.
Calendar Schedule Actual Schedule
Bill 1* Follows Deviates from Bill 2 Calendar Calendar Bill 3 Bill 4 Bill 2 Bill 2 Bill 5 Bill 3 Bill 4 Bill 6 Bill 4 Bill 5
Note: * Bill skipped on a previous day
Figure 3.3: Actual Method Used to Count Skipped Bills.
55 To alleviate this problem, I use a second method to compare the schedules. I only
look at “new” hills, which are bills that have not been previously skipped. According to
this measure, the calendar order would be followed if Bills 2, 3, and 4 were scheduled
(see column 2 in Figure 3.3) because Bill 1 was skipped on a previous day. Flowever, the
calendar order would not he followed if Bills 2, 4, and 5 were scheduled (see column 3 in
Figure 3.3) because Bill 3 was skipped for the first time. This measure, then, captures the
discretion initially exercised over a bill without running into the problem that repeatedly
skipped hills pose.
Two additional issues arise when counting the number of skipped bills. First, privileged bills pose a problem when trying to create the calendar order. According to
the House Rules, privileged bills can be called up at any time. This poses a problem for
identifying where privileged bills should be placed in the calendar order. If privileged hills are kept in their actual location on the calendar, then privileged hills appear to “skip”
other bills when they are scheduled. However, privileged bills do not have to wait in
their calendar order so they technically do not skip other hills when scheduled. If privileged bills are placed at the top of the calendar, it could appear that other hills “skip”
the privileged hill if other hills are scheduled first. However, privileged hills do not have
to be immediately considered even after they are reported. In short, privileged hills do
not “skip” other bills and are not “skipped” themselves. Fortunately, this means that
ignoring privileged bills when creating the calendar order will not impact the results. In
this chapter, privileged bills are omitted from the analysis.
56 The second problem comes from bills that are scheduled before they are reported.
Roughly half of the bills that are seheduled in the House were not reported from
eommittee (see Figure 3.1). This poses a problem beeause while these bills will show up
in the aetual sehedule, they are not listed on the ealendar sehedule. Are all bills that have been reported “skipped” if one unreported bill is seheduled? Returning to the examples
in Figure 3.3, suppose that there is a Bill 7 that has not been reported and Bills 2, 3, 4,
and 7 are seheduled. On the one hand, the ealendar order is followed for bills that are on
the ealendar. On the other hand, bills are not seheduled that by the regular order of business should have been seheduled before Bill 7. For this analysis, if Bill 7 is
seheduled then the ealendar order is not followed. While this might be seen as too strict
of a test (or biased towards the null hypothesis), this approach carries with it the benefit
that any support for the alternative hypothesis will be more meaningfril.
3.2.1: Data
I collected data from the 100**’ and 105**’ Congress whieh includes every bill that
was either reported from a eommittee in the House, seheduled before it was reported, or passed by the Senate and sent to the House. This includes all House and Senate bills public and private. It includes House Resolutions, House and Senate Concurrent
Resolutions, and House and Senate Joint Resolutions. For eaeh bill (100**’: n=1411;
105**’: n=1345), I eolleeted the date it was reported, the date it was seheduled, the
ealendar it was plaeed on and the ealendar number. I also eolleeted the proeedure used to
57 bring the bill to tbe floor (speeial rule, unanimous eonsent, privileged, etc.).’^ From this
data, I ereated the ealendar order for eaeh day following the rules outlined above.
The 100**’ Congress had 298 legislative days and the 105**’ Congress had 251
legislative days.*^ However, not all of these days are ineluded in the analysis. There are
two types of days where the aetual sehedule eannot be ehanged by the Speaker. First,
there are legislative days when no legislation is eonsidered (100**’: n=64; 105**’: n=42).
The House is in session only to reeeive messages from the President or Senate, to hear
the State of the Union address, or to handle other business. Seeond, there are legislative
days when only privileged legislation is eonsidered (n= 13; n=19). This means that privileged bills took up tbe entire time available for eonsidering bills that day. The
Speaker cannot change this beeause privileged bills are formally out of his eontrol.
Including these days would be misleading beeause by définition tbese days do not have
any “skipped” bills. However, tbe Speaker did not have the opportunity to skip bills.
Therefore, including these days would bias tbe results toward the alternative hypothesis.
This leaves 221 legislative days in the 100**’ Congress and 190 legislative days in the
105**’ Congress where the Speaker had the opportunity to change the sehedule.
All bill data was collected from the Library of Congress’ THOMAS website (http://thomas.loc.gov).
The 100*'’ Congress had 299 calendar days. October 29, 1987 contained two legislative days. Dec. 21 and 22, 1987 was one legislative day. October 21 and 22, 1988 was one legislative day. The 105"’ Congress had 253 calendar days. May 22 and 23, 1997 was one legislative day. Nov. 9 and 10, 1997 was one legislative day. Since the House Rules pertain to legislative days, the calendars were constructed according to legislative days instead of calendar days.
58 3.3: Results
Figure 3.4 reports the pereentage of days in both Congresses where the ealendar
sehedule was followed exaetly. In the 100**’ Congress, the ealendar order was followed
on 81 (36.7 pereent) legislative days. In the 105**’ Congress, the ealendar was followed
on 53 (27.9 pereent) legislative days. This means that Speakers Wright and Gingrieh both followed the ealendar order about 30 pereent of the time. On these days, the
Speaker did not find a eompelling reason to ehange the order in whieh the bills were
reported from eommittee.
100**’ Congress 105**’ Congress
36.7% 27.9% (81 days) (53 days)
Note: Pereentages are of the total number of days where the Speaker had the opportunity to alter the sehedule (see text for defmition) - 221 days for the 100**’ Congress; 190 days for the 105**’ Congress
Figure 3.4: Pereentage of Legislative Days Where the Aetual Sehedule Follows the
Calendar Order Exaetly.
59 While 30 percent may not seem like a large number, it is hard to evaluate the
support for either hypothesis because there is nothing with whieh to eompare the pereentage. It could he that 30 pereent is a very low number. Suppose the Speaker
would follow the sehedule 30 pereent of the time simply by chance. In this ease, finding
a Speaker that follows the sehedule only 30 pereent of the time would support the null
hypothesis. On the other hand, it could he that 30 pereent is high, if the probability of
following the ealendar is lower. In this ease, while he does not follow the ealendar order
exclusively, it elearly plays a role in defining the agenda (tentative support for the
alternative hypothesis).
To evaluate the signifieanee of this pereentage, I estimated how often the Speaker
would follow the ealendar if he was seheduling hills randomly. In both the 100**’ and
105**’ Congresses, the average number of hills seheduled (on days when hills were
aetually seheduled) is 3. On average, there are 35 hills waiting on the ealendar to he
seheduled. I had STATA randomly select 3 hills without replacement from 35 available hills a total of 221 times (or the number of days in the 100**’ Congress). I added up the
number of days where the first 3 hills on the ealendar were selected and repeated this
simulation 100 times. In 5 of the 100 simulations, the ealendar order was followed only 1
day (0.45 pereent). In the other 95 simulations, the ealendar order was never followed.
This means that the probability of the Speaker following the ealendar order 30 pereent of
the time hy chance is essentially zero.
The upshot of this analysis is that the Speaker intends to follow the ealendar order
at least some of the time. The null hypothesis, in this sense, is elearly rejected. The
60 calendar plays an important role in defining the order in which bills will be considered
and the Speaker is not completely redetrning the agenda set by the committee system.
However, suggesting that this fully supports the alternative hypothesis would be
overstating the case. The Speaker does change the order in which bills are considered
around 70 percent of the time. Therefore, while the calendar order is clearly relevant, it
is also not ubiquitous. The Speaker does exercise discretion over the schedule and
change the agenda.
3.4: Scheduling With Bypass Procedures
Analyzing the scheduling practices of Speakers Wright and Gingrich has created a
general picture of scheduling in the modern House. Speakers clearly prefer to use bypass procedures to bring bills to the floor. This observation is not new (Bach and Smith 1988;
Rhode 1991; Sinclair 1983). However, contrary to the general perception in the
literature, the use of bypass procedures does not necessarily mean that the calendar order
has been changed. Rather, bypass procedures are used to structure the terms of debate
and limit the amount of time bills are allotted for consideration. In the end, it is clear that
Speakers use bypass procedures to schedule legislation regardless of whether or not the
calendar order is changed.
The importance of bypass procedures to the Speaker’s control over the terms of
debate raises a question about the test used in the previous section. Bypass procedures
are designed for different types of legislation. Unanimous Consent and Suspension of the
Rules are only suited to pass non-eontroversial bills. Both require substantial majorities
to pass and limit members’ rights dramatically. Special Rules, however, only require a
61 majority and are more suited to the debate neeessary when eonsidering eontroversial bills. This distinetion is important beeause it is a faetor used to define the work week in
the House. The setup of the average week in Congress is to eonsider non-eontroversial bills on Monday and Tuesday and eontroversial legislation at the end of the week. This is beeause members travel home for the weekend and do not return until late on Monday.
Considering non-eontroversial bills at the beginning of the week gives members the
freedom to miss the floor debate. To further aid members, the House has a eluster voting
rule where the “reeorded votes on a group of bills eonsidered under the suspension proeedure will be postponed until later that day or until the next day” (Oleszek 2001,
113). Members are still able to vote on the suspension bills even if they are not there for
the debate.
If the Speaker approaehes the seheduling deeision knowing that he will use bypass proeedures, then the divided work week will lead the Speaker to skip
eontroversial bills on non-eontroversial days and viee versa. The implieation is that the
test in the previous seetion will understate the number of days where the Speaker
sehedules bills in the order they are listed on the ealendar. That is, on days where non-
eontroversial bills are being eonsidered, it is possible that eontroversial bills will be
skipped while the non-eontroversial bills are eonsidered in their ealendar order. Figure
3.5 provides an example. On June 3, 1997, eight bills were on the House and Union
ealendars. Of these bills, seven were seheduled and one was skipped. June 3 was a
Tuesday and all the bills were seheduled under suspension of the rules. This is a typieal
ease of a day where non-eontroversial legislation dominated the agenda. H.R. 437, the
62 bill that was skipped, was considered later on under a speeial rule, whieh suggests that it
was a eontroversial bill. On this day, then, the ealendar order was followed within the set
of non-eontroversial hills.
Calendar Sehedule Aetual Sehedule Seheduling Method
House Calendar House Calendar 1. H. J. Res. 75 1. H. J. Res. 75 suspension
Union Calendar Union Calendar 1. H.R. 908 1. H.R. 908 suspension 2. H.R. 437* 3. H.R. 1420 suspension 3. H.R. 1420 4. H.R. 79 suspension 4. H.R. 79 5. H.R. 1019 suspension 5. H.R. 1019 6. H.R. 1020 suspension 6. H.R. 1020 7. H.R. 1439 suspension 7. H.R. 1439
Note: * Skipped bill. H.R. 437 was eonsidered June 18, 1997 under a special rule.
Figure 3.5: Legislative Day Where Non-eontroversial Bills Are Seheduled in Order hut
Skip Controversial Bills (June 3, 1997)
63 A more accurate test of the role that the calendar plays in setting the schedule is to look at controversial and non-eontroversial bills separately. How often are controversial hills considered in their calendar order and how often are non-eontroversial bills considered in their calendar order? To compare the schedules while controlling for controversy I divided the data into two separate datasets. The first contains all hills on the calendar that were considered under special rules. The second contains all hills on the calendar that were considered under suspension of the rules and unanimous consent.’’
Substantively this is the same as saying that the Speaker, when scheduling, looks at each type of hill in isolation. For example, when the Speaker makes scheduling decisions over controversial bills, he makes this decision as if the only hills on the calendar are controversial hills.
Figure 3.6 shows the results.’* The percentage of days where the calendar order is followed increases dramatically from the previous test. In both Congresses, the calendar order is followed around 80 percent of the time for both controversial and non- eontroversial hills. The difference between this result and the past test means that
The datasets only include bills on the calendar that were scheduled under each method. There are other bills on the calendar that were never scheduled after they were reported. Since these were not scheduled it is impossible to determine the method that would have been used and thus whether they are controversial. However, I reran the analysis with these bills in each dataset. This makes the assumption that the bills that were never scheduled were either controversial or non-controversial (depending on which dataset is analyzed). Doing this did not change the substantive results. The maximum drop in the number of days where the calendar order was followed from the reported results was only 5 percent.
The number of legislative days is different for each method because there were days when bills were not considered under a given method; these days are excluded. The percentage of zero skip days for each method, then, is out of those days where the method was actually used. This is especially important for suspension of the rules. Suspension is a procedure that is not in order everyday. So, for days when it is not in order, the Speaker does not have the opportunity to use it to set the schedule. The other methods are available each day and so excluding the days when they were not used may be inappropriate. However, this approach creates a stronger test and makes it less likely to reject the null hypothesis for each method.
64 controversial bills frequently “skip” non-eontroversial bills, but rarely skip otber
eontroversial bills. Tbis pattern bolds for non-eontroversial bills as well. Tbis suggests
tbat wben tbe Speaker “skips” other bills, be is not neeessarily altering tbe agenda for
stratégie reasons; ratber, be is organizing the work week into eontroversial and non-
eontroversial days. After this basie organization is done, the Speaker adheres faithfully
to the agenda set by the eommittee system.
100**’ Congress 105**’ Congress
77.6% 88.7% Controversial (76 days) (94 days)
83.0% 80.5% Non-Controversial (127 days) (153 days)
Note: Pereentages are of the total number of days wbere tbe Speaker bad tbe opportunity to alter the sehedule (see text for defmition) and relevant bills were eonsidered - for the 100**’ Congress: 98 eontroversial days, 153 non-eontroversial days; for the 105**’ Congress: 106 eontroversial days, 190 non-eontroversial days.
Figure 3.6: Pereentage of Days Where Calendar Order is Followed Exaetly Controlling
for Type of Bill
65 This result is most surprising for controversial bills. Sinclair (1983) writes that
“on major eontroversial legislation, strategic considerations override all others.” It is the
eontroversial bills where we would expect to see the most rearranging of the agenda.
These bills contain the leadership’s agenda and “timing” when (or if) bills are eonsidered
are ways for the leadership to achieve its policy goals. The general trend, though, is for
the calendar order to dominate. This is not to say that strategic scheduling does not
happen. After all, the calendar order is not followed around 20 percent of the days. The picture from this is that the Speaker is much less willing to change the calendar order
than previously thought.
3.5: Conclusion
The partisan theory of scheduling assumes that the Speaker freely sets the
sehedule. However, the results suggest a different picture. The Speaker exaetly follows
the sehedule around 30 percent of the time. And, when the Speaker changes the
sehedule, it is primarily to facilitate a work week that benefits all members. The
discretion is non-partisan and is best thought of as institutional. This is further evidence
that the Speaker faces institutional constraints when scheduling. He follows the calendar
to allow individual members to achieve their goals and he rearranges it to best suit their
representational needs.
This does not answer the question about what it means to follow the calendar in
terms of legislative benefits. The bias of the eommittee agenda is a key factor in the
theoretical predictions of the Speaker’s scheduling behavior. It is possible that the Cox
and MeCubbins cartel theory is consistent with this result. They argue that eommittees
66 rationally anticipate the Speaker’s partisan preferenees and produee a partisan agenda.
Thus, following the regular order is equivalent to enaeting the ideal party agenda. The nature of the eommittee agenda is the subjeet of the next ehapter.
67 CHAPTER 4
THE COMMITTEE AGENDA
In general, the Speaker follows the regular order of business. But it is also the
ease that the Speaker exereises diseretion over the sehedule. Not all bills that are
reported are seheduled and the Speaker sehedules unreported bills as well. The partisan
theory of the Speaker and my balaneing theory have different expeetations about how the
Speaker uses his seheduling authority. In Chapter 2 ,1 argued that the Speaker uses his
authority to faeilitate the eommittee agenda but supplements the agenda with unreported bills that balanee the eommittee bias. Party theory, in eontrast, argues that the Speaker uses his authority to bias the agenda towards partisan ends. This means that the
eommittee agenda is altered to advantage the party and unreported bills are seheduled to
further provide partisan benefits. These theories provide eontrasting expeetations about
how the Speaker exereises diseretion.
Empirieally, the nature of these eompeting elaims depends on the bias in the
eommittee agenda. If eommittees are biased towards partisan benefits, then the expeeted
seheduling behavior of reported bills is the same for both theories. Party theory expeets
the Speaker to further the partisan bias of the agenda and the balaneing theory expeets the
68 speaker to faeilitate the eommittee agenda, whieh implies furthering the partisan bias. In
this ease, a differenee arises in seheduling unreported bills. Party theory expeets the
Speaker to sehedule partisan bills and the balaneing theory expeets the Speaker to eounter
the partisan bias in the eommittee agenda by enhaneing information and gains-Ifom-
exehange benefits. The opposite pattern is true if eommittees are biased towards other benefits. In this ease, the partisan Speaker will have a partisan bias in botb aspeets of
sebeduling; the balaneing Speaker will bave a partisan bias in sebeduling unreported bills
(to balance tbe eommittee bias), but will bave non-partisan bias in sebeduling reported bills to faeilitate tbe eommittee agenda.
