Delaying Justice(s): A Duration Analysis of Supreme
Court Confirmations
Charles R. Shipan
Megan L. Shannon
University of Iowa
University of Iowa
Presidents traditionally have had great success when nominating justices to the Supreme Court, with confirmation being the
norm and rejection being the rare exception. While the confirmation process usually ends with the nominee taking a seat on
the Court, however, there is a great deal of variance in the amount of time it takes the Senate to act. To derive a theoretical
explanation of this underlying dynamic in the confirmation process, we draw on a spatial model of presidential nominations
to the Court. We then employ a hazard model to test this explanation, using data on all Supreme Court nominations and
confirmations since the end of the Civil War. Our primary finding is that the duration of the confirmation process increases
as the ideological distance between the president and the Senate increases. We also find evidence that suggests that the
duration increases for critical nominees and chief justices and decreases for older nominees, current and previous senators,
and nominees with prior experience on state and federal district courts.
D
uring his two terms as president, Ronald Reagan
nominated five people to the Supreme Court.
The first of these nominees was Sandra Day
O’Connor, who replaced Justice Potter Stewart upon his
retirement. O’Connor was nominated on August 19, 1981.
Thirty-three days later, on September 21, 1981, the Senate
confirmed her by a vote of 99-0.
Reagan’s final nominee was Anthony Kennedy, who at
the time was serving as an appellate court judge. Kennedy
was nominated in the aftermath of Robert Bork’s failed
attempt to fill the seat vacated by Lewis Powell, who had
resigned at the age of 79. As in O’Connor’s case, the Senate
confirmed Kennedy without a single opposing vote, 97-0.
In Kennedy’s case, however, the confirmation process took
much longer than it did in O’Connor’s case. Kennedy was
nominated on November 30, 1987, and was not confirmed
until February 3, 1988. Thus, his confirmation took nearly
twice as long as O’Connor’s.1
Like O’Connor and Kennedy, most nominees are confirmed, but behind this usual outcome lies a great deal of
variance in the amount of time it takes for the Senate to
confirm a nominee. To examine this variance, we draw
on a theory of Supreme Court nominations to specify the
conditions under which the Senate will have an incentive
to delay confirmation. After making this theoretical argument, we use a dataset consisting of all Supreme Court
nominations since the end of the Civil War to examine
why the confirmation process takes longer for some nominees than for others. Our analysis thus demonstrates how
the interaction among the president, the Senate, and the
Supreme Court can influence the confirmation process,
even if the process rarely ends in rejection. In addition, the
analysis provides empirical evidence on the factors that
affect the duration of the confirmation process.
Nominations, Confirmations,
and Durations
Given the importance of the Supreme Court in the
national policy-making process, it is not surprising that
Charles R. Shipan is Professor of Political Science, 341 Schaeffer Hall, University of Iowa, Iowa City, IA 52242-1409 ([email protected]). Megan L. Shannon is a Ph.D. Candidate in Political Science, 341 Schaeffer Hall, University of Iowa, Iowa City,
IA 52242-1409 ([email protected]).
We would like to thank Dan Fletcher, Chris Logli, and Marc Parrino for their helpful research assistance, Nolan McCarty and Keith Poole
for sharing data with us, Kathy Bawn, Sarah Binder, Fred Boehmke, Cary Covington, Doug Dion, Matt Gabel, Roger Hartley, Forrest
Maltzman, Linda Maule, Dan Morey, Tim Nokken, P. S. Ruckman, Gary Segura, and seminar participants at Texas A&M University for
helpful comments and discussions, and Matt Gabel for suggesting this topic in the first place.
1
This difference was not a function of congressional recesses—Kennedy’s confirmation took roughly twice as long as O’Connor’s regardless
of whether the unit of time is “days” or “days in session.”
American Journal of Political Science, Vol. 47, No. 4, October 2003, Pp. 654–668
C 2003
654
by the Midwest Political Science Association
ISSN 0092-5853
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DELAYING JUSTICE(S)
FIGURE 1 Duration of Supreme Court Nominations
Number of Days
100+
75-99
50-74
25-49
0-24
0
10
20
30
40
50
60
Number of Nominees
social scientists have paid a great deal of attention to
Supreme Court appointments. Many studies have focused
specifically on the confirmation process, taking (at least
implicitly) the existence of the nominee as exogenous
to the process.2 These studies have provided substantial
insights on a number of topics. For example, scholars
have examined the influence of policy preferences on
senators’ voting decisions (Cameron, Cover, and Segal
1990; Segal, Cameron, and Cover 1992), the institutional
factors that affect confirmation (Scigliano 1971; Segal
1987; Silverstein 1994), and the relationship between the
characteristics of the position that has opened on the
Court and a nominee’s success (e.g., Ruckman 1993). In
addition, scholars have looked outside the three branches
to examine the role played by interest groups (Caldeira
and Wright 1998; Segal, Cameron, and Cover 1992) and
the role of citizen preferences on issues such as race (e.g.,
Overby et al. 1992).
Other studies have focused on a variety of features of
the nomination process. Some of these studies have emphasized the primacy of policy concerns during the nomination stage (e.g., Watson and Stookey 1995; Moraski
and Shipan 1999; Bailey and Chang 2001), while others
have focused on the significance of personal attributes
and factors (e.g., Yalof 1999; Nemacheck and Wahlbeck
1998).3 Many of these studies either explicitly or implicitly treat the nomination process as a game in which a
2
We use nomination to refer to the president’s action and confirmation to refer to the Senate’s action.
3
See also Massaro (1978, 1990), Maltese (1995), Abraham (1999),
Johnson and Roberts (2001), and Nemacheck (2001). More generally, studies of Supreme Court nominees can be seen as a subset of
studies that analyze appointments not only to the Supreme Court,
president will anticipate the Senate’s action and, based on
his knowledge of the Senate’s preferences, will choose a
nominee who is closest to his ideal point and whom the
Senate will approve. To the extent that such anticipatory
behavior occurs, we would expect the Senate to approve all
presidential nominees. And in fact, that is close to what we
observe. Since the end of the Civil War, the Senate has confirmed nearly 90% of the nominees that it has considered.
