Parties and Stability in Legislative Voting Coalitions
Gerald C. Wright
Jennifer Hayes Clark
Indiana University-Bloomington
Paper Prepared for the 2005 State Politics and Policy Conference, East Lansing,
Michigan, May 13-14.
1
Introduction
One of the fundamental questions in democratic society concerns the extent to
which the will of the people can be realized through its democratic institutions and the
solidity of those decisions. One of the central tenets of democratic theory calls for
responsiveness to the citizenry. However, the extent to which democratic institutions
should strongly embody the principles of majority rule has faced considerable
disagreement among scholars of democratic theory.
According to Dahl,
"... virtually everyone assumes that democracy requires majority rule in the weak
sense that support by a majority ought to be necessary to passing a law. But
ordinarily supporters of majority rule mean it in a much stronger sense. In this
stronger sense, majority rule means that majority support ought to be not only
necessary but also sufficient for enacting laws." Robert Dahl, Democracy and its
Critics.
Social choice theories of politics (Arrow 1959; McKelvey and Schofield 1987)
provide a rather bleak view concerning the translation of individuals’ views, interests, or
preferences into a coherent collective choice. The key predictions and implications of
this work, particularly regarding the potential for instability of political choice by
majority rule, have been quite influential in the development of theory of legislative
voting and collective choice. This impact comes not from the accuracy in its predictions
but rather the apparent inconsistencies that emerged between the theoretical and
empirical studies of legislative voting. The real puzzle the emerged comes from the fact
that there is too much equilibrium in legislatures given the theoretical predictions of
McKelvey-Schofield Chaos results, for example.
The susceptibility of democratic decision-making to instability (McKelvey, 1976;
Schofield, 1978; McKelvey, 1979; McKelvey and Schofield, 1987) and manipulability
2
(Riker 1982) leads scholars to question our standard assumptions of democratic decisionmaking. To the extent that outcomes in real-world politics are highly sensitive to factors
like agenda-setting and methods of vote aggregation, determining the consequences, if
any, of a variety of constraints imposed on individual behavior and, thus, on collective
choices becomes a fundamental question of legislative decision-making and
representation.
Since the 1980s, research has focused primarily on determining what factors
constrain decision-makers engaging in collective choice. While the U.S. House has been
a fertile ground for building and testing theory, there are limits to inferences drawn on a
single case. In this paper, we examine the structure and stability of legislative voting
coalitions in a diverse set of social and institutional settings—state legislative chambers.
The first part of this research simply sets out to determine how pervasive these empirical
findings of legislative policy stability are. The next task will be to extend our discussion
beyond simply reporting the levels of stability to incorporate a discussion of the causes
and correlates of consistency in legislative voting structures and individual behavior over
time. We seek to identify the particular features influencing legislative decision-making
and to understand the mechanisms that give rise to stability and change in voting
coalitions. Finally, we integrate macro-level and micro-level analyses to achieve an
overall better account of the dynamic of legislative voting in contemporary state
legislatures.
Literature Review
A substantial amount of research has developed that seeks to examine the
apparent disparity between theoretical predictions and empirical observation. These
3
works have been particularly concerned with identifying the mechanisms that produce
stability within legislatures (Tullock 1981; Hoenack 1983).
One explanation arising from this literature highlights the vital role of institutions
in determining both the structure and the degree of stability in legislative decisionmaking (Shepsle 1979; Shepsle and Weingast 1981, 1986).1 In particular, Shepsle’s
(1979) research introduces us to the concept of the structure-induced equilibrium.
Subsequent research (particularly that of Shepsle and Weingast 1986 and Weingast and
Marshall 1988) has sought to understand precisely how legislative institutions influence
(or constrain) legislative voting, and thus, promote legislative stability.
The first theoretical proposition offered by scholars contends that institutions can
promote voting stability by forcing issues into a unidimensional policy space (Riker
1982) thereby constraining preference heterogeneity among actors. Scholars (Shepsle
1986; Shepsle and Weingast 1981) have identified a number of institutional features that
promote stability by constraining choice to a unidimensional space. This, along with
work by Black (1959), provides a necessary linkage between the structure of the policy
space (i.e., dimensionality) and the structure of collective choice over time.
Historical roll call analyses of the U.S. Congress have shown not only remarkable
levels of stability among members of Congress but also a high degree of aggregate-level
stability in patterns of legislative voting coalitions in the post-Civil War period. Poole
and Rosenthal (1997) find that most congressional voting over time has taken place in a
low dimensional space with a couple of periods of higher dimensionality interspersed.