The implication of this analysis extends beyond a simple description of the
eommittee agenda, whieh is necessary for further tests. It also provides an interesting test
of the party theory. Party cartel theory argues that the Speaker’s control over the
sehedule influences the agenda decisions of eommittees. The Speaker’s seheduling
“veto” gives eommittees an incentive to anticipate the Speaker’s partisan preferenees and produee a party-biased agenda. Since the Speaker possesses a strong veto in both of
these Congresses and both Speakers are eonsidered to be strong partisans, the eommittee
agenda in both Congresses should be biased towards partisan benefits.
In this ehapter, I lay the groundwork for testing the eompeting elaims of the partisan and balancing theories of scheduling by examining tbe nature of tbe eommittee
agenda. I explore the committees’ decision to report bills. Do eommittees report bills
that are more partisan, distributive, or informationally efficient than all the bills
introduced? In other words, what legislative benefits does the eommittee agenda
69 provide? The first step in examining the bias of the eommittee system is to expand on the
types of hills that produee distributive, partisan, and informational benefits.
4.1: Delivering Legislative Benefits: Theoretical Predictions
In reeent years the eongressional literature on legislative organization has foeused
on “the core problem members of the legislature are attempting to solve through their
ehoiee of institutional arrangements” (Sinelair 1994, 477). These problems inelude
eolleetive aetion problems, seeuring gains from exchange, and improving information.
By overeoming these problems, members are able to seeure different types of legislative benefits - distributive, informational effieieney, and partisan. Three theories have been
developed around these problems and benefits. Each offers a “stylized model” of how an
ideal legislature would produee distributive, informational, and partisan benefits. From
these models, theoretieal expeetations have been developed about the types of hills that
generally provide eaeh legislative benefit. These expeetations are the basis for the
empirieal analysis in this ehapter.
4.1.1: Gains from Exchange
Theories of exehange start with the hasie assumption that members have
heterogeneous preferenees. This heterogeneity eomes in part from the distriet, in part
from personal poliey goals, and in part from a desire to gain institutional prestige (Fenno
1978). Heterogeneous preferenees mean that members have different poliey goals (or hills) that they would like to pass. The fundamental ehallenge for a legislator, then, is to
seeure his poliey goals in a eompetitive environment where every other legislator is
trying to seeure her poliey goals. In the extreme ease, “a legislator is on the short end of
70 an n-l:l vote (as, say, when she proposes to target some specific expenditure on her
district at the expense of every other district)” (Shepsle and Weingast 1995, 10). Without
some solution, each member will face a similar vote and everyone will be deprived of tbe benefits that they need.
What is needed is some kind of cooperation or exchange. If member A can promise to vote for member B’s bill and vice versa, then support can be built for passing
a benefit. Tbe difficulty is making sure that deals can be made and tbat once made, deals
will stick. Making trades, however, are not easy because votes “are often not
simultaneous (one cannot always package all tbe deals into one big omnibus bill), and tbe
flow of benefits is not always contemporaneous (a project in one district may be in tbe
early planning stages wbile a project in another district is ready for contracts to be put out
to bid)” (Shepsle and Weingast 1995, 11).
Weingast and Marshall (1988) argue that, while trades on individual bills are
difficult, it is possible to structure a system of trading influence more generally and tbat
the committee system is designed to facilitate this type of trading. Committees are given jurisdiction over certain policy areas. This means that committees have control over the policies passed in their area of jurisdiction. Members choose to sit on tbe committees
tbat serve tbeir interests so tbat they can have control over the policies that affect them
the most. In exchange for control over bills in tbeir committee’s jurisdiction, members
give up control over bills sent to otber committees. Tbis norm of reciprocity allows
committees to build coalitions, logroll, and secure benefits for themselves. It allows
members to pass tbe policies that mean the most to them.
71 Gains from exchange theories are based on a demand-side view of institutions.
Members have preferenees over policies that they want passed and in this view
institutions are designed to increase the welfare of legislators by satisfying this demand.
The eommittee system is able to decrease transaction costs and act as “agents of
distribution,” giving poliey success to all members in areas that matter the most to their
legislative goals. In this way, the eommittee system allows the legislature to capture the
gains from exehange available in the House.
Empirieally, different types of hills can be seen as the product of cooperation or
exehange. Gains-from-exehange theories have their intellectual roots in the study of
distributive legislation. “[A distributive hill] is generally understood to he poliey that is
subdivided into discrete parts so that 1) the benefits targeted for one population or area
can be varied without affecting those going to others and 2) the costs are assumed by the
general population” (Collie 1988, 427). The polities surrounding distributive policies
clearly fit the problem eoneeptualized by gains-from-exehange theories. Eaeh member
has a distributive poliey that affects her distriet and must convince a majority to fimd the poliey. The general solution to this problem is to bundle distributive policies into one bill
so that the fate of eaeh distributive poliey is tied to the fate of the others- members
simultaneously vote to pass eaeh others distributive policies. Distributive bills, then, are
the result of solving this eolleetive problem.
Gains-from-Exchange Characteristic 1: Gains-from-exehange benefits are produced by passing distributive bills.
While gains-from-exehange theories began with a focus on distributive policies,
Weingast and Marshall (1988) broadened the theory to encompass exehange over diverse 72 policies. This type of exchange results in legislation that is large in scope and size.
Omnibus bills, as they are called, are large bills that have tremendous diversity in
content. These mega-bills often increase the chances for less popular measures to be
enacted. They can bundle “popular programs with painful spending cuts” (Davidson and
Olsezek 2000, 193). They can contain “sweeteners” that help gamer the necessary
support. They can also be used as legislative blackmail to force a “take it or leave it”
choice to the members. Regardless of their specific purpose, omnibus bills are the end products of legislative deals; they embody gains from exchange.
Gains-from-Exchange Characteristic 2: Gains-from-exehange benefits are more generally produced by passing omnibus bills.
4.1.2: Information
Institutions do not have to solely benefit members from the demand-side of the
equation. Institutions can be designed to facilitate the creation of legislation, increasing
the welfare of legislators by “enhancing productive efficiency on the supply side”
(Shepsle and Weingast 1995, 13). This is the basis for informational approaches to
institutional design.
The information rationale for institutions is based on two postulates. The first is
that legislative choices are made by majorities. The point is not that bills require the
support of a majority to pass, but rather that all choices - procedural and policy - are the
result of remote majoritarian decisions. Parliamentary law is based on the consent of the
majority and as a result, all decisions that govern procedure ultimately must have the
support of a majority. Krehbiel writes that “majorities determine policy choice and procedural choice, and no choice of the latter can undermine the fundamental principle of 73 majoritarianism in democratic, collective choice institutions” (1991, 16). The basic point
is that institutions are endogenous to the actors that inhabit them and institutions are
designed in order to produce certain benefits (and changed if the byproducts of that
design are too costly to a majority).
The second postulate is that members have uncertainty about the real world
effects of the policies they choose. “The quantity and quality of information available to
legislators is such that legislators must choose policies whose consequences they cannot
fully and perfectly anticipate” (Krehbiel 1991, 20). The implication of this postulate is
that information can be collected in order to reduce the uncertainty that members have
about the consequences of their policy choices. Reducing this uncertainty can change the policy choices that members make. The upshot is that an informed legislature will make
different policy choices than a legislature without information.
Taking these two postulates together leads to the conclusion that legislators,
through remote majoritarian choices, will create institutions that facilitate the collection
and dissemination of information. Committees, for example, will he created and given
incentives to specialize and become policy experts. In this way, the production (supply)
of legislation is more efficient because the legislature is able to capture the gains from
specialization that exist in the House (Gilligan and Krehbiel 1987, 1989, 1990; Krehbiel
1991).
Information Characteristic 1: Committees with greater expertise produce bills that provide more information.
Specialization, however, creates a principal-agent problem within the House. The
committees have specialized information that is difficult for the House to check. 74 Committees can use this expertise to produce non-majoritarian outcomes. If this
happens, the House bears a cost for specializing. The committee was trusted to gain
expertise and act in the interests of the House; instead it shirked and acted in its own
interest. In order for House members to he confident that the committee bill reflects the preferences of the House median, they must receive a “signal” that the bill has median
interests in mind.
In a series of articles, Gilligan and Krehbiel identify two signals of a committee’s
informational efficiency. First, the committee must not be a preference outlier.
Preference outliers are committees where the median member on the committee is
extreme relative to the median member of the House. The more extreme the committee,
the more likely it is that the hill will be extreme. Second, heterogeneous committees are
more informative than homogenous committees. The more diverse the viewpoints of the
committee members, the more likely it is that the hill is median centered. To gain the
support of a diverse committee, the hill must take into account diverse preferences. The
greater the heterogeneity, then, the more likely it is that the bill is a “good policy.”
Information Characteristic 2: Outlying homogenous committees produce bills with less informational efficiency that median-centered
A final prediction is that bills with a “confirmatory signal” are more informative.
Individual bills are more likely to be median-centered if it is supported by members of both parties. The logic is simple. “Two informed opinions are better than one, especially
when the informants are natural adversaries” (Krehbiel 1991, 84). This is actually the
logic that underlies the heterogeneity signal as well. The more diverse the viewpoints
75 included in the eoalition of support, the stronger the signal that the bill represents diverse viewpoints. In this ease, the to eus is speeifieally on the partisan divide in the House.
The most obvious “natural adversaries” in the House are members of eompeting parties.
The level of bipartisan support for a hill, then, is a signal of whether the hill is extreme or not.
Information Characteristic 3: Bills with a confirmatory signal are more likely to provide informational benefits.
4.1.3: Party Organization
Partisan rationales for legislative organization are based on the same types of eolleetive problems as gains from exehange and informational rationales. The key differenee is the to eus on the role of the majority party in solving the problems. For example, party theories aeeept that there are gains to be realized through exehange. It is eostly to have to build a new eoalition for eaeh bill to get legislation passed through the
House. Gains-from-exehange theory uses eommittees as the primary institution for overeoming this problem. Party theorists, however, argue that parties ereate long run voting eoalitions that allow members within the party to aehieve legislative success
(Aldrich 1995). Further, since parties ereate eoalitions that are not unanimous, members of the majority party are able to extract more benefits at the expense of minority party members.
Unlike the other theories of legislative organization, party rationales explicitly incorporate legislative leaders into the process. Leadership positions are the party solution to problems of coordination and eolleetive aetion. The primary role of leaders is to faeilitate the party’s eolleetive image (Cox and MeCubbins 1993). The party image is 76 important because it plays a role in a member’s electoral success. When a member of
Congress runs for reelection, part of bis success is based on bis party affiliation. Party
labels provide a cue to voters and public sentiment towards tbe party can affect a
member’s cbances of being elected. Each member bas an interest in having a positive party image to enhance his or her electoral chances. However, because the party image is
a public good, no individual member bas an incentive to work at maintaining the party
image. The answer is to create party institutions and leadership positions. Party
institutions provide a means for party members to work out disputes over strategies to
enhance the party image. Leaders, induced to internalize the collective interests of the party, create a legislative agenda to enhance the party image and use their authority to
monitor the behavior of members to prevent “tree-riding” (Cox and MeCubbins 1993).
Tbis creates a series of empirical claims that can be tested.
First, the Speaker wants to schedule bills that advantage majority party members.
One way to do tbis is to schedule bills tbat are proposed by majority party members. Tbis
gives majority party members legislative success for wbicb tbey can go home and claim
credit (Mayhew 1974). Being able to claim credit belps each member realize his or her
reelection goal, which in turn helps the Speaker obtain bis reelection goal. Wbile
sponsorship is only a rough gauge of the partisan bias in tbe bill’s content, showing favor
to majority party members’ bills can be used to “suggest tbe predominance of tbe
majority party in tbe setting of the legislative agenda” (Cox and MeCubbins 1993, 261).
Party Characteristic 1: Bills sponsored by majority party members provide majority party benefits.
77 The advantage of forming a party is that members of the majority party ean seeure
greater individual benefits (Aldrieh 1995). Further, the party ean foster a party image
that enhanees the reeleetion prospeets of the members (Cox and MeCubbins 1993). The
faet that being in the majority is better than being in the minority makes reeleetion a primary goal of the party. Cox and MeCubbins (1993) argue that beyond advaneing his
own reeleetion, the Speaker’s primary goal is to keep the majority party in the majority.
Without this, the Speaker eannot remain Speaker. To inerease the majority party’s
ehanees of remaining the majority, the Speaker will foeus attention on members who are partieularly vulnerable in their quest for reeleetion. The Speaker will prioritize bills
sponsored by members from marginal distriets.
Party Characteristic 2: Passing bills sponsored by majority party members who are electorally vulnerable provided majority party benefits.
Delivering the eolleetive benefits derived from a positive party image is not easy.
The Speaker frees a free-rider problem from the members of his party. There are times
when the polieies neeessary to build the party image eonfliet with individual members’
eonstitueney. This ereates an ineentive for the member to defeet from voting in favor of
the party poliey. The member might further be tempted to defeet beeause she reasons
that as long as the other members of the party vote for the bill, she will still get the
eolleetive benefit of a positive party image and be able to vote with her eonstitueney.
The problem for the Speaker is that if everyone uses this logie, the eolleetive benefits will
not be delivered. To solve this problem, the party members agree to give the Speaker the
authority to sanetion members who de feet. Cox and MeCubbins (1994) argue that the party must build a reputation for toughness, and this reputation will be maintained 78 through credible threats of punishment for defectors. The Speaker’s scheduling authority
can be used to deny defectors consideration of their bills. In other words, the Speaker can
refuse to schedule bills that are sponsored by members who vote against the party. Doing
so might endanger the chances that the party will remain in the majority. However, the
Speaker must punish dissidents at all costs because the reputation for toughness is
essential for delivering the collective benefits (Cox and MeCubbins 1994). In short, the
cost of making an example of one defector is less than the benefit of delivering the
collective good to all.
Party Characteristic 3: Members who are loyal to the party will be rewarded by having their bills chosen; members who often defect will be punished by having their bills vetoed.
In sum, the three theories of legislative organization have predictions about the
types of hills that reflect the achievement of legislative benefits. These predictions can be used to examine the committee agenda and determine the relative importance of providing these benefits.
4.2: The Committee Agenda
Before turning to the analysis, one important point must be made. The intention
here is not to establish a complete model of the committee agenda-setting process. Thus,
I am not explaining why committees report various bills; I am simply establishing how
the bills reported from committee differ from those not reported. This reflects the
committee “bias,” or the legislative benefits produced by the committee system. In this
way, the analysis in this section is largely descriptive.
79 I have collected data on every House bill and resolution introduced in the House
and every Senate bill and resolution (excluding simple Senate Resolutions) tbat passed
tbe Senate for tbe 100**’ and 105**’ Congresses. Tbe data used in tbis chapter and the
remaining chapters also includes bills tbat are “privileged.”’^ Tbe sponsor, cosponsors,
House committee(s), and legislative progress for each bill was collected from THOMAS
(bttp://tbomas.loc.gov), tbe Library of Congress’ website for bill-specific information.
For tbis analysis, only bills that were sent to a House committee are included. This
excludes bills that passed the Senate and were not referred to a committee. It also
excludes bills created by task forces and procedural bills that frequently bypass tbe
committee system, like resolutions to designate membership on certain committees. The
dataset, then, is the list of bills referred to House committees (N=13959).
The dependent variable is whetber or not a bill is reported from committee. Ten percent of the bills referred to a committee are reported (8 percent in the 100*’’ Congress
and 12 percent in the 105*’’ Congress). A bill is considered to be reported if all
committees bave reported the bill. Thus, for bills referred to multiple committees, all
must report the bill for it to be coded as reported. Tbis means that some bills have been
reported from a committee, but are not considered to be reported by tbe committee
system. This follows the rules that define when a bill is sent from tbe committee system
to the calendar system for scheduling. Eighteen percent of the bills referred to a
committee were multiply-referred in both the 100*’’ and 105*’’ Congresses.
See Chapter 3 for a discussion of privileged bills. Privileged bills were excluded from the analysis in Chapter 3, but are included in all analyses from this point forward.
80 4.2.1: Independent Variables
The different rationales for legislative organization produeed eight different
eharaeteristies of bills that refleet the provision of different benefits. Eaeh eharaeteristie
is measured using data about tbe bill’s sponsor or the eontent o f the bill itself. Summary
statisties for eaeb variable are presented in Figure 4.1. Gains-tfom-exebange theories
argue tbat distributive and omnibus bills seeure the benefits of exehanging support and
influenee.
Distributive: Distributive bills ean be trieky to operationalize beeause almost
every bill bas some distributive eontent. As Kingdon (1995, 39) puts it, “a distributive
element is generally added [to all polieies].” Tbis makes it diffieult to define a bill as
either distributive or not distributive. It makes more sense to tbink about bills as having
varying degrees of distributive eontent. For every bill introdueed, THOMAS lists subjeet
terms assigned by the Congressional Researeh Serviee. The terms are eolleetively ealled
the Fegislative Indexing Voeabulary Thesaurus, or FIV. If a bill impaets a speeifie state,
tbe state’s name is listed as part of tbe list of subjeet s. Tbe measure of distributive
eontent is tbe ratio of states listed to the total number of keywords plus the number of
states. The larger is this ratio, the greater the proportion of distributive eontent in the bill.
