IT’S THE JOURNEY, NOT THE DESTINATION: JUDICIAL
PREFERENCES AND THE DECISION-MAKING PROCESS
Carlos Berdejó *
I. INTRODUCTION
Much attention has been devoted to exploring, both theoretically and
empirically, the relationship between judges’ voting behavior and their
ideological preferences. For the most part, this line of research has been
motivated by the political theory of judicial decision-making, according to
which judges vote for the “liberal” or “conservative” outcome in a case
based on their policy or political preferences.1 The other paradigm
prevalent in the literature on judicial decision-making is the legal model,
which emphasizes judges’ sense of duty to follow existing legal principles
and norms.2 Although the weight of the existing empirical evidence has
supported the political theory, this imbalance may be attributed in part to
the challenges faced by researchers in empirically testing the legal model.3
The effect of judges’ individual preferences on their voting behavior
appears to be mediated (at least in appellate cases) by the interaction among
the members of the panel hearing the case; that is, not only does the
political ideology of a particular judge affect how that judge votes in a
given case, but so does the ideology of the other judges sitting in the panel.4
The evidence presented in several studies documents these “panel effects,”
∗
Associate Professor, Loyola Law School. The author conducted a major portion of this research
as a Terence M. Considine Fellow in Law and Economics at Harvard Law School and acknowledges
support from the school’s John M. Olin Center for Law, Economics, and Business. The author would
like to thank Daniel Chen, Joshua Fischman, Michael Guttentag, Louis Kaplow, Larry Katz, Pauline
Kim, Lee Petherbridge, Andrei Shleifer, Stephen Wasby, Jeffrey Yates, and participants at the 2010
Conference of Empirical Legal Studies and the 2011 Annual Meeting of the American Law and
Economics Association for their extremely helpful comments on earlier drafts.
1
For an early exposition of the theory that judicial decision-making is primarily driven by judges’
preferences over substantive policy outcomes, see Jerome Frank, What Courts Do in Fact, 26 ILL. L.
REV. 645, 653 (1932) (arguing that judges choose their preferred outcome in a case ex-ante and then
select the principles of law that are to be applied—or the set of facts to which these will be applied—in
order to reach that desired outcome).
2
For an overview of the leading theories of judicial decision-making, see Frank B. Cross,
Decisionmaking in the U.S. Circuit Court of Appeals, 91 CALIF. L. REV. 1457, 1461−90 (2003).
3
See Cross, supra note 2, at 1467−71 (arguing that the evidence lending support to the political
model is not necessarily incompatible with the legal model and that both legal and ideological variables
predict judicial decisions).
4
See, e.g., Richard L. Revesz, Environmental Regulation, Ideology, and the D.C. Circuit, 83 VA. L. REV.
1717, 1751–52 (1997).
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wherein “unified” panels (i.e., panels in which the three judges were
appointed by presidents of the same political party) tend to be more
ideological than “split” panels (i.e., panels in which two of the three judges
were appointed by presidents of the same political party).5 Related to these
“panel effects” is the hypothesis that judges may behave strategically to
maximize their preferences in the long run by moderating (or even
sacrificing) their views in any given case. This strategic theory posits that
judges do not naïvely vote according to their preferences on a case-by-case
basis, but rather take into account the likely responses of the Supreme Court
(which may reverse the panel’s decision),6 the other active judges in the
circuit (who may rehear the case en banc),7 and their panel colleagues.8
5
See, e.g., id. at 1751−56 (analyzing 250 D.C. Circuit rulings on challenges to decisions by the
Environmental Protection Agency between 1970 and 1994); Richard L. Revesz, Congressional
Influence on Judicial Behavior? An Empirical Examination of Challenges to Agency Action in the D.C.
Circuit, 76 N.Y.U. L. REV. 1100, 1122−24 (2001) (analyzing a sample of 350 D.C. Circuit rulings
involving challenges to the health and safety decisions of federal agencies between 1970 and 1996);
Cass R. Sunstein et al., Ideological Voting on Federal Courts of Appeals: A Preliminary Investigation,
90 VA. L. REV. 301, 329−30 (2004) (analyzing a sample of approximately 5,000 published opinions
from all circuits for the period 1995−2002). Similar “panel effects” have been documented along other
judicial characteristics, including gender and race. See, e.g., Adam B. Cox & Thomas J. Miles, Judging
the Voting Rights Act, 108 COLUM. L. REV. 1, 34−37 (2008) (finding that judges are more likely to vote
for liability under the Voting Rights Act when they serve in a panel with an African American judge);
Sean Farhang & Gregory Wawro, Institutional Dynamics on the U.S. Court of Appeals: Minority
Representation Under Panel Decision Making, 20 J.L. ECON. & ORG. 299, 321 (2004) (finding that male
judges vote more liberally in employment discrimination cases when one woman serves on a panel);
Jennifer L. Peresie, Female Judges Matter: Gender and Collegial Decisionmaking in the Federal
Appellate Courts, 114 YALE L.J. 1759, 1778 (2005) (documenting similar gender effects in sexual
harassment and discrimination cases).
6
See, e.g., Jonathan P. Kastellec, Panel Composition and Judicial Compliance on the U.S. Courts
of Appeals, 23 J.L. ECON. & ORG. 421, 425−27 (2007) (presenting a model focusing on the interaction
between appellate courts and the Supreme Court).
7
See, e.g., Virginia A. Hettinger et al., Comparing Attitudinal and Strategic Accounts of
Dissenting Behavior on the U.S. Courts of Appeals, 48 AM. J. POL. SCI. 123, 124−25 (2004) (presenting
a model in which judges’ strategic calculations about whether or not to dissent are a function of the
likelihood that other circuit judges will vote to review the panel’s decision en banc).
8
Cross and Tiller attribute panel effects to “whistle-blowing”—the presence of an “opposition
judge” who brings the other two judges to the “middle” as they prefer to avoid dealing with a dissenting
opinion that could increase the risk of rehearing and reversal. See Frank B. Cross & Emerson H. Tiller,
Judicial Partisanship and Obedience to Legal Doctrine: Whistleblowing on the Federal Courts of
Appeals, 107 YALE L.J. 2155, 2173−75 (1998) (finding that D.C. Circuit judges are more likely to defer
to agency opinions with which they presumably agree and are more likely to do so when they sit with
judges of the same party). Alternative theories posit that since it is costly to dissent (i.e., dissent
aversion), judges may choose not to vote according to their preferences when their vote is not pivotal,
particularly when there are differences among panel members in the intensity of their preference for a
particular outcome. See Lee Epstein et al., Why (and When) Judges Dissent: A Theoretical and
Empirical Analysis, 3 J. LEGAL ANALYSIS 101, 103−11 (2011); William M. Landes & Richard A.
Posner, Rational Judicial Behavior: A Statistical Study, 1 J. LEGAL ANALYSIS 775, 780 (2009). Some
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273
Some have argued that these strategic accounts of judicial behavior neglect
to take into account the internal dynamics of a panel—during deliberations
judges in a panel may persuade each other through the exchange of ideas,
arguments, insights, and experiences.9 Empirically, whether judges behave
strategically or not is still an open question.10
More generally, the theoretical and methodological limitations of
empirical studies of judicial behavior have been extensively debated.11 A
major criticism relates to the construction of the databases used in the
analyses—most studies exclude unpublished decisions, which account for a
significant percentage of appellate decisions.12 What makes this issue
have embraced behavioral or psychological mechanisms such as group polarization effects and
conformity pressure. See Sunstein et al., supra note 5, at 307–11, 337−46.
9
See, e.g., Harry T. Edwards, Collegiality and Decision Making on the D.C. Circuit, 84 VA. L.
REV. 1335, 1358−62 (1998) (arguing that panel effects reflect collegiality and compromise among panel
members); Harry T. Edwards, The Effects of Collegiality on Judicial Decision Making, 151 U. PA. L.
REV. 1639, 1659 (2003) (arguing that studies that ignore the possibility of collegiality overemphasize
the role played by partisan preferences in determining case outcomes); Revesz, supra note 5, at 1112
(noting that the results presented in earlier studies may be consistent with a “deliberation hypothesis”
wherein judges vote sincerely, but deliberations affect their sincere views). Some critiques of the
strategic model emphasize the very low rate of Supreme Court review of circuit court opinions. See
Cross, supra note 2, at 1483−84.
10
Using a sample of Title VII sex discrimination cases, Kim finds that judges’ voting behavior is
not influenced by the preferences of the Supreme Court, but that the preferences of the other active
circuit judges do matter, suggesting that judges may be voting strategically in the shadow of en banc
review by the other circuit judges. Pauline T. Kim, Deliberation and Strategy on the United States
Courts of Appeals: An Empirical Exploration of Panel Effects, 157 U. PA. L. REV. 1319, 1367−74
(2009). But cf. Cross, supra note 2, at 1489 (noting that although prior studies suggest that circuit
judges are somewhat strategic, the effect is small relative to the ideological effect); Hettinger et al.,
supra note 7, at 134−35 (arguing that judges do not condition their dissent on whether intervention by
the circuit sitting en banc would lead to the judge’s preferred outcome, but rather that the ideological
disagreement between a judge and the majority opinion writer has more power in explaining the filing of
a dissent). Overall, the evidence suggests that it is the threat of an en banc review (and not review by
the Supreme Court) that may motivate judges to behave strategically, if they do behave strategically at
all.
11
For a summary of the literature discussing the major methodological and theoretical criticisms of
quantitative analyses seeking to link judicial behavior and ideology, see Harry T. Edwards & Michael A.
Livermore, Pitfalls of Empirical Studies That Attempt to Understand the Factors Affecting Appellate
Decisionmaking, 58 DUKE L.J. 1895, 1912−22 (2009) (arguing that the reliance on the attitudinal model
by empirical studies is due in part to the advantage of the model’s “parsimonious explanation” that
facilitates their methodological design).
12
For a discussion of the decision to publish and the limitations associated with studies relying on
datasets that exclude unpublished decisions, see Stephen L. Wasby, Unpublished Decisions in the
Federal Courts of Appeals: Making the Decision to Publish, 3 J. APP. PRAC. & PROCESS 325, 330−31
(2001) (arguing that published rulings are an unrepresentative sample of all appellate decisions). For a
review of the process and guidelines followed by appellate courts in preparing published and
unpublished opinions, as well as the related policy concerns, see generally Stephen L. Wasby,
Unpublished Court of Appeals Decisions: A Hard Look at the Process, 14 S. CAL. INTERDISC. L.J. 67
(2004) and Stephen L. Wasby, Publication (or Not) of Appellate Rulings: An Evaluation of Guidelines, 2
SETON HALL CIRCUIT REV. 41 (2005). The exclusion of unpublished decisions can be especially
problematic in studies that pool cases from different circuits, as studies have documented variation in
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problematic from an empirical perspective is that published decisions are
not a random sample of all decisions rendered by the appellate courts; in
particular, one concern is that whether a decision is published or not may be
correlated with the composition of the panel writing the opinion.13
To complicate matters further, the decision to publish may be a
strategic one; that is, the decision to publish may be correlated not just with
the composition of a panel, but also with the decision reached by that
panel.14 In his study of asylum decisions in the Ninth Circuit, David Law
finds a significant relationship between how a judge votes on the merits of a
case and whether the opinion in that case is published—publication
increases the likelihood that certain judges (Democrats) vote in favor of
granting asylum.15 However, Law finds no difference in publication rates
between Democratic- and Republican-led panels (conditional on whether
asylum was granted) or between unified and split panels.16 This is
consistent with the evidence presented by Deborah Merritt and James
publication rates across areas of law and circuits, which may result from different publication criteria
and treatment of unpublished opinions. See, e.g., Michael Hannon, A Closer Look at Unpublished
Opinions in the United States Courts of Appeals, 3 J. APP. PRAC. & PROCESS 199, 207−20 (2001)
(summarizing differences in publication practices by circuit and area of law); Robert A. Mead,
“Unpublished” Opinions as the Bulk of the Iceberg: Publication Patterns in the Eighth and Tenth
Circuits of the United States Courts of Appeals, 93 L. LIBR. J. 589, 603−06 (2001) (documenting
variations in the publication rates across different areas of the law in the Eighth and Tenth Circuits);
Deborah Jones Merritt & James J. Brudney, Stalking Secret Law: What Predicts Publication in the
United States Courts of Appeals, 54 VAND. L. REV. 71, 85−86 (2001) (finding differences in the
publication of unfair labor practice appeals across circuits); Donald R. Songer, Criteria for Publication
of Opinions in the U.S. Courts of Appeals: Formal Rules Versus Empirical Reality, 73 JUDICATURE 307,
308–09 (1990) (describing the publication criteria of the different circuits as “broad, vague and giv[ing]
little detailed direction”); Donald R. Songer et al., Nonpublication in the Eleventh Circuit: An Empirical
Analysis, 16 FLA. ST. U. L. REV. 963, 981−82 (1989) (documenting variations in the publication rates
across different areas of the law in the Eleventh Circuit).
13
See, e.g., Songer et al., supra note 12, at 977−83 (finding that Republican-led panels are more
likely to publish their liberal decisions than Democratic-dominated panels); Patricia M. Wald, A
Response to Tiller and Cross, 99 COLUM. L. REV. 235, 246−47 (1999) (presenting anecdotal evidence
from the D.C. Circuit showing that unified panels are more likely to affirm by unpublished opinions than
divided panels and that Republican-led unified panels are more likely to dispose of matters by
unpublished opinions).
14
For a review of the literature on the strategic use of publication rules by judges, see David S.
Law, Strategic Judicial Lawmaking: Ideology, Publication, and Asylum Law in the Ninth Circuit, 73 U.
CIN. L. REV. 817, 821−29 (2005).
15
See Law, supra note 14, at 853−61. The author argues that these results suggest that voting and
publication may be strategically interconnected: judges may be willing to agree with a decision that runs
contrary to their preferences if the opinion remains unpublished, but may file a dissent if the majority
chooses to publish the opinion. Id. A similar conclusion is reached by Keele et al., who find that in
their sample of cases involving the U.S. Forest Service, judges’ decisions follow their ideological
preferences in published opinions, but not in unpublished opinions. See Denise M. Keele et al., An
Analysis of Ideological Effects in Published Versus Unpublished Judicial Opinions, 6 J. EMPIRICAL
LEGAL STUD. 213, 223−32 (2009).