While there is very little variance in the outcome of the
confirmation process, this does not mean that the Senate
treats all nominations equally.4 Perhaps the single biggest
difference across nominations has to do with how quickly
the Senate completes the confirmation process. As Figure
1 shows, there is plainly a great deal of variance in the
duration of the confirmation stage. The Senate addresses
many nominations very quickly, acting upon (and usually confirming) a majority of nominees within 24 days of
their nomination. For a substantial number of nominees,
however, the process takes longer than this. Some, such
as Sandra Day O’Connor, take slightly longer, but are approved within 50 days. Others, such as David Souter or
Anthony Kennedy, are approved within 75 days. And still
others, such as William Rehnquist or Clarence Thomas,
take up to 100 and 125 days, respectively. While all of
these examples, and most other nominees, were eventually
but also to other courts and agencies (e.g., Hammond and Hill 1993;
Nokken and Sala 2000; Snyder and Weingast 2000).
4
Studies that have identified factors that influence the confirmation or rejection of Supreme Court nominees include Scigliano
(1971), Palmer (1983), Segal (1987), and Ruckman (1993). Krutz,
Fleisher, and Bond (1998) use a large sample (N = 1447) to conduct
a careful test of all presidential nominees, including justices, across
institutions in the period between 1965 and 1994.
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CHARLES R. SHIPAN AND MEGAN L. SHANNON
approved, clearly there is a large amount of variance in the
process leading to Senate action that needs to be explained
in order for us to have a more complete understanding of
the politics of confirmations.
The Significance of Duration
While scholars have begun to investigate the causes
of delay in the confirmation of lower federal bench
nominees (Binder and Maltzman 2002; Binder 2001;
Martinek, Kemper, and Van Winkle 2002; Bell 2002;
Hartley and Holmes 1997, 2002), very little is known
about the factors that influence the duration of the
confirmation stage for Supreme Court justices. Yet
understanding the variance in this duration is important
for a number of reasons, some of which have to do with
policy implications, others of which have to do with
political implications, but all of which create the incentive
for the Senate to behave strategically.
First, given that the Supreme Court makes crucial
policy decisions across a wide range of policies, delaying
the confirmation of a nominee may have important policy
implications. Supporters of a nominee want to get him or
her on the Court as soon as possible, so he or she can start
influencing arguments, deliberations, and case decisions.
Opponents, on the other hand, want to delay this process.
Even if these opponents know that most nominees will
be approved, the longer it takes the nominee to reach
a seat on the Court, the longer it will take him or her
to start affecting the Court’s policy decisions. While long
durations are not standard, as Figure 1 demonstrates, they
also are far from rare. And because the Court generally
continues to hear and decide cases during confirmations,
this creates an opportunity for members of the Senate
to engage in strategic behavior, sometimes expediting the
process and sometimes delaying it.
Taking this logic one step further, the longer opponents can delay the nomination, the better chance they
have of rejecting the nominee, perhaps due to the discovery of a scandal (Cameron and Segal 2001). And our data
verify that confirmations that take longer are more likely
to fail: the number of days of Senate deliberation and the
final outcome of the nomination are negatively correlated
(r = −.37, p < .001). In addition, Figure 2 takes the duration categories from Figure 1 and reveals that the more
days spent in deliberation, the less likely the nominee is
to be confirmed. Thus, opponents not only delay the date
on which the nominee takes a seat on the Court, but in
some cases, by increasing the duration, they increase the
likelihood that a nominee will be rejected.
Second, Supreme Court confirmations are pivotal events in American politics. These are the most
FIGURE 2 Probability of Confirmation
1
0.9
0.8
Probability
0.7
0.6
Probability of Confirmation
0.5
Upper 95% Confidence Interval
Lower 95% Confidence Interval
0.4
0.3
0.2
0.1
0
0 - 24
25 - 49
50 - 74
75 - 99
Duration of Confirmation Process (in days)
100 - 124
125 - 149
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DELAYING JUSTICE(S)
high-profile appointments that a president makes, and
in some cases a new justice can shift policy outcomes toward the president’s ideal point. But the importance of
the confirmation process to the president extends well
beyond its policy significance. To begin with, a long,
hard-fought battle over a nominee can affect a president’s
standing with the public and with the Congress. Recent
work by Groseclose and McCarty (2001), for example,
has demonstrated that a political actor (e.g., Congress)
can use the presence of a third party (e.g., the public) to
inflict political damage on its opponent (e.g., the president) in a bargaining situation. In the case of Supreme
Court appointments, it is possible that as the Senate drags
out the confirmation process, the president will suffer politically. To the extent that this occurs, the Senate will benefit in numerous other ways, such as in bargaining with
the president over legislative bills, the budget, executive
branch acts, and other appointments.
To determine whether there is any evidence that the
president might suffer politically from a long, drawn-out
confirmation process, we collected Gallup’s presidential
approval data from 1937 to 1994. For each nomination,
we determined the president’s approval rating at the time
closest to the nomination and also at the time closest to
the final action (confirmation, rejection, withdrawal, or
end of session), then subtracted the initial approval rating from the final approval rating. Thus, this is a positive
number if a president’s approval ratings went up during
the nomination battle, and a negative number otherwise.
Next we looked to see whether there was a correlation
between the length of the process and the change in presidential approval. The correlation is negative and strong
(r = −.38, p < .05). This cannot be taken as conclusive
proof that longer confirmations lead to lower presidential approval ratings, as it may be that declining approval
ratings cause confirmations to take longer. Yet, we can
say with confidence that longer confirmations go handin-hand with a decline in approval ratings. Consequently,
the president is likely to be weaker, vis-à-vis the Senate, at
the end of a long confirmation process.5
Third, lengthy hearings bring attention to specific political and policy issues. During the Thomas confirmation,
for example, the Senate and the public initially focused on
Thomas’s attitudes toward abortion; but later the focus
shifted to the issue of sexual harassment and, to a lesser
but still important extent, race. Similarly, O’Connor’s
nomination forced questions over abortion to the fore
5
While we recognize that the Congress may suffer as a result of such
prolonged conflicts, we follow Groseclose and McCarty (2001) and
others in focusing on the ways in which the president can be hurt
by such bargaining episodes.
(O’Connor 1996). During the Bork nomination, questions about ideology and the meaning of the Constitution
took central stage. Earlier nominations raised other issues,
such as the debate about the relationship between religion and government that ensued from the nomination of
Louis Brandeis. Conversely, shorter hearings can limit the
likelihood that any damaging issues will be raised. Questions about the role that a former Ku Klux Klan member
should play in the government might have arisen in the
case of Hugo Black, as his connection with the Klan was
known prior to his confirmation. But because the nomination was rushed through the Senate without hearings,
the issue did not come up during his confirmation and
became a controversy only after he was approved (Watson
and Stookey 1995).