This follows the distributive measure first used by Krehbiel (1991) using FEGISFATE
keywords.
Omnibus: Omnibus bills are bills that eover a broad range of issue areas in one bill. I eapture tbe omnibus nature of the bill in two ways. First, the FIV keywords listed
in THOMAS identify the subjeets eovered by eaeb bill. Tbere are over 5500 FIV subjeet
81 Standard Mean Deviation Minimum Maximum
100“' Congress Gains-from-Exchange Distributive Content 0.025 0.073 0 0.5
Scope (# of keywords) 8.515 18.953 1 547
Multiple Referral 0.135 0.342 0 1 Information Years in House 11.371 8.271 0 45
Outlier 0.287 0.172 0 0.926
Minority Party Cosponsors 6.096 15.102 0 169 Partisan Republican Sponsored 0.373 0.484 0 1
Vote % for Democratic Party in last Election 0.097 0.249 -0.5 0.5
Democratic Party Unity 63.963 34.141 0 98.5
105“' Congress Gains-from-Exchange Distributive Content 0.008 0.022 0 0.269
Scope (# of keywords) 54.392 100.094 6 4130
Multiple Referral 0.122 0.327 0 1 Information Years in House 10.182 8.558 0 42
Outlier 0.531 0.308 0.003 1.381
Minority Party Cosponsors 6.943 18.248 0 204 Partisan Republican Sponsored 0.597 0.491 0 1
Vote % for Democratic Party in last Election -0.006 0.186 -0.5 0.5
Democratic Party Unity 41.830 50.759 0 398.5
Figure 4.1: Summary Statistics for Theoretically Derived Variables 82 terms. The total number of subject terms indicates scopetbe of tbe bill. Tbe larger is tbe
number, tbe more omnibus is tbe bill. Second, a bill tbat is referred to multiple
committees touches on a variety of issue areas. In addition, tbe bill tbat results is likely
tbe product of inter-committee logrolling. Bills tbat aremultiply referred are more
omnibus. Using THOMAS, I created a dummy variable for if a bill is referred to more
than one committee.
Information theories present four characteristics of bills tbat are more
informationally efficient. However, three of these characteristics have been developed in
reference to tbe nature of tbe committees tbat draft tbe bills - bills reported from
heterogeneous, non-outlying committees with more expertise provide tbe most
information. Using committee characteristics is possible wben examining tbe Speaker’s
decisions because be chooses between bills reported from different committees. In tbis
section, tbe choice is at tbe committee level so tbe characteristics tbat make different
committees more informative must be translated to individual bills within each
committee.
Expertise: Information is enhanced by tbe expertise of tbe members who draft tbe bill. In terms of committees, tbis refers to tbe collective expertise tbat tbe full committee brings to a bill. Within a committee, however, tbe expertise contained in a bill is
reflected in tbe bill’s sponsor. To capture tbe sponsor’s expertise, I include a variable for
83 the Sponsor’s tenure - the number of years the sponsor has served in theHouse.While this is not a perfect indicator of policy expertise, this measure combined with the other informational measures will provide a general picture of whether or not informational benefits are provided by committees.^’
Outliers: The premise of information theory is that the House prefers to have policies that are median-centered. To create policies that reflect the preferences of the chamber, committees must not be outliers. The same logic applies to bill sponsors.
Assuming that members introduce bills that reflect their general ideological outlook, the more extreme is a hill’s sponsor the less “median-centered” is the proposal. The degree to which the sponsor is an outlier is measured by the absolute difference between the sponsor’s W-NOMINATE score and the median of the chamber.
Data for the 100*'’ Congress came from David Lublin’s (1997)Congressional District Demographic and Political Data. The dataset covers the 8?"’ through the 104"’ Congresses. For the 105"’ Congress, I determined tenure by comparing the members of the 105"’ Congress to the 104"’ Congress in Lublin’s data.
Drawing on the sponsor’s characteristics is not the only way to capture bill-specific expertise. Krehbiel (1991) used a bill specific measure of expertise by counting the number of laws cited in the bill. This measure works well when dealing with highly controversial bills that receive special rules. However, when including less controversial bills, previous legislative work is not necessary to create a bill that is well researched. Thus, the number of laws cited is not an accurate measure of the expertise brought to the bill, when controversial and non-controversial bills are included.
W-NOMINATE scores, developed by Poole and Rosenthal (1985), are a widely used measure of member’s ideology. There are a number of other possible ideology measures that can be used in the future to validate these results (see Groseclose et al. 1999). However, NOMINATE scores have become the standard by which other ideology measures are compared. In addition, they are easily available from Keith Poole’s website (http://voteview.uh.edu/default_nomdata.htm). There are different versions of NOMINATE scores including one that allows for cross-chamber comparisons. However, the common space coordinates require some undesirable assumptions. The W-NOMINATE scores can only be used within each chamber. So, the outlier variable for Senate bills is the absolute distance between a Senator and the median of the Senate chamber.
84 Confirmatory Signal: The validity of information is enhanced by having “natural
adversaries” support the bill. The logie behind confirmatory signaling and
heterogeneity^^ is similar - diverse ideological or partisan support indicates a broader
more moderate poliey. It also ensures that information relevant to liberals, conservatives,
Democrats, and Republicans is revealed. In partisan terms, confirmatory signals come
from support by minority party members. Thus, the number of minority party cosponsors provides a signal about the diversity of support. The greater the number, the stronger the
confirmatory signal.
Majority Party Sponsor: The final set of variables eomes from the party theories.
Bills sponsored by majority party members deliver party benefits. I inelude a dummy
variable for bills sponsored by Republicans.^"^ This is neeessary for the interaction
variable I use to eapture electoral considerations of the party. In the 100*'’ Congress,
Republicans were the minority party, so bills sponsored by Republicans should be less
likely to be reported. In the 105*'’ Congress, they were the majority party.
Electoral Success: The majority party also wants to enhance its electoral success.
This means advaneing bills sponsored by marginal members of the majority party and
restricting bills sponsored by marginal members of the minority party. To eapture this, I
Information theories also show that heterogeneous committees provide more information. Creating a heterogeneity measure, however, for bills still in committee is not possible with the data available. One logical measure is to use the heterogeneity of the bill’s cosponsors. However, having a heterogeneous set of cosponsors is different than a heterogeneous committee. The logic behind heterogeneous committees is that there is a diverse set of members influencing the shape of the bill reported. Cosponsors, however, do not necessarily shape the bill. Cosponsorship is a cheap way to “claim credit” (Mayhew 1974) and doesn’t mean that the cosponsors influenced the creation of the bill. Cosponsorship is best used in confirmatory signally, not to indicate nature of the process for creating the bill.
Each member’s party affiliation is identified using Poole and Rosenthal’s DW-NOMINATE dataset.
85 included two variables. The first is the Demoeratie proportion of the two party vote
reeeived by eaeh sponsor in the last eleetion.^^ Sinee a differential efleet is expeeted for
Republieans and Demoerats, I also inelude an interaetion term between the Demoeratie proportion of the vote and whether the bill is sponsored by a Republiean. To ease in the
interpretation, the Demoeratie proportion variable is mean eentered.
Party Support: Party success is based on the support of party members in
advaneing party goals. Congressional Quarterly gives party support scores to eaeh
member based on how the member votes on key party votes. Party support scores are
listed in theCQ Almanac for eaeh session of Congress. I took the adjusted support score
(adjusted for being absent Ifom a vote) and averaged it over the two sessions. This
ereates a measure of support towards eaeh member’s party. I transformed the support
scores for eaeh party into one common scale measuring loyalty to the Demoeratie Party.
For Demoerats, this is simply the CQ party loyalty measure averaged over both years.
For Republieans, their Demoeratie loyalty is 100 (the maximum) minus their Republiean
loyalty. The result is Demoeratie Party Unity a scale of 0-100 where 0 is no support for
the Demoeratie Party and 100 is total support. This is the measure used for both
Congresses.
Additional Variables: In addition to the theoretically important variables, I
included control variables. The first is a control for the date the bill was introdueed. The
For the 100*'’ Congress, the percentage of the 2 party vote comes from David Lublin’s (1997) Congressional District Demographic and Political Data. Since his data only goes to the 104"’ Congress, data for the 105"’ Congress came from the official election results posted by the Office of the Clerk of the House (http://clerk.house.gov/members/election_information/elections.php).
86 variable counts a calendar day. There were 299 calendar days in the 100**’ Congress and
253 in the 105**’ Congress. The higher is the number, the later in the Congress the hill
was introduced. I also included dummy variables for eaeh committee. Committees have
different sized jurisdictions, vary in the number of bills referred to them, and vary in tbe
complexity of tbe bills tbey consider. To control for any differences between eommittees
in tbeir propensity to report bills, dummy variables are included.
4.2.2: Results
To examine the legislative benefits provided in the eommittee agenda, I estimated
three logistic regressions for eaeh congress. The first model includes all theoretically
derived independent variables. Tbis is not ideal, however, beeause two party variables
are highly correlated. Tbe dummy variable for Republiean Sponsored and the
Demoeratie Party Unity score are inversely correlated above /?=0.78 for botb congresses
(100**’: -0.92; 105**’: -0.78). In addition, the Republiean Sponsored variable is highly
correlated (r=-0.76) with the Outlier variable in the 105**’ Congress. A high level of
correlation between independent variables makes it harder to assess the individual effects
of the two variables and increases the probability of committing a Type II error - failing
to reject a null hypothesis that is false (Gujarati 1995). Thus, I estimate two more
models. The first excludes the Demoeratie Party Unity variable and tbe Outlier
variable.Tbe second excludes the Republiean Sponsored variable and the two election
variables beeause these variables are based on an interaction with the Sponsor variable.
The correlation in the 100*'’ Congress between the outlier and sponsor variables is much lower (r=0.42), but to maintain the consistency in models across the two congresses, I excluded it from the second model in the lOO"’ Congress. Including it, however, does not change any of the substantive results.
87 The results for the 100**’ Congress are shown in Figure 4.2 and the results for the 105**’
Congress are presented in Figure 4.3.
The control variables included in the model are generally as expected. Bills
introduced later in the congress are less likely to be reported. There are a number of plausible reasons for this. First, the bills considered most important by individual
members and the majority party are probably introduced early in the session leaving less
important bills for later. Second, hills introduced earlier in the congress give committees
more time to collect information and prepare a bill to be reported. Third, bills that are
introduced earlier give the sponsor more time to build a coalition in support of the hill.
For all of these reasons, it is not surprising that hills introduced earlier are more likely to he reported.
The committee control variables uncover the different propensities of each
committee to report hills in their jurisdiction. In general, the coefficients for each
committee reflect the relative proportion of the hills referred to committee that are
reported. The proportion of bills reported from a committee depends on two factors.
First, committees with more bills referred to them report a lower proportion of hills.
Committees with significant negative coefficients typically have more bills referred to
them. Second, some types of committees report fewer hills because the legislation is
more controversial and complex. Policy committees, for example, tend to deal with more
complex and controversial legislation than constituency committees. Therefore, policy
committees have coefficients that are negative and have a larger impact on the predicted probability than constituency committees.
88 Regarding the theoretical variables, the results show that committees in both
Congresses report bills witb characteristics reflective of all three legislative benefits.
Bills with higher distributive content and covering a larger number of subjects are
significantly more likely to be reported in botb Congresses. Bills sponsored by more
experienced members and bills witb an informative signal are more likely to be reported.
Finally, bills sponsored by majority party members and bills sponsored by more loyal
majority party members are more likely to be scheduled. Multiply referred bills are
more likely to be reported in tbe 100**’ Congress, but less likely (altbough insignificantly)
to be reported in the 105**’ Congress. This lends support to the argument that these
theories, although often portrayed as mutually exclusive, are different angles of “the same
very complex puzzle” (Shepsle and Weingast 1995, 23).
While the results suggest all three benefits are produced, there are a few key
variables that are either insignificant or in opposite directions. In the 105**’ Congress,
multiply referred bills are less likely to be reported, although tbe coefficient is
insignificant in tbe first two models. There are two possible interpretations. Committees
in the 105**’ may be less efficient at providing gains-from-excbange across committees.
Tbe committee reforms of the 104**’ Congress strengthened committee chairs and may
have led to less willingness to compromise across committee jurisdictions. The other
interpretation is that Speaker Gingrich used his power of referral differently than Speaker
Wright. For example, multiply referred bills include sequential referrals, which can be used for delaying tactics (or for keeping a bill from being reported from tbe committee
system). Gingrich was more likely to use sequential referral than Wright. Since the other
89 Equation (1) (2) (3) Constant -1.950*** -1.674*** -2.936*** (0.411) (0.226) (0.242) Date Introduced -0.001 -0.001 -0.001 (0.001) (0.001) (0.000) Gains-from-Exchange Distributive Content 3.298*** 3.290*** 3.165*** (0.551) (0.551) (0.527) Scope (# of keywords) 0.036*** 0.036*** 0.025*** (0.003) (0.003) (0.002) Multiple Referral 0.833*** 0.834*** 0.552*** (0.238) (0.238) (0.208) Information Years in House 0.010* 0.011** 0.013** (0.005) (0.005) (0.005) Outlier -0.157 -0.215 (0.335) (0.312) Minority Party Cosponsors 0.007** 0.007*** 0.008*** (0.003) (0.003) (0.003) Partisan Republican Sponsored -0.778** -1.050** (0.351) (0.229) Vote % for Democratic Party in last Election 0.876** 0.822** (0.354) (0.349) Republican Sponsor* Democratic Election -1.928** -1.888** (0.925) (0.925) Democratic Party Unity 0.004 0.013*** (0.004) (0.002) Prestige Committee Appropriations -0.524 -0.542 -0.009 (0.351) (0.350) (0.305) Budget 0.097 0.114 0.778 (0.914) (0.912) (0.882) Rules -2.513*** -2.513*** -2.142*** (0.436) (0.410) (0.416) Ways and Means -3.913*** -3.911*** -3.346*** (0.411) (0.410) (0.363) (continued on next page)
Figure 4.2: Logistic Regression Predicting Which Bills are Reported from Committee in
the 100**’ Congress.
90 Figure 4.2 (continued)
Policy Committee Banlcing -1.946*** -1.937*** -1.444*** (0.340) (0.340) (0.307) Foreign Affairs -2.955*** -2.950*** -2.456*** (0.411) (0.411) (0.359) Energy -1.015*** -1.010*** -0.650*** (0.227) (0.227) (0.194) Judiciary -0.495** -0.497** -0.161 (0.209) (0.209) (0.178) Education -1.480*** -1.475*** -1.010*** (0.285) (0.284) (0.251) Government Operations -0.867*** -0.873** -0.382 (0.344) (0.344) (0.309) Constituency Committee Agriculture -0.781*** -0.783*** -0.707*** (0.243) (0.242) (0.210) Armed Services -1.642*** -1.653*** -1.476*** (0.342) (0.341) (0.336) Interior 0.046 0.046 0.420** (0.217) (0.217) (0.187) Merchant Marine -0.557** -0.560** 0.195 (0.252) (0.253) (0.221) Transportation -0.871*** -0.868*** -0.480** (0.243) (0.243) (0.213) Science 0.018 0.019 0.332 (0.289) (0.288) (0.259) Small Business -0.829 -0.810 -0.336 (0.518) (0.517) (0.484) Veterans Affairs -1.110*** -1.145*** -0.545* (0.307) (0.305) (0.279) Other Committee Administration -1.729*** -1.729*** -1.324*** (0.363) (0.363) (0.336) Post Office -2.144*** -2.138*** -1.943*** (0.290) (0.289) (0.269) Intelligence 0.927 0.920 1.263** (0.650) (0.649) (0.629)
Number of Cases 7274 7274 7702 Log likelihood -1639.706 -1640.249 -1752.083 Pseudo R2 0.227 0.227 0.205 Correctly Predicted 91.96% 91.93% 91.90%
Note: Standard errors in parentheses; *p<0.10; **p<0.05; ***p<0.01 91 Equation (1) (2) (3) Constant -4.268*** -4.092*** -1.910*** (0.393) (0.317) (0.203) Date Introduced -0.003*** -0.003*** -0.003*** (0.001) (0.001) (0.001) Gains-from-Exchange Distributive Content 10.180*** 10.104*** 9.574*** (1.842) (1.840) (1.784) Scope (# of keywords) 0.006*** 0.006*** 0.006*** (0.001) (0.001) (0.001) Multiple Referral -0.421 -0.429 -0.530* (0.277) (0.278) (0.279) Information Years in House 0.026*** 0.027*** 0.027*** (0.006) (0.006) (0.006) Outlier 0.344 -1.088*** (0.250) (0.196) Minority Party Cosponsors 0.001 0.001 -0.002 (0.003) (0.003) (0.002) Partisan Republican Sponsored 1.769*** 1.697*** (0.309) (0.265) Vote % for Democratic Party in last Election 0.208 0.284 (1.020) (1.019) Republican Sponsor* Democratic Election 2.343** 2.367** (1.136) (1.137) Democratic Party Unity -0.001 -0.006*** (0.001) (0.000) Prestige Committee Appropriations -0.648 -0.664 -0.427 (0.466) (0.468) (0.480) Budget -3.164*** -3.161*** -3.125*** (0.624) (0.623) (0.615) Rules 3 444*** 3.467*** 3.622*** (0.216) (0.215) (0.214) Ways and Means -1.427*** -1.432*** -1.353*** (0.228) (0.228) (0.227) (continued on next page)
Figure 4.3: Logistic Regression Predicting Which Bills are Reported from Committee in
the 105**’ Congress.