16
See Law, supra note 14, at 848−49, 861−62.
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275
Brudney suggesting that the likelihood of publication in labor law appeals is
not affected by the ideology of the panel, whether it is split or unified, or
the outcome of a case.17
As with previous studies, we find that the political composition of a
panel is a strong predictor of final case outcomes.18 The probability of
success of the U.S. government in criminal and immigration cases
decreases with the number of Democrats sitting on the panel.19 Similarly, a
plaintiff’s probability of success in civil rights and prisoner petition cases
increases with the number of Democrats on a panel.20 In addition, we also
find that panel composition affects variables that that are descriptive of the
process through which the panel reached that particular decision and that
are independent of the identity of the prevailing party in the appeal. Panels
dominated by Democratic appointees are more likely than panels dominated
by Republican appointees to hold oral arguments, fail to reach consensus
more often, and are more prone to reversing the decision being reviewed.21
These Democratic-led panels also take longer to prepare an opinion and are
more likely to publish their opinions than Republican-led panels.22
These differences in dissents, reversals, hearing oral arguments,
publication of opinions, and time to prepare an opinion are not readily
explained by a panel’s political and policy preferences and conceivably
could reflect variation in judges’ approach to the deliberation and decisionmaking process. For example, Democratic-led panels take longer to prepare
their opinions regardless of whether the outcome reached by the panel in
that decision is liberal or conservative.23 Similarly, Democratic-led panels
choose to hold oral arguments more often than Republican-led panels when
reviewing liberal as well as conservative lower court decisions.24 Our
analyses of the differences across panels in the treatment of lower court
decisions also reveal an interesting interaction between process and
outcome variables. Although Republican-led panels seem to reverse liberal
17
See Merritt & Brudney, supra note 12, at 94−103.
See infra Part III.A.
See infra pp. 282–84 and Table 1.
20
See infra pp. 282–84 and Table 1.
21
See infra pp. 286–89 and Table 2.
22
See infra pp. 286–89 and Table 2. In addition, we find that unified panels are more likely to
publish their opinions than split panels (whether Democratic- or Republican-led). Throughout this
Article, we refer to panels with two Democratic appointees and one Republican appointee as split
Democratic-led panels; similarly, we refer to panels with two Republican appointees and one
Democratic appointee as split Republican-led panels. We refer to panels in which the three member
judges are Democratic appointees as unified Democratic-led panels, and refer to those panels in which
the three judges are Republican appointees as unified Republican-led panels.
23
See infra Part III.B and Table 4.
24
See infra Part III.B and Table 5A.
18
19
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lower court decisions at a higher rate than conservative ones, unified
Democratic-led panels appear to be more even in their treatment of liberal
and non-liberal lower court decisions.25
We also find that two factors are behind the differences in publication
rates between Democratic- and Republican-led panels that we document.
First, Democratic-led panels are more likely to reach a liberal outcome than
Republican-led panels and, on average, decisions embodying liberal
outcomes tend to be published more often.26 Second, not only are unified
Democratic panels more likely to reach a liberal outcome, but they are also
more likely to publish their liberal decisions than unified Republican
panels.27 In other words, differences in publication rates appear to be
driven for the most part by the subset of liberal decisions. This relationship
between panel composition and publication raises questions about the
interpretation of the results in those empirical studies that rely solely on a
sample of published opinions. To illustrate this potential bias, we examine
the role played by the political preferences of the judges sitting in a panel
and the directionality of the lower court opinion being reviewed in the
panel’s decision whether or not to reverse in our subsets of published and
unpublished opinions. The results are substantially different in these two
subsets, with panels (in particular unified Democratic-led ones) appearing
to be much more ideologically driven in the subset of published opinions.28
The next Part presents a brief overview of the Ninth Circuit and of
general appellate procedures relevant to our empirical work, and introduces
our dataset and some of the variables used in our analyses. Our baseline
results are presented in Part III and further examined in greater detail in Part
IV. Part V concludes.
II. BACKGROUND ON THE NINTH CIRCUIT AND OUR DATASET
A. The Ninth Circuit
The U.S. Court of Appeals for the Ninth Circuit is the largest of the
thirteen courts of appeals (in terms of number of judges) and covers close to
20% of the U.S. population.29 The large number of judges and the diversity
25
See infra Tables 6, 7.
See infra Figure 1.
27
See infra Figure 1 and Table 3.
28
See infra Figures 3A, 3B.
29
Examining the Proposal to Restructure the Ninth Circuit: Hearing Before the S. Comm. on the
Judiciary, 109th Cong. (2006) (statement of Rachel Brand, Assistant Att’y Gen., U.S. Dep’t of Justice),
available at http://www.judiciary.senate.gov/hearings/testimony.cfm?id=e655f9e2809e5476862f735
da11bf1f9&wit_id=e655f9e2809e5476862f735da11bf1f9-2-1. The Ninth Circuit has appellate
26
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It’s the Journey, Not the Destination
277
of legal issues that the court faces make studying decision-making in the
Ninth Circuit particularly rewarding, as it provides variation along these
dimensions, while holding constant the written and unwritten practices
relating to the hearing of oral arguments, the writing of opinions and
dissents, and the treatment of lower court decisions.30 Below, we discuss
two features of the Ninth Circuit procedural rules that will guide us in
interpreting our results: the assignment of cases to judges and the Circuit’s
en banc review procedure.
1. Assignment of Cases to Judges
Once the briefs in an appeal have been filed, a staff attorney classifies
the case by type, issue, and difficulty, assigning it a weight intended to
measure the relative amount of time and effort that such a case should
demand.31 The place of a particular case on the court’s calendar is a
function of both the statutory priority and the length of time the appeal has
been pending.32 The clerk sets the time and place of the court calendars,
with each court calendar usually consisting of one week of multiple
sittings.33 A computer then randomly assigns judges to particular weeks on
the calendars.34 At the time judges are assigned to panels, the clerk does
not know which cases will ultimately be allocated to each of the panels.35
jurisdiction over the district courts located in the states of Alaska, Arizona, California, Hawai’i, Idaho,
Montana, Nevada, Oregon, and Washington, as well as over the territorial courts of Guam and the
Northern Mariana Islands. Map of the Ninth Circuit, U.S. COURTS FOR THE NINTH CIRCUIT,
http://www.ca9.uscourts.gov/content/view.php?pk_id=0000000135 (last visited Oct. 14, 2012). Some
have argued that the circuit’s large size and the diverse scope of legal issues arising in its different states
prevent it from being administered efficiently and maintaining a coherent body of law. See generally
Stefanie A. Lindquist, Bureaucratization and Balkanization: The Origins and Effects of DecisionMaking Norms in the Federal Appellate Courts, 41 U. RICH. L. REV. 659 (2007).
30
See generally Lindquist, supra note 29.
31
See 9TH CIR. R., COURT STRUCTURE AND PROCEDURES § E(1).
32
Direct criminal appeals receive preference and are placed on the first available calendar after
briefing is completed. See FED. R. APP. P. 45(b)(2). Many other cases are accorded priority by statutory
priority or the length of time the cases have been pending. See 9TH CIR. R. 34-3.
33
9TH CIR. R., COURT STRUCTURE AND PROCEDURES § E(4), (5).
34
9TH CIR. R., COURT STRUCTURE AND PROCEDURES § E(2). Panels consist of no fewer than two
members of the Ninth Circuit, at least one of whom must be an active circuit judge. Id. § E(5). Each
active judge is expected to hear approximately eight monthly calendars of five panel sittings each during
a given year. U.S. COURT OF APPEALS FOR THE 9TH CIRCUIT, GENERAL ORDERS § 3.2(b) (2011)
[hereinafter GENERAL ORDERS], available at http://www.ca9.uscourts.gov/datastore/uploads/rules/
general_orders/general_orders11_11.pdf. District judges are brought up to sit with the court, by
designation, within the first year of being appointed. Id. § 3.3(a). Senior circuit judges are given a
choice as to how many cases they desire to hear and may choose not to travel far from their home base.
Id. § 3.2(c). In addition, district court judges or visiting judges (from other circuits) may be assigned to
a panel upon the recusal of a circuit judge initially receiving the case. Id. § 3.2(h).
35
9TH CIR. R., COURT STRUCTURE AND PROCEDURES § E(2). There are some noteworthy
exceptions to the rule of random assignment of cases to panels. See id. § E(4). A case heard on a prior
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Once they have read the parties’ briefs, the members of the panel choose the
cases for which they wish to hold oral arguments.36
The names of the judges on each panel are released to the general
public on the Monday of the week preceding arguments, and once these are
revealed motions for continuance may not be filed.37 After oral arguments,
the judges in the panel confer on the cases they have heard and each judge
then expresses his or her tentative views with votes cast in reverse order of
seniority.38 After this conference, the judges reach a tentative decision
regarding the disposition of each case and whether it should be in the form
of a published opinion.39 Each judge sitting in the panel is then assigned a
subset of the cases by the presiding judge for the preparation of a final
opinion.40
The random assignment of judges and cases to panels is crucial for our
identification strategy, as it will allow us to draw causal inferences on the
effect of panel composition in our empirical analyses below. To verify that
random assignment took place, in Part II.B.2 we provide evidence that
panel composition is orthogonal to case characteristics.
appeal may be set before the same panel upon a later appeal. Id. If the panel that originally heard the
matter does not specify its intent to retain jurisdiction over any further appeal, the parties may file a
motion to have the case heard by the original panel. Id. Matters on remand from the U.S. Supreme
Court are referred to the panel that previously heard the matter. Id. In addition, efforts are made to
assign several cases on the same subject to a panel on a given day (e.g., a panel may receive several
immigration cases), and if there are cases related to one that has been assigned to a particular panel,
these may also be assigned to that panel. See GENERAL ORDERS, supra note 34, at § 3.3(b).
36
FED. R. APP. P. 34(a)(2). Any party may file (or be required by the court to file) a statement
explaining why oral argument should or should not be held. Id. at 34(a)(1). Oral argument must be
allowed in every case unless the three judges in the panel unanimously agree that it is unnecessary
because (i) the appeal is frivolous, (ii) the dispositive issues have been authoritatively decided, or (iii)
the facts and legal arguments presented in the briefs and record are enough for the panel to reach a
decision. Id. at 34(a)(2).
37
See 9TH CIR. R., COURT STRUCTURE AND PROCEDURES § E(3). This timing differs from that of
the D.C. Circuit, where panels are announced before litigants file their briefs, potentially affecting the
mix of cases heard by judges, as marginal litigants could drop their appeal or decide to spend fewer
resources depending on the panel’s membership. See generally Richard L. Revesz, Litigation and
Settlement in the Federal Appellate Courts: Impact of Panel Selection Procedures on Ideologically
Divided Courts, 29 J. LEGAL STUD. 685 (2000).
38
9TH CIR. R., COURT STRUCTURE AND PROCEDURES § E(8).
39
Id. The Ninth Circuit rules set the criteria for publishing an opinion. Opinions that may be
published are those that (i) establish, modify, clarify, or criticize a rule of law, (ii) call attention to a rule
of law that has been overlooked, (iii) involve issues of substantial public importance, (iv) follow a
reversal or remand by the Supreme Court, or (v) are accompanied by a separate concurring or dissenting
expression, and the author of such separate expression requests publication. 9TH CIR. R. 36-2.
Unpublished (memoranda) dispositions and orders have no precedential value. Id. at 36-3(a). Although
unpublished opinions issued during the time period under analysis (1991−2006) may not be cited
(subject to certain exceptions), unpublished dispositions or orders issued on or after January 1, 2007
may be cited. Id. at 36-3(b)−(c); FED. R. APP. P. 32.1(a).
40
9TH CIR. R., COURT STRUCTURE AND PROCEDURES § E(8).
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It’s the Journey, Not the Destination
279
2. Limited En Banc Review
The Ninth Circuit’s limited en banc review procedure has been of
particular interest to commentators.41 While cases accepted for rehearing en
banc in other circuits are heard by all active judges, in the Ninth Circuit en
banc panels are composed of the chief judge and ten randomly selected
active judges.42 Under this limited en banc review procedure, it might be
more difficult for a judge sitting on a three-judge panel to predict the
composition of the en banc panel that could review the panel’s decision
(unless the political composition of the circuit was highly uneven). In such
a setting, a three-judge panel may even decide to defy circuit precedent in
the hope of drawing a favorable panel for the en banc rehearing.43
Arguably, under the Ninth Circuit’s limited en banc review procedure,
panel members have less incentive to behave strategically in response to the
ideology of the other members of the circuit court. This allows us to
explore the interaction of ideology and judicial behavior without having to
worry that much about the implications of the strategic model of judicial
behavior.44
B. Data and Construction of Variables
1. Data
We retrieved from Lexis all available published and unpublished Ninth
Circuit opinions for the period 1991−2006 for which the names of the
judges were available. From the text of these opinions, we extracted the
date of the judgment, the name of the judges in the panel, the name of the
district court judge (when applicable), whether a dissenting opinion was
filed (and the name of its author), the disposition of the case, and the docket
number for the appellate case (and the district court case, when applicable).
41
See FED. R. APP. P. 35(a). Generally, en banc rehearings are not favored and ordinarily are not
ordered unless: (1) en banc consideration is necessary to maintain uniformity of the court’s decisions; or
(2) the proceeding involves a question of exceptional importance. Id.
42
9TH CIR. R. 35-3.
43
Some authors have argued that this limited en banc procedure, coupled with the circuit’s size,
adversely affects the quality of its output. See, e.g., Richard A. Posner, Is the Ninth Circuit Too Large?
A Statistical Study of Judicial Quality, 29 J. LEGAL STUD. 711, 713−16 (2000) (noting that the Ninth
Circuit has the highest rate of summary reversals by the Supreme Court and that it ranks eleventh among
regional circuits in out-of-circuit citations); Kevin M. Scott, Supreme Court Reversals of the Ninth
Circuit, 48 ARIZ. L. REV. 341, 352−53 (2006) (arguing that the adoption of the limited en banc
procedure has played an important role in increasing this reversal rate).