Finally, the study of the duration of the confirmation
process can provide us with some insight into a separate issue: the consequences of divided government. Over
the past decade, many scholars have followed Mayhew’s
(1991) lead and have attempted to sort out whether the
presence of divided government reduces the likelihood
the government will pass important laws (e.g., Howell et
al. 2000). Others have looked at the influence of divided
government on a variety of other topics, including the partisanship of laws (Thorson 1998), the use of presidential
vetoes (Cameron 2000), and delegation to bureaucracies
at both the federal and state levels (Epstein and O’Halloran
1999; Huber and Shipan 2002; Huber, Shipan, and Pfahler
2001). Given the relationship between divided government and these other things, it might be expected that
divided government would influence whether the Senate
approves a president’s Supreme Court nominees.
Somewhat surprisingly, however, divided government does not seem to affect the likelihood that the Senate
will approve a nominee. In Table 1 we create a variable
called Confirmed, which takes on a value of 1 if the Senate
TABLE 1 Probit Analysis of Supreme Court
Nominee Confirmation, 1866–1994
Model 1
Divided Control
Constant
Log Likelihood
LR 2
Pseudo-R2
N
−0.204
(0.405)
1.133∗∗∗
(0.191)
−34.79
0.25
0.004
87
Numbers in parentheses are z-statistics, calculated using robust
standard errors. Levels of significance are denoted as follows:
∗
p < .10, ∗∗ p < .05, ∗∗∗ p < .01.
658
confirms the nominee and 0 otherwise, and use probit to
regress this variable on Divided Control, which takes on
a value of 1 when the president’s party does not control
the Senate and 0 when his party does control the Senate.
The results show that divided control is not a significant
predictor of a nominee’s success or failure.
In one sense, the results in Table 1 are not surprising.
Krutz, Fleisher, and Bond (1998), in their comprehensive analysis of all presidential nominations to all offices
and positions between 1965 and 1994, found that divided
government was not a significant predictor of Senate confirmation. On the other hand, we might expect that if divided government is important in a range of other areas,
then it would certainly be significant for appointments to
the Supreme Court.6 It is possible, however, that divided
government does have an influence on the confirmation
process, but that the influence is subtler than simply determining whether the nominee is accepted or rejected.
Instead, divided government may affect the pace at which
a confirmation occurs, which in turn leads to all of the
consequences discussed earlier in this section.
As this discussion makes clear, the duration of
Supreme Court confirmations has a number of implications for policy and politics. It also may provide additional insight into the effects of divided government on
the political process. Yet at this point, we know very little
about the duration of Supreme Court confirmations. In
the next section we begin to remedy this gap by building
on a theory of the appointment process.
The Nomination Game and Delay
in the Confirmation Process
In a recent article, Moraski and Shipan (1999) develop a
theory that explores the interaction among the president,
the Senate, and the Supreme Court over nominations to
the Court. The primary goal of their “Nomination Game”
is to identify which of these institutions will be influential
(and when) during the nomination process. More specifically, the game spells out the conditions under which
the president will or will not be constrained in his choice
of a nominee. Thus, the theory focuses specifically on
how institutions and preferences shape Supreme Court
nominations.
Moraski and Shipan model the process as a game
in which all actors seek to obtain the best possible policy
outcomes from the Court. In the first stage of the game, the
6
Our finding of insignificance holds even when we more fully specify the empirical model. Other studies (e.g., Segal 1987; Ruckman
1993), however, that look further into the past, do find that divided
government is a significant predictor of rejection.
CHARLES R. SHIPAN AND MEGAN L. SHANNON
president acts strategically and considers the preferences
of the Senate when selecting a nominee.7 The Senate then
considers this nominee and ultimately votes to confirm or
reject him. Based on this sequence, the model identifies
three distinct nomination regimes. While the interested
reader is directed to Moraski and Shipan’s article for the
model’s details, for our purposes we need to spell out the
conditions under which each of these nomination regimes
occurs and to see what implications these regimes have for
the confirmation process.
The first regime exists whenever x s < x p < x j , where
x s is the ideal point of the median member of the Senate,
x p is the President’s ideal point, and x j is the ideal point
of the median member of the Court.8 Under this regime,
the president is completely unconstrained and can choose
a nominee, x n , who shares his ideal point (i.e., x n = x p ),
since any nominee he chooses will move the new Court
median toward not only his ideal point, but also toward
the Senate’s ideal point as well. Certainly, the Senate would
prefer a nominee located at x s , but it prefers one located
at x p to one located closer to x j , and it also prefers the
new median produced by the president’s nominee to the
status quo.
In the second regime, the Senate is closer than the
president to the Court median, and the president and
the Senate median both are more liberal, or more conservative, than the Court.9 Under these conditions, the
president may choose a nominee who moves the Court
toward his ideal point; but unlike in the first regime, he
is somewhat constrained by the Senate and cannot simply choose a nominee who shares his ideology. Instead,
he must choose a nominee who will be located near the
Senate median (i.e., such that x n = 2x s – x j ). From the
Senate’s point of view, this will produce a new Court
7
The game includes the following assumptions. First, all actors have
perfect and complete information about the other actors’ preferences. Second, the actors have single peaked preferences over a
unidimensional policy space. Third, the seat on the Court remains
vacant until the Senate confirms a nominee.
8
When a vacancy leads to an eight-member Court, the median
member of the Court is defined as the midpoint between the fourth
justice (J4 ) and the fifth justice (J5 ). In this case, x j = (x j4 + x j5 )/2
is considered to be the Court’s median after a vacancy occurs; in
other cases, x j is simply the median member of the Court. Note
that the mirror images of the configurations discussed in the text
produce the same regimes.
Formally, this regime occurs whenever x p < x s < x j , x s > (x j4 +
x j )/2, and x p < 2x s − x j . If x p < x s < x j and either of the latter
two conditions are not met, then the observation is classified as
belonging to Regime 1. That is, not only must the Senate be closer
than the president to the Court median; but also the Senate must
be closer to the median than to the next more liberal (conservative)
justice and the president must be farther from the Senate than the
Senate is from the median justice.
9
DELAYING JUSTICE(S)
median that is just as good as the status quo. Furthermore, most senators will favor this nominee because of
his close proximity to the Senate’s ideal point and because
he may cause future Court decisions to shift toward the
Senate median.