1
Riker (1982) offers a particularly strong critique of institutional explanations of stability in which he
argues that the chaos problem is not simply restricted to policy voting but can also manifest itself in the
selection of institutions as well (since institutions are after all endogenous). Therefore, the fact that
institutions promote stability does not really “solve” the problem but only begs the question, “why so much
stability?”.
4
Because the periods in periods of higher dimensionality correspond to periods in which
the two-party system was undergoing great transition, it appears that political parties
offer a critical role in promoting stabile voting alignments.
This leads us to the second theoretical proposition which emphasizes the
importance of political parties in promoting stability within legislatures. While scholars
have general simply taken the low-dimensional structure of legislative voting as a given,
comparative legislative research has provided a number of explanations of the
mechanisms by which political parties structure legislative voting, including party
leadership within the legislature (Jenkins 2000) and the electoral connection (Wright and
Schaffner 2002). To gain analytical leverage on the relationship between political
parties, dimensionality, and legislative voting stability, comparative legislative research
will allow us to isolate the leading factors that influence the dimensionality of legislative
voting. If indeed the unidimensional voting structure is primarily a result of strong party
leadership controlling the agenda to achieve partisan policy goals then we should expect
higher levels of dimensionality in chambers with much weaker party leadership.
The conditional party government theory (Aldrich 1995; Aldrich and Rohde 2001;
Rohde 1991), for example, suggests that party influences legislative behavior as a result
of collective electoral goals and party incentives for achieving those goals. Importantly
for our purposes, the conditional partisan theories of legislative behavior emphasize that
party influence is variable. The degree to which individual electoral considerations are
filtered through partisanship is conditional on the strength of legislative parties.
Furthermore, party strength is a function of the preferences of individual members.
According to the conditional party government thesis, the costs and benefits of delegating
5
authority to party leadership is influenced by the degree of homogeneity of preferences
within the parties and the degree of heterogeneity between the two parties in the
legislature. To the extent that 1) the party label has different importance across the states
and 2) preferences within and between the political parties vary significantly across
states, we can explore this linkage and its ultimate effect on legislative stability through
our comparative analysis.
Roll call voting studies examining individual-level patterns have found
remarkable stability. Scholars have identified a number of sources influencing individual
members’ patterns of voting stability. The first explanation stresses the significant
influence members’ ideology has on voting decisions. Poole and Rosenthal’s (1991;
1997) extensive examination of the voting in the U.S. Congress found strong patterns of
individual member voting stability, which they argue results from constancy in members
ideology. Other research has examined the electoral sources of change and stability in
legislative behavior. In particular, do changes in members’ electoral circumstances result
in changes in legislative voting? Determining the sources of individual member stability
may help to further clarify the extent to which more variable factors outside the realm of
usual legislative institutional explanations impact the overall aggregate patterns exhibited
in legislative voting coalitions over time.
Overall, the findings of this research have strengthened the belief of the
unchanging legislator. The general voting patterns for members of the U.S. House over
the last forty years exhibited remarkable stability (Poole and Romer 1993) even among
those members aspiring for higher office (Hibbing 1986; Grofman, Griffin, and Berry
1995). Similar patterns of stability have also been found for comparisons between
6
retiring and non-retiring members (Lott 1987) suggesting the central role of member
ideology in roll call voting. Finally, studies examining the effects of redistricting on
voting behavior have produced mixed results regarding the impact of redistricting on
individual members’ voting behavior. While Glazer and Robbins (1983) found
differences in pre- and post- reapportionment legislative voting behavior, other research
has found little impact of redistricting on individual-level legislative voting behavior
(Poole and Romer 1993). Another way in which the redistricting process may provide
considerable change in the structure and stability of voting patterns is through
membership turnover and the extent to which these membership changes alter the
partisan composition within the legislature. We now turn to the primary task of this
research—examining the role that these various factors play in the overall structure and
stability of legislative voting.
Data and Measures
Our data collection for the overall project has four phases. One is a full crosssection collection of the roll calls cast in the 99 state legislatures and both houses of
Congress for the 1999-2000 sessions. That collection is complete and 99 percent is
available on our website. A second phase is a parallel post-2000 redistricting collection
covering the legislative sessions for 2003-2004. The third collection is our “modern”
time series for about half of the states with yearly collections of all competitive roll calls
in the chambers for varying periods of time, ranging from six to eighteen years. The final
collection is an experimental effort to collect full historical series for individual states
which will permit testing of a host of hypotheses about the development of legislatures in
the states as political systems.
