Public Opinion and the U.S. Courts of Appeals:
The Case of Abortion
Christopher D. Johnston
Assistant Professor
Department of Political Science
Duke University
Campus Box 90204
Durham, NC 27708
christopher.johnston@duke.edu
Maxwell Mak
Assistant Professor
Department of Political Science
John Jay College of Criminal Justice
445 W. 59th Street
New York, NY 10019
mmak@jjay.cuny.edu
&
Andrew H. Sidman
Assistant Professor
Department of Political Science
John Jay College of Criminal Justice
445 W. 59th Street
New York, NY 10019
asidman@jjay.cuny.edu
Authors are listed in alphabetical order.
Abstract
Given that a vast majority of cases remain final at the U.S. Courts of Appeals, circuit court jurists
should decide in a manner consistent with Supreme Court precedent if the federal judiciary is to
function appropriately. Lack of such constraint would pressure the Supreme Court to constantly
engage in error correction of lower court decisions, or risk the practical undermining of its
authority. While there is no doubt that legal considerations constrain lower court judges (e.g.,
Benesh 2002; Songer et al 1994), questions remain about the extent to which popular sentiment
influences the decisions of the circuit courts, as has been suggested for the Supreme Court (e.g.,
Epstein and Knight 1998; McGuire and Stimson 2004). To test the impact of public opinion on
circuit court decision-making, we construct an original measure of abortion “mood” and examine
the effect of popular sentiment on abortion cases decided from 1973 to 2006. We find that the
role of public opinion is conditional on the legal context and the ideology of a particular jurist.
Specifically, judges are strategic in their uses of public opinion to advance their policy
preferences. Our analysis provides an important examination of the sources of constraint on
lower court decision-making.
All Article III jurists enjoy the constitutional protection of life tenure, which removes any
direct electoral accountability as well as provides an institutional insulation from the ebbs and
flows of popular sentiment. Through the power of judicial review, judges at all levels of the
federal judiciary must constantly encounter and answer questions of constitutionality regarding
the actions of the popularly-elected branches. With this ability to strike down actions or laws as
inconsistent with the constitution, federal judges are placed in a peculiar position of either
validating the positions of the majoritarian branches of government or standing against the
position supported by those duly-elected with popular support. The countermajoritarian
difficulty is ever present not only for the justices themselves, but also the judges at the U.S.
Courts of Appeals. Moreover, as the number of cases at the circuit courts increases, potential
collisions with popular-elected branches also increase. As a result, the potential for judges to
stand apart from popular sentiment, or public opinion, rises as well.
Despite the fact that federal judges do not need to run for reelection, there are several
potential explanations as to why public opinion may directly influence the choices judges and
justices make.1 First, with neither the power of the purse nor the sword, the federal judiciary is
reliant on the coordinate branches of government to carry out its decisions. Without the support
of the legislature or the executive, the Court truly can be considered the least dangerous branch.
As a result, judges and justices should be mindful of the popular will because the coordinate
branches, which are charged with the enforcement of court decisions, listen and adhere to public
opinion (e.g., Giles, Blackstone, and Vining 2008; Mishler and Sheehan 1993; McGuire and
1
Norpoth and Segal (1994) provide empirical evidence suggesting that public opinion does indeed have an effect—
at least, indirectly through the advice and consent process. Known as the replacement hypothesis (Funston 1975),
this indirect influence suggests that the impact of public opinion is seen primarily through the nomination and
confirmation process. In other words, judges being placed on the bench by popularly elected officials should be at
least somewhat representative of public opinion at the time of their nomination. Thus, as presidents and Senators
replace judges within the federal judiciary, public opinion should be mirrored through the policy preferences Article
III judges. This paper does not discount the replacement hypothesis as an avenue for popular sentiment to affect
decisions within the federal judiciary. Rather, this paper focuses on the direct influence of public opinion.