44
See discussion of the strategic model of judicial behavior, supra notes 6−10 and accompanying
text.
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For each docket number, we restricted our analysis to the first disposition of
the case by a three-judge panel and excluded later rehearings. Using the
docket numbers and date of judgment obtained from the text of the
opinions, we matched each opinion to the Administrative Office of the U.S.
Courts Database (“AOC Database”).45 The AOC Database contains
information on the outcome of the case (e.g., whether the judgment below
was reversed or affirmed), the type of case (e.g., Administrative, Criminal,
Civil-U.S., Civil-Private, and Bankruptcy), the nature of the suit, whether
the United States was a plaintiff or defendant, and whether the United
States was the appellant or the appellee, among other data.46 Biographical
information for the appellate and district court judges in the database was
obtained from the Multi-User Data Base on the Attributes of U.S. Appeals
Court Judges.47
Our final sample contains 62,767 cases.48 The majority of these are
civil cases, either involving the United States (13.98%) or private parties
(38.05%).49 Criminal appeals account for 28.52% of the sample.50 The
U.S. government is a party in 59.35% of the cases, appearing as an
appellant in 3.30% of them.51 Panels held oral arguments in 40.63% of the
cases and published their opinions 17.19% of the time.52 The majority of
cases (86.78%) affirm the decision being appealed.53 A judge files a dissent
in 4.12% of the cases in the sample.54 Approximately three-quarters of the
cases in the sample are heard by split panels. Republicans dominate panels
in 46.56% of the cases (11.53% of the time sitting in unified panels and in
35.03% of the cases dominating a split panel). Democrats dominate panels
45
The AOC database is available at the Inter-University Consortium for Political and Social
Research website, http://www.icpsr.umich.edu/icpsrweb/ICPSR/. For an analysis of the reliability of the
AOC Database, see Theodore Eisenberg & Margo Schlanger, The Reliability of the Administrative
Office of the U.S. Courts Database: An Initial Empirical Analysis, 78 NOTRE DAME L. REV. 1455
(2003).
46
For cases in which the United States was not a party, we use the AOC Database district court
level data to determine the disposition at the lower level.
47
Gary Zuk et al., Multi-User Database on the Attributes of United States Appeals Court Judges
1801−2000, ICPSR (2009), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/6796. For more recent
appointees, we supplemented this dataset with information from the Federal Judicial Center’s
Biographical Directory of Federal Judges. History of the Federal Judiciary, FED. JUDICIAL CTR.,
http://www.fjc.gov/history/judges.html (last visited Nov. 22, 2012). We do not have biographical
information for all judges who are members of the panel for 553 cases, which we drop from our sample.
48
See infra Appendix Table 1.
49
See infra Appendix Table 1.
50
See infra Appendix Table 1. The remaining cases are appeals from administrative actions
(16.52%), the vast majority of which are immigration cases. See infra Appendix Table 1.
51
See infra Appendix Table 1.
52
See infra Table 2.
53
See infra Table 2 (only 13.21% of cases were reversed).
54
See infra Table 2.
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281
in about 53.44% of the cases (13.87% of the time in unified panels and
39.57% in split panels). Altogether, the database contains approximately
300 judges, including visiting circuit judges and district court judges who
are assigned to panels.55 Of these judges, fifty-five Ninth Circuit judges
appear in 500 or more cases; thirty of these judges are Democratic
appointees.
2. Evidence of Random Assignment
The interpretation of the results presented throughout this Article
hinges on whether the random assignment of judges and cases to panels
holds for the cases in our sample. Although, as noted in Part II.A, judges
and cases are randomly assigned to panels,56 random assignment may not
have taken place due to strategic actions taken by litigants. For example, a
party may drop a case or be more willing to settle once panel membership is
disclosed (which would result in a correlation between the characteristics of
the cases that we examine and the characteristic of the panels that hear
them).57
To confirm that the cases in our sample have been randomly allocated
across panels, we regress a series of case characteristics on a set of indicator
variables measuring the political composition of the panel (i.e., the number
of Democratic appointees) and a set of year fixed-effects.58 These
55
In 13.08% of the cases there is a district court judge serving in the panel, while in 8.12% there is
a judge from outside the Ninth Circuit.
56
See supra notes 33−34 and accompanying text.
57
See discussion on the strategic action of litigants, supra note 37. Since in the Ninth Circuit the
members of a panel are announced shortly before oral arguments, we doubt that strategic actions of
litigants are inducing a material bias in our sample.
58
Following existing studies, throughout this Article we proxy for a judge’s political ideology by
using the party of that judge’s appointing president. It should be noted that some scholars have
proposed more complex continuous scores to measure ideology. For a discussion on the construction of
the various measures of judicial ideology and their relative performance, see generally Joshua B.
Fischman & David S. Law, Empirical Research on Decision-Making in the Federal Courts: What Is
Judicial Ideology, and How Should We Measure It?, 29 WASH. U. J.L. & POL’Y 133 (2009). A number
of studies have found a strong correlation between the preferences of appointing presidents and their
appointee-judges’ voting behavior. See, e.g., Susan B. Haire, Judicial Selection and Decisionmaking in
the Ninth Circuit, 48 ARIZ. L. REV. 267, 275−84 (2006) (examining the voting of judges in the Ninth
Circuit in the years 1977−2002 by party of the appointing president); Gregory C. Sisk & Michael Heise,
Judges and Ideology: Public and Academic Debates About Statistical Measures, 99 NW. U. L. REV 743,
787−89 (2005) (finding a close relationship between the party of a judge’s appointing president and that
judge’s common space ideology score); Donald R. Songer & Martha Humphries Ginn, Assessing the
Impact of Presidential and Home State Influences on Judicial Decisionmaking in the United States
Courts of Appeals, 55 POL. RES. Q. 299, 316 (2002) (finding a strong association between the
preferences of an appointing president and the votes of his appointees to the court of appeals during the
period 1960−1993). Other studies have found that common space scores and the party of appointing
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specifications test whether certain types of panels are more likely to be
assigned certain types of cases. The first set of these specifications
considers the following case characteristics: whether the United States is a
party; whether the United States is the appellee; and whether the appeal
involves a criminal case, a U.S. civil case, a private civil case, a civil rights
case, an immigration case, or a prisoner petition case. The results of these
specifications are presented in Appendix Table 1. Another set of
specifications focuses on the directionality of the decision being reviewed
by the panel on appeal—whether the district court judge was a Democratic
appointee, whether the defendant prevailed in a criminal case, and whether
the plaintiff prevailed in a civil rights or prisoner petition case. The results
for this second set of specifications are presented in Appendix Table 2.
Overall, the results strongly suggest that cases are randomly allocated
across panel types—none of the coefficients for each panel type are
statistically significant and testing the three coefficients together yields Fstatistics smaller than two.59
III. PANEL COMPOSITION AND DECISION-MAKING
A. Panel Composition and Case Outcomes
Our initial set of analyses examines the relationship between panel
composition and case outcomes. We classify panels based on the number
of Democratic appointees and test whether panel composition is related to
the outcome in criminal, immigration, prisoner petition, and civil rights
cases by estimating the following specification:60
α
1
2
3
(1)
where
is the outcome of interest (we consider four such outcomes;
whether the U.S. lost in a criminal or immigration appeal and whether the
1,
plaintiff prevailed in a prisoner petition or civil rights case);61
president are nearly equivalent in predicting judicial voting. See, e.g., Fischman & Law, supra, at
190−98.
59
See infra Appendix Tables 1, 2.
60
Throughout this Article we estimate specifications as linear probability models. As a robustness
check, in a set of unreported analyses we estimate comparable logistic regressions and find the marginal
effects to be similar.
61
We estimate specification (1) separately for each of these four types of cases. In criminal and
immigration cases our outcome variable is an indicator variable equal to 1 if the appellate panel fully
reversed a case where the United States was an appellee or if the court did not fully reverse a case in
which the United States was an appellant. For prisoner petition and civil rights cases we use an
indicator variable equal to 1 if the appellate panel fully reversed a case where the plaintiff in a civil case
was an appellant or if the panel did not fully reverse a case where the plaintiff was an appellee.
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283
2 , and
3 are dummy variables indicating whether there were
one, two, or three Democratic appointees in the panel hearing case i;62
is a set of year fixed-effects;63 and is an error term.64
Three interesting patterns emerge from the estimates of these
specifications, which are presented on Table 1. First, consistent with
existing studies, the ideological composition of a panel is strongly
correlated with the identity of the prevailing party.65 For example, the
probability of a decision being unfavorable to the U.S. government in
criminal and immigration appeals increases with the number of Democrats
sitting in the panel.66 On the other hand, plaintiffs in civil rights and
prisoner petition cases are more likely to prevail when Democratic
appointees dominate the panel.67 Another noteworthy pattern is that the
estimated differences between Democratic- and Republican-led unified
panels, which are measured by the coefficient on Dem3, are quite large in
magnitude (representing at least 60% of the corresponding sample average)
and highly significant for each of the four types of cases we analyze.68 On
the other hand, the estimated differences between split Democratic- and
Republican-led panels (measured by the coefficient difference Dem2Dem1) are markedly attenuated relative to their unified analogues (the
62
For example,
1 is an indicator variable equal to 1 if only one judge in the panel hearing
case i was appointed by a Democratic president (and 0 otherwise);
2 equals 1 if two of the judges
in the panel are Democratic appointees; and
3 equals 1 if all three judges in the panel are
Democratic appointees. The omitted group in these regressions is
0 , a panel consisting of three
Republican appointees.
63
This set of year-specific fixed-effects captures changes in the composition of the judiciary in the
Ninth Circuit as well as shocks or trends affecting judicial decision-making that are common to all
judges in a given year. One could also control for the composition of the judiciary by creating fixedeffects for each “roster” of active judges (rosters change as active judges retire and are replaced by new
appointees). The results presented in this Article are robust to the use of this alternative measure as a
control.
64
In all calculations of statistical significance throughout this Article, standard errors are clustered
at the three-judge group level.
65
See infra Table 1. These results are consistent with studies such as Law’s, which finds that
Democratic-led panels are significantly more likely than Republican-led panels to grant some form of
relief to asylum-seekers and that the probability of a pro-asylum decision jumps significantly with each
additional Democratic appointee on the panel. See Law, supra note 14, at 843, 847−48.
66
See infra Table 1, columns (1) and (2).
67
See infra Table 1, columns (3) and (4).
68
See infra Table 1. As an example, let us consider criminal cases (see column (1) of Table 1).
The coefficient on Dem3 indicates that unified Democratic panels are 6.98 percentage points more likely
than unified Republican panels to find in favor of the defendant in a criminal appeal. Given that, on
average, defendants prevail on appeal 9.95% of the time, the relative magnitude of this difference of
6.98 percentage points is quite substantial.
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magnitude of the difference of coefficients on
21 is generally
one-third to one-half of the magnitude of the coefficient on
3).69
Notably, while split Republican-led panels do not appear to behave
significantly differently from unified Republican-led panels, unified
Democratic-led panels do behave significantly differently from split
Democratic-led panels.70 The magnitudes of the coefficients on Dem1
(which measures the difference between split and unified Republican-led
panels) are relatively small across the four types of cases we analyze; in
comparison, the differences between the coefficients on Dem3 and Dem2
(which measure the differences between split and unified Democratic-led
panels) are always statistically significant and of greater magnitude than the
coefficients on Dem1.71
69
See infra Table 1. Let us again consider criminal cases (column (1) of Table 1). The difference
between the coefficients on Dem2 and Dem1 (i.e., Dem2-Dem1) indicates that split Democratic-led
panels (i.e., panels with two Democratic appointees) are 3.55 percentage points more likely than split
Republican-led panels (i.e., panels with two Republican appointees) to find in favor of the defendant in a
criminal appeal. Although this difference is large and statistically significant, it is much smaller than the
analogous difference between unified Democratic and Republican panels, 6.98 percentage points (i.e.,
the coefficient on Dem3).
70
See infra Table 1 and supra note 69.
71
See infra Table 1. Consider immigration cases (column (2) of Table 1). The coefficient on
Dem1 indicates that split Republican panels (i.e., panels with two Republican appointees) are 3.59
percentage points more likely than unified Republican panels (i.e., panels with three Republican
appointees) to find in favor of the individual in an immigration appeal. In contrast, the difference
between the coefficients on Dem3 and Dem2 (i.e., Dem3-Dem2) indicates that unified Democratic-led
panels (i.e., panels with three Democratic appointees) are 9.30 percentage points more likely than split
Democratic-led panels (i.e., panels with two Democratic appointees) to find in favor of the individual in
an immigration appeal.
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285
TABLE 1. PANEL CHARACTERISTICS AND CASE OUTCOMES
(1)
(2)
(3)
(4)
Defendant
Win:
Criminal
Individual
Win:
Immigration
Plaintiff
Win:
Prisoner
Petition
Plaintiff
Win:
Civil
Rights
Dem1
0.0066
0.0359
0.0185*
0.0304**
[0.0080]
[0.0238]
[0.0111]
[0.0152]
Dem2
0.0421***
0.0980***
0.0454***
0.0665***
[0.0089]
[0.0239]
[0.0118]
[0.0163]
0.0698***
0.1910***
0.0865***
0.1070***
[0.0123]
[0.0379]
[0.0173]
[0.0220]
Dem3-Dem2
0.0277
0.0930
0.0411
0.0405
Prob>F
0.0151
0.0027
0.0108
0.0413
Dem2-Dem1
0.0355
0.0621
0.0269
0.0361
Prob>F
0.0000
0.0002
0.0049
0.0034
Mean Outcome
Observations
R-squared
0.0995
17,023
0.008
0.1460
8,115
0.040
0.1327
9,620
0.015
0.1395
5,565
0.011
Panel type
Dem3
Note: Robust standard errors, clustered at the three-judge group level, in brackets (*
significant at 10%; ** significant at 5%; *** significant at 1%). The outcome in column (1)
is an indicator variable equal to 1 if the appellate outcome was favorable to the defendant in
a criminal case; in column (2) the outcome is an indicator variable equal to 1 if the appellate
outcome was favorable to the individual in an immigration case; in column (3) the outcome
is an indicator variable equal to 1 if the appeal was favorable to the plaintiff (petitioner) in a
case involving a prisoner petition; and in column (4) the outcome is an indicator variable
equal to 1 if the appeal was favorable to the plaintiff in a civil rights case. The explanatory
variables of interest are Dem1, Dem2, and Dem3—a set of dummies indicating the number
of Democrats in the panel. All regressions include year fixed-effects.