7
This paper is our first look at the second phase with the specific purpose of
assessing the longitudinal stability of the character of legislative roll call coalitions over
time as well as some examination of the stability of relative ideological and partisan
voting of individual legislators in different contexts.
Here we examine the consistency of legislative roll call voting at the macro and
micro levels in nineteen chambers. These include the upper and lower houses for
Alabama, Georgia, Indiana, Maryland, Michigan, North Carolina, New Jersey,
Oklahoma, Utah and the unicameral Nebraska legislature. These chambers provide us
with a nice regional mix as well as variation on the chief cross-sectional features of
dimensionality and strength and balance of parties which we uncovered in the initial
series (Wright and Osborn 2002; Wright and Winburn 2003). This is a preliminary
report, and the full assessment of stability and change in legislative voting coalitions and
individual-level legislative behavior will be part of the final assessment.
We look at all competitive roll calls which includes all those in which the losing
side included at least five percent of those voting on the roll call. Across chambers, and
even over time, we see quite a variation in the numbers of competitive roll calls in the
states. The first column of figures in Table 1 shows the numbers of roll calls for our two
sessions for each of the 17 chambers. Even among this small sample of chambers we see
that there is considerable variation in the roll call load, from just 111 competitive roll
calls in the ’03-’04 session of the Indiana Senate to almost 1,600 votes in the ’99-’00
Michigan Senate.
We will be looking at several features of voting coalitions. Some of these are
simple measures such as the numbers and the levels of competitiveness of the roll calls
8
over time for each chamber. We will also be examining the structure of roll call voting
using NOMINATE scores to assess the dimensionality and classification success of
examining voting in one and two dimensions. We will then turn to an examination of
individual behavior looking at the relative stability of roll call voting for legislators over
time.
Analysis
A point we often return to is the fact that our theories and our pictures of
legislatures have been dominated by the preponderance of legislative research in the US
on the US Congress. These studies report a good deal of stability from one legislative
session to the next, both in things like dimensionality and party polarization and in the
ideological or partisan character of individual roll call scores. The upshot is that findings
in a cross sectional analysis of one congressional session are quite likely to be largely
replicated in other sessions in that general temporal era. It would be a huge surprise, for
example, if the strong unidimensional structure we find in Congress in recent years were
to suddenly change in the next legislative session. Rather, we assume that continuity of
the institutional rules and membership guarantee that the broad outlines of legislative
decision making will remain the same and any change, such as the number of bills
passing or failing, will generally occur within these familiar patterns.
Currently we do not know if this kind of stability is characteristic of other
legislative settings or whether Congress is exceptional in the remarkable temporal
consistency of its roll call structures. There are arguments that can be made either way.
One the one hand, state legislatures are reasonably mature institutions existing within
ongoing electoral systems and we have no reason to suspect that they behave wildly
9
differently from one legislative session to the next. In this general view we assume that
any complex institution develops patterns for dealing with its business—in this case,
collective decisions on whether to pass legislation—and that these patterns will generally
persist over time.
An opposite view is easily imagined as well. The patterns of stability seen in
Congress are a product of high levels of stability among a large membership (100 and
435 for the Senate and House) meeting in a full time legislature. The numbers and the
frequency or iterations of interactions are likely to contribute routinized ways of dealing
with decisions and these can be expected to carry over from one legislative session to the
next. In addition, congressional roll calls are carried out with a relatively clean
unidimensional structure which, as discussed above, provides a constraint that can yield
stable outcomes.
The states, or at least many of them, are different in ways that suggest less
stability. First they are smaller: all of the state senates are smaller than the US Senate and
all of the state lower houses are smaller than the US House. In most states, the upper and
lower houses are quite substantially smaller than their national counterpart. On top of
this, turnover in the states is much higher than in Congress (Squire 1988; Niemi). A
general lack of continuity facilitated by smaller numbers of legislators is reinforced by
the higher turnover rates. Thus, we might expect that as relatively new sets of individuals
come together for shorter periods of time that there will be more variation in the character
of roll call decisions from one session to the next in the states.