Stimson 2004). Second, and similarly, sustained and prolonged deviations from public opinion
may decrease the legitimacy of the institution and, as evinced in several instances, place the
federal judiciary in direct confrontation with the majoritarian branches of government (e.g.,
Hooper 2005; Lindquist and Yalof 2001; Scott 2004). Third, judges are indeed members of the
public and may be influenced by popular sentiment through their encounters with legal and
extralegal actors (e.g., Epstein and Knight 1998; Slotnick 1984).
While these explanations may hold true and explain the influence of public opinion in
previous examinations of the Supreme Court (e.g., Giles, Blackstone, and Vining 2008; Mishler
and Sheehan 1993, 1996; Stimson and McGuire 2004), few (e.g., Calvin, Collins and EshbaughSoha 2010) have attempted to decipher the influence of popular sentiment at the U.S. Courts of
Appeals. Moreover, few if any of these previous examinations have incorporated the most
important aspect of judicial decision-making, especially at the circuit courts: the legal context.
This paper attempts to resolve both omissions in an examination of the potential influence of
public opinion on abortion cases decided at the Courts of Appeals. We argue that extralegal
factors such as public opinion influence judges at the Courts of Appeals, but such effects should
be conditional on the legal context and the ideological preferences of lower court judges. In other
words, judges are strategic, using public opinion as a tool to vote consistently with their policy
preferences when voting in accordance with precedent and the legal context would yield a less
optimal policy outcome.
We test our conditional theory of the influence of public opinion on abortion cases
decided at the U.S. Courts of Appeals from 1973 to 2005. With Supreme Court preferences being
arguably more liberal than popular sentiment for most of the time period examined, the judicial
decision-making environment suggests conservative jurists will be the ones most likely to utilize
public opinion as strategic cover to vote consistently with their policy preferences. In contrast,
liberal judges, lacking majoritarian support, are more sensitive to the justices’ preferences,
attempting to maintain positions closer to their preferred positions. Consistent with these
theoretical propositions, the voting behavior of conservative jurists evinces a long-term
relationship with public opinion, yet little to no substantive relationship with Supreme Court
ideology independent of popular sentiment. Conversely, liberals show both short- and long-term
relationships with Supreme Court preferences, but appear unmoved by the ebbs and flows of
popular sentiment. Our examination of lower court decision-making in the area of abortion
contributes a deeper understanding of the evolution of abortion policy as well as a more refined
perspective of the choices lower court judges make in the presence of presence of various
constraints.
Judicial Decision-Making, Public Opinion and the U.S. Courts of Appeals
Judges at the U.S. Courts of Appeals have the policy preferences (e.g., Giles, Hettinger
and Peppers 2002; Songer and Haire 1992), hoping to make decisions as consistent with their
ideologies. As the court directly below the Supreme Court, judges at the Courts of Appeals,
however, are charged, first and foremost, with the duty of applying legal considerations—as
established by the justices—in their decisions (Benesh 2002; Gruhl 1981; Klein 2002; Songer
and Haire 1992; Songer, Segal and Cameron 1994). Failure to do so increases the odds that
circuit court decisions may be petitioned for review (Songer, Segal, and Cameron 1995) and
subject to potential reversal by the nation’s highest court. Aside from the reversal of their
decisions, judges under these conditions pay both a reputational and ideological cost in having
the reprimand made into national precedent. Under this institutional framework, circuit court
judges must be wary of deviating from Supreme Court decisions unless conditions are ripe for
such strategic action.
Public opinion serves as a potential factor signaling the conditions under which breaking
with the Supreme Court may yield two plausible outcomes for a decision that is ideologically
congruent with the policy preferences of the jurist. First, the decision will remain final at the U.S.
Courts of Appeals because the Supreme Court will deny it certiorari. Or, second, the decision
will be upheld by the Supreme Court. Thus, the influence of popular sentiment should not be
direct as considered by most previous examinations of the influence of public opinion on judicial
decision-making. Rather, by altering the probability that a decision will be overturned by the
Supreme Court, public opinion’s impact should be conditional on a given judge’s ideology and
the decision-making environment.