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B. Panel Composition and Procedural Outcomes
Next, we ask whether panel composition is also related to variables that
are descriptive of the process of adjudication and independent of the
identity of the prevailing party. We consider the following process
variables: whether a judge in the panel dissented, whether the panel
reversed the decision being reviewed, whether the panel held oral
arguments, whether the panel published the opinion, and the time elapsed
between oral arguments and the completion of the opinion.72 To analyze
the relationship between these variables and the composition of the panel,
we estimate for each such variable a specification similar to equation (1),73
, a set
but we include as part of our set of controls the variable
of fixed-effects corresponding to different types of cases.74 The results of
these analyses are presented in Table 2.75
Not surprisingly, dissents are more likely to be filed in cases heard by
split panels than in cases heard by unified panels.76 Although this
difference between split and unified panels holds when looking separately
at Republican- and Democratic-led panels, dissents are in general more
likely to be filed in Democratic-led panels.77 For instance, dissents are
more likely to be filed in those split panels led by Democrats than in split
panels led by Republican appointees (i.e., compare the coefficient on Dem1
with the coefficient on Dem2); the difference (0.014) represents over 30%
of the average rate of dissent for cases heard by split panels.78 A similar
pattern holds for cases heard by unified panels—the dissent rate in unified
72
See infra Table 2.
See infra Table 2. The outcome variables in these regressions are (i) Reverse, an indicator
variable equal to 1 if the appellate panel reversed in full the lower court or agency decision; (ii) Hearing,
an indicator variable equal to 1 if the appellate panel held oral arguments; (iii) Published, an indicator
variable equal to 1 if the appellate panel published the opinion; and (iv) Length, the time elapsed
between the hearing date and the opinion date (for cases in which oral arguments were held), winsorized
at 5%. See infra Table 2.
74
See infra Table 2. Using the classification of cases from the AOC Database, we assign cases to
one of the following categories to construct these case type fixed-effects: Administrative-Immigration,
Administrative-Others and Bankruptcy, Civil (U.S.), Civil (Private), Civil Rights, Prisoner Petitions, and
Criminal. For a discussion of the AOC Database, see supra notes 45−46 and accompanying text.
75
To verify that the substance of the results we describe below do not differ greatly across types of
cases, we estimate the specification separately for each case type (rather than just including case type
fixed-effects). Although there is a slight variation of the magnitude of the coefficients, their signs and
relative magnitudes, as well as their statistical significance, are fairly homogeneous across the different
types of cases. See infra Table 2.
76
See infra Table 2.
77
See infra Table 2, column (1).
78
See infra Table 2, column (1).
73
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It’s the Journey, Not the Destination
287
Democratic panels is significantly higher than in unified Republican panels
(see coefficient on Dem3, 0.015).79
The rate of reversals, the likelihood of oral arguments being held, and
the probability of an opinion being published all increase with the number
of Democrats sitting in the panel.80 The magnitudes of the variation in
these variables across panel types are substantial and statistically
significant. Let us start by analyzing the coefficient on
3, which
measures the difference between unified Democratic and unified
Republican panels. For reversals, this coefficient is 0.085, indicating that
unified Democratic panels are 8.5 percentage points more likely than
unified Republican panels to reverse the opinion being reviewed.81 This
difference represents over 60% of the average reversal rate of our sample.82
Similarly, unified Democratic panels are 14.2 percentage points more likely
to hold oral arguments than unified Republican panels, a difference
representing approximately 35% of the average publication rate in the
sample.83 Conditional on hearing oral arguments, unified Democratic
panels take, on average, twelve days longer than unified Republican panels
to finalize their opinions, a difference representing over 15% of the sample
average.84 Unified Democratic panels are also more likely to publish their
opinions; their publication rate is 4.64 percentage points higher than the
publication rate of unified Republican panels, a difference representing over
25% of the average publication rate in our sample.85
To compare the behavior of split Democratic- and Republican-led
panels, we estimate the differences between the coefficients
2 and
1 (which are also provided on Table 2, along with their corresponding
F-statistics).86 Differences between split panels track the pattern found in
unified panels: split Democratic-led panels are more likely than
Republican-led split panels to reverse the decisions they review, to hold
oral arguments, and to publish their opinions, which they also take longer to
prepare.87 However, these differences between split panels are quite
attenuated in magnitude relative to the differences between Democraticand Republican-led unified panels. For example, the difference in
publication rate between split Democratic- and split Republican-led panels,
79
80
81
82
83
84
85
86
87
See infra Table 2, column (1).
See infra Table 2.
See infra Table 2, column (2).
See infra Table 2, column (2).
See infra Table 2, column (3).
See infra Table 2, column (5).
See infra Table 2.
See infra Table 2.
See infra Table 2.
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0.017, is relatively small (representing just under 10% of the sample
average, 0.172) and is barely statistically significant at the 10% level.88
TABLE 2. PANEL CHARACTERISTICS AND PROCEDURAL OUTCOMES
(1)
(2)
(3)
(4)
(5)
Panel type
Dissent
Reverse
Hearing
Publication
Time to
Write
Dem1
0.0103**
[0.0041]
0.0136*
[0.0077]
0.0353
[0.0324]
-0.0060
[0.0154]
-1.024
[2.930]
Dem2
0.0241***
[0.0051]
0.0484***
[0.0084]
0.0868**
[0.0341]
0.0106
[0.0157]
7.331**
[2.911]
Dem3
0.0146***
[0.0056]
0.0848***
[0.0115]
0.142***
[0.0425]
0.0464**
[0.0186]
12.070***
[3.306]
Dem3-Dem2
Prob>F
-0.0095
0.1170
0.0364
0.0002
0.0552
0.1209
0.0358
0.0102
4.739
0.0394
Dem2-Dem1
Prob>F
0.0138
0.0019
0.0348
0.0000
0.0515
0.0342
0.01655
0.0917
8.355
0.0000
0.0412
0.1322
0.4063
0.1719
76.4187
62,767
60,690
62,657
62,138
24,547
0.006
0.016
0.110
0.051
0.034
Mean
Outcome
Observations
R-squared
Note: Robust standard errors, clustered at the three-judge group level, in brackets (*
significant at 10%; ** significant at 5%; *** significant at 1%). The outcome in column (1)
is an indicator variable equal to 1 if a judge dissented; in column (2) the outcome is an
indicator variable equal to 1 if the panel reversed the decision being reviewed; the outcome
in column (3) is an indicator variable equal to 1 if the panel held oral arguments; the
outcome in column (4) is an indicator variable equal to 1 if the opinion was published; and
the outcome variable in column (5) is equal to the number of days between oral arguments
and the opinion date (winsorized at the 5% level). The explanatory variables of interest are
Dem1, Dem2, and Dem3—a set of dummies indicating the number of Democrats in the
panel. All regressions include year fixed-effects and case type fixed-effects.
At a first glance, these differences across panels in dissents, reversals,
hearing oral arguments, publication of opinions, and time to prepare an
88
See infra Table 2, column (4).
2013]
It’s the Journey, Not the Destination
289
opinion are not necessarily explained by the ideology-based preferences of
the panel members over certain outcomes (i.e., propensity to favor certain
type of litigants) and could reflect variation in judges’ approach to the
deliberation and decision-making process.89 One may wonder, however,
whether differences across panels in these procedural variables are
somehow related to the differences in case outcomes across panels that we
documented in Table 1.90 To further explore whether these differences
across panels in procedural variables are linked to the ideology and political
preferences of the judges sitting in a panel, in the next Part we explore the
interaction of these process-related variables with the ideological direction
of a panel’s decision and the political and policy preferences of the judges
assigned to the panel.
IV. PROCEDURAL PREFERENCES IN DECISION-MAKING
A. Differences in Publication Rates
Our initial analysis reveals two general facts about the relationship
between a panel’s composition and the panel’s decision whether or not to
publish its opinion. First, unified panels are more likely to publish their
opinions than split panels.91 Second, split and unified Democratic-led
panels are more likely to publish their opinions than split and unified
Republican-led panels, respectively.92 According to the estimates presented
in column (4) of Table 2, the difference in publication rates between unified
89
See supra Table 2.
Compare supra Table 1 with supra Table 2.
91
See supra Table 2. We should note that the magnitude of this difference in publication rates
between split and unified panels is much smaller for Republican-led panels (see magnitude of the
coefficient on Dem1 at Table 2, column (4), 0.006) than Democratic-led panels (see magnitude of the
coefficient difference Dem3-Dem2 at Table 2, column (4), 0.036). Though partially contradicting Law’s
empirical findings, this general result confirms his hypothesis that undivided panels may publish at a
more aggressive rate than divided panels, in the absence of a minority judge to slow the lawmaking
inclinations of the majority. See Law, supra note 14, at 861−62. This result also partially contradicts
Merritt and Brudney’s study, in which the authors find that unified panels publish at the same rate as
divided panels. See Merritt & Brudney, supra note 12, at 103−07.
92
See supra Table 2. Initially, one may posit that the higher rate of publication by Democratic-led
panels simply reflects the higher rate of dissensus that characterizes decision-making in these panels (see
Table 2, column (1)). This theory is attractive since, on average, the majority publishes its decision
55.50% of the time when there is a dissent. On the other hand, when there is no dissenting judge, panels
publish their opinions just 15.56% of the time. However, Democratic-led panels have lower publication
rates than Republican-led panels in cases in which a dissent is filed. This is true for split panels (52.21%
vs. 56.70%) as well as for unified panels (58.63% vs. 65.73%). Also, Democratic-led panels have
higher publication rates than Republican-led panels in cases in which no dissent was filed. This is true
for split panels (15.28% vs. 14.67%) as well as for unified panels (18.29% vs. 15.48%).
90
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Democratic and unified Republican panels is 0.0464 (i.e., the coefficient on
Dem3), which represents approximately 27% of the average publication rate
in the sample.93 The difference between split Democratic-led panels and
split Republican-led panels is much smaller, 0.0166 (i.e., the coefficient
difference Dem2-Dem1), representing just under 10% of the average
publication rate in the sample.94
Understanding the relationship between panel composition and
publication is important for a number of reasons. Many studies of judicial
decision-making have only examined published cases.95 If published
decisions are not a random sample of the universe of decisions (e.g., if
publication is correlated with panel composition), then the interpretation of
the results in these studies is less straightforward.96 In addition, since
published cases tend to carry more weight than unpublished decisions,
systematic differences in publication rates across panels could have
implications for the development of precedent.97 Of particular interest to us
is whether the decision to publish an opinion may serve as a channel
through which panels advance their ideology by selectively choosing which
of their decisions to publish. To address this question, in our analyses
below we measure the ideological directionality of a panel’s decision by
following the methodology used in the Songer U.S. Court of Appeals
Database and code a decision as “liberal” if: the defendant prevailed in a
criminal case; the individual prevailed in an immigration case; the plaintiff
prevailed in a civil rights case; or the petitioner prevailed in a prisoner
petition case.98
93
See supra Table 2.
See supra Table 2. Although consistent with Law’s general finding that unified Democratic
panels published 12.6%, while unified Republican-led panels published 4.7%, of their decisions, these
results seem to contradict Merritt and Brudney’s finding of no significant relationship between the
number of Democratic appointees on a panel and the likelihood of publication. See Law, supra note 14,
at 861−62; Merritt & Brudney, supra note 12, at 98−100.
95
See supra notes 12−13 and accompanying text.
96
See supra notes 12−13 and accompanying text.
97
If split panels are less likely to publish their opinions than unified panels and published opinions
carry more precedential weight than unpublished opinions, then legal precedent is more likely to be
established by unified panels, which may tend to be more polarized along ideological lines in their
decision-making. Note that unpublished dispositions and orders have no precedential value. 9TH CIR.
R. 36-3(a).
98
See DONALD R. SONGER, THE UNITED STATES COURT OF APPEALS DATA BASE
DOCUMENTATION FOR PHASE I, available at http://artsandsciences.sc.edu/poli/juri/cta96_codebook.pdf.
As a result, our analyses in this Part consider only those immigration, criminal, civil rights, and prisoner
petition cases for which we have the ideological directionality of the panel’s opinion. See supra Table
1. Throughout this Article we follow this methodology when coding the directionality of lower court or
appellate court decisions.
94
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In the set of cases we consider below, unified Democratic-led panels
publish their opinions 14.8% of the time, over 30% higher than the average
publication rate for unified Republican panels (11.3%).99 One could
imagine a number of factors that could be driving this difference. First,
Democratic-led panels may tend to reach liberal decisions more often than
Republican-led panels. In fact, Democratic-led unified panels reach a
liberal outcome 17.88% of the time, while their Republican counterparts do
so 7.81% of the time.100 If liberal decisions are on average more likely to
be published than non-liberal ones (and on average they are—29.8% vs.
9.7%, respectively), then differences in publication rates would mostly
follow mechanically, even if Democratic- and Republican-led panels had
the exact same publication rates for liberal and non-liberal decisions.101
A more interesting question is whether or not, conditional on case
outcome, Democratic and Republican panels publish their opinions at the
same or different rates. For example, if Democrats were twice more likely
than Republicans to publish their opinions, regardless of whether or not the
outcome was liberal, then one could argue that outcome-based preferences
have a low impact on the decision to publish; that is, differences in
publication rates would mostly reflect different proclivities for
publication.102 However, if differences in these conditional probabilities
varied across case outcomes, then one could argue that the decision to
publish could be being used as a channel to advance the panel’s ideological
preferences. This would be the case if, for example, Democrats were 50%
more likely to publish their opinions than Republicans when reaching a
liberal outcome, but only 20% more likely to do so when the outcome they
reach is not liberal.103 In that case, both process preferences (i.e., a
99
See infra Table 3.