Regimes 1 and 2 exist whenever the Senate and the
president both are more liberal, or both are more conservative, than the Court. In the third regime, however, the
Senate and president are typically more ideologically distant from each other and are situated on opposite sides of
the Court (e.g., when x p < x j < x s ). Given such a configuration of preferences, the president is fully constrained in
his choice of nominees—he cannot move the Court in his
direction at all, because any movement in this direction
is a movement away from the Senate’s ideal point. Similarly, the Senate cannot force the president to nominate
someone who will move the Court toward its preferred
point, as this would represent a movement away from the
president’s ideal point. Hence, the equilibrium prediction
for this third regime is that the president will nominate
someone whose ideal point is located at the current Court
median (i.e., x n = x j ).
What implications do these three nominations have
for the duration of the confirmation stage? In the first two
regimes, if the Senate approves the president’s nominee,
it will gain from approving a new justice whose policy
preferences are similar to those of the median member of
the Senate and who causes the new Court median to be at
least as good, and often better, than the status quo. To the
extent that senators are motivated by policy concerns—
either because they treat policy as an intrinsic goal, or
because they view policy as a means toward another goal,
such as reelection—they will want to move quickly to
approve nominees in these first two regimes.
The third regime, however, is different. We expect the
Senate to be more likely to delay approval in this regime
for three reasons. First, since there is little likelihood that
the president will nominate someone who would move
the Court toward the Senate in this regime, the Senate will
have no incentive to confirm the nominee quickly. That is,
unlike the first two regimes, in which the Senate benefits,
both immediately and in the future, from approving the
president’s nominee, in the third regime there is no policy
payoff to approving a nominee and hence no incentive to
act quickly. Given that senators have limited amounts of
time, and numerous ways to spend this time, they will see
little payoff to acting quickly in this regime.
Second, it is conceivable that in such a regime,
the president might attempt to move the Court toward
his own ideal point and away from the Senate’s ideal
point (Johnson and Roberts 2001). While the Nomination Game is one of perfect information, we can briefly
659
consider what would happen in Regime 3 if the Senate
and president were uncertain about the exact location of
the nominee. Instead of a nominee whose ideal point is
equal to x j , consider a nominee located at x j + , where
∈ [−ε,ε]. To begin with, if we assume that senators are
risk averse, they will prefer the status quo, with the Court
median remaining at x j , to a nominee whose ideal point is
distributed around this point. Furthermore, because the
Senate will worry that the president might try, even in
such a regime, to move the Court toward his ideal point,
it will spend more time evaluating such a nominee in an
attempt to learn the sign and size of . Thus, uncertainty
about the location of the nominee in this regime will lead
to a longer confirmation period.10
Third, and perhaps most importantly, the Senate may
benefit from prolonging the confirmation process and
might achieve some political, as opposed to policy, benefits from drawing out the confrontation over a nominee
in this regime. As we discussed in the previous section,
Congress can benefit from prolonged showdowns with
the president, and evidence indicates that a drop in presidential approval is correlated with the length of the confirmation process. To the extent that the Senate prefers to
face a politically weakened president—most likely because
the president and the Senate majority are from different
parties—it will see some benefit in a protracted battle
over confirmations. Thus, we expect the Senate to benefit
from delay in the third regime, because it is in this regime
that we are most likely to see a great degree of ideological disagreement between the president and the Senate,
with a liberal president opposing a conservative Senate or
a liberal Senate opposing a conservative president.
The preceding discussion shows that although the
primary purpose of the Nomination Game is to explain
the ideological position of nominees, it also has clear
repercussions for confirmations. More specifically, it has
implications for the speed of the confirmation process.
The Senate will have an incentive to act more slowly, for
10
A similar argument could be made about the second regime. That
is, one could argue that in Regime 2, as in Regime 3, the president
may try to appoint a nominee who would make the new Court
median worse than the status quo for the Senate. We have three
responses to this valid point. First, the Senate and president are
more likely to be from opposing parties in Regime 3 than in Regime
2; and in the next paragraph in the text we detail how the Senate
can benefit from a longer confirmation period, an argument that
makes the most sense in the context of a president and Senate from
opposing parties. Second, to the extent that we are incorrect about
Regime 2 causing less delay than Regime 3, it biases our results
against producing significant findings. Third, it is worth noting that
very few nominations are likely to fall into Regime 2, since there
are a number of necessary conditions for this regime. Moraski and
Shipan (1999) classify only three nominations in the past sixty years
as belonging to this regime.
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CHARLES R. SHIPAN AND MEGAN L. SHANNON
both policy and political reasons, in the third regime than
in the first two regimes. We turn now to a test of this
hypothesis.
Hypotheses and Data
To test our hypothesis about the relationship between the
political regime and duration, we have collected data on
all Supreme Court appointments since the nomination of
Henry Stanbery in 1866. We chose this time frame because it allows us to examine all nominations that have
taken place under the stable two-party Republican-andDemocrat system and during the period in which the size
of the Court has remained fixed at nine members. The resulting dataset has information for 87 nominees. Of these
87 nominees, the Senate confirmed 75, rejected 7, and
took no action on 2. The remaining three nominations
were withdrawn from consideration.
For our empirical test, ideally we would like to determine the specific regime type for each nominee to the
Court. Unfortunately, Moraski and Shipan’s analysis provides regime classifications for only a limited number of
nominees, those nominated in the post-WWII era. Furthermore, although Moraski and Shipan find strong support for their model based on the regime classifications
that they computed, Bailey and Chang (2001) have introduced an alternative method for determining interinstitutional ideal points that casts some doubt on these
classifications.
Fortunately, we can draw on the definition of the third
regime to develop appropriate and available proxies. Recall that the primary characteristic of the third regime is
that the Court’s ideal point lies between the ideal points of
the president and the Senate. To the extent that the president and Senate are located close together, the nomination
is more likely to be in the first two regimes, under which
we expect quick confirmations. On the other hand, when
the Senate and the president are located far from each
other—when they are ideologically distant—the Court is
much more likely to be located between these other two
actors.
Thus, one good proxy for Regime 3 is Divided Control, which takes on a value of 0 when the president’s
party controls the Senate and 1 otherwise. Under divided
control, the president and Senate are more likely to be
ideologically far apart from each other, thereby increasing the likelihood that the Court lies between the two.