A third reason to expect differences between the states and Congress is that we
know from our cross-sectional analysis of the 1999-2000 sessions that some of the states
10
show higher dimensionality and lower levels of successful predictions from the
NOMINATE analyses compared to the US House and Senate. While most of the
chambers showed patterns of partisanship and dimensionality roughly equivalent to those
of Congress, a significant number have quite different patterns. Thus, the relatively
unstructured voting patterns we found in Nebraska, Rhode Island, Idaho and West
Virginia suggest greater room for individual volatility in voting patterns than the tightly
structured partisan context of Congress and the majority of state legislative chambers.
In this paper, we assess change and stability at two levels. The first is a macrolevel analysis in which we will examine the selected parameters of the overall structure of
roll call voting and see how much they change across sessions, and whether the patterns
of change are uniform. We would expect that the larger, more professionalized
legislatures will witness greater stability.
It may well be the case that those chambers that show less structure at one time
point are not necessarily more likely to undergo changes in partisanship or
dimensionality, but rather they will be stable in their relative lack of dimensional
structure. We might well find that instability in coalition formation from one roll call to
the next is simply the equilibrium state or norm for some chambers.
This still leaves open for investigation the question of when the structure of roll
call voting will change, and what factors will induce such change. We will address this
below after addressing the more descriptive question on the prevalence of temporal
stability across a number of diverse legislative settings.
The second type of analysis includes assessments of change and stability at the
individual-level. Here we do not feel comfortable with assuming that state legislators
11
have a coalition identity (set of ideal points) that they carry with them for their terms in
public life. Many are amateurs and with high levels of turnover, relatively short sessions,
and perhaps being less constrained by constituency, we expect that state legislative roll
call voting, at least in the less professionalized chambers, will be less stable over time.
Macro Comparisons
We look at changes in several features of the overall patterns of roll call voting in
nineteen legislative chambers. These will include the “load” or simply the numbers of
competitive roll calls that members vote on as well as the competitiveness of the roll
calls. One can imagine that life is quite different in a chamber in which the vast majority
of legislation passes with near unanimous majorities than one in which high percentages
of the bills are close votes, perhaps even with some doubt about their passage. We will
then look at classification success from fitting NOMINATE dimensions to the patterns of
roll call voting which tells us how well the overall patterns of voting can be accounted for
by a reduced set of dimensions. Third, we examine the complexity of the roll call issue
space as indicated through the inclusion of a second dimension to the roll call space, and,
finally, the partisan structure of the space reflecting how much party affiliation dominates
voting on competitive roll calls. In future analyses, encompassing a larger sample of
chambers we will look at changes in roll rates, or the frequency and conditions under
which the minority party wins on party votes.
Load and Competitiveness. One factor that surely affects the development of
patterns of legislative decision making is the shear load of the decisions that have to be
made. Some legislatures limit the numbers of bill that members can introduce, while
others grant their committees greater gate keeping powers, which in effect limits the
12
number of bills. We can see from Table 1 that there is a huge variation among chambers
in the numbers of competitive votes they deal with ranging in our sample from 111 in the
2000-2001 Indiana Senate to over 1,400 bills in the Oklahoma Senate in their 2003-2004
session. When we look at the changes in the bill loads, there is not a great deal of
continuity: the correlation between the two sessions is .61. For most of the chambers the
numbers of bills voted on remains stable but the Michigan House saw a substantial drop
(1,129 to 739) while both houses in Oklahoma skyrocketed, doubling and almost tripling
the numbers of competitive bills considered.
[Table 1 about here]
Simple counts of roll calls, however, while giving a glimmer of one aspect of
decision making on the floor, can hide as much as they reveal. For example, in Illinois
(not included in this analysis) the chair allowed a single vote to be recorded for over 200
separate bills. That is, the formal record showed separate roll calls, but the breakdown on
each of 237 consecutive bills was the same 32 to 16 with two voting present.
Probably more telling are the levels of competitiveness of the roll call votes.