See infra Table 3.
101
See infra Table 3 and Figure 1. For example, let us assume that all types of panels publish their
opinions 20% of the time when they reach a liberal outcome, but publish them only 10% of the time
when the outcome they reach is a non-liberal one. Even though these conditional publication rates are
the same across all panels, if Democrats reach a liberal outcome more often than Republicans, they will
on average publish their decisions more often. In essence, this is how Law explains the differences in
publication rates between Democratic-led and Republican-led panels in his sample of asylum cases.
Law, supra note 14, at 848−49.
102
This would be the case if Democratic-led panels were 50% more likely to publish both their
liberal and non-liberal opinions than Republican-led panels. For example, if Republicans publish 10%
of their opinions for liberal outcomes and do so 4% of the time for non-liberal ones, while Democrats
publish their opinions 15% and 6% of the time, respectively.
103
In his study, Law finds no evidence supporting this factual scenario, as Democratic-led panels
were no likelier than Republican-led panels either to publish pro-asylum decisions or to leave antiasylum decisions unpublished (though both types of panels do publish their pro-asylum decisions at a
higher rate than their anti-asylum decisions). Law, supra note 14, at 848−49. Law finds that
Democratic-led panels publish at a higher rate than Republican-led panels not because they publish pro100
292
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preference to publish their decisions more often) and ideological
preferences over case outcomes (i.e., a preference to favor criminal
defendants) would explain differences in publication rates.104
A cursory look at the raw data provides a preliminary answer. Figure 1
presents the average publication rates for each type of panel broken down
by the ideological directionality of the outcome reached in a decision. As
noted earlier, unified Democratic-led panels publish their opinions 14.84%
of the time, while unified Republican-led panels publish their opinions
11.33% of the time.105 If we focus solely on non-liberal decisions, this
difference in publication rates virtually disappears: unified Democratic-led
panels publish their non-liberal opinions 10.57% of the time, a rate quite
similar to the publication rate of Republican-led panels, 10.09%.106
However, if we focus on liberal decisions, the difference in publication
rates across panel types is more significant: 34.43% for unified Democraticled panels vs. 25.97% for unified Republican panels.107 The magnitude of
these differences in publication rates between split Democratic- and
Republican-led panels is substantially narrower.108 In cases in which the
panel reaches a non-liberal outcome, split Democratic-led panels publish
their opinions 9.54% of the time, while split Republican-led panels do so
9.40% of the time.109 In cases in which the panel reaches a liberal outcome,
split Democratic-led panels publish their liberal opinions 29.60% of the
time, while split Republican-led panels do so 27.67% of the time.110
asylum decisions at a higher rate than Republican panels do, but because these Democratic-led panels
are much likelier to reach pro-asylum decisions. Id. It is also worth noting that this factual scenario
runs counter to Songer et al.’s finding that Republican-led panels are more likely to publish their liberal
decisions than Democratic-dominated panels. See Songer et al., supra note 12, at 977−83.
104
A more extreme example would have Democrats publishing liberal opinions 50% more often
than Republicans and Republicans publishing 50% more often than Democrats their non-liberal
decisions. In such a case, ideology, at least as measured in terms of outcome-based preferences, would
appear to be paramount.
105
See infra Figure 1.
106
See infra Figure 1.
107
See infra Figure 1.
108
See infra Figure 1.
109
See infra Figure 1.
110
See infra Figure 1.
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293
To further explore the relationship between panel ideology, case
outcomes, and publication rates, we estimate the following specification:
∑ α
∗
∑ (2)
where
, the outcome of interest, is an indicator variable equal to
is an indicator
1 if the panel published its opinion in case ;
variable equal to 1 if the panel reached an outcome that we code as
is a set of indicator variables based on a count of the
liberal;111
number of Democratic appointees sitting in the panel reviewing case ;112
,
, and are the same variables that were previously
and
111
For a discussion of the methodology we follow in coding case outcomes, see supra note 98 and
accompanying text.
112
As in our earlier specifications,
1 is an indicator variable equal to 1 if only one judge on the
panel hearing case i was appointed by a Democratic president;
2 equals 1 if two of the judges on
the panel are Democratic appointees; and
3 equals 1 if all three judges on the panel are Democratic
appointees. The omitted group in these regressions is
0 , a panel consisting of three Republican
appointees.
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defined.113 The results for this specification are presented in Table 3,
column (2). Column (1) of Table 3 replicates the baseline regression of
column (4) in Table 2 to confirm that the relationship between panel
composition and publication rate, which we document in our sample, holds
in the subset of cases that are included in our analyses in this Part.114
We start by considering differences in publication rates across panels in
cases in which the panels reach a decision that we code as not representing
3 (i.e., 0.009) measures the
a liberal outcome.115 The coefficient on
difference in publication rates between unified Democratic panels and
unified Republican panels in cases in which the panels reached a non-liberal
outcome.116 To draw an analogous comparison between split panels, we
look at the difference between the coefficients
2 and
1 (i.e.,
0.006).117 Both of these differences are statistically insignificant and their
magnitudes are small relative to the average publication rate of non-liberal
decisions (0.097), confirming that panels are equally likely to publish their
non-liberal opinions, regardless of whether they are led by Republican or
Democratic appointees.118
To measure differences between unified Democratic- and unified
Republican-led panels in the publication of liberal decisions, we look at the
+
*
, which indicates that unified
coefficient sum
Democratic panels are more likely than unified Republican panels to
publish a liberal decision.119 This difference of 0.0995 is statistically
significant and represents about a third of the average rate of publication of
liberal opinions (0.2979).120 Although split Democratic-led panels are also
more likely than split Republican-led panels to publish their liberal
opinions, the difference is small and not statistically significant.121
113
See supra notes 61–64 and accompanying text.
See infra Table 3, column (1) and supra Table 2, column (4). The results presented in column
(1) of Table 3 confirm that in the set of cases included in these analyses, unified Democratic panels are
more likely than unified Republican panels to publish their opinions in this subset of cases (see
coefficient on
3) and split Democratic panels are more likely to publish their decisions than split
Republican panels (see coefficient difference
2
1).
115
See supra note 98 and accompanying text.
116
See infra Table 3, column (2).
117
See infra Table 3, column (2).
118
See infra Table 3, column (2). Though insignificant, these differences are positive, suggesting
that Democratic-led panels may be slightly more likely than Republican-led panels to publish their nonliberal decisions. Law also finds that Democratic-led panels publish a slightly greater (but insignificant)
fraction of their anti-asylum opinions. Law, supra note 14, at 848.
119
See infra Table 3, column (2).
120
See infra Table 3, column (2).
121
See infra Table 3, column (2). The difference between split Democratic- and split Republican+
led panels in the publication of their liberal decisions is measured by the coefficient sum (
*
)-(
+
*
). The magnitude of this difference, 0.0275, is
114
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295
TABLE 3. PREDICTING PUBLICATION
(1)
Dem1
Dem2
Dem3
(2)
-0.0057
-0.0118
[0.0148]
[0.0130]
0.0103
-0.0060
[0.0153]
[0.0133]
0.0416**
0.0091
[0.0187]
[0.0157]
LibOutcome
0.1560***
[0.0268]
Dem1*LibOutcome
0.0294
[0.0302]
Dem2*LibOutcome
0.0510*
[0.0294]
Dem3*LibOutcome
0.0904***
[0.0330]
Mean Outcome
Mean Outcome (if LibOutcome=1)
Mean Outcome (if LibOutcome=0)
Observations
R-squared
0.1215
0.2979
0.0969
39,961
0.022
0.1215
0.2979
0.0969
39,961
0.064
Note: Robust standard errors, clustered at the three-judge group level, in brackets (*
significant at 10%; ** significant at 5%; *** significant at 1%). The outcome in columns (1)
and (2) is an indicator variable equal to 1 if the panel published its opinion. The explanatory
variables of interest are (i) Dem1, Dem2, and Dem3—a set of dummies indicating the
number of Democrats in the panel; (ii) LibOutcome, an indicator variable equal to 1 if the
panel reached a decision which we code as liberal; and (iii) an interaction between these
terms. A decision is coded as liberal if: (a) the defendant prevailed in a criminal case; (b) the
individual prevailed in an immigration case; (c) the plaintiff prevailed in a civil rights case;
or (d) the petitioner prevailed in a prisoner petition case. All regressions include year fixedeffects and case type fixed-effects.
These estimates confirm the intuition behind Figure 1. Although there
are not significant differences across panels in the publication of non-liberal
opinions, there is a large and significant difference between unified
Democratic- and Republican-led panels (though not between split
relatively small (representing less than 10% of the average publication rate of liberal opinions) and is not
statistically significant.
296
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Democratic-led and split Republican-led panels) in the publication of liberal
opinions.122
Having gathered the evidence, we can now decompose the overall
differences in publication rates between unified Democratic and unified
Republican panels. First, unified Democratic panels are more likely to
reach a liberal decision than unified Republican panels and liberal decisions
are on average more likely to be published.123 However, this explains only
part of the difference in publication rates we observe across panels. Not
only are unified Democratic panels more likely to reach a liberal outcome,
but they are much more likely to publish their liberal decisions than unified
Republican panels.124 On the other hand, they are as likely as unified
Republican panels to publish their non-liberal decisions.125
Why are unified Democratic panels more likely to publish their liberal
opinions? On a normative level, the patterns we document could be
particularly problematic if these Democratic panels are actively trying to
influence the development of precedent by selectively publishing certain
opinions in order to further their political and policy preferences. This,
however, may be a risky strategy. Although publishing an opinion may
have a greater effect on precedent, its publication could also increase the
probability that a case is reviewed (and potentially reversed) either by the
other circuit court judges sitting en banc or by the U.S. Supreme Court.126
An alternative inference is that these unified panels are being more careful
122
See supra Table 3. Another approach to understanding the link between panel ideology and the
decision to publish is to measure the extent to which a given type of panel is more or less likely to
publish liberal opinions relative to non-liberal opinions. To measure this within-panel difference, we
∗
(and for a unified Republican panel,
focus on the coefficient sums
+
just the coefficient on
). In general, all types of panels are more likely to publish liberal
opinions than non-liberal opinions, a fact which, given the manner in which we code a liberal opinion,
may not be that surprising. See supra note 98 and accompanying text. Notably, this “publication gap”
between liberal and non-liberal decisions increases with the number of Democratic appointees sitting in
the panel: 0.1560, 0.1854, 0.2070, and 0.2464. See supra Table 3. That this publication gap is much
larger for unified Democratic panels than for unified Republican panels is precisely what the significant
coefficient on the interaction term
3∗
, 0.0904, indicates. See supra Table 3. The
difference in this publication gap between split Democratic- and split Republican-led panels is a
relatively small and statistically insignificant sum (0.0216). See supra Table 3.
123
See supra Table 1 and Figure 1.
124
See supra Table 1 and Figure 1.
125
See supra Figure 1.
126
See 9TH CIR. R. 36-3(a). See generally Posner, supra note 43, at 716−18. To determine whether a
decision in our sample was subsequently reheard en banc or granted certiorari by the U.S. Supreme
Court, we rely on the opinion headings that we retrieved from our Lexis search. See supra pp. 279–81.
Not surprisingly, published opinions are reviewed at a much higher rate than non-published opinions—
although only about 0.1% of the cases in our sample are reviewed, over 3.4% of the subset of published
cases are. Given this data collection method and the general low number of subsequent reviews, any
estimates obtained using this variable are likely to be quite noisy.
2013]
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297
in examining the legal issues in front of them, preparing perhaps clearer and
better reasoned opinions.127 In order to make any such normative
judgments we would need to have information on the relative content,
substance, and quality of these published and unpublished liberal opinions
authored by unified Democratic-led panels. Although we lack such
qualitative information in our dataset, in the next Part we use the number of
days it takes a panel to prepare an opinion and differences across panels in
the decision of whether or not to hold oral arguments as proxies for a
panel’s care and effort in its decision-making.128
What the results presented thus far do allow us to conclude is that not
only are published opinions a non-random sample of all decisions, but also
that the subset of published opinions may in fact look very different from
the subset of unpublished opinions.129 If this is true, then interpreting the
results of many of the studies that rely on samples that exclude unpublished
opinions may be less straightforward.130 We further explore the empirical
implications of this particular finding in Part IV.C below.
B. Preparing the Opinion
1. Time Taken to Prepare an Opinion
The number of days it takes a panel to complete an opinion after
hearing oral arguments is positively correlated with the number of
Democratic appointees sitting in the panel.131 To further explore the
relationship among panel composition, case outcome, and publication, we
127
For example, one would expect unified Democratic-led panels to be more careful in articulating
their arguments in an opinion if liberal decisions by these panels are more likely to be reviewed en banc
or by the U.S. Supreme Court. See supra pp. 279–80.
128
See infra Part IV.B.
129
See infra Table 4.
130
See, e.g., Wald, supra note 13, at 246−47 (arguing that the failure to include unreported decisions
where “partisan decisionmaking seem[s] particularly unlikely” from statistical analyses can yield results
that exaggerate the partisan nature of judicial decision-making).
131
See supra Table 2, column (5). Our outcome variable in these analyses is the time elapsed
between the hearing date and the judgment date (for cases in which oral arguments were held),
winsorized at 5%. Winsorising is a technique employed to reduce the influence of outliers in statistical
analyses, thus allowing more robust inferences. Winsorize, NAT’L INST. OF STANDARDS & TECH.,
http://www.itl.nist.gov/div898/software/dataplot/refman2/auxillar/winsor.htm (last updated Apr. 4, 2003). A
95% winsorization sets all data points that fall below the 5th percentile level to the value of the 5th
percentile, while data above the 95th percentile is set to the 95th percentile. See id.