Another good proxy for Regime 3, one which taps into
the partisan underpinnings of ideological disagreement
that we discussed in the previous section, is the distance
between the president and the median member of the Sen-
ate majority party. The greater this distance, which we call
President-Majority Party Distance, the more likely it is that
the Court lies between the president and Senate. To determine the median position of the majority party in the
Senate, we use first-dimension DW-NOMINATE scores,
which are available for our entire time period and which
are scaled to allow comparisons across time. Because these
scores are not available for presidents before Truman, as
a proxy for the president’s ideal point, we follow McCarty
and Razaghian (1999) and McCarty and Poole (1995) and
use the value for the median member of the president’s
party in the Senate.11 Since we take the absolute value of
the difference between the two parties’ medians, this variable will take on a value of 0 under unified control and
positive values under divided control.
The primary hypothesis derived from the theory is
that delay is more likely during periods where the president and Senate are farther apart ideologically. To measure
this ideological distance, we therefore rely on the two measures described above—a dichotomous measure (Divided
Control) and a more continuous measure derived from
DW-NOMINATE scores (President-Majority Party Distance, which is actually the same as the distance between
the two parties interacted with Divided Control). Because
these two variables are so highly correlated with each other
(r = .94, p < .001), we test both in separate equations,
but do not include them in the same regressions.12
11
We also created a related variable that uses DW-NOMINATE
scores for presidents who have such scores (Truman through
Clinton) and rely on the proxy discussed in the text for other presidents. This hybrid variable produces results that are as strong as,
and in some cases stronger than, those we report.
12
One alternative to these measures would be to use the median of
the Senate Judiciary Committee. We acknowledge that although the
importance of the committee has changed over time, and although
it rarely has gatekept Supreme Court nominations, the committee can play a role in the confirmation process. Still, for a variety
of reasons, we prefer to use the measures described in the text.
Empirically, high levels of collinearity preclude us from including
committee medians along with floor or party-level measures. Furthermore, it is reasonable to assume that the committee acts as an
agent of the party with respect to Supreme Court nominations. This
is consistent with the findings that the Judiciary Committee usually does not differ significantly from the party median (Cox and
McCubbins 1991); and our own calculations show that between
1947 and 1996, the median absolute difference between the floor
and the committee median was only six points on the ADA scale.
Finally, the theoretical model indicates that committees would play
an independent role only in certain unique circumstances that are
unlikely to occur—most notably, under Regime 3, when there is
divided control but the committee is an outlier whose ideology is
closer to the president’s than to the party’s; or under Regimes 1 and
2 when there is unified government but the committee is an outlier
in the opposite ideological direction (e.g., a Senate and president
that are more liberal than the Court, but a committee that is more
conservative than the Court).
DELAYING JUSTICE(S)
Additional Explanatory Factors
While Divided Control and President-Majority Party Distance are the primary theoretical variables we wish to test,
we recognize that a number of other factors might also
cause the Senate to give greater scrutiny to a nominee,
thereby prolonging the confirmation process. While these
do not derive directly from the Nomination Game, they
are factors that other empirical and descriptive studies
have identified as influencing the confirmation process
and need to be included in our statistical tests.
First, the nominee’s personal characteristics might
affect the length of the confirmation process. In particular, following our earlier discussion, any characteristics
that decrease the Senate’s uncertainty about a nominee
will reduce the duration. To begin with, if, for example,
the nominee is currently or has previously served in the
Senate, we expect a quicker confirmation. We particularly
expect less delay for nominees who are currently serving
in the Senate, as other senators will be familiar with the
nominee and will take less time to gather information
during confirmation hearings. As Abraham has argued in
his vivid history of Supreme Court appointments,
Would any of the thirty [nominees] who failed
in being confirmed have been approved had they
been members of the Senate at the time of their
nomination? The evidence is persuasive that they
would have: the Senate almost invariably treats
as a cas d’honneur the Presidential designation
of a sitting member and normally also, although
not so predictably, of a past colleague in good
standing. (1999, 33)
To capture this effect we create two variables—Current
Senator and Previous Senator—which we set equal to 1
for nominees who fit those descriptions.
We also include the age of the nominee as an independent variable (Palmer 1983). Because appointments
to the Court are lifetime appointments, it is conceivable
that a younger nominee, who might have a long tenure
on the Court, will come under greater scrutiny than an
older nominee. Thus, we expect that as this variable,
Age, increases, the duration of the confirmation should
decrease.
Another nominee characteristic that might influence
the duration of the confirmation battle is the nominee’s
level of qualification, since all else equal, highly qualified
nominees are likely to be approved more quickly than
less-qualified nominees (Spaeth 1979). To account for
this factor, we rely on measures of nominee quality that
661
are accessible for all nominees in our data.13 We employ
three dichotomous variables, State Court Experience, Federal District Court Experience, and Federal Appellate Court
Experience, which indicate whether the nominee served
on a court at one of these levels. Such experience serves
as a measure of quality (Hartley 2001) and also can decrease the Senate’s uncertainty about the nominee’s ideology. Hence, we expect the presence of such prior judicial
experience to expedite the confirmation process.
Second, characteristics of the position on the Court
itself might influence the duration of the confirmation
process. One such characteristic is whether the nomination is to the position of chief justice. Such nominations
might take longer than other nominations, as the chief
justice has numerous powers, such as the power to assign
opinions when he is part of the majority, that are greater
than those possessed by associate justices (e.g., Maltzman,
Spriggs, and Wahlbeck 2000). To account for this, we include a variable called Chief Justice, which takes on a value
of 0 for associate justice nominations and 1 for chief justice nominations.
While all appointments to the Court are important,
some are more important than others because they hold
out the possibility of an immediate change in the Court’s
behavior. Following Ruckman (1993), we define a Critical
Nomination as one that would have a substantial influence
on the partisan balance of the Court—more specifically, a
nomination in which the replacement of a departing justice by someone from the opposing party would lead to a
one-member partisan split, create a partisan deadlock, or
establish a new partisan majority on the Court. Furthermore, we would expect that while all critical nominations
will take longer than noncritical nominations, those critical nominations that take place during divided control
are likely to come under even greater scrutiny. Thus, following Binder and Maltzman (2002), we also include the
interaction of Critical Nomination with Divided Control.
Third, we include variables that capture the role of the
Senate and the president. Divided Control and PresidentMajority Party Distance, which were discussed at length
earlier, obviously tap into the level of disagreement between the president and the Senate. In addition, we also
need to control for the timing of the nomination within
the congressional session. Grossman and Wasby (1972)
13
Ideally, of course, we would like to use more direct measures of
qualifications, but both the ABA ratings and the Segal-Cover measures of qualifications exist for fewer than half of the justices we
analyze. The ABA ratings, while useful at the lower court level (e.g.,
Binder and Maltzman 2002) are much less useful at the Supreme
Court level. From 1956, when the Bar issued its first rating, through
1970, nominees could be rated either “Qualified” or “Not Qualified,” and all nominees—including Nixon’s much maligned nominations of Carswell and Haynsworth—were rated as qualified.