Increasing ideological divergence between a given judge’s ideology and High Court
decision-making should increase the attractiveness of breaking with precedent (Bueno de
Mesquita and Stephenson 2002). Circuit court judges, however, cannot deviate from the
Supreme Court simply because they ideologically prefer such actions without the increased
possibility of review and reversal by the justices. Under these circumstances, a judge that votes
in accordance with ideology, fails to adhere to precedent and makes a decision that does not
mirror public opinion places himself in harm’s way. Not only did this jurist vote ideologically,
but voted ideologically in a manner that deviated from the duties of circuit court judges (i.e.,
apply legal principles consistent with the nation’s highest court) and would probably fail to
garner public acceptance. When ideology and the legal context are divergent, an increase in
ideological voting will thus occur if and only if public opinion is in accordance with judicial
policy preferences.
When public opinion and policy preferences are convergent and therefore predict similar
outcomes in terms of judicial voting behavior, it increases the likelihood that such a decision will
be acceptable to the public as well as decreases the potential that such a decision will be
overturned by the Supreme Court. As Bickel (1962) notes, the Supreme Court must rest its
decisions on great and widely accepted principles; we believe that these principles are
majoritarian values, expressed through contemporaneous public opinion. Public acceptance of
decisions from the federal judiciary increases as such decisions comport and mirror the will of
the people. Thus, if a lower court judge deviates from precedent, but has crafted a decision
mirroring the positions of popular sentiment, it forces the justices to stand against public opinion
in order to remedy such noncompliance or decisions that run counter with the ideological
preferences of the Supreme Court.
The justices care about the legitimacy of the Supreme Court (e.g., Epstein and Knight
1996); the power of the Supreme Court emanates from diffuse support, or overall belief of the
polity in the legitimacy of the institution (Clark 2011). Maintenance of this diffuse support
allows the justices to occasionally break with the public will in specific instances. Thus, issue- or
case-specific support may increase or decrease depending on the issue, but higher levels of
diffuse offers the justices sufficient “cover” from decisions that are inconsistent with
majoritarian values and the popular will.
Historically, consistent, sustained and systematic deviations from public opinion and
majoritarian values have proven to be problematic for the Supreme Court. Examples include the
battle over the communism cases from the House Un-American Activities Committee (HUAC).
Even though these cases are often perceived as Supreme Court challenges to the majoritarian
branches of government, an often overlooked aspect is that these cases were petitioned from
Courts of Appeals decisions that supported public opinion at the time. Watkins v. United States
(1957) reversed the en banc decision in Watkins v. United States (D.C. Cir. 1956), which upheld
a conviction of contempt from Watkins’ refusal to answer questions before a legislative hearing.
In the wake of the decision, Congress considered removing the Court’s appellate jurisdiction to
review and decide cases emanating from HUAC.
By undoing decisions arguably supported by public opinion, the Supreme Court placed
itself in direct confrontation with the legislative and executive branches, threatening the
legitimacy and policy-making ability of the institution. The D.C. Circuit was ordered to
reconsider the question in Barenblatt v. United States (1958) in light of Watkins. If Watkins and
therefore the relevant legal context established by the Court were to hold, the D.C. Circuit
decision should have reversed a conviction of contempt for Barenblatt, whose circumstances
were similar to those of Watkins. Instead, the D.C. Circuit distinguished the factual
circumstances from Watkins, affirmed a charge of contempt of Congress and continued to mirror
the preferences of popular sentiment. After the petition for the writ of certiorari was granted, the
Supreme Court was faced with remedying the inconsistency of Barenblatt with Watkins and
again standing against the popular will. Instead, the Court equivocated, upholding the conviction
and affirming the D.C. Circuit decision.