Where policy decisions are hotly contested within the legislature we might expect a high
percentage of bills passing by small margins. In contrast, if the committees and
leadership are able to exercise substantial agenda control, they should lose few votes and
perhaps pass many with huge margins. Table 2 shows that the ranges of lopsided votes,
which we define as bills with majorities of greater than 70 percent were the rule in a
number of chambers, constituting clear majorities in most of the chambers. We also look
at how many of the competitive votes were close, defined by the majority getting 60% of
less of the vote. The character of the chambers varies a good deal on this factor. Notice
13
that there were virtually no close votes in the North Carolina Senate in the earlier session
(1.5%) but this increased to over a quarter of the votes in the later session. The biggest
changes in bill competitiveness occurred in the Michigan House and the North Carolina
Senate. The former became less competitive with a doubling of the lopsided votes while
the number of competitive voters fell from a half to a third. The NC Senate, in contrast,
became more competitive, but with almost 60 percent of the votes being lopsided in the
2003-2004 session, it moved from the chamber with the largest percentage of lopsided
votes to around the middle of the distribution. We also find that the Utah Senate had
markedly fewer competitive votes in the 2003-2004 session while the trend was in the
opposite direction for the Utah House, but the change was not that considerable. For
other chambers, like the Indiana House and both chambers in Alabama, the patterns of
competitiveness remained virtually unchanged from one session to the next.
[Table 2 about here]
We have seen fair levels of stability for most chambers with a few that seem to
have had quite different sessions in terms of load or competitiveness. Our next step is to
examine the primary indicators of the overall structure of roll call voting, namely the
dimensionality. Table 3 shows the percentage of roll calls correctly predicted on the
basis of a one-dimensional NOMINATE solution, and then accompanying these, the
increment in this which comes from a two-dimensional solution.
[Table 3 about here]
A single dimension does a more than adequate job of accounting for roll call
voting in most of the legislatures. The average percentage of correctly predicted roll calls
for our 19 chambers is 88% for both sessions. Table 3 shows the figures for each
14
chamber. The Nebraska unicameral, with its nonpartisanship shows the lowest success in
correct predictions, conforming with prior findings (Wright and Schaffner 2002). We
also see that adding a second dimension adds very little improvement to the predictions
using just the first dimension with only a less than two percent improvement for most of
the chambers. We see that the Nebraska legislature shows the largest percentage
increase, albeit by a small margin.
The correct predictions criterion can be misleading since the prediction success
can be quite high with just naive guessing of the largest marginals. However, the
lopsidedness of roll call votes does very little to account for chamber differences in the
success of NOMINATE predictions. The correlations between the percent correctly
predicted on the basis of one dimension and the percentages of lopsided votes are not
significant; in fact they are weakly negative for both sessions.
Nevertheless, the preferred method is to look at how well the one or two
dimensional solutions improve upon what would be achieved with naïve guessing. The
results are provided in table 4. The improvements over raw guessing are substantial in
most cases. The APRE1 (one dimensional proportion reduction in error) measures are
largest for the chambers with more competitive roll calls (r=.60 and .63 for the 19992000 and 2003-2004 sessions). The Michigan House during the 1999-2000 session has
the largest APRE1 measure while the lowest is Nebraska where the NOMINATE scores
for either one or two dimensional solutions do not provide an impressive account of the
roll call voting structure.
[Table 4 about here]
15
Of particular interest for our analysis here is the stability of these dimensional
structures. We want to know if there is significant fluctuation from one session to the
next in the fit for the NOMINATE analyses. What we find is surprisingly strong levels of
stability. Simply examining the overall proportion of votes correctly classified with a
one-dimensional NOMINATE analysis illustrates this great uniformity across time,
(r=.90). Similarly, the APRE1 solutions show similar relative performance across our
two sessions, r=.80. The Michigan House again shows the clearest example of change. It
had the highest APRE1 measure in 1999-2000, with an increment for the second
dimension of just 1.5%. The improvement over guessing for the 2003-2004 session was
less dramatic, but still among the highest of our sample of chambers, but with that change
came a larger increment in the APRE with the second dimension (3%). We suspect the
explanation for the differences shown by the Michigan House lies in the increased
partisanship that characterizes Michigan, and perhaps the effects of term limits which
greatly increased the level of turnover there.
Micro Analysis
We now turn to an assessment of individual-level voting stability focusing in
particular on the relationship of individual patterns of voting to the overall aggregate
characteristics of legislative voting. The first factor we examine is the overall continuity
in legislative membership, which is measured by comparing the 1999-2000 session data
to the 2003-2004 session data. Prior research has found considerably greater levels of
membership turnover in state legislatures compared to the U.S. Congress. In addition,
the data we compare represents pre- and post- reapportionment sessions, which could
either heighten or significantly lessen turnover depending on the nature of the
16
redistricting process in a particular state. Because of the considerable variation across
legislatures, these data provide an excellent opportunity to examine the effects of
membership turnover on patterns of voting over time.