92 Figure 4.3 (continued)
Policy Committee Banlcing -0.603** -0.632** -0.528* (0.301) (0.301) (0.297) International Relations -1.094*** -1.100*** -1.381*** (0.292) (0.291) (0.304) Energy 0.079 0.080 0.096 (0.215) (0.215) (0.214) Judiciary 0.300 0.314 0.425** (0.194) (0.194) (0.193) Education -0.297 -0.305 -0.293 (0.265) (0.265) (0.263) Government Reform -0.646** -0.650** -0.588** (0.289) (0.289) (0.288) Constituency Committee Agriculture -0.233 -0.226 -0.196 (0.321) (0.321) (0.314) National Security -2.805*** -2.780*** -2.728*** (0.627) (0.625) (0.632) Resources 0.846** 0.856*** 0.930*** (0.203) (0.203) (0.202) Transportation 0.340 0.334 0.336 (0.222) (0.222) (0.220) Science 0.865** 0.850** 0.960*** (0.355) (0.354) (0.349) Small Business 1.000 1.015* 1.015* (0.617) (0.617) (0.595) Veterans Affairs 0.323 0.355 0.175 (0.348) (0.344) (0.355) Other Committee Oversight -1.655*** -1.675*** -1.670*** (0.441) (0.442) (0.450) Intelligence 2.149*** 2.130*** 2.119*** (0.752) (0.749) (0.714)
Number of Cases 6020 6020 6020 Log likelihood -1446.763 -1447.905 -1505.303 Pseudo R2 0.345 0.344 0.318 LR chi2(32) 1522.66 1522.26 1405.58 Correctly Predicted 91.36% 91.31% 90.71%
Note: Standard errors in parentheses; *p<0.10; **p<0.05; ***p<0.01
93 two gams-from-exchange variables are significant in the expected direction; the multiple
referral variable does not imply that committees did not produce gains-from-exchange. It
can only raise questions about whether or not committees in the 105**’ Congress were as
efficient at producing gains-from-exchange as committees in the 100**’ Congress.
In both Congresses, the outlier and confirmatory signal variables are not
consistently significant. In tbe 100**’ Congress, botb coefficients are correctly signed, but
only the confirmatory signal variable is significant. In the 105**’ Congress, the only
significant variable is tbe outlier variable in the third model. It is correctly signed in this
model, but not in the first model. The confirmatory signal variable is correctly signed in
tbe first two models, but not in the third. While each model has at least one of these
variables in the expected direction, support for informational efficiency is weak in the
105**’ Congress. The evidence in the 100**’ Congress is much stronger.
Finally, the marginal election variables are mostly significant, but not in tbe
expected direction. In botb Congresses, bills sponsored by marginal members are less
likely to be reported. Tbe effect is not significant for Democrats in the 105**’ Congress, but the coefficient is still positive. It is important not to read too much into what this
means. It could be that safe members can spend more time legislating instead of
campaigning and thus create higher quality bills that committees prefer. Or, safe
members have more time to sponsor complex legislation. Whatever the alternative story,
it is clear that committees are less likely to report bills from marginal members and to tbe
extent tbat members need bills to “claim credit,” committees do not belp marginal
members.
94 In both Congresses, the eommittee agenda provides all three types of legislative benefits. Bills that provide greater gains-lfom-exehange, information, and partisan benefits are more likely to be reported than hills that provide fewer benefits. This is
interesting heeause the bias of the eommittee system is not apparent from the signifieanee
of the variables alone. All benefits are provided, but some types of benefits may be
relatively more important. Theorists have foeused on the tradeoffs that exist between
strueturing eommittees that provide different benefits and so, while all benefits are provided, different benefits may lead to different ehanges in the predieted probability of a bill being reported.
There are multiple ways to uneover the relative impaet of eaeh variable. The
simplest is to eompare ehanges in the predieted probability of a bill being reported that
result from ehanges in different variables. Using the logit estimates, all independent
variables exeept one are held eonstant at their mean while the remaining variable is
ehanged to ealeulate the assoeiated ehange in the predieted probability of a bill being
reported. Figure 4.4 shows the results for the ten theoretieally important variables in both
Congresses. The probabilities are ealeulated using the first of the three models. I
ealeulated the probabilities using all three models and the substantive results are the
same. Sinee the substantive results do not vary, using the first equations allows the
ehanges in the probability for all variables of interest to he shown. Eaeh eell in Figure
95 100**’ Congress 105**’ Congress
Gains-from-Exchange
Distributive Content 0.010 0.011
Seope (# of keywords) 0.038 0.041
Multiple Referral 0.013 -0.006
Information
Years in House 0.003 0.011
Outlier -0.001 0.005
Minority Party Cosponsors 0.005 0.001
Partisan
Republiean Sponsored -0.010 0.049
Dem. Eleetion Margin 0.010 0.000
Rep. Eleetion Margin -0.003 0.025
Demoeratie Party Unity 0.005 -0.002
Figure 4.4 Net Effeets of Theoretieally Important Variables on a Bill’s Probability of
Being Reported
96 4.4 answers the following question: what is the net change^’ in the predicted probahility
that a hill is reported if the specified variable is increased one standard deviation from its
mean?
In the 100**’ Congress, the two variables associated with the largest change in the predicted probability are gains-from-exchange variables (scope and multiple referral).
The distributive variable is fifth, after two party variables are in effect “tied” for third
(Republican Sponsored and the Election Margin for Democrats). These results indicate
that committees in the 100**’ Congress were more biased towards providing gains-from-
exchange than partisan benefits as expected by the balancing theory. In the 105**’
Congress, being sponsored by a Republican produces the biggest change in the probability of being reported. In addition, the electoral margin for Republicans has the
third largest effect. It is premature, however, to conclude that committees in the 105**’
were dominated by partisan interests, because the second largest change in a hill’s probability of being reported is associated with the scope of the hill.
Another way to assess the relative importance of variables is to compare odds
ratios. Using the logit model, the parameters can he transformed into odds ratios, which
indicate the expected change in odds of a bill being reported for a change in the
independent variable holding all other variables constant. The advantage of odds ratios is
that they are not dependent on the specific values of the other variables. To compare
odds ratios, I calculated the change in the odds for a standard deviation increase in the
The net effect means that changes in interaction terms are also included in the effect. For example, changes in the Republican Sponsor variable also cause changes in the interaction term. To calculate the predicted probability of the Sponsor variable, the interaction term is also changed.
97 100“’ Congress 105*“ Congress
Odds Ratio Pereent Odds Ratio Pereent Change Change
Gains-from-Exchange
Distributive Content 1.264 26.4 1.243 24.3
Seope (# of keywords) 1.975 97.5 1.961 96.1
Multiple Referral 1.387 38.7 0.852 -14.8
Information
Years in Flouse 1.092 9.1 1.244 24.4
Outlier 0.974 -2.6 1.119 11.9
Minority Party Cosponsors 1.138 13.8 1.022 2.2
Partisan
Republiean Sponsored 0.688 -31.2 2.375 137.5
% Demoeratie in Eleetion 1.255 25.5 1.043 4.3
Republiean Sponsor* 0.802 -19.8 1.225 22.5 Demoeratie Eleetion
Demoeratie Party Unity 1.131 13.1 0.953 -4.7
Figure 4.5: Change in the Odds of a Bill Being Reported for a Standard Deviation
Inerease in Theoretieally Derived Variables.
98 variable of interest. Figure 4.5 shows the odds ratios for the ten variables of interest using tbe first model of tbe three models for each Congress. The odds ratio cell in the
figure answers the following question: what is the change in the odds of a bill being
reported if tbe specified variable is increased by one standard deviation? The odds ratios
can be somewhat difficult to interpret because they are “multiplicative coefficient[s],
which means that positive effects are greater than 1 and negative effects are between 0
and 1” (Long 1997, 82). To aid in interpretation, I have calculated the percentage change
in the odds associated with the given odds ratio.
The differences between the committees of the 100th and 105th Congresses come
through in the odds ratios as well. In the 100**’ Congress, the scope and multiple referral
of a bill increase tbe odds more tban otber variables. Being sponsored by a Democrat has
the next biggest effect followed by tbe amount of distributive content. The gains-lfom-
exehange bias in tbe 100**’ Congress comes througb more strongly using odds ratios. In
tbe 105**’ Congress, tbe story is different. Being sponsored by a Republican increases tbe
odds of being reported by over 137 percent. Tbe scope of tbe bill, the tenure of the
sponsor and the bill’s distributive content follow in importance.
Since tbe difference between the two Congresses seems to be between tbe relative
importance of gains-lfom-exehange and party considerations, one additional look at the
data is useful. Holding all other variables at tbeir mean values, I simultaneously changed
all gains-lfom-exehange variables one standard deviation to measure the change in the predicted probability of a bill being reported for gains-lfom-exehange variables in
general. I did tbe same tbing for all the party variables, except I either increased or
99 decreased one standard deviation based on the direction of the variable (so tbe direction
of the change was all in the same partisan direction). The results are listed in Figure 4.6.
The aggregate effects are clear. In the 100**’ Congress, a bill with all the gains-lfom-
exehange characteristics had a greater probability of being reported than a bill witb all the
characteristics that advantaged the Democratic Party. In the 105**’ Congress, the opposite
was true. Bills that helped the Republican Party were more likely to be reported than bills that provided gains-Ifom exchange.
100**’Congress 105**’Congress
Gains-If om-Exchange 0.087 0.047
Partisan 0.011 0.098
Figure 4.6: Net Effects of Eegislative Benefits on a Bill’s Probability of Being Reported
4.3: Implications
The committee bias of tbe 100**’ Congress raises questions about the extent to
which the party cartel portrait of the Flouse is correct. Cox and McCubbins argue tbat tbe
majority party often relies on an “automatic pilot” control over tbe agenda. Tbis means
100 that the party structures committees and uses its leaders in such as way so as to create
incentives so that a party agenda is automatically produced without leaders having to
exercise “active” agenda control. The focus in their book is on the committee system.
The committee system is set on “automatic pilot” in two ways. First, the majority party
sets up the committee system. They create committees, assign jurisdictions, determine
the ratio of majority to minority party members, assign members to committees, and
choose committee chairs. This allows the party to “stack the deck” in its favor by creating
committees that are ideologically predisposed to produce partisan outcomes.
Second, the party gives leaders the ability to sanction members and committees
for bad behavior. The party can remove members from committees, eliminate
committees, change jurisdictions, and reallocate resources. Most importantly, the
Speaker can “veto” hills reported from committee and adjust the schedule to advance partisan goals. The ability to sanction members changes committee incentives. To avoid
sanctions and to ensure that their hills are scheduled, committees reprioritize their agenda
to match the party’s preferences.
The data presented here raises questions about the effectiveness of the scheduling
“veto” in changing committee incentives. Wright and Gingrich are both considered by
legislative scholars to be very partisan Speakers. The veto threat should have given
committees an incentive to be biased towards partisan ends. Flowever, in the 100*'’
Congress, the committee system prioritized gains-from-exchange benefits over partisan benefits. One explanation may be that Wright was less partisan than Gingrich. Perhaps
the “conditions” for party government were not as strong during the 100**’ Congress.
101 However, the 100**’ Congress at the time was considered to be the pinnacle of party
resurgence (Rohde 1991). If Wright’s partisanship was not enough to put committees on
“automatic pilot,” then the generalrzeability of the party cartel model of the House is very
weak. The scheduling “veto” simply does not have as much effect on committee agendas
that party theory expects.
This does not get around the fact that committees in the 105**’ Congress had a partisan hias. It may be that the scheduling veto is a weak incentive, but it is possible that
Gingrich effectively used his veto (or sent credible threats) and changed the committee
agenda. A more plausible story, however, comes from party theory’s other method of
control - structuring the committee system. The Republican takeover of the House led to
a reorganization of the committee system. First, committees that were traditionally
Democratic strongholds were eliminated (Merchant Marine, District of Columbia, and
Post Office). Second, committee chairs were given more authority and the influence of
subcommittees was reduced. Third, Gingrich selected committee chairs who were loyal
to the party and in doing so bypassed more senior members. The result was a committee
system more firmly in the hands of the committee chairs who were more ideologically
committed to the party agenda (see Smith and Lawrence 1997). Through these structural
reforms, the committees of the 105**’ Congress were more centralized and biased towards
majority party benefits.
In the 100**’ Congress, the story was different. Subcommittees had greater
influence over the committee agenda. The reforms of the 1970s reduced the power of
committee chairs and gave subcommittees jurisdictional guarantees. In effect, the agenda
102 was influenced by many different members. Davidson (1981, 131) said tbat “in place of party labels tbere are individual politicians in business for themselves . . . instead of a few
leaders or checkpoints for legislation, tbere are many.” Tbis presents a problem for tbe party’s automatic control. Tbe key to automatic control is to “give majority party
members significant advantages at every stage of tbe legislative process” (Cox and
McCubbins 1993, 258). Tbis is easier in a more centralized system because loyal party
members can be placed in each position. The more decentralized the system, the more
diversity there are among the party members in control. Tbus, despite the homogeneity
of the party in the 100*'’ Congress, the structural setup of the committee system did not
“automatically pilot” the party agenda as it did in the 105*'’ Congress.
The results in this chapter are not incontrovertible evidence that the scheduling
veto is a weak form of committee agenda control. After all, committees in both
congresses produced partisan benefits. However, the pattern of committee bias suggests
tbat structural changes in tbe committee system are tbe cause of tbe change in committee bias, not changes in the partisanship of the Speaker. Committees are designed at the beginning of each congress and through this design they are “stacked” in favor of producing different types of benefits. In the lOO"’ Congress, the decentralized control of
the committee system produced gains from exchange. In the 105*'’ Congress, the more
centralized system provided partisan benefits. Once committees are set up, the Speaker
has little effect on changing the underlying incentives of the system and has little effect
on changing the committee agenda.
103 4.4: Conclusion
Theoretical expectations about the Speaker’s scheduling behavior rest on the
nature of the committee agenda. My balancing theory argues that the Speaker will
facilitate the eommittee agenda by reinforcing the benefits produced by committees and
will balance the final agenda by scheduling unreported bills that are underproduced by
eommittees. Party theory, in contrast, expects that the Speaker will advance partisan
goals regardless of the eommittee agenda. The first step in testing these expectations is to
establish the nature of eommittee agenda.
In this chapter, I outlined the three theories of legislative organization that form
the basis for the different possible types of legislative benefits that can be produced.
Eaeh theory posits different types of bills that deliver eaeh benefit. Using these predictions, I examined which types of bills are more likely to be reported from
eommittee. In both Congresses, committees provided all three legislative benefits.
However, committees of eaeh Congress differed in the emphasis they placed on different benefits. In the 100**’ Congress, gains-fiom-exehange benefits had the largest impaet on
the probability that a bill would be reported. In the 105**’ Congress, partisan benefits had
the largest impaet.
The shift in eommittee bias raises questions about the effect of the Speaker’s
scheduling veto on eommittee priorities. Party cartel theory argues that eommittees
adjust their priorities in order to report bills that reflect the partisan bias of the Speaker.
However, even though Speaker Wright is considered a very partisan Speaker, the
committees in the 100**’ Congress emphasized gains-fiom-exehange over partisan
104 benefits. The implication is that party control over the committee agenda is best understood through the design of the committee system, rather than control over the
schedule.
105 CHAPTER 5
BALANCING THE LEGISLATIVE AGENDA
Committees produce the default schedule in the House, hut the Speaker has the
authority to change the schedule so that the final legislative agenda differs from the
committee agenda. The Speaker can change the legislative agenda in two basic ways -
he can change the regular order of business or he can schedule hills that have not been
reported. In Chapter 3 ,1 showed that the Speaker generally follows the regular order of business. After organizing the work week, the Speaker follows the committee agenda
over 75 percent of the time. The analysis in Chapter 4 demonstrated that by following
the committee agenda, the Speaker accepted the gains-from-exchange hias of the 100*'’
Congress and the partisan hias of the 105**’ Congress. However, the analysis to this point
has not considered how the Speaker changes the schedule. Despite the general adherence
to the calendar order, the Speaker does not schedule all the bills reported from
committees and schedules around 600 unreported hills (100**’: n=577; 105**’: n=643). In
this chapter, I examine the Speaker’s decision to change the legislative agenda.
Partisan theories of the House see the Speaker’s control over the schedule as a
tool for advancing partisan interests. Cox and McCubbins (2002, 153) argue that the
106 Speaker’s scheduling authority is key to the majority party’s ability to exercise “positive”
and “negative agenda control” - the ability to advance and block policy changes
respectively. Sinclair (1995, 210) argues that the Speaker uses his scheduling authority
to consider legislation when the party has “the requisite votes and when the political benefits of passage are at their height.”