In sum, lower court judges must be strategic in their deviations of Supreme Courtestablished precedent. When ideologically consistent to do so, siding with public opinion serves
as a signal to lower court judges that breaking away from the relevant legal context may yield
ideologically favorable outcomes. This allows jurists to vote in accordance with their policy
preferences because their decisions will comport with majoritarian values. In doing so, judges
will make it more difficult for the justices to undo such a decision, placing the nation’s highest
court in a tenuous position of standing against popular sentiment to remedy ideologically or
legally inconsistent lower court decisions. As such, the justices may simply avoid reviewing the
case or upholding the ruling.
The Case of Abortion: The Legal Context and Public Opinion
We examine the proposition of strategic applications of public opinion on abortion cases,
which is an ideal issue area of empirical verification of the theory advanced above. First,
abortion has been one of the most salient and politicized issues in the last thirty plus years,
making an examination of decisions handled by the Courts of Appeals important and pertinent.
Second, compliance and responsiveness is generally lower for civil rights and civil liberties
(Baum 1978); as an example of the latter, abortion cases already may be subject to possible
judicial defiance. Lastly, given the politicized nature of abortion, there are serious doubts as to
whether circuit court judges would even use the legal context or public opinion in making
decisions. It may be the case that ideology is the sole predictor of the choices judges make.
In 1973, Roe v. Wade established that strict scrutiny should be the test of constitutionality
for abortion regulations; under this standard, judges must determine whether a law advances a
compelling government interest and whether that law is the least restrictive of means to advance
that interest. Strict scrutiny places the burden of proof on the government, making it more
difficult for a restriction on abortion to survive a challenge of constitutionality. The legal context
under the compelling interest standard offers the most protection of individual liberties and
decisions—more often than not—should be supportive of abortion rights. It should be the case
that liberal jurists, who are assumed to prefer supporting abortion rights, adjudicate under a legal
context that reinforces their policy preferences. Deviating from strict scrutiny would defy
rationality. Thus, if public opinion is to operate as a strategic tool in the aftermath of Roe,
conservative jurists should be the ones most likely to break from precedent (i.e., in terms of
judicial behavior, voting to uphold restrictions on abortion) and utilize majoritarian sentiments to
do so. As such, we hypothesize:
(1) Decision-making of conservative jurists will be conditional on public opinion, but not
liberals judges.
With respect to moderate judges, there are two plausible hypotheses in regards to their voting
behavior. First, they adhere to their institutional role being unmoved by popular sentiment.
Second, these jurists will be sensitive to shifts in public opinion, but for different reasons than
their conservative brethren. Namely, these jurists would most likely adjust decision-making to
comport with public opinion not for strategic purposes in deviating from precedent, but rather for
the purposes of maintaining consistency of legal decisions with the public good.
Abortion jurisprudence also underwent a potential change in Planned Parenthood v.
Casey (1992), which established the undue-burden standard as the appropriate level of judicial
scrutiny for government restrictions on abortion challenged as unconstitutional.2 Whereas
rational basis and strict scrutiny would predict conservative and liberal outcomes, respectively,
undue burden places the legal considerations in between. This change allows for a prediction that
circuit court judges post-Casey should be less supportive of the right to an abortion, ceteris
paribus. This represents an alternative explanation for potential changes in conservative
decision-making. In other words, it predicts a change in behavior due to the Court altering its
2
The Supreme Court actually changed to the undue-burden standard in Webster v. Reproductive Health Services
(1989). There is, however, uncertainty as to the effectiveness of Webster in shifting abortion jurisprudence. First,
only one opinion and one justice (O’Connor) in Webster actually endorsed undue burden. Second, there was no
clarification as to what type of provision constitutes an undue burden on a woman seeking an abortion. Third, there
was conflict with the opinion (Rehnquist) that received the title “Judgment of the Court” and the opinion
(O’Connor) that was the law of the land according to the Marks Doctrine, which was established in Marks v. United
States (1977). Clear and unambiguous Supreme Court policies are most likely to elicit compliance at the lower
courts (Canon and Johnson 1998). When compared to Casey, Webster arguably does not fall into this category.
Due to the multiple ambiguities of the law in Webster, Casey is the appropriate and effective shift in abortion
jurisprudence, because it placed undue burden on firmer and surer legal ground.
own precedent, rather than circuit court judges deviating strategically using popular sentiment as
a guide.