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restrict our analysis in this Part to those cases for which we have coded the
directionality of the panel’s decision.132
In this subset of cases, unified Democratic panels take about 7.25%
longer (74.20 vs. 69.18 days) than unified Republican panels to complete an
opinion after hearing oral arguments, while split Democratic-led panels take
4.38% longer (68.52 vs. 65.65 days) than split Republican-led panels.133
Though relatively small, these differences are almost exclusively driven by
the subset of published opinions.134 On average, unified Democratic-led
panels take 17.5% longer (about 19 days) than unified Republican panels to
prepare their published opinions, a difference which is statistically
significant at the 1% level.135 Not only do unified Democratic-led panels
take longer to prepare their published opinions than unified Republican
panels, but they also take longer to prepare their published opinions than
split panels.136 On the other hand, when we look at the subset of
unpublished opinions, differences across panels in terms of the time that
they take to prepare an opinion are small and statistically insignificant.137
132
For sake of brevity and clarity of exposition, our analysis in this Subpart relies on the comparison
of raw means. The results we describe in this Part are robust to the inclusion of controls for year and
type of case in a multivariate regression, such as equations (2) and (3) above. See supra pp. 282–84.
133
See infra Table 4, column (1). Both of these differences are statistically significant at the 10%
level.
134
See infra Table 4.
135
See infra Table 4, column (2).
136
See infra Table 4. Unified Democratic-led panels take 10.51% longer than split Republican-led
panels (127.08 vs. 114.99 days) and 6.13% longer than split Democratic-led panels (127.08 vs. 119.75
days) to prepare their published opinions. See infra Table 4. These differences are statistically
significant at the 5% and 10% levels, respectively.
137
See infra Table 4, column (3).
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299
TABLE 4. TIME BETWEEN HEARING AND JUDGMENT
(1)
Panel type
Dem0
Dem1
Dem2
Dem3
All
69.18
65.65
68.52
74.20
Panel A –
All Decisions
(2)
(3)
Not
Published Published
108.08
48.48
114.99
45.23
119.75
46.73
127.08
49.35
Panel B –
Published Decisions
(4)
(5)
Liberal
125.42
128.88
130.56
130.64
Non
Liberal
103.90
110.10
113.95
124.21
Note: The outcome in all columns is the time elapsed between the hearing date and the
judgment date (for cases in which oral arguments were held), winsorized at 5%. Column (1)
includes all cases for which we are able to code the ideological directionality of the opinion.
Columns (2) and (3) classify the cases according to their publication status. Columns (4) and
(5) contain published opinions that we classify as liberal or non-liberal, respectively.
Why do unified Democratic panels spend more time than other types of
panels in preparing their published opinions? As noted earlier, one
plausible inference is that these unified Democratic panels are putting more
effort into the analysis of the legal issues involved in a case, preparing
perhaps opinions of a higher quality.138 Another possible explanation is that
if these unified Democratic-led panels are “overreaching” or engaging in
some sort of “judicial activism,” they would possibly need to take more
time in preparing their opinions.139 Alternatively, one can imagine that to
the extent that liberal decisions rendered by unified Democratic panels are
more likely to be reviewed by the circuit court sitting en banc or the U.S.
Supreme Court, these panels may be more careful in preparing and crafting
their decisions.140
Under the two last explanations, we would expect the amount of time
spent by panels in preparing a published opinion to vary with the outcome
138
These results are particularly interesting in light of the fact that unified Democratic panels
publish a higher percentage of their opinions. See supra Table 3 and Figure 1. Thus, if publication and
the time it takes a panel to prepare an opinion are proxies for the effort spent by a panel, one could argue
that unified Democratic-led panels are working a bit harder. Of course, the variable we use in this Part
is not necessarily a perfect measure of the effort expended by a panel in preparing an opinion, since
panels may start working on an opinion prior to oral arguments, or just work more days but fewer hours
per day. In addition, since these unified Democratic panels publish more of their opinions, one could
expect them to spend more time overall preparing these. See supra Table 4.
139
See supra Table 4.
140
See supra notes 91–92.
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of the case. That is, we would expect unified Democratic-led panels to take
longer to prepare their liberal published opinions relative to their nonliberal ones. Panel B of Table 4 divides the sample of published opinions
by their outcomes, which we classify as liberal and non-liberal, following
the same methodology described in Part IV.A. One can readily observe that
unified Democratic-led panels take longer than unified Republican panels to
prepare both their liberal and non-liberal published opinions, though the
difference is smaller and not statistically significant for the former set of
cases.141 Although all panels generally take more time in preparing a
published opinion in which they reach a liberal decision than those in which
they reach a non-liberal one, the magnitude and significance of this
difference does vary significantly across panel types.142 In particular, this
gap is greater for unified Republican panels than for unified Democratic
panels, and for the latter, the difference is even statistically insignificant.143
In other words, unified Democratic panels (i) take longer than other types of
panels to prepare both their liberal and non-liberal published opinions and
(ii) spend roughly the same amount of time in preparing the liberal and nonliberal opinions that they choose to publish.144
2. Hearing Oral Arguments
Our analyses in the previous Part were limited to those cases in which
the panel held oral arguments. As we document earlier in this Article, the
likelihood that a panel holds oral arguments increases with the number of
Democratic appointees sitting in the panel.145 Unified Democratic-led
panels are 40.23% more likely (0.5124 vs. 0.3654) than unified Republican
panels to hold oral arguments; similarly, split Democratic-led panels are
16.8% more likely (0.4544 vs. 0.3890) than split unified panels to hold oral
arguments.146 What could be driving these differences? As noted in our
discussion of differences in publication rates and the number of days taken
by panels to prepare an opinion, unified Democratic panels may be
exercising more care or trying to become fully informed prior to reaching a
decision.147 On the other hand, as we also noted earlier, one could argue
that these Democratic-led panels choose to hear oral arguments when they
disagree with the policy or political implications of the lower court decision
141
142
143
144
145
146
147
See supra Table 4, columns (4) and (5).
See supra Table 4, columns (4) and (5).
See supra Table 4, columns (4) and (5).
See supra Table 4, columns (4) and (5).
See supra Table 2, column (3).
See infra Table 5A, column (1).
See supra note 127 and accompanying text.
2013]
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301
in order to search and find a ground for appeal.148 Under the latter
explanation, one would expect these Democratic-led panels to hold oral
arguments more often when reviewing a decision rendered by a Republican
district court judge or a conservative decision.
TABLE 5A. ORAL ARGUMENTS HEARD—BY DISTRICT COURT JUDGE
Panel type
Dem0
Dem1
Dem2
Dem3
(1)
All
0.3654
0.3890
0.4544
0.5124
Appointing President of
District Court Judge Is . . .
(2)
(3)
Democratic
Republican
0.3803
0.3573
0.3869
0.3903
0.4449
0.4612
0.5020
0.5203
Note: The outcome in all columns is an indicator variable equal to 1 if the panel
assigned to case i held oral arguments. Column (1) includes all cases in which the appellate
panel is reviewing a decision by a district court judge, while columns (2) and (3) restrict the
sample to cases in which the appellate panel is reviewing decisions rendered by Democratic
and Republican district court judges, respectively.
Democratic-led panels are more likely to hold oral arguments than
Republican-led panels regardless of whether the district court judge who
rendered the decision being reviewed is a Democratic or Republican
appointee.149 Unified Democratic-led panels are 32.00% more likely than
unified Republican panels to hold oral arguments when reviewing decisions
rendered by Democratic district court judges (i.e., 0.5020 vs. 0.3803).150
When reviewing decisions rendered by Republican district court judges,
unified Democratic panels are 45.62% more likely to hold oral arguments
(i.e., 0.5203 vs. 0.3573).151 In addition, unified Democratic-led panels
appear to be more even in their selection of cases for oral arguments.152
Unified Democratic panels are 3.6% more likely to hold hearings when
reviewing decisions rendered by Republican district court judges than when
148
See supra pp. 297–300.
See supra Table 5A.
See supra Table 5A, column (2).
151
See supra Table 5A, column (3). As in most of the results presented earlier, differences between
split panels are narrower, but track the patterns that we observe for differences across unified panels.
Split Democratic-led panels are 15.00% and 18.17% more likely than split Republican panels to hold
oral arguments when reviewing a decision rendered by Democratic and Republican district court judges,
respectively. See supra Table 5A, columns (2) and (3).
152
See supra Table 5A.
149
150
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reviewing decisions by Democratic district court judges (i.e., 0.5203 vs.
0.5020; compare columns (2) and (3) of Table 5A), a difference that is not
statistically significant. Unified Republican panels are 6.6% more likely to
hold hearings to review decisions of Democratic district court judges than
Republican district court judges (i.e., 0.3803 vs. 0.3573).153 This gap is
slightly larger than that of unified Democratic panels and statistically
significant at the 10% level, suggesting that political and policy preferences
may play a bigger role in the decision of unified Republican-led panels on
whether or not to hold oral arguments in a particular case.154
Since the party of the district court judge may not be a perfect proxy for
the ideological direction of the lower court decision being reviewed by an
appellate panel, we next create an indicator variable that is equal to 1 if we
code the lower court decision under review as liberal and is equal to 0 if we
code the lower court decision as non-liberal.155 Using this alternative
measure of the ideological directionality of the decision being reviewed
leads us to a similar conclusion: Democratic-led panels are more likely than
their Republican-led counterparts to hold oral arguments regardless of
whether the decision being reviewed is coded by us as liberal or nonliberal.156 Differences among unified panels are substantial: unified
Democratic panels are 19.11% more likely to hold oral arguments than
unified Republican panels when reviewing a liberal lower court decision
(0.7628 vs. 0.6404); for non-liberal decisions this difference is 53.15%
(0.4429 vs. 0.2892).157
Although panels are generally more likely to hold oral arguments when
reviewing a liberal lower court decision than when reviewing a non-liberal
one, the relative differences vary widely across panel types, as can be
observed by comparing columns (2) and (3) of Table 5B for each type of
panel. While unified Republican panels are about 121.44% more likely to
hold an oral argument when reviewing a liberal lower court decision
relative to a non-liberal one (i.e., 0.6404 vs. 0.2892), the corresponding gap
153
See supra Table 5A, columns (2) and (3).
See supra Table 5A.
155
See supra note 98 and accompanying text. As in earlier analyses, we follow the methodology
used in the Songer U.S. Court of Appeals Database to determine the directionality of these lower court
decisions. See supra note 98. Note that this restricts our sample to those criminal, prisoner petition, and
civil right cases in which we were able to code the directionality of the district court decision. To verify
random assignment in this sample, we estimate a specification in which the dependent variable is an
indicator variable equal to 1 if we code the decision below as liberal and the explanatory variables are
indicator variables for the count of Democrats in the panel and a set of year fixed-effects. In this
regression, the coefficients on the panel type indicators are small and insignificant, both individually and
as a group. See infra Appendix Table 2, column (5); discussion supra Part II.B.2.
156
See infra Table 5B, columns (2) and (3).
157
See infra Table 5B.
154
2013]
It’s the Journey, Not the Destination
303
for unified Democratic-led panels is 72.22% (i.e., 0.7628 vs. 0.4429).158
For Democratic- and Republican-led split panels, the corresponding
differences represent 108.5% (i.e., 0.7295 vs. 0.3871) and 88.45% (i.e.,
0.6778 vs. 0.3250), respectively.159 In other words, not only are
Democratic-led panels more likely than Republican-led panels to hear oral
arguments when reviewing both liberal and non-liberal decisions, but these
Democratic-led panels also appear to be more even-handed in their
selection of cases for oral arguments.160
TABLE 5B. ORAL ARGUMENTS HEARD—BY OUTCOME BELOW
Panel type
Dem0
Dem1
Dem2
Dem3
(1)
All
0.3016
0.3374
0.3994
0.4549
Outcome Below is . . .
(2)
(3)
Liberal
Non-Liberal
0.6404
0.2892
0.6778
0.3250
0.7295
0.3871
0.7628
0.4429
Note: The outcome in all columns is an indicator variable equal to 1 if the panel
assigned to case i held oral arguments. Column (1) includes all cases in which the appellate
panel is reviewing a decision for which we code the directionality of the outcome below as
liberal or non-liberal, while columns (2) and (3) restrict the sample to cases in which the
appellate panel is reviewing decisions that we code as liberal and as non-liberal,
respectively.
C. Reversing Lower Courts
The results presented in column (2) of Table 2 suggest that Democraticled panels (in particular unified ones) are more likely than Republican-led
panels to reverse lower court decisions. Such higher reversal rates may be
consistent with a number of explanations. As noted earlier, these
Democratic-led panels may be exercising more care in their analysis of a
case and the decision being reviewed.161 Alternatively, one could argue that
these Democratic-led panels may not be applying the law in a
straightforward manner, and may be perhaps less willing to defer to district
158
See infra Table 5B.
See infra Table 5B.
160
See infra Table 5B.
161
See supra note 127 and accompanying text. For example, appellate panels can monitor district
court judges through the review of the lower court decisions in light of the parties’ appellate briefs and
the entirety of the trial record. See Susan B. Haire et al., Appellate Court Supervision in the Federal
Judiciary: A Hierarchical Perspective, 37 LAW & SOC’Y REV. 143, 148 (2003).
159
304
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courts and choose to reverse decisions with which they do not agree.162 In
this Part, we explore the link between political ideology and differences in
reversal rates by considering the identity of the district court judge and the
disposition of the case below in determining the treatment of a case at the
appellate level by different types of panels.
1. Reversals and the Identity of the District Court Judge
If differences in reversal rates are driven by political or policy
preferences, one would expect panels dominated by Democratic appointees
to be less likely to reverse decisions made by district court judges who are
also Democratic appointees and more likely to reverse decisions made by
Republican appointees to the district court. On the other hand, if
Democratic-led panels are equally likely to reverse decisions rendered by
Republican and Democratic district court judges, then one could argue that
political ideology by itself does not necessarily explain circuit judges’
decisions whether or not to reverse.
Figure 2 provides a graphical representation of the average reversal
rates for each type of panel broken down by the party of the president that
appointed the district court judge who authored the lower court decision
being appealed.
Three interesting patterns are noticeable.