The Speaker’s partisan hias leads to two specific claims about the Speaker’s
scheduling behavior. First, the Speaker will “veto” hills on the calendars that are less partisan. Time on the floor is scarce and if some hills on the committee agenda are less partisan than others, the Speaker will schedule the reported bills that are more partisan.
Second, the Speaker will use his authority to schedule unreported hills that advance partisan goals. For whatever reason, committees may not report all the party bills the
Speaker wants to include in the final agenda. Thus, to ensure that the final agenda
delivers the maximum party benefit, the Speaker will add party hills to the schedule.
In contrast, I argue that the Speaker uses his authority to facilitate the committee
agenda. The Speaker is not a purely partisan leader, but rather one that is caught between
institutional and partisan responsibilities. The goal of the Speaker is to produce a final
agenda that provides gains-fiom-exehange, informational, and partisan benefits. In doing
so, the Speaker facilitates the committee agenda. This does not mean that all reported hills are scheduled. The committee system has a legislative hias that he balances by
scheduling unreported hills. To make room for these hills, the Speaker will “veto” hills
on the regular order of business. Flowever, in making choices over which hills to veto,
the Speaker will not alter the general tendency of the committee agenda. Through this
107 strategy, the Speaker gives committees agenda control over their jurisdiction and provides a balance of benefits that serve both institutional and partisan interests.
This leads to two expectations that contrast with the party theory. First, the
Speaker will “veto” bills that are the least congruent with the committee hias. For
example, if the committee agenda has a strong distributive tendency, the Speaker will
veto bills that are low in distributive content, ensuring that the distributive bias is preserved. Second, to balance the agenda, the Speaker will schedule unreported bills that provide benefits undersupplied by the committee agenda.
In this chapter, I test these competing expectations. First, I look at the Speaker’s
scheduling decision over reported bills. Using logistic regression, I examine the types of benefits that the Speaker is most likely to schedule. To test the two theories, I compare
the Speaker’s scheduling bias to the committee bias. Second, I use the same method to
determine the Speaker’s scheduling bias in unreported bills. Again, comparing these
results to the committee bias provides a test of the two theories. Before getting to the
analysis, however, I present a different method for operationalizing the informational
variables.
5.1: Information Variables
Information theories have been developed to around the structure of committees.
In chapter 4 ,1 presented three different characteristics of the types of bills that provide
informational benefits. Two of these were directly related to characteristics of the
composition of committees. First, committees with more expertise provide more
108 informational benefits. Seeond, eommittees that are non-outlying and heterogeneous are
more informative. In Chapter 4, the analysis was on eommittee deeisions. Sinee
eommittee level eharaeteristies do not vary within eommittee, the eoneepts embedded in
tbese predietions bad to be translated into bill speeifie ebaraeteristies. The Speaker’s
seheduling deeision, however, does not have this problem. The Speaker can use the
composition of the eommittee as an indicator of informational effieieney. Using
eommittee composition variables allows for a more direct test of tbe importance of
informational ebaraeteristies because tbey are closer to tbe actual predietions of
information theories.
Committee Expertise: Committees with greater expertise bring better information
to the table. Krehbiel (1991) measures eommittee expertise as the mean number of years
tbat tbe members of the committee have served on the eommittee. Specialization and
expertise come with time spent in particular areas of public policy. Serving on a
committee builds tbis expertise. The more veteran the eommittee members, the more
expertise they embody. Thus, for eaeh eommittee I ealeulated the average number of
years members bad served on the eommittee. Committee service for the 100*’’ Congress
was collected from Nelson’s (1993)Committees in the U.S. Congress, 1947-1992. Sinee
his data end with the lOU* Congress, 1 supplemented his data with committee rosters printed in theCongressional Quarterly Almanac (1992-98) to determine eommittee
service in the 105*’’ Congress.
Outliers and Heterogeneity: The preference outlier and heterogeneity
eharaeteristies are based on bow the ideology of the eommittee differs from the House
109 ideology. Committees are outliers if the median of the eommittee is extreme relative to
the median of the House. Outlying eommittees are less likely to represent the preferenees
of the lull ehamber (Gilligan and Krehbiel 1990). Committees are heterogeneous if they
are ideologieally diverse. Heterogeneous eommittees are more informative heeause they provide more eredible information (Gilligan and Krehbiel 1989). To eapture these
eoneepts, Krehbiel (1991) used ADA seores to measure the ideology of members. From
this, he ealeulated the median seore and standard deviation for eaeh eommittee and the
lull House. Committees were relatively more outlying the greater the distanee the
eommittee median was from the House median. Similarly, eommittees were relatively
more heterogeneous, the greater their standard deviation was eompared to the House’s
standard deviation.
Debate is widespread about how to best measure ideology (see Groseelose et al.
1999). I ereated outlier and heterogeneity measures using Poole and Rosenthal’s (1985)
W-NOMINATE seores.^* The outlier variable is the absolute dilferenee between the
median ideology seore of the eommittee and the median ideology seore of the House.
The heterogeneity variable is the differenee between the standard deviation of the
ideology seores of the eommittee and the standard deviation of the House. The
heterogeneity variable is not the absolute differenee like the outliers variable is. The
heterogeneity variable is a measure of the relative spread of ideology. So, if the
See Chapter 4 for a discussion of W-NOMINATE scores.
110 committee represents a broader cross-section of the House than is typical, this will send a positive sign to the House that their interests are served.
Initially, these measures did not pose a problem. The correlation between tbe two
variables is relatively low for both Congresses. However, in the 105**’ Congress, the
correlation between the outlier and heterogeneity variables is high for the subset of bills
reported from committee (r=0.65). In estimating the model predicting the Speaker’s
scheduling decision over reported bills, the correlation between the two variables inflates
tbe standard errors and increases the chance of a Type II error. To overcome this problem, I created a different method for capturing heterogeneity and extremity.
Each committee has both Democratic and Republican Party contingents. Across
committees, tbe median of each party contingent varies. For example, some committees
have more a more liberal Democratic contingent and others bave a more conservative
Democratic contingent. The same is the case for the Republicans. The median members
of each committee’s party contingent can be used to capture tbe relative heterogeneity
and extremity of the committee. For example, if the median member of both the
Republican and Democratic Party contingent are moderate, tben the committee is not
much of an outlier (both moderate party medians create a moderate committee median) but it is homogenous (not much variation between medians). Contrast this with a
committee whose median members are both relatively extreme. In this case, the
committee is still not an outlier (the extreme medians counteract each other to keep the
committee median moderate), but it is heterogeneous (tbere is more variation in the
committee). Figure 5.1 shows the different types of committees that result from different
111 Party median configurations. In the off diagonal cells, the eommittee is an outlier because both party medians are in the same direction and create an outlier committee
median. The heterogeneity of the eommittee is somewhere in-between the homogenous
eommittee (two moderate medians) and the heterogeneous eommittee (two extreme
medians).
Demoeratie Median Moderate Extreme
Moderate Homogenous Semi-Homogenous Republiean Inlier Outlier Median Extreme Semi-Homogenous Heterogeneous Outlier Inlier
Figure 5.1: Committee Composition and Informational Effieieney
To demonstrate that this method captures the same idea as the outlier and
heterogeneous measures traditionally used, I divided eommittees in the 100**’ and 105**’
Congresses according to their party contingents. Using W-NOMINATE seores as the
measure of ideology, I classified a party contingent as extreme if the median member was
more liberal or conservative than the average party contingent for that party. Eikewise, I
classified a party contingent as moderate if the median member was less liberal or
112 Demoeratie Median Moderate Extreme 100*'' Congress Moderate Agrieulture Distriet of Columbia Appropriations Edueation Republiean Armed Sendees Foreign Affairs Median Banking Post Offiee Merehant Marine Rules
Extreme Commeree House Administration Seienee Budget Small Business Government Operations Veterans Affairs Interior Judieiary Publie Works Standards of Offieial Conduet Ways and Means lOS"* Congress Moderate Intelligenee Appropriations Transportation Banking Republiean International Relations Median House Oversight Rules
Extreme Agrieulture Commeree Budget Edueation National Seeurity Judieiary Resourees Government Reform Seienee Rules Small Business Standards of Offieial Conduet Veterans Affairs
Note: Moderate party medians are party eontingents wbose median is more moderate tban tbe average party eontingent of all eommittees. Extreme party medians are more extreme tban tbe median. Ideology is measured using Poole and Rosenthal’s W-NOMINATE seores.
Figure 5.2: The Party Contingent Median for Eaeh Committee
113 conservative (more moderate) than the average party eontmgent (see Figure 5.2 for the
eommittee breakdown).
To see the relationship between party medians and eharaeteristies of the full
eommittee, I ealeulated the standard deviation and median for eaeh eommittee. Figure
5.3 shows the average standard deviation for the eommittees in eaeh eell. In both
Demoeratie Median Moderate Extreme
100*'' Congress Moderate 0.309 0.336 Republiean Median Extreme 0.330 0.372
lOS"* Congress Moderate 0.512 0.588 Republiean Median Extreme 0.539 0.603
Note: Cell entries are the average standard deviation of the eommittees listed in Figure 5.2. Moderate party medians are party eontingents whose median is more moderate than the average party eontingent of all eommittees. Extreme party medians are more extreme than the median. Ideology is measured using Poole and Rosenthal’s W-NOMINATE scores.
Figure 5.3: Relationship between Committee Party Medians and the Full Committee
Standard Deviation
114 Congresses, the eommittees with moderate party eontingents have the lowest average
standard deviation; eommittees with extreme party eontingents have the highest standard
deviation. Committees with only one extreme party median have an average standard
deviation in between the others. Thus, using party medians for eaeh eommittee eaptures
the heterogeneity of the eommittee.
Likewise, party medians eapture the outlier eoneept. In Figure 5.4, the average
median of the eommittees in eaeh eell are shown. The numbers in the 100*’’ Congress are
negative beeause tbe W-NOMINATE seores range from -1 to I witb negative numbers being more liberal. To ease tbe interpretation, tbe absolute differenee between the
average eommittee median and the full ehamber is shown in parentheses. The
eommittees on the main diagonal are elosest to the ehamber median (non-outliers) and
tbe eommittees on tbe off diagonal are farthest (outliers). Again, this matehes my
expeetations.
Committee party medians ean be used to eapture the outlier and heterogeneity
eharaeteristies of different eommittees. In plaee of the Sponsor Outlier variable used in
Chapter 4 ,1 inelude in eaeb equation tbe Demoeratie and Republiean Party medians for
the bill’s eommittee. For multiply referred bills, I take tbe average party median for all
tbe eommittees to wbieh tbe bill was referred. These variables ean be used to test the
extent to whieh the Speaker advanees bills from informationally effieient eommittees.
By examining tbe predieted probabilities that result from different eonfigurations of party
medians, the Speaker’s propensity to sehedule bills from outlying and homogenous
eommittees ean be determined.
115 Democratic Median Moderate Extreme
100*'' Congress Moderate -0.041 -0.191 Republican (0.012) (0.123) Median Extreme -0.068 -0.060 01015) 01007)
lOS"* Congress Moderate 0.383 0.451 Republican (0.018) (0.086) Median Extreme 0.490 0.432 01125) 01067)
Note: Cell entries are the average committee median of the committees listed in Figure 5.2. In parentheses is the absolute distance the average median is from the median of the full chamber; it is the traditional measure of “committee outlier.” Moderate party medians are party contingents whose median is more moderate than the average party contingent of all committees. Extreme party medians are more extreme than the median. Ideology is measured using Poole and Rosenthal’s W-NOMINATE scores.
Figure 5.4: Relationship between Committee Party Medians and Full Committee Median
116 5.2: Scheduling Reported Bills
In both the 100**’ and 105**’ Congresses just under 90 pereent of the bills reported from eommittee were seheduled. In Chapter 3,1 showed that most of these bills were eonsidered in their ealendar order; but, not all bills are seheduled. Both Wright and
Gingrieh exereised diseretion over whieh bills to sehedule and whieh bills to veto. Party theories prediet that party bills will not be vetoed. In winnowing down the list of reported bills that are seheduled, a partisan Speaker would veto non-partisan bills in order to make the final agenda deliver greater partisan benefits. This is a null hypothesis that ean be tested. In eontrast, 1 argue that the Speaker faeilitates the eommittee agenda.
Thus, in the 100**’ Congress, the Speaker will be more likely to sehedule gains-from- exehange bills than partisan bills. In the 105**’ Congress, the Speaker will be more likely to sehedule partisan bills. In this seetion, 1 test my alternative hypothesis against the null.
The data used for this analysis is a subset of the data used in Chapter 4. Instead of ineluding all bills sent to a eommittee, the dataset ineludes all bills reported from eommittee. In the ease of multiply referred bills, only bills that were reported from all eommittees are ineluded. In the 100**’ Congress, 645 bills were reported from eommittee.
In the 105**’ Congress, 731 bills entered the ealendar system. The dependent variable is a dummy variable for whether or not the bill was eonsidered on the floor. The independent variables are the same as in Chapter 4 with a few exeeptions. The information variables from Chapter 4 are replaeed with the eommittee level variables (see Appendix for the same models run using the information variables from Chapter 4). The dummy variables for eaeh committee are replaeed with dummy variables for Each and Smith’s (1988)
117 classification of committee types (Prestige, Policy, Constituency, Other). Since the information variables are eommittee level variables, the individual committee variables were perfectly eollinear. The figures in Chapter 4 show whieh eommittees fall in eaeh category. Finally, the Date Introduced variable is replaeed with a ealendar variable, whieh is eaeh bill’s ealendar number. This is a control variable for tbe ealendar order.
Following tbe ealendar means that bills bigber up on the ealendar (those with lower numbers) will be seheduled first.
5.2.1: Results
For eaeh Congress, I estimated three different logistic regressions. As in the analysis of eommittee reports, the Republiean Sponsored variable and the Demoeratie
Party Unity variable are bigbly correlated (100**’: p= -0.89; 105**’: p= -0.67). It is difficult to determine independent effects with eollinear variables, so in Equation 2 I exclude the unity variable. In Equation 3 ,1 exclude tbe sponsor variable and tbe election variables
(beeause they are interactions with the sponsor variable). The results for the 100**’ and
105**’ Congresses are found in Figures 5.5 and 5.6 respectively. Notice in both
Congresses, the bilFs placement on the ealendar is significant and in the expected direction. As bills are reported and placed lower on tbe ealendar, tbe probability of being seheduled decreases. This is further support for the conclusion in Chapter 3 that the regular order of business plays a significant part in determining the actual legislative sehedule.
The partisan and balancing theories of scheduling differ in their predictions of the types of bills tbat tbe Speaker will sehedule. The partisan theory expects partisan
118 characteristics to be dominant in determining whieh bills are seheduled. In this way, the
Speaker biases the eommittee agenda to partisan ends. The balaneing theory, in eontrast,
expects the Speaker to facilitate the eommittee agenda and select bills to be seheduled based on the bias of the eommittee system. In Chapter 4 ,1 established that the eommittee
system in the 100**’ Congress had a gains-from-exehange bias and eommittees in the 105**’
Congress had a partisan bias. My balaneing theory expects that gains-from-exehange
eharaeteristies will be most important in the 100**’ Congress and partisan characteristics
will be most important in the 105**’ Congress.
The results support the balaneing picture of scheduling. In the 100**’ Congress, partisan characteristics are not significant in any of the models, but the distributive gains-
from-exehange variable is significant in all three. In the 105**’ Congress, the opposite pattern holds. The gains-from-exehange variables are all insignificant while the
Demoeratie Party Unity variable is significant in both equations in whieh it is included.
Speakers Wright and Gingrieh differ, then, in the types of bills that they carry from the
ealendar to the floor. Wright made sure that bills with high distributive content were
seheduled. Gingrieh made sure that members who were loyal to the Republiean Party
had their bills eonsidered. In this way, both Speakers facilitated the bias of the
eommittees system.