Data and Methods
Dependent Variable. In order to test the hypotheses discussed above, original data was
collected for all abortion cases decided at the U.S. Courts of Appeals from 1973 to 2005.
Identification of the population of abortion cases was completed through searches on
Lexis/Nexis3, which includes information for some case opinions that were unpublished.4 Crosspetitioned cases were counted as separate cases if they challenged different provisions or aspects
of a government regulation seeking to restrict the right to an abortion. Cases containing multiple
dockets were also counted as separate cases if the circuit court opinions made note of the
controversies as being different for each docket, indicated different provisions from each docket,
or arose from different states within the circuit. In order to be included in the population of cases
employed in this paper, cases had to pertain to the constitutionality of abortion regulations that
seek to limit the right to an abortion in general, as a target of government spending, or as a
medical procedure.5 The dependent variable is coded 1 if a judge votes in favor of abortion
rights, 0 otherwise. For ease of discussion, we refer to a vote in favor of abortion rights as a
liberal vote.
3
While this method does place much discretion in identifying the relevant population of cases, the selection process
proceeded quite cautiously to ensure that as many relevant cases were included. First, searches on Lexis/Nexis were
completed employing three main search terms: “abortion”, “trimester” and “viability”. Searches employing major
Supreme Court decisions in the area of abortion were also completed; they were Roe, Doe v. Bolton (1973), Akron,
Webster, and Casey. Second, each case was then screened to ensure that it involved a controversy surrounding a
government regulation of abortion.
4
As Songer (1988) cautions, the use of Shepard’s Citations only elicits cases include full citations or case names in
the opinion. Lexis/Nexis is a more appropriate source for case selection. Although it occasionally suffers from
problems of search over-inclusion as well as under-inclusion, it does offer some information for unpublished
opinions.
5
Cases where the controversy began with such a regulation, but the overall question answered by the court focused
on standing, justiciability, or jurisdiction, were also included. If one is to accept the possibility of opinions being
post-hoc justifications for ideological voting, omission of such litigation and the subsequent decisions would be
problematic and bias the results.
[Figure 1 here]
Abortion Mood. To assess the effects of public opinion on decision-making, we created a
new measure of the aggregate preferences of the public on the issue of abortion, which will
hereafter be labeled “abortion mood” and is presented in Figure 1. The term “mood” is intended
to reflect the latent nature of the variable which we seek to operationalize. The issue of abortion
can be complex, and contains a number of qualitatively distinct facets. Our measure represents
the public’s general orientation, or tendency, toward the issue, averaging over the idiosyncrasies
of the individual facets. In this sense, our approach is in accord with previous research on
aggregate opinion which seeks a meaningful “signal” within the noise of many separate polling
items, and focuses on changes at the margin rather than the objective level (i.e. percentage
support) of opinion on a given issue (Durr 1993; Erikson, MacKuen and Stimson 2002; Mishler
and Sheehan 1993; Stimson 1991; Stimson, MacKuen and Erikson 1995).
To obtain the marginals for our analysis, we searched Roper’s IPOLL Database using the
search query “abortion.” We did not limit our search to a specific time period, and we obtained
items for every year spanning the period 1972-2009. We excluded from consideration any items
which referenced political figures, parties or other political institutions. We also excluded any
items which allowed for multiple responses.6 We restricted our data to major survey
organizations. These considerations produced 742 survey marginals for the period. We then
examined the items individually, and coded each into one of twenty-three qualitatively distinct
categories representing the substantive content of the item. A small number of items suggested
membership in more than one category. In such cases, we made a subjective judgment as to the
6
For example, an item which asked respondents to choose a set from a list of abortion rights would be excluded.
dominant theme of the item. The category listings and additional information concerning our
selection procedures are contained in Appendices A and B.