Table 5 presents measures of legislator continuity within each chamber for the
two sessions being examined. Membership continuity varies considerably across
chambers, due to both institutional (e.g., term limits) and electoral (e.g., district-level
party competition) forces. The extent to which membership turnover influences the
overall aggregate structure of legislative voting is a factor we will explore now in our
examination of individual influences shaping the structure and stability of voting in
legislatures.
[Table 5 about here]
For the majority of the chambers, the patterns of legislative voting remained
relatively stable from the 1999-2000 session to the 2003-2004 session. Among the
chambers experiencing change, the Georgia House is particularly noteworthy because of
the widespread changes that came from their redistricting process. The redistricting
process in Georgia was unique in two regards. First, there was an extremely high level of
contentiousness between the two parties as the Democratic majority was barely able to
pass their redistricting plan. Second, with this plan, Georgia reinstituted multi-member
districts in several areas, particularly in the Southern parts of Georgia. Despite these
concerns, Georgia experienced relatively low levels of membership continuity over the
course of our analysis time frame (see Table 5). Graphs 1 & 2 show the overall structure
of voting in the Georgia House as is given by their NOMINATE scores. The structure of
voting in the later House appears to be much more partisan, with considerable party
17
polarization emerging as the chamber experienced a shift in partisan control to the
Republican party establishing unified government in the state of Georgia. Pearson
correlations of individual member’s ideological stability demonstrate very high levels of
stability among those members serving for both periods (.92); however, member
continuity was considerably low in the Georgia House.
[Graphs 1 & 2 about here]
Another legislature which surprisingly showed remarkable levels of stability, at
both the individual and aggregate level was the Nebraska Unicameral legislature.
Despite the unstructured nature of voting, Nebraska legislators show very high levels of
stability rivaling that of the other partisan legislative chambers, including the U.S.
Congress. Graphs 3 & 4 illustrate these patterns of conflict over time. While there are no
clear patterns of ideological voting, the stability exhibited in individual-level voting
behavior suggests that there is some mechanism inducing legislative stability. This will
be something we will return to in later analyses.
[Graphs 3 & 4 about here]
While prior research has argued that parties are central to establishing individualand aggregate-level stability, our findings do not offer such overwhelming support for
this relationship between parties and stability. For example the relationship between the
first dimension nominate scores for the two sessions examined is generally high (mean
correlation is .91); however, variations in this continuity appear to be unrelated to
relationship between party and roll calls (see, e.g., Table 7).
[Table 7 about here]
18
Conclusions
In general, we find remarkable levels of stability in both individual- and
aggregate-levels of legislative voting. While the overall findings seem consistent with
the congressional literature, this analysis raises a number of concerns regarding the
predominant views of what causes stability. In particular, we do not find an
overwhelming relationship between the strength of parties and legislative stability. This
preliminary analysis raises a number of questions which will be subjected to further
analyses in the future. In particular, one puzzle to explore in the future involves the
levels and patterns of individual level legislator continuity in legislatures with weaker
dimensional structures. In addition, future analyses will seek to further clarify the
sources of legislative stability with a more specific focus on internal institutional
arrangements and, in particular, their effects on the complex relationship between
individual- and aggregate-level voting.
19
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21
Table 1. Numbers of
Competitive Roll Call Votes,
1999-2000 & 2003-2004 in 19
Chambers
Chamber
AL-h
AL-s
GA-h
GA-s
IN-h
IN-s
MD-h
MD-s
MI-h
MI-s
NC-h
NC-s
NE-b
NJ-h
NJ-s
OK-h
OK-s
UT-h
UT-s
total Ns
’99-’00 ’03-04
355
523
181
263
417
501
318
512
474
363
239
111
425
378
359
462
1129
739
510
415
548
419
204
217
221
188
208
291
166
126
776
1516
481
1408
412
476
314
310
22
Table 2. Changes in Roll Call Competitiveness 1999-2000/2003-2004
Chamber
Majority > 70%
Majority <61%
1999-2000
2003-2004
1999-2000 2003-2004
AL-h
AL-s
GA-h
GA-s
IN-h
IN-s
MD-h
MD-s
MI-h
MI-s
NC-h
NC-s
NE-b
NJ-h
NJ-s
OK-h
OK-s
UT-h
UT-s
57.5
69.6
54.7
38.7
45.8
54.0
72.2
60.4
25.8
33.7
57.5
80.9
43.4
56.7
65.7
70.4
67.8
66.5
56.4
56.8
71.9
45.9
34.2
46.0
64.9
50.0
57.6
49.8
49.2
64.9
59.9
54.8
51.9
69.0
58.0
58.1
58.4
72.9
19.7
17.1
26.1
28.6
39.5
16.3
11.5
20.9
53.1
39.0
23.9
1.5
33.9
24.0
16.3
15.7
12.3
15.5
20.4
26.8
16.3
27.3
47.9
38.8
16.2
16.4
15.6
30.4
29.2
16.9
27.6
24.5
36.4
20.6
25.6
21.0
22.9
10.6
23
Table 3. Correct Roll Call Predictions from One and Two
Dimensional NOMINATE Analyses.