This is especially interesting in light of party cartel expeetations about the
Speaker’s reaction to different types of eommittee agenda. Party cartel theory expects
that the Speaker will use “active” control over eommittees that do not advance the party
agenda. The absence of “active” control means that eommittees are working on
119 Figure 5.5: Logistic Regression Predicting Which Reported Bills are Scheduled in the
100**’ Congress
120 Equation (1) (2) (3) Constant -0.206 -1.011 -0.667 (2.058) (1.746) (1.813)) Calendar Number -0.002*** -0.002*** -0.002*** (0.001) (0.001) (0.001) Gains-from-Exchange Distributive Content 8.209*** 8.123*** 8.506*** (2.736) (2.721) (2.735) Scope (# of keywords) 0.005 0.005 0.005 (0.004) (0.004) (0.004) Multiple Referral -1.052 -1.054 -1.038 (0.743) (0.741) (0.742) Information Committee Seniority 0.133 0.144 0.112 (0.259) (0.260) (0.260) Republican Median 8.968*** 9.014*** 9.410*** (2.591) (2.580) (2.577) Democratic Median -1.995 -1.742 -2.520 (2.845) (2.825) (2.779) Minority Party Cosponsors -0.006 -0.005 -0.005 (0.008) (0.008) (0.008) Partisan Republican Sponsored 0.012 0.650 (1.316) (0.985) Vote % for Democratic Party in last Election -0.825 -0.729 (1.025) (1.014) Republican Sponsor* Democratic Election 2.147 2.285 (3.572) (3.476) Democratic Party Unity -0.008 -0.008 (0.011) (0.006) Committees Prestige 0.455 0.455 0.469 (1.251) (1.250) (1.254) Policy -0.674 -0.687 -0.728 (0.707) (0.705) (0.705)) Constituency -0.306 -0.255 -0.312 (0.838) (0.834) (0.836))
Number of Cases 620 620 638 Log likelihood -177.233 -177.509 -178.675 Pseudo R2 0.148 0.147 0.149 Correctly Predicted 89.52% 89.52% 89.66%
Note: Standard errors in parentheses; *p<0.10; **p<0.05; ***p<0.01 121 Figure 5.6: Logistic Regression Predicting Whieh Reported Bills are Seheduled in the
105**’ Congress
122 Equation (1) (2) (3) Constant 1.256 -0.448 0.544 (4.027) (3.815) (3.823) Calendar Number -0.006*** -0.006*** -0.006*** (0.001) (0.001) (0.001) Gains-from-Exchange Distributive Content 1.081 0.431 1.186 (5.415) (5.252) (5.390) Scope (# of keywords) 0.000 0.000 0.000 (0.000) (0.000) (0.000) Multiple Referral 1.215 1.124 1.129 (1.403) (1.395) (1.403) Information Committee Seniority -0.355 -0.279 -0.346 (0.401) (0.398) (0.402) Republican Median 1.735 2.092 1.609 (4.986) (4.890) (4.926) Democratic Median -3.303 -2.917 -3.233 (2.472) (2.429) (2.476) Minority Party Cosponsors 0.011 0.011 0.011 (0.008) (0.008) (0.008) Partisan Republican Sponsored -0.987 0.221 (0.937) (0.632) Vote % for Democratic Party in last Election -1.025 -0.391 (2.209) (2.067) Republican Sponsor* Democratic Election -0.103 -1.058 (2.721) (2.586) Democratic Party Unity -0.016* -0.010** (0.009) (0.004) Committees Prestige 3.291** 3.242** 3.253** (1.420) (1.414) (1.421) Policy 2.043 1.915 1.992 (1.370) (1.364) (1.372) Constituency 2.131 2.044 2.090 (1.500) (1.489) (1.501)
Number of Cases 729 729 729 Log likelihood -207.909 -210.479 -208.722 Pseudo R2 0.226 0.216 0.223 Correctly Predicted 88.61% 88.20% 88.75%
Note: Standard errors in parentheses; *p<0.10; **p<0.05; ***p<0.01 123 “automatic pilot.” Contrary to this expectation, the Speaker uses “active” party control precisely when he does not need to exercise control. Speaker Wright should have been
the most prone to use party eharaeteristies beeause the eommittee agenda did not have a
strong partisan bias. Since the eommittee system did not have a strong “automatic pilot,”
Speaker Wright should have exereised more “active” control over the agenda. Speaker
Gingrieh, on the other hand, had a eommittee system with a strong partisan bias. Since
there was an element of “automatic” agenda control, there did not need to be as much
“active” control. However, just the opposite occurred. The Speaker does not appear to use his scheduling authority to alter the eommittee agenda and advance partisan interests.
Rather, the Speaker faeilitates the eommittee agenda and makes scheduling choices based
on the nature of the eommittee agenda.
In addition to the gains-from-exehange and partisan variables, the information
variables are interesting. In the 100**’ Congress, the Republiean Median variable is positive and significant. This means that the Speaker is more likely to sehedule bills that
come from eommittees with more conservative Republiean eontingents. Taken by itself,
the Republiean Median variable ean be interpreted as a confirmatory signal. The
Democrats are the majority party in the 100**’ Congress and Republicans are the “natural
adversaries.” From an information signaling perspective, the more extreme is the
ideology of the Republicans, the stronger the signal. Speaker Wright favored bills with a
strong signal. Ceteris paribus, Wright was more likely to sehedule bills from eommittees
with a more conservative Republiean eontingent.
124 To explore the extremity (outlier) and heterogeneity characteristics both the
Democratic and Republican medians must he used. I calculated the predicted probability
of a bill being scheduled for four different pairs of party medians. The party median pairings match the committee types summarized in Figure 5.1. I used the minimum and
maximum of each variable to calculate the probabilities for each cell. For example, to
calculate the moderate/moderate cell I used the minimum Republican Median (100**’:
0.149; 105**’: 0.625) and the maximum Democratic Median (100**’: -0.040; 105**’: -0.170).
To calculate the extreme/extreme cell I used the maximum Republican Median (100**’:
0.473; 105**’: 0.750) and the rninimum Democratic Median (100**’: -0.378; 105**’: -0.560).
All other variables are held at their mean values. The probabilities for both congresses
are shown in Figure 5.7.
Both Speakers have an informational bias. The information variables in the 105***
Congress are not significant, hut they tell the same story as the 100**’ Congress. In both
cases, committees that are heterogeneous and moderate (extreme/extreme) have the
highest probability of being scheduled. Thus, committees that have both informational
attributes and are the most informationally efficient have the greatest probability of
having their bills scheduled. The second most preferred committee type is biased
committees towards the minority party. Thus, both Speakers look for support from the
minority party when choosing the hills to schedule. This paints a much different picture
than a purely partisan Speaker using his authority to advance party goals. Even in the
case of Gingrich, who advances partisan goals, decisions are tempered by informational
125 Democratic Median Moderate Outlier 100*'' Congress
Moderate 0.576 0.702 Republican Median Outlier 0.932 0.966
lOS"* Congress
Moderate 0.827 0.945 Republican Median Outlier 0.856 0.953
Note: Cell entries are the predicted probabilities of being scheduled for different values of committee party medians for Equation 1 in Figures 5.6 and 5.7. Predicted probabilities are based on the minimum and maximum party medians. Ideology is measured using Poole and Rosenthal’s W-NOMINATE scores, which range from -1 to 1 with I being conservative. Thus, Republican outlier is the maximum Republican Party median. Since more liberal committees are negative, the Democratic outlier is the minimum Democratic Party median.
Figure 5.7: Predicted Probability of Being Scheduled By Committee Party Medians
126 efficiency (although the insignificance of the variables necessitates some hesitation in
making this conclusion).
The general picture that arises is one of a Speaker who uses his scheduling
authority to facilitate the committee agenda. First, the Speaker follows the calendar order
allowing bills reported earlier in the session to be scheduled over bills reported later in
the session. Second, since not all bills are scheduled, the Speaker ensures that bills that
reflect the committee bias the best are brought to the floor. Third, in selecting bills to
schedule, the Speaker looks for bills that have the greatest informational efficiency. This pattern is consistent with my balancing theory of scheduling. The next step in testing the partisan and balancing theories of scheduling is to explore how the Speaker schedules unreported bills.
5.3: Scheduling Unreported Bills
Around fifty percent of the bills scheduled in the House are brought to the floor
without being reported from committee (100**’: 57 percent; 105**’: 49 percent). The shear
volume of bills brought to the floor through this route opens the door for tremendous
agenda control by the Speaker. In the 100**’ Congress, around 10,000 bills and resolutions
were not reported. In the 105**’ Congress, over 8000 bills and resolutions were left. The
Speaker’s scheduling authority allows him to pick from these bills the 600 or so that he
wants to schedule. In essence, the Speaker has the power to bypass committees directly bring bills to the floor. In doing so, he can fundamentally change the nature and bias of
the legislative agenda.
127 This does not mean that eommittees are uninvolved. The Speaker eommunieates
with eommittee ehairs and bill sponsors. Committees vote to have their bills eonsidered under suspension instead of reporting them. Sponsors petition the Speaker to have their bills brought up under suspension. Thus, many of these deeisions are made with the
eonsent of eommittees. This is not surprising sinee the Speaker is an agent of the
ehamber and eireumventing eommittees is risky when trying to maintain support. Yet
even with eommittee eonsultation, the Speaker has tremendous agenda setting authority.
It is surprising that the literature is silent on the use of bypass procedures to
eireumvent eommittees. In general, empirical and theoretical studies explicitly exclude bills that take this path to the floor. Therefore, spécifié theoretical predictions about
scheduling unreported bills do not exist. However, the general spirit of the party cartel
and other partisan theories (i.e. conditional party theory) suggest that leaders use their
authority to advantage the majority party. The partisan expectation, then, is that the
Speaker will sehedule unreported bills that further provide partisan benefits. In fact, the
Speaker’s absolute diseretion over whieh bills to sehedule suggests that partisan
eharaeteristies will be the only factors that determine whether or not unreported bills are
seheduled. The Speaker does not have to sehedule any unreported bills. If eommittees
are asking for non-partisan (or minority party) bills to be seheduled without a report, a partisan Speaker should find no utility in scheduling these bills. Committees with non partisan bills must report them and plaee them in the regular order of business.
In eontrast, I argue that the Speaker schedules unreported bills to balance the
sehedule. Committees cannot be fine-tuned to provide the balance between partisan,
128 informational and gains-lfom-exchange benefits that members demand. Members give
tbe Speaker authority to dip into eommittee jurisdietions so tbat tbe final agenda provides
all three benefits. I expeet, then, that the Speaker will sehedule bills tbat provide benefits
tbat are undersupplied by the eommittee system. More preeisely, I expeet that Wright
will sehedule partisan bills during the 100**’ Congress and Gingrieh will sehedule gains-
from-exehange bills during the 105**’ Congress.
On the one hand, the balaneing theory expeetations are preeise. I expeet eertain benefits to be provided. On tbe other hand, the expeetation is loose. I do not make an
argument about tbe “optimal” balanee in tbe sehedule. This means that the Speaker may
sehedule types of bills tbat are also supplied by tbe eommittee system. For example, tbe
optimal balanee might demand that additional partisan bills be supplied, even if tbe
eommittee system is biased towards partisan benefits. In this ease, the Speaker will
sehedule unreported partisan bills. However, I prediet tbat the Speaker will also sehedule
gains-from-exehange bills.
The data used in this analysis are all bills and resolutions introdueed in tbe House,
or passed in the Senate, that are not reported from eommittee. This ineludes multiply
referred bills that are only reported from one eommittee. The dependent variable is
dummy variable for whether or not the bill was eonsidered on tbe floor. The independent
variables are the same as those used for reported bills witb one exeeption. Tbe ealendar
number variable is exeluded (beeause none of these bills are on tbe ealendar) and is
replaeed by the Date Introdueed. This is the same variable used in Chapter 4. Bills are
129 coded for the legislative day they are introduced. Higher numbers mean the bill was
introduced later in the Congress.
5.3.1: Results
As with the previous analyses, I estimated three logistic regressions to manage the
collinearity problem associated with the Republican Sponsor and Democratic Party Unity
variables. The results for the 100**’ and 105**’ Congresses are shown in Figures 5.8 and
5.9 respectively. Almost all of the variables are significant, hut the directions are not
always in expected directions.
To deliver gains-lfom-exchange benefits both Speakers scheduled larger and
more distributive bills. In Gingrich’s case, this supports the balancing theory. The
committees of the 105**’ Congress were biased more towards partisan benefits and
Gingrich uses his authority to schedule unreported bills that deliver gains-lfom-exchange benefits. In Wright’s case, scheduling distributive hills furthers the committee bias
towards gains-lfom-exchange benefits. This does not contradict the balancing
expectations because I do not make claims about the optimal balance. The true test of balancing comes in scheduling partisan bills.
In both cases, unreported multiply referred bills are less likely to he scheduled.
Multiply referred hills involve more complex jurisdictional issues and tap into multiple
aspects of public policy. Scheduling bills before they are reported does not allow
committees to issue committee reports, which can have informational value. Further, the process of marking up the hill and reporting it allows committees to put their individual
130 Figure 5.8: Logistic Regression Predicting Whieh Unreported Bills are Scheduled in the
100**’ Congress
131 Equation (1) (2) (3) Constant 0.423 1.637** 0.669 (0.856) (0.765) (0.677) Date Introduced 0.003*** 0.003*** 0.002*** (0.001) (0.001) (0.000) Gains-from-Exchange Distributive Content 2.459*** 2.415*** 2.693*** (0.740) (0.738) (0.623) Scope (# of keywords) 0.009*** 0.009*** 0.007*** (0.003) (0.002) (0.001) Multiple Referral -1.423*** -1.418*** -1.468*** (0.217) (0.216) (0.180) Information Committee Seniority -0.336** -0.338** -0.293** (0.139) (0.138) (0.122) Republican Median -3.811*** -3.882*** -3.554*** (1.091) (1.085) (0.924) Democratic Median 2.914* 2.777** 1.751 (1.309) (1.306) (1.120) Minority Party Cosponsors 0.018*** 0.017*** 0.014*** (0.002) (0.002) (0.002) Partisan Republican Sponsored 0.252 -0.650*** (0.363) (0.234) Vote % for Democratic Party in last Election -0.799* -0.837* (0.434) (0.434) Republican Sponsor* Democratic Election 2.654** 2.595** (1.073) (1.069) Democratic Party Unity 0.014*** 0.007*** (0.004) (0.001) Committees Prestige -2 977*** -2.993*** -3.514*** (0.382) (0.381) (0.373) Policy -0.925*** -0.915*** -1.294*** (0.172) (0.170) (0.147) Constituency -2.142*** -2.164*** -2.180*** (0.299) (0.298) (0.250)
Number of Cases 6651 6651 7138 Log likelihood -1272.965 -1278.122 -1661.434 Pseudo R2 0.193 0.190 0.193 Correctly Predicted 93.56% 93.56% 91.44%
Note: Standard errors in parentheses; *p<0.10; **p<0.05; ***p<0.01 132 Figure 5.9; Logistic Regression Predicting Which Unreported Bills are Scheduled in the
105“’ Congress
133 Equation (1) (2) (3) Constant 4.362*** 4.317*** 5.229*** (1.482) (1.481) (1.461) Date Introduced 0.005*** 0.005*** 0.005*** (0.000) (0.000) (0.000) Gains-from-Exchange Distributive Content 17.835*** 17.851*** 17.319*** (2.039) (2.042) (1.978) Scope (# of keywords) 0.002*** 0.002*** 0.002*** (0.000) (0.000) (0.001) Multiple Referral -2.239*** -2.240*** -2.362*** (0.359) (0.360) (0.355) Information Committee Seniority 0.248 0.264* 0.241 (0.159) (0.159) (0.158) Republican Median -10.103*** -10.324*** -9.679*** (1.943) (1.936) (1.926) Democratic Median 2.946*** 2 999*** 2.832*** (1.119) (1.121) (1.101) Minority Party Cosponsors 0.010*** 0.009*** 0.008*** (0.002) (0.002) (0.002) Partisan Republican Sponsored 1.039*** 1.180*** (0.240) (0.222) Vote % for Democratic Party in last Election 1.043 1.078 (0.743) (0.747) Republican Sponsor* Democratic Election -2.398** -2.458*** (0.939) (0.940) Democratic Party Unity -0.001 -0.006*** (0.001) (0.001) Committees Prestige -3.048*** -3.066*** -3.055*** (0.384) (0.384) (0.378) Policy -0.747** -0.747** -0.868*** (0.301) (0.302) (0.298) Constituency -2.384*** -2.392*** -2.465*** (0.439) (0.440) (0.431)
Number of Cases 5365 5365 5365 Log likelihood -1234.09 -1235.187 -1260.198 Pseudo R2 0.154 0.153 0.136 Correctly Predicted 92.10% 92.12% 92.08%
Note: Standard errors in parentheses; *p<0.10; **p<0.05; ***p<0.01 134 stamp on the bill that is sent to the floor. Unreported bills may not bave tbe full gains-
from-exehange until all eommittees have their input and report the bill. The eomplexity
of multiply referred bills may mean that gains-from-exehange are best eaptured by being
reported and plaeed on the ealendar. Thus, by not sebeduling unreported multiply
referred bills, tbe Speaker is aetually inereasing the potential gains-from-exehange.
Delivering informational benefits is also a priority, but the results are less elear
eut. In both Congresses, the Speaker looks for a eonfirmatory signal. Minority party
support is signifieant in every equation. However, eommittee heterogeneity is not
important to either Speaker. Figure 5.10 shows the predieted probabilities for different
eonfigurations of party eontingents. The eommittees with the highest probability of being sebeduled are tbe most homogenous (moderate/moderate). The eommittees with
the lowest probability are the most heterogeneous (extreme/extreme). Despite the laek of
heterogeneity, both Speakers ehoose low varianee eommittees that are not outliers. So,
there is still a preferenee for eommittees that roughly mateh the median preferenees of the
full ehamber. Further, the eonfirmatory signal on eaeh bill inereases the information
transferred from the homogenous eommittees. Remember that homogenous eommittees
are the least likely to have their bills seheduled after they are reported. Perhaps this is the
Speaker’s way of ensuring that these eommittees have aeeess to the sehedule. But he
does so in a way that eneourages information beeause be also looks for a eonfirmatory
signal on a bill by bill basis.