662
note that the timing of nominations is occasionally a key
factor in confirmation, particularly for late-session nominations under a Senate that is attempting to complete
business before the end of the session. A nomination made
near the end of each session will reach its final outcome,
whether approval, rejection, or the end of the session,
more quickly than a nomination made earlier. To capture
this potential effect, we include a control variable called
Time Remaining in Session, which we operationalize as the
number of days from the date of nomination to the last
day of that congressional session.14
It is also possible that factors specific to the president
will affect the length of the confirmation. Based on studies
of Supreme Court confirmations (Segal 1987; Ruckman
1993) and also the duration of lower court appointments
(Binder and Maltzman 2002; Martinek, Kemper, and Van
Winkle 2002), we include two such factors: Unelected,
which equals 1 for presidents who obtained their position
through succession rather than through election, and Last
Year, which is set equal to 1 in the last year of a president’s
term (Segal 1987).
We recognize that there are other factors that might
influence the duration of the confirmation process. A
nominee who faces a scandal, for example, can be expected to face a more drawn-out confirmation process
than a nominee with a spotless record. Of course, it is
possible that the discovery of a scandal is endogenous to
the duration—the longer the duration, the more time opponents have to uncover a scandal (Cameron and Segal
2001). More importantly, perhaps, there are no readily
available historical data on scandals; and since the focus
of our article is not on scandals, we do not pursue this
issue further.15 We also lack precise data on a number of
other factors that might influence the duration of a nomination. For example, presidents with higher approval ratings might be able to move their nominees through the
Senate more quickly. Similarly, we might expect nominees
14
A nomination made late in the session might also present an opportunity for senators who oppose the nomination to use delay to
their advantage, slowing the confirmation process. This scenario is
particularly likely under divided government. However, our data
does not support this expectation: we interacted Time Remaining
with Divided Control and found this interaction term had no significant influence on duration.
15
When we include indicator variables for Fortas, who had a clearcut scandal, or for other, more arbitrary choices of nominees
who might be classified as suffering from scandals (e.g., Clarence
Thomas), the results were not significant and did not affect our
other results. However, the relationship between duration, scandals, and confirmation is considerably more complicated than this
and a deserving topic of research on its own. For an example of
a study that successfully includes scandals as a causal variable, see
Krutz, Fleisher, and Bond (1998). For the only example of research
that attempts to build a theory around scandal, and that attempts
to code scandals over a time period as long as the one we examine,
see Cameron and Segal (2001).
CHARLES R. SHIPAN AND MEGAN L. SHANNON
who are strongly supported by major interest groups to
sail through the Senate more quickly than nominees who
face significant opposition. However, these sorts of data
are unavailable for our entire time period.
Method
We use a hazard rate model to test our hypotheses
about delay in the confirmation process (McCarty and
Razaghian 1999; Bell 2002; Binder and Maltzman 2002;
Martinek, Kemper, and Van Winkle 2002). The hazard
model is particularly well suited for investigating the duration of the confirmation process, as our dataset contains
several nominees on whom the Senate took no action. This
methodological approach is superior to alternatives such
as OLS, where information on these right-censored nominations would be lost. A duration model allows us to treat
these nominations as right-censored and to avoid the selection bias that would occur if we eliminated nominees
on which the Senate took no final action.
A hazard model allows us to estimate the effect of variables on the hazard rate of an event (Box-Steffensmeier
and Jones 1997). Since we are interested in explaining the
length of the confirmation process, in this case the hazard rate is the “risk” of Senate action—that is, the risk of
confirmation or rejection.16 Thus, the hazard rate tells us
the likelihood that the confirmation process will reach its
conclusion at time t +1 if it has not done so at time t.
For our analysis we use the Cox proportional hazard
model, which makes the least restrictive assumptions for
the baseline hazard in the class of continuous time-event
history models.17 The hazard rate formula is:
h(t) = exp( x)ho (t)
where h(t) is the hazard rate, ho (t) is the baseline hazard
rate, and x is a matrix of estimated coefficients and variables. The coefficients indicate whether an independent
variable significantly increases or decreases the hazard
rate, using standard errors to determine statistical significance. By using the Cox model, we assume that each covariate has a proportional and constant effect on the risk.
We can determine if a variable increases duration by
looking at its effect on the baseline hazard rate. A positive
16
Results are essentially the same if we run the regressions using
“confirmation” as the risk, rather than “action.”
17
Parametric models, such as the Weibull or exponential, require
specifying a particular distributional form of the baseline hazard.
We use the Cox model, which is semiparametric and does not require us to make strong assumptions about the shape and distribution of the hazard. Within the Cox model, we also tried several
alternatives to the default Breslow method for handling tied failure
times and did not find substantive differences between the findings
produced by these alternatives.
663
DELAYING JUSTICE(S)
coefficient indicates that the variable increases the hazard
rate, which means that the presence of the variable increases the rate at which the Senate is likely to take action.
A negative coefficient indicates that the variable decreases
the hazard rate of action, or that it delays such action.18
Results
To estimate the model, we collected data on the length of
time each nomination was considered before the Senate
confirmed or rejected the nominee, using Epstein et al.
(1996). The nomination’s duration consists of the total
number of calendar days from the date of the president’s
nomination to the date of final action.19 For reasons discussed earlier, we include all nominations sent to the Senate between 1866 and 1994 in the analysis.20 In the following sections we present the results of our Cox proportional
hazard analysis.21
18
Because we have multiple observations for some nominees, we
calculate robust standard errors, clustering on each nominee. For
example, President Hayes nominated a former college classmate,
Stanley Matthews, in late January of 1881. The Senate Judiciary
Committee refused to report the nomination to the floor, citing
concerns over Matthew’s ties to railroad interests. Two months later,
President Garfield renominated Matthews, who was ultimately confirmed by a vote of 24 to 23 (Abraham 1999). Other nominees
who appear more than once in the dataset are Abe Fortas, Charles
Hughes, Edward White, Harlan Stone, and William Rehnquist. With
multiple observations for certain nominees, the possibility arises
that standard errors are correlated among observations. Yet, the
conventional estimate of variance assumes independent observations, and may produce inaccurate standard errors if observations
are correlated. The robust estimate of variance allows us to relax the
assumption of independence among observations, and obtain more
accurate estimates of standard errors among independent clusters
(i.e., nominees).