One-dimension Increment with second Dim.
Chamber ’99-00 ’03-04
’99-00
’03-04
AL-h
.853
.844
1.8
2
AL-s
.866
.884
2.3
1.8
GA-h
.855
.876
1.2
.8
GA-s
.908
.897
.8
1.4
IN-h
.905
.895
.6
.7
IN-s
.871
.863
1.1
1.9
MD-h
.879
.897
.8
.6
MD-s
.874
.886
2.2
1.5
MI-h
.93
.895
.6
.9
MI-s
.913
.924
1.5
.7
NC-h
.86
.857
1
1.7
NC-s
.911
.911
1.6
.5
NE-b
.782
.81
2.4
2.4
NJ-h
.932
.949
-1.9
.8
NJ-s
.902
.9
1.5
1.7
OK-h
.875
.895
.9
.7
OK-s
.855
.859
1.7
1.4
UT-h
.842
.835
1.5
1
UT-s
.85
.865
1.8
2.1
24
Table 4. Proportion-Reduction in Error Measures for
One and Two Dimension NOMINATE Solutions.
APRE1
APRE2-APRE1
Chamber
’99-00 ’03-04
’99-00
’03-04
AL-h
.428
.425
.071
.075
AL-s
.438
.444
.095
.086
GA-h
.475
.583
.043
.026
GA-s
.695
.695
.028
.042
IN-h
.684
.658
.019
.022
IN-s
.492
.406
.042
.082
MD-h
.414
.61
.038
.023
MD-s
.499
.567
.086
.057
MI-h
.807
.627
.015
.03
MI-s
.733
.724
.045
.025
NC-h
.463
.383
.039
.074
NC-s
.513
.642
.09
.023
NE-b
.288
.302
.078
.09
NJ-h
.727
.817
-.077
.028
NJ-s
.566
.581
.067
.071
OK-h
.431
.583
.038
.026
OK-s
.374
.458
.07
.054
UT-h
.335
.37
.061
.039
UT-s
.453
.409
.067
.089
25
Table 5. Membership Continuity
99-00 & 03-04
total
Chamber
% membshp
both yrs
continuity
AL-h
.55
AL-s
.72
GA-h
.38
GA-s
.44
IN-h
.62
IN-s
.75
MD-h
.50
MD-s
.54
MI-h
.22
MI-s
.09
NC-h
.42
NC-s
.41
NE-b
.52
NJ-h
.59
NJ-s
.57
OK-h
.51
OK-s
.72
UT-h
.34
UT-s
.74
26
Table 6. Pearson Correlations
99-00 & 03-04
Chamber
both yrs
AL-h
AL-s
GA-h
GA-s
IN-h
IN-s
MD-h
MD-s
MI-h
MI-s
NC-h
NC-s
NE-b
NJ-h
NJ-s
OK-h
OK-s
UT-h
UT-s
r1
0.951
0.816
0.923
0.819
0.987
0.968
0.750
0.959
0.904
0.974
0.914
0.985
0.905
0.946
0.814
0.947
0.857
0.959
0.960
r2
0.381
0.380
0.637
0.301
0.620
0.637
0.302
0.642
0.178
0.647
0.242
0.276
0.281
0.242
0.074
0.446
0.596
0.438
0.259
27
Table 7.