135 Democratic Median Moderate Outlier 100*'' Congress
Moderate 0.168 0.069 Republican Median Outlier 0.056 0.021
lOS"* Congress
Moderate 0.195 0.072 Republican Median Outlier 0.065 0.022
Note: Cell entries are the predicted probabilities of being scheduled for different values of committee party medians for Equation 1 in Figures 5.10 and 5.11. Predicted probabilities are based on the minimum and maximum party medians. Ideology is measured using Poole and Rosenthal’s W-NOMINATE scores, which range from -1 to 1 with I being conservative. Thus, Republican outlier is the maximum Republican Party median. Since more liberal committees are negative, the Democratic outlier is the minimum Democratic Party median.
Figure 5.10: Predicted Probability of Being Scheduled By Committee Party Medians
Committee seniority is another interesting result. In the lOO"’ Congress, senior
committees are significantly less likely to have bills scheduled. In the 105"' Congress,
committee seniority positively impacts the probability of being scheduled, but is only
significant in one of the three equations. The differential impact of seniority between the
two Congresses makes speculation difficult. It is possible that the advantage of senior 136 committees is their ability to write informative reports or hold informative mark-up
sessions. Thus, there is an informational value to having senior committees report their hills; scheduling bills that have not been reported forfeits that informational advantage.
That may explain the 100*'’ Congress, but it raises questions about the 105**’. It is
also possible that senior committees create better hills and thus members do not need a
report to know that expert knowledge was brought to the table. Thus, senior committees
do not need to report bills to convey information; scheduling unreported hills from senior
committees may he more informative than bills from less senior committees. This
explains the 105*'’ Congress, hut casts doubt on the informational approach in the lOO"’
Congress. Without more precise predictions about unreported hills (or the value of
committee reports) from information theories, it is difficult to conclude one way or
another about the informational consequences of these results. However, in light of the
other informational variables in the model it is clear that informational efficiency is at
least part of the Speaker’s scheduling decision.
Partisan considerations are also important for both Speakers. Wright and
Gingrich both show a preference for majority party sponsored hills and especially hills
sponsored by more loyal members of the party. Interestingly, Gingrich did not use
scheduling to help electorally marginal members. The positive coefficient on the
Democratic Party Unity variable means that Democrats from safer districts were more
likely (although insignificantly) to have their hills scheduled. The negative coefficient on
the interaction variable means that safer Republicans were more likely to have their hills
scheduled. Wright was different. He was more likely to schedule bills sponsored by
137 marginal members in both parties. To tbe extent that legislative sueeess is important for
eleetoral sueeess, Wright helped marginal members of bis party in their eleetoral pursuit
and Gingrieh did not. However, Wright also helped marginal Republieans.
On the whole, both Speakers provide partisan benefits. Again, this supports the balaneing expeetation. Wright seheduled partisan bills to balanee the gains-from-
exehange bias of the eommittees in the 100**’ Congress. Gingrieh also seheduled partisan bills. In his ease, partisan benefits furthered the partisan bias o f the eommittee system.
This is the most ambiguous result regarding tbe partisan and balaneing expeetations. As
tbe partisan theory expeets, Gingrieh further biased the already partisan eommittee
agenda with partisan bills. However, Gingrieh also seheduled bills tbat provide gains-
from-exehange and informational benefits. From a partisan standpoint, these benefits
should not be important.
The pieture that emerges from this analysis is a Speaker that uses his authority to
sehedule unreported bills tbat advanee all three types of legislative benefits. This is perhaps the strongest evidenee that the Speaker is not a strong partisan but rather aets as
an agent of both tbe ehamber and tbe majority party. Sebeduling unreported bills is the
sole prerogative of the Speaker and if purely partisan seheduling deeisions are to be made
anywhere, they would be made here. Instead the Speaker advanees all three goals. In
doing this, he ereates a balaneed frnal agenda. In the 100**’ Congress, eommittees had a
gains-from-exehange bias. In response, partisan eharaeteristies were important in
Wright’s seheduling of unreported bills. Committees in the 105**’ Congress had partisan
138 priorities. In response, the distributive nature of the bill was important in Gingrieh’s
seheduling of unreported hills.
5.4: Conclusion
Partisan theories of seheduling suggest that the Speaker uses his seheduling
authority to advanee party goals at the expense of other eonsiderations. Speeifieally, this
means that the Speaker rearranges the regular order of business to advantage partisan
interests. This is espeeially the ease if the eommittee system does not provide an agenda biased towards partisan goals. Without a partisan eommittee agenda, the Speaker must
exereise “aetive” eontrol over the agenda to advanee partisan interests. In addition, the
Speaker will use his authority to sehedule unreported bills that also advanee partisan
interests. Beeause seheduling unreported hills is entirely at the Speaker’s diseretion, partisan charaeteristies will be the only important faetors.
In eontrast, 1 argued that the Speaker is an agenda of both the ehamher and the
majority party. This means that the Speaker has an interest in ereating a final agenda that provides all three types of legislative benefits (partisan, informational, and gains-fiom-
exehange). In ereating this agenda, the Speaker does not alter the hasie tendeney of the
eommittee system; instead, he faeilitates the eommittee agenda ensuring that hills
eonsistent with the eommittee bias are seheduled. This does not neeessarily ereate the
optimal balanee between all three benefits. To ensure the proper halanee, the Speaker uses his authority to sehedule unreported bills. Speeifieally, the Speaker will sehedule hills that provide benefits under-produeed by the eommittee system.
139 In this chapter, I tested these competing expectations. First, I examined the
Speaker’s scheduling decision over reported bills. In Chapter 4 ,1 discovered that
committees in the 100**’ Congress had a gains-from-exchange bias while committees in
the 105**’ Congress had a partisan bias. Consistent with the balancing theory, I
demonstrated that the Speaker’s scheduling decision of reported bills reinforces the
committee bias. Three factors are significant in the scheduling decision of reported hills.
First, calendar order is important (consistent with the results of Chapter 3). Second, the
nature of the committee bias is important. Third, the Speaker looks for informational
efficiency.
I also examined the Speaker’s scheduling decision over unreported hills.
Contrary to the partisan theory, I show that the Speaker provides all three legislative benefits, not just partisan benefits. This is also consistent with the balancing theory. In
the 100**’ Congress, Wright balanced the committee agenda by providing partisan benefits. In the 105**’ Congress, Gingrich balanced the committee agenda by delivering
distributive benefits. The general conclusion that comes from this is that the Speaker is
not a strong partisan purely interested in advancing partisan interests. Rather, the
Speaker is an agent of the chamber and the majority party balancing the legislative
demands of these competing principals.
140 CHAPTER 6
CONCLUSION
In the modern House, the Speaker has heen given greater control over the legislative agenda. Through his procedural control of the scheduling decision, the
Speaker has been given an effective veto over which hills are scheduled and when. The centralization of the scheduling decision and the increased partisanship in the House has led scholars to argue that the agenda in the House is a partisan agenda that advantages the members of the majority at the expense of the minority (Aldrich and Rohde 2001; Cox and McCuhbins 1993; Kiewiet and McCuhbins 1991; Rohde 1991; Sinclair 1995, 2000).
In this dissertation, I have presented empirical evidence that calls this portrait of the scheduling decision into question. In the process, I have outlined an alternative theory of scheduling that focuses on the Speaker’s need to balance partisan and institutional demands. In this chapter, I summarize my basic argument and draw out the implications for current theories of legislative organization, the basis of agenda control in the House, and the nature of legislative politics.
141 6.1 : Summary of Argument
The Speaker is a unique leader beeause he is eaught between the conflieting
demands of his institutional responsibility and partisan loyalty. His institutional
responsibility derives from the faet that he is the only leader in the House eleeted by the
lull ehamher. The offiee of the Speaker was ereated to oversee the operation of the
House and ensure a fair and effieient eonsideration of legislation. His partisan loyalty
eomes from his membership in the majority party and the faet that the eleetion as Speaker
is almost always a straight party vote. The tension between these two eompeting prineipals demands a delieate balaneing aet when setting the sehedule. Leaning too far
towards one prineipal at the expense of the other has eleetoral eonsequences. History has
shown that being too partisan will bring revolt by the House and being too fair will bring
anger from the party. The Speaker must balanee the demands of these prineipals and any
theory of the Speaker’s seheduling deeision must reeognize this need for balanee.
Balaneing the agenda means that the Speaker must ereate an agenda that provides
legislative benefits important to both the ehamher and the majority party. The literature
on institutional design has identified three primary legislative benefits demanded by all
legislatures - gains-from-exehange, information, and party benefits. Committees ean be
designed to provide these benefits, but there is fundamental tradeoff that exists when
eonstrueting eommittees - produeing one benefit eomes at the expense of produeing
others. As a result, the Speaker must use his seheduling authority to ensure that all benefits are provided and that the optimal balanee is reaehed between ehamher and party
demands.
142 The optimal balance between the partisan and chamber benefits varies over time.
Thus, my theory does not make any claims about the correct proportion of partisan and
chamber benefits in the final agenda. However, I have made specific claims about
general patterns in scheduling. The first is that the Speaker will follow the eommittee
agenda. The eommittee system is the primary institution that filters through the massive
volume of bills proposed in each congress. Individual members work hard to select bills
in their jurisdiction that fit various political and policy goals. The Speaker, as an agent of
the chamber, finds it dangerous to alter the agenda set by the eommittee system. This
impinges on eommittee rights and reduces the ability for individual members to pursue
their own goals. The best strategy for the Speaker is to facilitate the eommittee agenda.
This leaves the agenda setting in the hands of eommittees and helps satisfy a basic
institutional demand for fairness. The major change that the Speaker makes when
seheduling the eommittee agenda is to organize the work week so that non-eontroversial bills are considered early in the week, allowing members the luxury to spend more time
in the district.
Balaneing the sehedule, however, requires some change in the eommittee agenda.
Committees cannot be designed to provide all benefits in the proper balanee. As a result,
the Speaker uses his authority to augment the eommittee agenda. The Speaker schedules bills that have not been reported from eommittee to round out the final agenda. He
makes sure that the agenda is balanced by seheduling bills that provide benefits undersupplied by the eommittee system. Since eommittees reeognize that they cannot provide the optimal balanee, they give up some autonomy over their jurisdiction and
143 allow the Speaker to dip into their set o f bills. In this way, the final agenda provides the balanee demanded by the ehamher and the majority party and eommittees retain primary
eontrol over the agenda in their jurisdietion.
This does not mean that eommittees always have their bills seheduled. For
different reasons, the Speaker does not sehedule all the bills reported from eommittee.
One reason is that eommittee bills do not always have enough support to pass. The
Speaker does not want to waste time on the floor eonsidering bills that be knows will not pass. Another reason is that balaneing the sehedule may require unreported bills to take
the plaee of reported bills on the sehedule. Flowever, when ehoosing between reported bills, the Speaker will make sure that bills eonsistent with the general legislative bias of
the eommittee system will be seheduled. That is, if the eommittee system has a general bias towards distributive benefits, the Speaker will make sure that bills high in
distributive eontent are seheduled. Bills low in distributive eontent, however, may be
“vetoed” to make room for unreported bills in the final agenda. In short, when the
Speaker cannot follow the eommittee agenda exactly, he ensures that the basic legislative
tendeney of the eommittee system is seheduled.
The Speaker, in my view, is not a strong partisan. Rather, he is leader constrained by the expectations of the full chamber and the majority party. This means that the
Speaker is reluctant to challenge the agenda setting power of the eommittee system. In
changing the agenda, the Speaker works to strike a balanee the preserves the interests of
the eommittees and provides all three types of legislative benefits. Securing partisan
144 benefits are just one of the Speaker’s seheduling objeetives. He is mueh more eoneerned
with passing a halaneed agenda than a partisan one.
6.2: Implications
My argument has several implieations for theories of legislative organization and
our understanding of the House in general. In reeent years, various party theories have
developed that make speeifie elaims about the Speaker’s use of his seheduling authority
and the effeet this has on agenda eontrol in the House. First, the hasie assumption of
these theories is that the Speaker is an agent of the party and pushes as partisan an agenda
as is supported by members of the majority party (Cox and MeCuhhins 1993; Aldrieh and
Rohde 2001; Sinelair 1995). In the past twenty years, the inereased homogeneity of the parties has ereated a modern Speaker that is highly partisan and interested in advantaging
the majority party at every turn (Rohde 1991). Yet the evidenee presented in this
dissertation supports the portrait of a Speaker interested in following the eommittee
agenda and balaneing the legislative sehedule. This is the ease despite the faet that both
the Speakers studied here (Wright and Gingrieh) are eonsidered to he modern examples
of extreme partisanship.
Seeond, Cox and MeCuhhins (1993; 1994; 2002) party eartel theory argues that
seheduling is important to the majority party’s ability to usurp the agenda setting power
of the House. The Speaker’s partisan seheduling is said to ehange the incentives of
eommittees so that the hills reported from eommittee satisfy the partisan demands of the
Speaker. In this way, party eartel theory suggests a fundamental shift in the understanding of agenda-setting in the House. In this view, the agenda is defined by the
145 speaker and other party leaders from the top down. Committees do not control the agenda because the Speaker successfrilly uses the scheduling veto to controlde facto which bills will be reported.
The evidence supports something very different. Committees in the 100**’
Congress were not primarily partisan committees. Rather, they were biased towards providing gains-from-excbange benefits. In the 105**’ Congress, the committee system showed a partisan bias, but tbis was after major reforms at tbe beginning of tbe 104**’
Congress. Tbe change in committee agendas is hard to explain by changes in the partisanship of the Speaker because botb Wrigbt and Gingrich are considered to be very strong partisans. The change is better explained by tbe 1994 reforms in the committee system that strengthened the role of committee chairs and created a group of committee chairs that were more ideologically committed to the party agenda (Smith and Lawrence
1997).
These results challenge the very assumptions that party cartel theory makes about tbe effect of the scheduling veto on committees and the Speaker’s propensity to use the veto. First, these results imply that the speaker’s scheduling veto is ineffective at changing the incentives of the committee system. The committee system is an enormous institution that can only be changed througb structural reform. When committees are created and rules defined at the beginning of each congress, committees can be set up to efficiently supply different types of benefits. But once committees are in place, their incentives cannot be changed. Second, these results suggest that the Speaker does not try to use his scheduling authority to change committee incentives. Instead of punishing
146 committees for underprodueing partisan benefits, the Speaker faeilitates the eommittee bias. Tbe reluetanee of tbe Speaker to issue sanetions and punish members is eonsistent
with other studies that have raised doubts about the implieations of eartel theory in other
leadership deeisions (Sehiekler and Rieh 1997).
The balaneing theory of sebeduling also ehanges how we eoneeptualize the polities of the modem House. Many aeeept that the modern House is dominated by partisan polities. Robde (1991, 171) eoneluded a deeade ago tbat “our textbook pieture
must ehange not only to eneompass stronger parties in the House, but also to inelude
stronger and more influential party leaders.” He is earefiil not to assert that parties are all
eneompassing, but more reeent party theories have painted House polities as primarily partisan (Cox and MeCubbins 1993). In addition, the “eonditions” that support party
government are at eonsidered to be at their height and expeeted to eontinue into the
foreseeable future (Aldrieb and Rohde 2001).
The pieture of polities in the House presented here is fundamentally different.
Partisan divisions are not dominant; rather, mueh of the business of the House is spent on bills tbat advantage tbe ebamber and belp all members. In manyrespects, tbe Speaker
ean be seen as a leader wbo works to ensure tbat partisan polities is not dominant. He
organizes the work week to benefit all members, be ensures tbat gains-lfom-exebange are
realized, and be encourages bills with informational effieieney to be part of tbe final
agenda. In otber words, legislative polities is as mueh about aebieving common, party
neutral goals, as aebieving partisan goals. This is finding is espeeially interesting beeause botb Wrigbt and Gingrieh are eonsidered to be very partisan Speakers. This begs
147 the question, if Wright and Gingrieh are highly partisan Speakers, what role do party henetits play when the Speaker is a weak partisan?
One reason that my results support a less partisan story than other studies is my hroader foeus on all legislation. Conventional studies of the House foeus on “major”
legislation. These bills are generally seleeted heeause of their eontroversy and partisan
eontent. As a result they are unrepresentative, are biased towards finding partisan
eonfliet, and eannot be taken to refleet the nature of polities in the House as a whole. The
true nature of legislative polities ean only he found by looking at all hills, major and
minor. While noneontroversial bills are often dismissed as uninteresting, they are not unimportant. As Congressman Clem Miller (1962, 44) pointed out, minor bills “may he
the life-blood of individual eongressmen.” If this is the ease (and I believe it is),
legislative polities is as mueh about ehoosing whose noneontroversial bills are seheduled
as it is about whieh major hills make the agenda. In taking this eomprehensive view, I
find that the partisan nature of legislative polities is greatly exaggerated. Perhaps the
nature of legislative polities is not mueh different than when Mayhew (1974, 105) wrote
that “the interesting division in eongressional polities is not between Demoerats and
Republieans, but between politieians in and out of offiee.”
To he elear, I am not suggesting that parties are unimportant. The eleetoral and
legislative benefits that parties provide are important parts of the story. However, they
are not the only part of the story and are possibly not the dominant part of the story.