19
When a confirmation occurs on the same day as a nomination,
we treat the confirmation as occurring on the following day so that
the estimation does not drop the observation. This follows the approach taken by Binder and Maltzman (2002). Also like Binder and
Maltzman, we do not subtract congressional recess days from the
analysis. Although recesses at the end of the nineteenth and beginning of the twentieth centuries tended to be long, the nominations
did not overlap with these recesses. Moreover, “congressional days”
and “total days” are highly correlated (r = .85, p < .001), and our
results are essentially the same whether we use congressional days
or total days as the measure of duration. See Bell (2002) for an
additional defense of using total days.
20
In the case of Homer Thornberry in 1968, the Senate did not
consider the nominee, but for reasons that had nothing to do with
the president, the Senate, or the nominee himself. Thornberry was
to fill the associate seat that Abe Fortas would have left vacant
once Fortas was approved as Chief Justice; but since the Senate
never confirmed Fortas to the position of Chief Justice, it never had
the opportunity to address the Thornberry nomination. Thus, we
exclude the Thornberry nomination from our analysis.
21
Results using the Weibull model are essentially the same as those
produced by the Cox model.
In columns 1 and 2 of Table 2 we provide a basic
and initial test of our primary theoretical prediction. The
results in these two columns demonstrate preliminary
support for our theoretical proposition, with both coefficients being significant and having the expected sign.
Column 1 shows that Divided Control produces additional delay in the confirmation process, while column 2
shows that as President-Majority Party Distance increases,
so does the length of the confirmation process. Interestingly, these results starkly contrast with those in Table 1,
which showed that divided control had no effect on the
success or failure of a nomination. Clearly, then, there
is more going on during the confirmation battles than
a simple “confirm” or “reject” decision, and time is an
important political aspect of these battles.
Of course, we need to control for the other variables
that we identified as possibly influencing the duration of
the confirmation process. Columns 3 and 4 present the
results when we include these other independent variables in our analysis. The most important finding in these
columns is that even when we include all of these other
potential influences, our proxies for the third regime remain significant in the predicted direction, with Divided
Government and President-Majority Party Distance significant at p < .01 and p < .05, respectively.22
In addition, many of the other independent variables
we identified also influence the length of the confirmation process in the ways we expected them to. Among
the nominee’s characteristics, we find strong support for
the role of Current Senator.23 In addition, we find support for two of the three qualifications variables, with
experience on a state or federal district court leading to
22
In a recent paper, Bond, Fleisher, and Krutz (2002) make the
important point that because nominees can exit the confirmation
process in a variety of ways, a competing risks model is more appropriate than a Cox or Weibull model. Then, in their empirical work,
they find that divided government does increase the duration for
confirmations, but does not increase the duration for rejections. Because so few Supreme Court nominees were rejected or withdrawn,
we cannot analyze our data using a competing risks framework.
However, basic statistical tests do indicate that both confirmations
and rejections take longer under divided government than under
unified government. The mean number of days to confirmation is
twice as long under divided government as under unified government; similarly, divided government produces an increase of 60%
in the mean number of days to rejection for the seven nominees
who were rejected.
23
Some studies (e.g., Hartley 2001; Martinek, Kemper, and Van
Winkle 2002; Bell 2002) have suggested that a candidate’s race and
sex may influence the duration of the confirmation process for
lower court nominees. At the level of the Supreme Court, of course,
only two women and two blacks have been nominated. When we
include variables measuring these attributes, they are not significant.
664
CHARLES R. SHIPAN AND MEGAN L. SHANNON
TABLE 2 Cox Regression of Duration of Supreme Court Confirmations,
1866–1994
Variable
Regime Proxies
Divided Control
President-Majority
Party Distance
Nominee Characteristics
Age
1
−0.56∗∗∗
(0.20)
–
2
–
−0.81∗∗∗
(0.34)
–
–
Current Senator
–
–
Previous Senator
–
–
State Court
Experience
Federal District
Court Experience
Federal Appellate
Court Experience
Nature of Position
Chief Justice
–
–
–
–
–
–
–
–
Critical Nomination
–
–
Critical Nomination
–
× Divided Control
Senate and Presidential Characteristics
Time Remaining in
–
Session
Last Year of
–
Presidential Term
Unelected President
–
Log Likelihood
2
N
−288.54
8.06∗∗∗
87
–
–
–
–
−288.86
5.86∗∗∗
87
3
−0.65∗∗∗
(0.23)
–
4
–
−0.78∗∗
(0.42)
0.02∗
(0.02)
2.56∗∗∗
(0.47)
−0.36
(0.52)
0.64∗∗∗
(0.26)
0.83∗∗
(0.45)
−0.20
(0.26)
0.02∗
(0.02)
2.56∗∗∗
(0.47)
−0.32
(0.53)
0.65∗∗∗
(0.26)
0.84∗∗
(0.45)
−0.23
(0.26)
−0.65∗
(0.44)
−1.41∗∗
(0.72)
1.47
(0.89)
−0.62∗
(0.44)
−1.36∗∗
(0.71)
1.22
(0.86)
−0.003∗∗
(0.001)
−0.40
(0.55)
0.52
(0.46)
−272.67
79.22∗∗∗
87
−0.002∗∗
(0.001)
−0.37
(0.55)
0.54
(0.47)
−273.36
76.54∗∗∗
87
Numbers in parentheses are robust standard errors. Levels of significance are denoted as follows:
∗
p < .10, ∗∗ p < .05, ∗∗∗ p < .01 (one-tailed tests) and are marked for only those variables that are significant
in the predicted direction.
a shorter confirmation process.24 Unexpectedly, however,
appellate court experience, which is the most prestigious
24
We also tested the effect of judicial experience by including years
served on an appellate court or on a federal district court as independent variables. These variables did not significantly affect
duration, which seems to indicate that the service itself, and not
the length of service, is more relevant, perhaps because service of
and visible judicial experience a nominee could have, is
not significant.25
any length indicates that the nominee had already been vetted by
the Senate.