First,
Democratic district court judges appear to be reversed more often than
Republican district court judges.163 Second, Democratic-led panels are
more likely than Republican-led panels to reverse decisions by both
Democratic and Republican district court judges, with unified Democraticled panels exhibiting higher reversal rates than split Democratic-led
panels.164 That is, the probability that a Republican district court judge is
reversed increases with the number of Democrats sitting in the panel, but so
does the probability that a Democratic district court judge is reversed.165
Finally, Democratic-led panels seem to treat decisions by Republican and
Democratic district court judges quite evenly (i.e., reversing them at similar
rates), while unified Republican panels reverse decisions by Democratic
district court judges more often.166
162
Haire et al., supra note 161, at 145. Circuit court judges may use the appellate review process
not just to monitor decision-making by district court judges, but also to ensure that the decisions are
consistent with the panel’s policy preferences. Id. Anderson argues that appellate courts choose to
revisit factual determinations by trial courts for ideological reasons. See Robert Anderson IV, Law,
Fact, and Discretion in the Federal Courts: An Empirical Study, 2012 UTAH L. REV. 1.
163
See infra Figure 2.
164
See infra Figure 2.
165
See infra Figure 2.
166
See infra Figure 2.
2013]
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305
To explore these relationships in a more rigorous manner, we estimate
the following specification:
α
∑ ∑ (3)
∗
where
, the outcome of interest, is an indicator variable equal to 1
is an
if the appellate panel reversed the lower court’s decision;
indicator variable equal to 1 if the district court judge who heard case was
is a set of indicator variables
appointed by a Democratic president;
based on a count of the number of Democratic appointees sitting in the
,
, and
are the same
panel reviewing case ; and
167
variables defined in previous specifications.
indicator variables
In these regressions, the coefficients on the
2,
3 ) will tell us whether the number of Democrats
(i.e.,
1,
sitting in a panel increases the probability that a decision rendered by a
Republican district court judge will be reversed. Meanwhile, the coefficient
will tell us whether a unified Republican-led panel is more
on
likely to reverse the decision of a lower court when the case was decided by
a Democratic appointee (relative to a Republican appointee). The
+
*
will tell us whether the
coefficient sums
probability that a decision rendered by a Democratic district court judge is
167
See supra notes 61–64 and accompanying text.
306
UNIVERSITY OF LOUISVILLE LAW REVIEW
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reversed increases or decreases with the number of Democratic appointees
sitting in the panel.168
Column (1) of Table 6 presents the estimates for specification (3),
which confirm the patterns observed in Figure 2. First, on average,
decisions rendered by Democratic district court judges are more likely to be
reversed than those rendered by Republican ones—the coefficient on
, as well as the coefficient sums
+
*
,
are positive.169 Second, the number of Democratic appointees sitting in a
panel is positively correlated with the probability that a lower court decision
is reversed.170 The probability that a Republican district court judge is
reversed increases with the number of Democrats sitting in the panel—the
coefficients on
1,
2, and
3 are positive and statistically
significant.171 Likewise, the probability that a Democratic district court
judge is reversed also increases with the number of Democrats sitting in the
+
*
panel—the coefficient sum
increases with j, that is, the number of Democratic appointees in the
panel.172 Most importantly, differences in the treatment of decisions by
Democratic and Republican judges are not fully explained by the party
affiliation of the district court judge.173 Although Democratic-led panels are
more likely than Republican-led panels to reverse decisions rendered by
Republican district court judges, these Democratic-led panels are at the
same time more likely than Republican-led panels to reverse decisions
rendered by Democratic district court judges.174 While unified and split
Republican-led panels do seem to reverse Democratic district judges more
often than they reverse Republican district court judges,175 Democratic-led
168
See supra Figure 2. If Republican-led panels are more likely to reverse Democratic district court
should be positive. If an increase in the number of Democrats sitting in a panel
judges,
should be correlated with higher rates of reversal for Republican district court judges, then we would
2 , and
3 to be all positive, their magnitudes increasing in
expect the coefficients on
1,
that same order. If we expect Democratic-led panels to be less prone to reversing Democratic district
with
2 , and
3 should be
court judges then the coefficients on the interactions of
negative.
169
See infra Table 6, column (1).
170
See infra Table 6, column (1).
171
See infra Table 6, column (1).
172
See infra Table 6, column (1).
173
See, e.g., infra Table 6.
174
See infra Table 6, column (1).
175
See infra Table 6, column (1). Unified Republican panels are more likely to reverse decisions
rendered by Democratic district court judges than Republican district court judges—the coefficient on
is 0.0185, which represents about 14.26% of the average reversal rate in our sample (0.1297)
and is statistically significant at the 10% level. The same is true for split Republican-led panels, though
+
* m is equal to
the magnitude is slightly smaller—the coefficient sum of
0.0107 and statistically significant at the 5% level.
2013]
It’s the Journey, Not the Destination
307
panels reverse decisions by Democratic and Republican district court judges
at similar rates.176
176
See infra Table 6. The coefficient sums
+
*
and
+
*
, which indicate whether split Democratic-led panels and unified Republican-led
panels reverse Democratic district court judges more often than Democratic district court judges, are
small in magnitude (equal to 0.0062 and 0.0024, respectively) and are statistically insignificant.
308
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TABLE 6. REVERSALS BY PARTY OF DISTRICT COURT JUDGE
Dem1
Dem2
Dem3
DemDist
DemDist *Dem1
DemDist *Dem2
DemDist *Dem3
DemDist+DemDist *Dem1
Prob>F
DemDist+DemDist *Dem2
Prob>F
DemDist+DemDist *Dem3
Prob>F
Mean Outcome
All
DemDist=1
DemDist=0
Observations
R-squared
(1)
All
(2)
Published
(3)
Unpublished
0.0131*
0.0303
0.0110*
[0.00727]
[0.0207]
[0.0064]
0.0454***
0.0961***
0.0338***
[0.00791]
[0.0213]
[0.0069]
0.0737***
0.120***
0.0554***
[0.0109]
[0.0268]
[0.0094]
0.0185*
0.0328
0.0137
[0.00953]
[0.0300]
[0.00889]
-0.0078
-0.0066
-0.0048
[0.0108]
[0.0344]
[0.0101]
-0.0123
-0.0370
-0.0069
[0.0110]
[0.0338]
[0.0104]
-0.0161
-0.0589
-0.0065
[0.0134]
[0.0395]
[0.0132]
0.0107
0.0262
0.0089
0.0394
0.1323
0.0732
0.0062
-0.0042
0.0068
0.2648
0.7910
0.2113
0.0024
-0.0261
0.0072
0.7992
0.3156
0.4624
0.1297
0.1362
0.1254
47,381
0.016
0.2814
0.2905
0.2753
8,450
0.015
0.0967
0.1022
0.0931
38,739
0.013
Note: Robust standard errors, clustered at the three-judge group level, in brackets (*
significant at 10%; ** significant at 5%; *** significant at 1%). The outcome in columns
(1), (2), and (3), is an indicator variable which equals 1 if the panel reversed the district court
in full. The explanatory variables of interest are (i) Dem1, Dem2, and Dem3, a set of
dummies indicating the number of Democratic judges who sat in the panel; (ii) DemDist, an
indicator variable equal to 1 if the decision under review was rendered by a judge appointed
by a Democratic president; and (iii) a set of interactions between these variables. Columns
(2) and (3) restrict the sample to published and unpublished decisions, respectively. All
regressions include year fixed-effects and case type fixed-effects.
2013]
It’s the Journey, Not the Destination
309
The analyses presented in column (1) of Table 6, as well as Figure 2,
include both published and unpublished opinions. We next examine
whether the decision to publish mediates the relationship between ideology
and reversals, by estimating specification (3) separately for published and
unpublished decisions.177 The estimates of these specifications are
presented in columns (2) and (3) of Table 6. Generally, the conclusions
drawn from our analysis of our entire sample apply to both subsets of
published and unpublished decisions. However, it is worth noting that in
the sample of published decisions, unified Democratic-led panels do seem
to reverse decisions by Republican district court judges at a higher rate than
decisions by Democratic district court judges.178 While the coefficient sums
+
*
and
+
*
are
positive in column (3) of Table 6, these coefficient sums are negative in
column (2). Although the magnitudes of these differences are rather small
and are not statistically significant,179 the fact that the sign of the coefficient
sum switches between published and unpublished opinions emphasizes the
importance of distinguishing between published and unpublished
The apparent difference in the treatment by unified
opinions.180
Democratic-led panels of Democratic and Republican district court judges
can be appreciated graphically by comparing Figures 2A and 2B, which
replicate Figure 2, but using exclusively published and unpublished
opinions, respectively.
177
See supra Table 6, columns (2) and (3).
See supra Table 6, column (2).
179
See supra Table 6. For example, the difference for unified Democratic panels is 2.61 percentage
points, which represents less than 10% of the average reversal rate in published opinions.
180
See supra Part IV.A.
178
310
UNIVERSITY OF LOUISVILLE LAW REVIEW
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2013]
It’s the Journey, Not the Destination
311
2. Reversals and the Outcome Below
The identity of the district court judge may not be the best proxy for the
ideological direction of a lower court decision and as a result may not tell
us much about the panel’s political or policy-based motivations, if any, in
reversing that lower court decision. As an alternative measure, we create an
indicator variable, LibBelow, that is equal to 1 if we code the lower court
decision under review as liberal and is equal to 0 if we code the lower court
decision as non-liberal.181 Figure 3 provides a graphical representation of
the reversal rates for each type of panel by the directionality of the decision
being reviewed. The patterns depicted in Figure 3 suggest that both the
ideological directionality of a lower court decision and the composition of
the panel reviewing it have a substantial effect in determining the likelihood
of reversal.182
181
As in earlier analyses, we follow the methodology used in the Songer U.S. Court of Appeals
Database to determine the directionality of these lower court decisions. See supra note 155.
182
Of course, the directionality of the lower court decision being reviewed is not by itself the best
proxy for whether or not that particular decision should in fact be reversed. In order to draw any
conclusions on the ideological motivation of panels, we would need to know a bit more about the
relative complexities of the issues involved in (and other characteristics that may predict the reversal of)
these liberal and non-liberal lower court decisions. Without such qualitative data, it is difficult to
conclusively determine whether the differences in reversal rates that we observe are motivated by
preferences over final outcomes, or whether they are the result of different levels of care and
examination of a lower court’s decision.
312
UNIVERSITY OF LOUISVILLE LAW REVIEW
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First, it appears that, on average (and for each type of panel), liberal
lower court decisions are more likely to be reversed relative to non-liberal
decisions.183 Second, while the probability of a liberal lower court decision
being reversed increases with the number of Republican appointees sitting
in the panel and decreases with the number of Democratic appointees, the
probability of a non-liberal decision being reversed increases with the
number of Democratic appointees and decreases with the number of
Republican appointees sitting in the panel.184 Finally, Democratic-led
panels appear more even-handed in the treatment of different lower court
opinions.185 While unified and split Republican-led panels are about six
and five times more likely, respectively, to reverse a liberal lower court
decision than a non-liberal one, unified Democratic-led panels are just 76%
more (i.e., 1.76 times as) likely to reverse liberal lower court decisions than
non-liberal ones.186
To control for year and the nature of the underlying case being
reviewed by a panel, we estimate the following specification:
α
∑ ∑ (4)
∗
Equation (4) is identical to specification (3),187 but instead of employing
the variable DemDist, we employ LibBelow as the proxy for the ideological
directionality of the lower court decision being reviewed.
Our
interpretation of the estimates of this regression, presented in column (1) of
Table 7, would be similar to our interpretation of the coefficients in
equation (3).
We can summarize these results as follows. First, Republican-led
panels are more likely than Democratic-led panels to reverse liberal
decisions, while Democratic-led panels are more likely than Republican-led
183
See supra Figure 3. This is consistent with Cross’s findings that conservative lower court
decisions are more likely to be affirmed than liberal lower court decisions in published appellate
opinions, regardless of panel composition. See Cross, supra note 2, at 1504−06.
184
See supra Figure 3. Unified Republican panels are 52.55% more likely than unified Democratic
panels to reverse a liberal district court decision (0.3740 vs. 0.2452). On the other hand, unified
Democratic panels reverse non-liberal district court decisions 120% (i.e., 2.2 times) more often than
Republican panels (0.139 vs. 0.063). Comparing split panels reveals a similar pattern, though the
differences are quite smaller. Split Republican panels are 15.68% more likely to reverse a liberal lower
court decision than split Democratic panels (0.3830 vs. 0.3311), while split Democratic panels are
43.54% more likely to reverse a non-liberal lower court decision than split Republican ones (0.1088 vs.
0.758).
185
See supra Figure 3.
186
See supra Figure 3.
187
See supra p. 305.
2013]
It’s the Journey, Not the Destination
313
panels to reverse non-liberal ones.188 Second, while Republican-led panels
seem to reverse liberal decisions at a much higher rate than non-liberal
decisions, unified Democratic-led panels appear to be more even in their
treatment of liberal and non-liberal lower court decisions.189 In fact, both
split and unified Democratic-led panels are more likely to reverse liberal
lower court decisions than non-liberal lower court decisions.190
The latter result seems to be inconsistent with the findings of previous
studies that have analyzed the role played by the political and policy
preferences of appellate panels in the decision whether or not to reverse
lower court judgments.191 For example, Haire et al. find that appellate
panels are less likely to reverse a district court decision when the policy
position taken by the lower court is consistent with the policy preferences
of the majority of the circuit judges in the panel, suggesting both that
Republican-led panels are more likely to reverse liberal lower court
opinions than non-liberal ones (a finding consistent with the results
presented in this Article) and that Democratic-led panels are more likely to
reverse non-liberal opinions than liberal ones (a finding contradicted by the
results presented in this Article).192 Similarly, Cross finds that unified
Democratic-led panels are more likely to reverse conservative lower court
decisions than liberal ones (a finding contradicted by the results presented
in this Article), while the other types of panels reverse liberal lower court
opinions at a higher rate than non-liberal ones, with unified Republican-led
188
See infra Table 7, column (1). The coefficients on Dem1, Dem2, and Dem3 are positive and
increase monotonically, which tells us that non-liberal lower court decisions are more likely to be
reversed when there are more Democratic appointees sitting in the panel. To compare the reversal rates
of liberal lower court opinions across panel types, we need to compare the coefficient LibBelow (0.351)
and the coefficient sum Dem1+LibBelow+LibBelow*Dem1 (0.3768) with the coefficient sums
Dem2+LibBelow+LibBelow*Dem2 (0.2938) and Dem3+LibBelow+LibBelow*Dem3 (0.1847). This is
consistent with Cross’s finding that the probability of a liberal lower court opinion being reversed
increases with the number of Republican appointees, while on the other hand, the probability of a nonliberal opinion being reversed increases with the number of Democratic appointees. See Cross, supra
note 2, at 1504−05.