Highly partisan and eontroversial bills make up a small pereentage of the total legislative
agenda and when the seope is expanded to take in the total legislative pieture, the
148 Speaker’s attention to non-partisan concerns becomes clear. In short, from the evidence presented here, the Speaker is as concerned with maintaining the “cross-party conspiracy
among incumbents to keep their jobs” (Mayhew 1974, 105) as he is with “increasing the probability that [the majority] party secures a majority” (Cox and McCuhbins 1993, 128).
To accurately capture the role that the Speaker plays in legislative outcomes, theories
must recognize that the Speaker is not only an agent of the party, but an agent of the
chamber as well.
149 APPENDIX A
DATA COLLECTION
Since the data used in this dissertation is different than past data on Congress, it is useful to outline in more detailexactly how the data was eolleeted. The primary
difference between this data and past data is the volume of bills contained in the analysis.
The ability to rapidly collect data on thousands of hills eomes from the eleetronie nature
of the data available through the Library of Congress’ THOMAS website
(http://thomas.loe.gov). THOMAS began in 1995 with the start of the 104**’ Congress^^
and has continuously updated the information available for each Congress as well as the
number of Congresses available.
Two pages of THOMAS were the primary source of data for this research. Most
of the data was taken from the “Bill Summary and Status” section. Within this section of
THOMAS are two pages - the summary page and the subject page. Every hill and
resolution introduced in the House and the Senate has a separate summary webpage that
lists the title of the bill, the dates that the bill made a step in the legislative process, the
see About THOMAS at http://thomas.loc.gov/home/abt_thom.html
150 committee(s) it was referred to, the eosponsors and the dates they signed on, and related hills in the House or Senate. The information ahout a hill’s progress through the
legislative proeess is extensive. The dates are listed for when a hill is introdueed,
referred to a eommittee or subeommittee, has hearings in a eommittee or suheommittee,
is voted on, ordered to be reported, and reported. When a bill is reported, the ealendar
number is listed. When a bill is seheduled, the date it is seheduled, the method used to
eonsider the hill, amendments that are offered, and the outeome are listed. During
eonsideration of a hill, the time is listed when amendments are offered as well as any
other motions eoneeming the bill. The same level of detail is used in both the House and
the Senate.
Eaeh bill also has a suhjeet page. The subjeet page lists the Legislative Indexing
Voeabulary used to elassity eaeh hill. The number of subjeets listed ranges from 1 to
hundreds (547 is the most in the 100**’ and 105**’ Congresses). The majority of the data
needed for the analysis was taken from the summary page. The suhjeet page was used
for the seope and distributive variables.
The ehallenge in eolleeting this data is first downloading the two pages for all
14,000 hills and then turning the HTML files into datasets. Downloading the pages ean he done by using almost any free download manager found on the weh. To transform the
HTML files into datasets I used two methods. Lirst, I hand eoded all the information
about a hill’s progress. I eoded when a hill was introdueed, when it was ordered to he
reported, when it was reported, the ealendar it was sent to and the ealendar number, when
151 it was scheduled, the method used to eonsider the bill (and the H. Res. used as the speeial rule if applieable), and the outeome.
Seeond, I had a eomputer program writtenextract to data from the pages. The sponsor, cosponsor, and eommittee information from the summary pages were all eolleeted through the program. I also used a program to extract the subjeet data from the subjeet pages. The program also identified and counted the total number of keywords and the total number states listed in the keywords. Creating the variables was relatively simple from the raw data. Sponsor and eommittee variables simply required matching the raw data listing the sponsors and eommittees for eaeh bill with another dataset that contained information (ideology, tenure, party, etc.) about sponsors and committees eolleeted from other sources.
The eomputer program that I used was developed by Jim Ludwig, the resident eomputer programmer in the Department of Political Science at the Ohio State
University. The programs are available from the author. It is important to note that the programs are “brute force” programs that will not work on other types of webpages.
Further, the nature of eaeh program limits its use on other THOMAS pages. We discovered that the HTML format within THOMAS varies by Congress. As we encountered different formats, the program was made more general; but, it is limited to the pages we used.
152 APPENDIX B
ALTERNATE MODELS FOR ANALYSIS IN CHAPTER 5
In Chapter 5, the variables used to capture informational henefits are different than the variables used in Chapter 4. This may cause some concern ahout the inferences made ahout the importance of informational henefits at different stages. In this
Appendix, I present the logistic regression models from Chapter 5 using the informational variables from Chapter 4. The substantive results made in Chapter 5 are consistent with the results of these models.
153 Equation (1) (2) (3) Constant 3 449*** 3.124*** 3.336*** (1.277) (0.707) (0.759) Calendar Number - 0.002*** - 0.002*** - 0.002*** (0.001) (0.000) (0.000) Gains-from-Exchange Distributive Content 8.690*** 8.636*** 8.825*** (3.075) (3.067) (3.053) Scope (# of keywords) 0.010 0.009 0.009 (0.006) (0.006) (0.006) Multiple Referral -0.124 -0.138 -0.098 (0.567) (0.564) (0.565) Information Years in House -0.005 -0.005 -0.004 (0.018) (0.017) (0.018) Outlier -0.479 -0.559 -0.493 (1.160) (1.131) ( 1.102) Minority Party Cosponsors -0.009 -0.008 -0.009 (0.009) (0.008) (0.008) Partisan Republican Sponsored -0.026 0.287 (1.395) (0.955) Vote % for Democratic Party in last Election -0.439 -0.368 (1.140) (1.116) Republican Sponsor* Democratic Election 0.972 1.049 (3.400) (3.359) Democratic Party Unity -0.004 -0.004 (0.013) (0.006) Prestige Committee Appropriations -0.898 -0.883 -0.877 (0.837) (0.834) (0.837)
Budget -1.959 - 2.011 -2.044 (1.524) (1.514) (1.509)
Rules -1.188 - 1.200 -1.248 (0.992) (0.990) (0.987) Ways and Means 0.186 0.201 0.154 (1.152) (1.150) (1.147) (continued on next page)
Figure B.l Logistic Regression Predicting Whieh Reported Bills are Seheduled in the
100**’ Congress
154 Figure B.l (continued)
Policy Committee Banlcing -1.789*** -1.795*** -1.794*** (0.668) (0.667) (0.667) Foreign Affairs -0.330 -0.352 -0.333 (0.945) (0.941) (0.938) Energy -0.178 -0.192 -0.225 (0.496) (0.494) (0.495) Judiciary 0.679 0.672 0.660 (0.540) (0.539) (0.539) Education -1.159* -1.175* -1.180* (0.615) (0.612) (0.611) Government Operations 0.767 0.794 0.842 (0.924) (0.923) (0.912) Constituency Committee Agriculture -0.660 -0.641 -0.726 (0.586) (0.583) (0.584) Armed Services 1.117 1.141 1.068 (1.436) (1.423) (1.424) Interior 0.310 0.306 0.378 (0.598) (0.598) (0.595) Merchant Marine -0.839 -0.829 -0.854 (0.538) (0.537) (0.539) Transportation -0.357 -0.361 -0.327 (0.703) (0.704) (0.699) Science -0.168 -0.159 -0.082 (0.736) (0.735) (0.726) Veterans Affairs -0.576 -0.611 -0.701 (1.232) (1.227) (1.204) Other Committee Administration -0.666 -0.678 -0.648 (0.930) (0.928) (0.916) Post Office -0.157 -0.170 -0.189 (0.716) (0.715) (0.716) Intelligence -2.814* -2.797* -2.807* (1.517) (1.514) (1.499)
Number of Cases 621 621 638 Log likelihood -174.256 -174.303 -175.550 Pseudo R2 0.171 0.171 0.173
Note: Standard errors in parentheses; *p<0.10; **p<0.05; ***p<0.01
155 Equation (1) (2) (3) Constant 6.180*** 4.341*** 4.628*** (1.596) (1.072) (0.611) Calendar Number -0.007*** -0.007*** -0.008*** (0.001) (0.001) (0.001) Gains-from-Exchange Distributive Content -1.376 -1.780 -0.993 (5.871) (5.713) (5.837) Scope (# of keywords) 0.001 0.000 0.000 (0.001) (0.001) (0.001) Multiple Referral 0.399 0.391 0.282 (0.702) (0.694) (0.686) Information Years in House 0.014 0.014 0.018 (0.017) (0.018) (0.017) Outlier 0.318 0.292 0.323 (0.739) (0.724) (0.692) Minority Party Cosponsors 0.013 0.011 0.012 (0.009) (0.009) (0.009) Partisan
Republican Sponsored -1.543 - 0.000 (1.233) (0.788) Vote % for Democratic Party in last Election -3.125 -2.812 (2.601) (2.582) Republican Sponsor* Democratic Election 2.004 1.481 (3.109) (3.101)
Democratic Party Unity - 0.021 -0.013*' Prestige Committee Appropriations 0.190 0.138 0.172 (1.308) (1.302) (1.303) Budget
Rules 0.118 0.253 0.236 (0.584) (0.572) (0.573) Ways and Means -0.959 -0.876 -0.835 (0.596) (0.585) (0.587)
(continued on next page)
Figure B.2: Logistic Regression Predicting Whieh Reported Bills are Seheduled in the
105**’ Congress
156 Figure B.2 (continued)
Policy Committee
Banlcing -1.046 -1.390* - 1.210 (0.811) (0.785) (0.793) International Relations -0.390 -0.075 -0.277 (0.866) (0.872) (0.861) Energy -1.126** -0.964* -1.023** (0.540) (0.527) (0.519) Judiciary -0.481 -0.462 -0.424 (0.485) (0.475) (0.475) Education -1.440 -1.350** -1.368** (0.621) (0.620) (0.611) Government Reform -0.007 -0.150 0.000 (0.762) (0.773) (0.764) Constituency Committee Agriculture 0.479 0.530 0.539 (1.286) (1.268) (1.263) National Security -2.096 -2.227* -1.934 (1.338) (1.350) (1.328) Resources -1.390*** -1.295*** -1.288*** (0.462) (0.453) (0.441) Transportation -0.994* -0.952 -0.883 (0.590) (0.582) (0.580) Science -1.909** -2.270*** -2.023** (0.874) (0.849) (0.861) Small Business
Veterans Affairs -0.099 -0.077 -0.056 (1.239) (1.212) (1.235) Other Committee Oversight -2.923*** -2.878*** -2.883** (1.013) (1.000) (1.004) Intelligence -1.624 -1.529 -1.571 (1.504) (1.508) (1.481)
Number of Cases 722 722 722 Log likelihood -193.185 -194.857 -194.427 Pseudo R2 0.273 0.267 0.268
Note: Standard errors in parentheses; *p<0.10;**p<0.05; ***p<0.01
157 Equation (1) (2) (3) Constant -4.717*** -3.400*** -4.776*** (0.414) (0.193) (0.188) Date Introduced 0.004*** 0.004*** 0.003*** (0.000) (0.000) (0.000) Gains-from-Exchange Distributive Content 0.834 0.780 0.896 (0.742) (0.741) (0.599) Scope (# of keywords) 0.019*** 0.019*** 0.007*** (0.003) (0.003) (0.001) Multiple Referral 0.339 0.324 0.042 (0.211) (0.209) (0.175) Information Years in House 0.042*** 0.045*** 0.040*** (0.005) (0.005) (0.004) Outlier -0.307 -0.413 0.021 (0.353) (0.351) (0.267) Minority Party Cosponsors 0.020*** 0.020*** 0.017*** (0.002) (0.002) (0.002) Partisan Republican Sponsored 0.303 -0.677*** (0.345) (0.224) Vote % for Democratic Party in last Eleetion -0.256 -0.366 (0.388) (0.385) Republican Sponsor* Democratic Election 1.629 1.558 (1.079) (1.072) Democratic Party Unity 0.014*** 0.011*** (0.004) (0.001) Prestige Committee Appropriations -0.462 -0.525 -0.144 (0.412) (0.409) (0.390) Budget 1.591 1.688 1.826 (1.144) (1.136) (1.136) Rules -1.864*** -1.873*** -1.426*** (0.428) (0.428) (0.393) Ways and Means -2.394*** -2.402*** -2.168*** (0.319) (0.319) (0.305) (continued on next page)
Figure B.3: Logistic Regression Predicting Whieh Reported Bills are Seheduled in the
100**’ Congress 158 Figure B.3 (continued)
Policy Committee Banlcing -0.013 0.029 0.280 (0.233) (0.231) (0.215) Foreign Affairs 0.664*** 0.711*** 1.022*** (0.168) (0.167) (0.145) Energy -0.899*** -0.857*** -0.202 (0.237) (0.235) (0.187) Judiciary -1.355*** -1.343*** -0.742*** (0.246) (0.245) (0.199) Education -0.635** -0.605** -0.270 (0.276) (0.275) (0.248) Government Operations -0.752* -0.806* -0.444 (0.451) (0.451) (0.407) Constituency Committee Agriculture -0.240 -0.261 0.198 (0.237) (0.235) (0.181) Armed Services -0.453 -0.490* -0.154 (0.288) (0.287) (0.265) Interior -0.704** -0.674** 0.133 (0.294) (0.293) (0.225) Merchant Marine -0.300 -0.281 -0.047 (0.293) (0.293) (0.273) Transportation -0.434 -0.417 0.077 (0.280) (0.279) (0.239) Science -0.525 -0.521 -0.065 (0.450) (0.448) (0.389) Small Business -0.677 -0.613 -0.050 (0.746) (0.746) (0.620) Veterans Affairs -0.735* -0.865** -0.469 (0.407) (0.406) (0.396) Other Committee Administration 0.569*** 0.587*** 0.959*** (0.221) (0.220) (0.197) Post Office 0.957 *** 0.987*** 1.763*** (0.151) (0.149) (0.116) Intelligence 0.402 0.422 0.159 (0.589) (0.589) (0.603)
Number of Cases 7578 7578 9762 Log likelihood -1525.574 -1532.385 -2100.301 Pseudo R2 0.204 0.200 0.191
Note: Standard errors in parentheses; *p<0.10; **p<0.05; ***p<0.01
159 Equation (1) (2) (3) Constant -3.590*** -3.798*** -2.751*** (0.276) (0.258) (0.154) Date Introduced 0.003*** 0.003*** 0.003*** (0.000) (0.000) (0.000) Gains-from-Exchange Distributive Content 11.839*** 11.855*** 11.495*** (1.661) (1.662) (1.647) Scope (# of keywords) 0.000 0.000 0.000 (0.000) (0.000) (0.000) Multiple Referral -0.735**** -0.730*** -0.818*** (0.255) (0.255) (0.254) Information Years in House 0.016*** 0.015*** 0.019*** (0.005) (0.005) (0.005) Outlier -0.273 -0.293 -0.737*** (0.214) (0.215) (0.179) Minority Party Cosponsors 0.010*** 0.010*** 0.009*** (0.002) (0.002) (0.002) Partisan Republican Sponsored 0.513** 0.694*** (0.203) (0.185) Vote % for Democratic Party in last Eleetion 0.822 0.867 (0.621) (0.623) Republican Sponsor* Democratic Election -2.828*** -2.907*** (0.813) (0.813) Democratic Party Unity -0.002** -0.004*** (0.001) (0.000) Prestige Committee Appropriations 1.906*** 1.937*** 2.269*** (0.423) (0.421) (0.394) Budget -0.307 -0.314 -0.224 (0.668) (0.669) (0.662) Rules -0.850 -0.854 -0.815 (0.608) (0.608) (0.605) Ways and Means -1.613*** -1.603*** -1.577*** (0.241) (0.241) (0.240) (continued on next page)
Figure B.4: Logistic Regression Predicting Whieh Unreported Bills are Seheduled in the
105**’ Congress
160 Figure B.4 (continued)
Policy Committee Banlcing 0.160 0.160 0.192 (0.247) (0.246) (0.245) International Relations 1.516*** 1.559*** 1.486*** (0.147) (0.145) (0.144) Energy -1.039*** -1.015*** -1.010*** (0.282) (0.281) (0.281) Judiciary 0.232 0.243 0.292** (0.150) (0.149) (0.147) Education -0.127 -0.130 -0.113 (0.237) (0.237) (0.236) Government Reform 1.239*** 1.237*** 1.273*** (0.168) (0.168) (0.164) Constituency Committee Agriculture -0.724* -0.724* -0.697 (0.436) (0.436) (0.433) National Security -0.626* -0.609* -0.628* (0.349) (0.349) (0.351) Resources -0.091 -0.088 -0.059 (0.189) (0.189) (0.188) Transportation -0.459 -0.456* -0.422 (0.268) (0.268) (0.265) Science 0.709 0.696 0.737 (0.450) (0.450) (0.450) Small Business 0.024 0.027 -0.112 (0.814) (0.814) (0.842) Veterans Affairs -2.251** -2.176** -2.416** (1.014) (1.013) (1.018) Other Committee Oversight 0.770*** 0.772*** 0.829*** (0.225) (0.225) (0.223) Intelligence -0.493 -0.524 -0.416 (1.078) (1.080) (1.069)
Number of Cases 8002 8002 8002 Log likelihood -1826.412 -1828.504 -1841.548 Pseudo R2 0.150 0.149 0.143
Note: Standard errors in parentheses; *p<0.10; **p<0.05; ***p<0.01
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