25
One possible explanation for this, of course, is that the qualification of a nominee is also endogenous. That is, the nomination
665
DELAYING JUSTICE(S)
TABLE 3 Magnitude of Significant Covariate Effects on the Duration of
Confirmation
Hazard Rate Change
Variable
Divided Control
President-Majority
Party Distance
Current Senator
State Court Experience
Federal District Court
Experience
Chief Justice
Critical Nomination
Change in X
(from, to)
Based on Column 3
of Table 2
Based on Column 4
of Table 2
(unified, divided)
(0, 1.07)
−47.80%
–
–
−54.16%
(0, 1)
(0, 1)
(0, 1)
1193%
89.64%
129%
1194%
91.55%
132%
(0, 1)
(0, 1)
−47.79%
−75.34%
−46.21%
−74.33%
Two of the variables associated with the nature of the
position have the predicted effects. First, we find that an
appointment to the position of chief justice takes longer
than an appointment to a seat as an associate justice. Second, we find that critical nominations take longer than
other nominations, although we do not find that this effect is exaggerated under divided control. Interestingly,
Binder and Maltzman’s (2002) findings are exactly the
opposite. For lower courts, they find that critical nominations take longer than noncritical nominations only
when control of the government is divided. This discrepancy between the findings for the Supreme Court and
lower courts is certainly worthy of future exploration.
Finally, we find little support for the institutional variables.26 The amount of time remaining in the session does
have a significant effect on the duration. More specifically,
a nomination that is made closer to the end of the session
results in a shorter confirmation process. We do not, however, find any support for the presidential variables that
regime may affect the qualification level that a president looks for in
a nominee. Because we are drawing on a model in which actors are
motivated by policy, we do not explore this further in this article,
but recognize it as an important topic for future research.
26
In addition to the institutional variables reported in the table, we
also examined whether intraparty heterogeneity influences the duration of the confirmation process. One might expect that the president needs dependable partisans and hopes also to be able to work
with opposition party members, and thus benefits when his party is
homogenous and the party opposing him is heterogeneous. To test
this, we used NOMINATE scores (Poole and Rosenthal 1997, 2001)
to create two variables—Heterogeneity of the President’s Party, and
Heterogeneity of Party Opposing the President—and added these
variables to the regressions reported in columns 3 and 4 of Table 2.
These variables were not significant, and their inclusion had little
effect on our other results.
denote whether a president is unelected or whether he is
serving the last year of his term. Furthermore, a variety of
other potential presidential variables that we examined,
such as whether the president is serving his second term,
whether this is his first nomination, and the total number
of justices he has placed on the Court, have no effect on
duration.27
Based on the results shown in columns 3 and 4 of
Table 2, we can calculate the substantive effect of our primary theoretical variables. As shown in Table 3, a nominee’s hazard rate decreases by 47.80% during periods
when partisan control of the Senate and the presidency
is divided. Similarly, when the president was the most
ideologically distant from the majority party in our data,
the nominee’s hazard rate fell by 54.16%. Consistent with
Abraham’s observation reported earlier, the Senate’s hazard rate increased by a whopping 1,193% when the nominee was serving in the Senate at time of consideration.
Table 3 shows how the hazard rate decreases for chief justices and critical nominations and increases for nominees
with federal district or state court experience.
27
Many duration models, including the Cox model, assume that
each covariate has a proportional effect on the hazard of failure;
hence, estimating these models when the hazards are not proportional can result in biased coefficients and decreased power of significance tests (Box-Steffensmeier and Zorn 2001). Analysis using
the stphtest routine in Stata 6.0, however, indicates that nonproportionality is not a problem. In addition, when we account for
time in a different manner—including a trend variable to pick up
other, unmeasured factors that might have caused the duration to
increase over time—Divided Control remains strongly significant,
and President-Majority Distance also remains significant, albeit at
a lower level of significance. Our other findings similarly remain
substantially the same.
666
Conclusions and Future Research
Because of the important role that the Supreme Court
plays in setting policy, the nomination and confirmation
of justices to the Court is a supremely political process.
Here we have shown a specific way in which political factors, such as the ideological separation between the president and the Senate, affect confirmations. Namely, these
political factors affect the duration of the confirmation
process.
It is worth emphasizing that we derive our primary
hypothesis about the effects of ideological separation
from a model of the nomination process. Although the appointment process consists of two clearly related stages—
first, the nomination, and second, the confirmation—
previous studies of the Senate’s confirmation process generally have treated these stages in isolation from each other
(although see Massaro 1990 for an important exception).
More specifically, most studies of the confirmation process simply take the existence of the nominee as given and
ignore any implications that the politics of the nomination stage might have for the confirmation stage. Such
an approach does not take into account the fact that the
president’s choice of a nominee is a strategic, political
decision, one that is shaped by institutional configurations that may affect not only the nomination but also the
confirmation. In contrast, we derive a hypothesis about
confirmations from a model of nominations. Given that
our results support this hypothesis, our analysis suggests
that future studies of the confirmation process should
not treat the nomination stage as exogenous, but rather
should consider the underlying politics that led to a nominee being chosen in the first place.
Our empirical results demonstrate that confirmation
proceeds more quickly for some nominees, such as those
who are sitting senators or have prior judicial experience,
than for other nominees. More importantly, our results
confirmed our primary hypothesis that ideological disagreement between the president and the Senate would
increase the duration of the confirmation process. This
hypothesis itself is not all that surprising; we might have
simply stated this hypothesis as an empirical observation
and used that to defend our inclusion of independent
variables that measure conflict between the president and
the Senate. But our approach in this article has the benefit
of providing a solid theoretical basis for the inclusion of
such variables and of showing how the regime type of the
nomination stage can affect duration at the confirmation
stage.
Future research can build on this study in a number
of ways. First, rejections were more common prior to the
CHARLES R. SHIPAN AND MEGAN L. SHANNON
Civil War. It would be interesting to see whether delay
similarly occurred during these earlier years of the republic; or if senators opposing the president have substituted
delay for rejection. In addition, it would be useful to obtain more nuanced measures of some of our variables,
especially qualifications. Along other lines, while some of
our results are similar to those found for lower courts
(Binder and Maltzman 2002; Martinek, Kemper, and Van
Winkle 2002; Bell 2002), others are not, and it is worth
considering why these differences might occur. For example, it would certainly be worth investigating the ways
in which the higher level of salience for Supreme Court
confirmations might alter the costs and benefits, relative
to lower court confirmations, of delay. While these sorts
of improvements would add to our overall understanding
of the confirmation process, our results here have demonstrated that Supreme Court confirmations vary in theoretically predictable ways. To recognize this, scholars need
to look not only at the final confirmation, which masks
important political aspects of the process, but also the
effect of time in the confirmation battle.
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