189
See infra Table 7, column (1).
190
See infra Table 7.
Note that the coefficient sums LibBelow+LibBelow*Dem2 and
LibBelow+LibBelow*Dem3 are positive and significant.
191
See infra notes 192−194 and accompanying text.
192
See Haire et al., supra note 161, at 159. It should be noted that Haire et al.’s methodology
assumes that Democratic- and Republican-led panels will behave similarly in treating (i.e., will reverse
at the same rates) those lower court opinions with which they do not “agree” (i.e., non-liberal and liberal
lower court opinions, respectively). Id. at 158. To the extent that Democratic- and Republican-led
panels and split and unified panels behave differently (as we have shown in this Article), such a coarse
approach may not allow us to identify more nuanced distinctions in reversal behavior across panels.
314
UNIVERSITY OF LOUISVILLE LAW REVIEW
[Vol. 51:271
panels exhibiting the widest gap (a finding consistent with the results
presented in this Article).193
One possible explanation for these disparities is that most of the studies
analyzing judicial behavior (including these studies by Cross and Haire et
al.) have relied solely on a set of published opinions, thus excluding
unpublished opinions from their analysis.194 To the extent that the set of
published opinions are inherently different from the set of unpublished
opinions (and the evidence we have presented in this Article suggests they
are), one may question how the results from these studies should be
interpreted and how general these are in describing judicial behavior.
To ascertain the role played by the exclusion of unpublished opinions in
explaining the differences highlighted above between our results and those
in earlier studies, we estimate equation (4) using only the subset of
published opinions in our sample. These estimates are presented in column
(2) of Table 7. In this set of published opinions, unified Republican-led
panels are still more likely to reverse liberal lower court decisions relative
to non-liberal lower court decisions (the coefficient on LibBelow is still
positive and statistically significant).195 However, our results are strikingly
different for unified Democratic-led panels. In this set of published
opinions, unified Democratic-led panels are more likely to reverse nonliberal lower court opinions relative to liberal lower court opinions (which
is now consistent with the results presented by Haire et al. and Cross).196 If
one compares the coefficient sum LibBelow+LibBelow*Dem3 in columns
(1) and (2) of Table 7, one can notice that this sum has switched signs, from
0.1050 to -0.1070.197 That is, when we look at the entire sample (including
unpublished opinions), unified Democratic-led panels appear more likely to
reverse liberal lower court opinions than non-liberal ones.198 But when we
look exclusively at published opinions, these same unified Democratic-led
193
See Cross, supra note 2, at 1504−05.
See Cross, supra note 2, at 1498 n.271; Haire et al., supra note 161, at 156. Another possible
explanation is that our sample is restricted to the Ninth Circuit, while the studies by Haire et al. and
Cross include cases from all circuits. While the circuit judges of the Ninth Circuit (and their panel
dynamics) are not necessarily representative of other circuits, we find that in the subset of published
opinions in our sample, unified Democratic-led panels, for example, behave in a manner that is
consistent with the findings in these earlier studies. This suggests that differences in published and
unpublished opinions are driving, at least in part, the disparities between these results in the existing
literature and ours.
195
See infra Table 7.
196
See infra Table 7.
197
See infra Table 7. It is worth noting that the positive coefficient sum LibBelow+LibBelow
*Dem3 in column (1) of Table 7 was statistically significant and that the negative coefficient sum
LibBelow+LibBelow*Dem3 in column (2) is almost statistically significant at the 10% level.
198
See infra Table 7.
194
2013]
It’s the Journey, Not the Destination
315
panels are now more likely to reverse non-liberal lower court opinions than
liberal lower court opinions.199 Figures 3A and 3B provide a graphical
representation of these results by replicating Figure 3 for published and
unpublished opinions, respectively.
199
See infra Table 7.
316
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TABLE 7. REVERSALS—BY OUTCOME BELOW
Dem1
Dem2
Dem3
LibBelow
LibBelow *Dem1
(1)
All
(2)
Published
0.0113*
0.0517**
[0.00663]
[0.0207]
0.0448***
0.131***
[0.00737]
[0.0218]
0.0797***
0.192***
[0.0108]
[0.0289]
0.351***
0.444***
[0.0461]
[0.0795]
0.0145
-0.140
[0.0536]
[0.0915]
-0.102*
-0.315***
[0.0528]
[0.0895]
-0.246***
-0.551***
[0.0596]
[0.104]
0.3655
0.0000
0.3040
0.0000
0.2490
0.0000
0.1290
0.0018
Prob>F
0.1050
0.0057
-0.1070
0.1082
Mean Outcome
All
if LibBelow=1
if LibBelow=0
Observations
R-squared
.1074
.3747
.0976
28,231
0.038
.2687
.4303
.2501
3,963
0.046
LibBelow *Dem2
LibBelow *Dem3
LibBelow + LibBelow *Dem1
Prob>F
LibBelow + LibBelow *Dem2
Prob>F
LibBelow + LibBelow *Dem3
Note: Robust standard errors, clustered at the three-judge group level, in brackets (*
significant at 10%; ** significant at 5%; *** significant at 1%). The outcome in columns (1)
and (2) is an indicator variable which equals 1 if the panel reversed the district court in full.
The explanatory variables of interest are (i) Dem1, Dem2, and Dem3, a set of dummies
indicating the number of Democratic judges who sat in the panel; (ii) LibBelow, an indicator
variable equal to 1 if we code the lower court decision being reviewed as liberal; and (iii) a
set of interactions between these variables. Column (2) restricts the sample to published
decisions. Both regressions include year fixed-effects and case type fixed-effects.
2013]
It’s the Journey, Not the Destination
317
318
UNIVERSITY OF LOUISVILLE LAW REVIEW
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V. CONCLUSION
The results presented in this Article contribute to our understanding of
the relationship between the political and policy preferences of circuit court
judges and their decision-making. Consistent with prior studies, we find
that political and policy preferences have an effect on final case
outcomes—the presence of Democrats in a panel is associated with less
favorable outcomes for the United States in criminal and immigration cases
and more favorable outcomes for plaintiffs in private civil and civil rights
cases.200 In addition, we uncover evidence that suggests that political
ideology is also correlated with a number of outcomes that are independent
of the party that prevails in the appeal.201 The presence of Democrats in a
panel increases the likelihood of oral arguments being held and of the
opinion being published (and of the time elapsed between oral arguments
and the final decision).202 Democratic-led panels are also characterized by
higher rates of dissent and reversals of lower court decisions.203
The evidence we have presented suggests that differences in these
process-related variables are not necessarily explained by a panel’s political
and policy preferences and could conceivably reflect variation in judges’
approaches to the deliberation and decision-making processes.204 For
example, Democratic-led panels choose to hold oral arguments more often
than Republican-led panels both when reviewing liberal as well as
conservative lower court decisions and take longer to prepare their opinions
regardless of the outcome they reach.205 While Republican-led panels seem
to reverse liberal lower court decisions at a higher rate than conservative
ones (whether measured by the ideology of the district court or the
directionality of the decision being reviewed), unified Democratic-led
panels (which exhibit the highest rates of reversals) appear to be more even
in their treatment of liberal and non-liberal lower court decisions.206
Our results also illustrate differences in publication rates across panels
and shed light on the factors that may drive these differences. Democraticled panels are not only more likely to reach a liberal outcome than
Republican-led panels, but they are also more likely to publish their liberal
decisions than unified Republican panels.207 As noted in the Introduction,
200
201
202
203
204
205
206
207
See supra p. 275.
See supra Table 1.
See supra Table 2.
See supra Table 2.
See supra pp. 286–89 and Table 2.
See supra Table 2.
See supra Figures 2A, 2B.
See supra Figure 1.
2013]
It’s the Journey, Not the Destination
319
this relationship between panel composition and publication raises
questions about the interpretation of the results in those empirical studies
that rely solely in a sample of published opinions.208 We illustrate this
potential bias in our analyses of panels’ reversals of lower court opinions.209
We examined the role played by the dominant political preferences in a
panel and the directionality of the lower court opinion being reviewed in the
panel’s decision whether or not to reverse in both subsets of published and
unpublished opinions.210 The results are substantially different in these two
subsets, with panels (in particular unified Democratic-led ones) appearing
to be much more ideologically driven in the subset of published opinions.211
In general, our results highlight the importance of considering judges’
approaches to the decision-making process to gain a more comprehensive
understanding of the differences in case outcomes that have been
documented elsewhere in the literature. Differences in the voting behavior
of Democratic and Republican appointees may reveal more than just
conflicting preferences over final outcomes—they could also reflect
differences in judicial philosophy and in the judges’ approach to
deliberating and analyzing cases. This distinction is very important—there
is a significant difference between having preferences over a final outcome
and manipulating legal reasoning to achieve that outcome and having
differences in legal reasoning that in general lead to different final
outcomes.
208
209
210
211
See supra pp. 271–73.
See supra Part IV.C.
See supra Figure 3.
Compare supra Figure 3A with supra Figure 3B.
F test
Prob > F
[0.0044]
-0.0065
[0.0050]
0.9670
37,254
[0.0131]
-0.0066
[0.0174]
0.5935
62,767
0.061
0.980
1.110
0.345
0.009
-0.0057
-0.0050
0.016
[0.0045]
[0.0124]
0.705
0.549
0.010
0.2852
62,767
[0.0154]
-0.0019
[0.0126]
0.0086
[0.0122]
0.0129
-0.0018
-0.0036
[0.0118]
0.111
0.954
0.010
0.1398
62,767
[0.00753]
0.0004
[0.00587]
0.071
0.975
0.012
0.3805
62,767
[0.0167]
0.0039
[0.0123]
0.0056
0.0044
0.0019
[0.00584]
0.0029
(5)
Civil, Priv.
(4)
Civil, US
[0.0179]
-0.0068
0.0051
0.360
0.782
0.006
0.1113
62,767
0.688
0.559
0.114
0.1408
62,767
[0.0235]
-0.0202
0.0062
[0.00603]
[0.00788]
[0.0166]
-0.0201
(7)
Immig.
[0.00593]
0.0053
(6)
Civ. Right
1.001
0.391
0.005
0.1891
62,767
[0.0154]
-0.0143
[0.0138]
-0.0142
[0.0140]
0.0008
(8)
Pris. Pet.
UNIVERSITY OF LOUISVILLE LAW REVIEW
R-squared
Mean Outcome
Observations
Dem3
Dem 2
Dem1
(3)
Criminal
(2)
US App.
(1)
US Party
Note: Robust standard errors, clustered at the three judge group l level, in brackets (* significant at 10%; ** significant at 5%; *** significant
at 1%). The outcome in column (1) is an indicator variable equal to 1 if the decision under review was rendered by a judge appointed by a
Democratic President; in column (2), the outcome is a variable equal to 1 if the decision under review was favorable for the defendant in a
criminal case; in column (3), the outcome is a variable equal to 1 if the decision under review was favorable for the petitioner in a prisoner
petition case; and in column (4), the outcome is a variable equal to 1 of the decision under review was favorable to the plaintiff in a civil rights
case. Column (5) pools all cases from columns (2) - (4). The explanatory variables of interest are Dem1, Dem2 and Dem3 - a set of dummies
indicating the number of Democrats in the panel. All regressions include year fixed-effects.
APPENDIX TABLE 1: ALLOCATION OF CASES ACROSS PANELS BY TYPE OF CASE
320
[Vol. 51:271
2013]
It’s the Journey, Not the Destination
321
APPENDIX TABLE 2: ALLOCATION OF CASES ACROSS PANELS BY THE
IDEOLOGICAL DIRECTIONALITY OF THE DECISION BEING REVIEWED
Note: Robust standard errors, clustered at the three-judge group l level, in brackets (*
significant at 10%; ** significant at 5%; *** significant at 1%). The outcome in column
(1) is an indicator variable equal to 1 if the decision under review was rendered by a judge
appointed by a Democratic president; in column (2), the outcome is a variable equal to 1 if
the decision under review was favorable for the defendant in a criminal case; in column
(3), the outcome is a variable equal to 1 if the decision under review was favorable for the
petitioner in a prisoner petition case; and in column (4), the outcome is a variable equal to
1 of the decision under review was favorable to the plaintiff in a civil rights case. Column
(5) pools all cases from columns (2)−(4). The explanatory variables of interest are Dem1,
Dem2, and Dem3—a set of dummies indicating the number of Democrats in the panel.
All regressions include year fixed-effects.
(1)
(2)
(3)
(4)
“Liberal Outcome Below Is . . .”
(5)
DemDist
Criminal
U.S. lost
Pris. Pet
Pet. won
Civ. Rights
Pltf. won
Combined
LibBelow
0.0134
0.0039
-0.0038
0.0130
0.0032
[0.0089]
[0.0051]
[0.0057]
[0.0138]
[0.0046]
0.0031
0.0038
-0.0025
0.0080
0.0029
[0.0090]
[0.0052]
[0.0057]
[0.0139]
[0.0046]
-0.0049
0.0024
0.0046
0.0150
0.0052
[0.0111]
[0.0060]
[0.0077]
[0.0164]
[0.0055]
Mean
Outcome
0.3994
0.0283
0.0297
0.0715
0.0361
Observations
R-squared
F test
Prob > F
48,584
0.043
1.908
0.126
17,718
0.003
0.230
0.875
9,707
0.003
0.590
0.622
5,621
0.003
0.404
0.750
33,046
0.001
0.300
0.823
Dem1
Dem2
Dem3