Chid
Effects of Party on Individual-level Stability
pit11
pit12
pi1diff
pit21
pit22
pi2diff
alh
0.942
0.960
0.018
0.239
0.028
-0.211
als
1.377
1.054
-0.323
0.003
0.107
0.104
gah
0.929
1.160
0.231
0.001
0.207
0.206
gas
1.463
1.218
-0.245
0.019
0.180
0.161
inh
1.314
1.395
0.081
0.260
0.211
-0.049
ins
1.349
1.309
-0.039
0.144
0.064
-0.079
mdh
1.002
0.875
-0.127
0.165
0.096
-0.069
mds
1.320
1.159
-0.161
0.153
0.080
-0.073
mih
1.471
1.168
-0.303
0.069
0.026
-0.044
mis
1.701
1.515
-0.186
0.051
0.056
0.004
nch
1.126
0.990
-0.136
0.097
0.069
-0.028
ncs
1.745
1.357
-0.388
0.050
0.038
-0.012
neu
0.832
0.995
0.163
0.170
0.290
0.120
njh
1.219
1.351
0.132
0.188
0.121
-0.067
njs
1.556
1.359
-0.197
0.211
0.267
0.056
okh
1.137
1.257
0.119
0.139
0.195
0.055
oks
1.447
1.239
-0.208
0.107
0.300
0.194
uth
1.144
0.940
-0.204
0.376
0.393
0.016
uts
1.432
1.248
-0.183
0.247
0.132
-0.115
Note: pit11: effect of pid on 1st dim. Nominate scores at time 1 (1999-2000); pit12: effect of pid
on 1st dim. Nominate scores at time 2 (2003-2004); pi1diff: difference in the effects of pid on 1st
dim. Nominate scores from time 1 to time 2. pit21: effect of pid on 2nd dim. Nominate scores at
time 1 (1999-2000); pit22: effect of pid on 2nd dim. Nominate scores at time 2 (2003-2004);
pi2diff: difference in the effects of pid on 2nd dim. Nominate scores from time 1 to time 2.
28
Graph 1: Pattern of Roll Call Voting, Georgia House 1999-2000
.988
R
R
R
R
R
R
RR
R
R
R
R
R
R
R
D R
R
R
R
R
R
RR
R
R
R
R
1st nom coord at time 1
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
I R
RR
R
R
R
D
DD
DD
D
D
D
D
DD D
D
DD D
D
D
D
DD
D
D D D
D D
DD
R
D
R
DD
D
D
R
R
D
DD
R
R
D
D
D
R R R R
R
R
D
R
R
R
R
R
D
R
R
R
D
D
D
D
DD
D D
D
D D
D
D
DD D
D
D DD D
R
D
D
D
D D
D
DD
D
D
R
D D
D
D
D
DD D
D
D
D
D
D
DD
D D D
D
D
D
D
D
DD D
DD
D
-.946
-.845
.949
2nd nom coord at time 1
Graph 2: Pattern of Roll Call Voting, Georgia House 2003-2004
.997
1st nom coord at time 2
R
R
R
R
R
R
R
R R
R
R R
R
R R
R
R
D
R
R
R
R
R
R
R
RR
R R
RR R
R
RR R
R R
RR
R R
R
R R
R
RR
R R
R
R
R
R
R
R
R
R
R
RR
R
R
R
R R
R
R
R
R
R
R
D
D
D
D
D
D
D
DDD
D
D
D
D
R
D D
D
I
D
D D
D
D D D
D
D
D
D
D
D D DD
D D
D
D D
DD D
D
D
D
D
D D
D DD D D
D
D
D
D
D
D
DD
D
D
D D
D
DD
D
D
D
D D
D DD
DD
D
D
D
D
D
D
DD
D
D
D DD
D
DDD
D
DD
D DD
D
D
D
D
D
-.941
-1
.843
2nd nom coord at time 2
29
Graph 3: Pattern of Roll Call Voting, Nebraska Legislature 1999-2000
DD
D
.998
I
D
D
D
D
D
D
D
D
D
1st nom coord at time 1
R
D
D
D
R
D
R
R
D
R
R
R
I
R
R
R
R
R
R
R
R
D
R
R
R
R
D
R
R
R
RR
D
R
R
-.965
R
R
R
-.92
.731
2nd nom coord at time 1
Graph 4: Pattern of Roll Call Voting, Nebraska Legislature 2003-2004
.979
D
D
D
I
D
D
D
R
D
D
D
D
D
I
1st nom coord at time 2
I
R
R
R
R
R
R
R
D
R
R
R
R
D
R
R
R
R
R
R
I
R
RR
R
R
R
R
R
-1
RR
IR
-.979
R
.803
2nd nom coord at time 2
30