Most items were naturally in a “Support/Oppose” format, but a meaningful proportion
had to be transformed to accommodate a dichotomous operationalization. When items contained
an even number of ordered categories, we simply split responses into two groups with an equal
number of categories. When an odd number of ordered categories were utilized, we combined
the categories to the left and right of the median category. We then transformed each individual
item into a ratio which divided the percent falling within the “liberal” category by the percent
giving either a “liberal” or “conservative” response.
We consider the ratio for a given item in a given year to be a manifestation of (1) the
latent, general orientation of the aggregate public to the issue of abortion in that year, and (2) the
idiosyncratic characteristics of the item itself. This perspective falls within the domain of
psychometrics known as Item Response Theory (IRT; Embretson and Reise 2000). In the typical
case, IRT models treat a given observed response as cross-nested within a particular item and a
particular unit of observation. The item characteristics include a “difficulty” parameter and a
“discrimination” parameter, which in a regression context are equivalent to a constant term and
the beta coefficient for the latent variable for that particular item as follows:
(1) yijk = αk + βkθj + εijk, for j = 1, …, J units, and k = 1, …, K items.
We estimate the model within a Bayesian, multilevel framework which has important advantages
in the present context. Specifically, the item parameters are themselves given a probability
distribution, and are thus assumed to be random draws from a common population of items. This
can be equivalently considered in terms of a prior distribution for these parameters, which serves
to “partially pool” estimates to the prior’s mean when the number of observations for a given
item is low (Gelman and Hill 2007). This allows us to use all items collected throughout the
entire period, even those for which we have only a single observation. For the latter instances,
the estimates for the item-specific parameters are simply the means of the common distributions
for the difficulty and discrimination parameters respectively. For items with more than one, but
relatively few observations, the partial pooling approach generates estimates with greater
efficiency.
A final consideration for estimation concerns the temporal nature of the latent variable θ.
In the typical IRT case, the units of observation are assumed to be exchangeable such that the
unit identifiers contain no additional information relevant to estimation. In our case, these
identifiers index years, and thus we expect the value of θ in period t to be more related to its
value at t-1 than at t-2. We integrate this information into the model by assuming that the θ
series represents a “random-walk” process such that θt is a function of the previous period’s
value plus some random disturbance. This is operationalized via a prior distribution for the θt
with a mean equal to θt-1, and a variance set by the researcher. The variance chosen determines
the degree of smoothing of values across time (Martin and Quinn 2002; West and Harrison
1997). The model was estimated via the Gibbs sampler in WinBUGS (Lunn, Thomas and
Spiegelhalter 2000). We describe the procedure in greater detail in the Appendix C.
As a sanity check on our estimates, we compared our series to the results from two
alternative estimation procedures. First, we averaged the values for all General Social Survey
abortion items within a given year to create a series which spans the time period 1972-2008 (with
a number of gaps). Second, we estimated abortion mood utilizing Stimson’s (1991) recursive
algorithm which he developed for similar purposes. The correlations between our series and
these alternatives were .63 and .88, respectively. The high correlations of these series,
particularly with Stimson’s measure, give us confidence in the validity of our estimation
procedure. The lower correlation with the GSS series is also to be expected, given the coarse
operationalization. We include plots of all three estimated series in Appendix D. The same
basic patterns of opinion are evident in all three series.
Judge Ideology. Judge’s ideologies are ideological scores derived from the Giles et al.
(2001) coding strategy. A given judge’s ideology takes on the value of the nominating
president’s common space score (Poole 1998) if senatorial courtesy is inactive. If senatorial
courtesy is in play, a given judge’s ideology takes on the value of the home-state senator of the
president’s party; if both home-state senators share the same party affiliation as the nominating
president, the judge’s ideology is measured as the average of the senators’ common space scores.
Supreme Court Ideology. In addition to the ideology of the judge, we control for the
ideology of the Supreme Court and ideology of the remaining panelists on which the appellate
judge serves for a given case. To measure Supreme Court ideology, we employ the Epstein,
Martin, Segal and Westerland (2006) Judicial Common Space (JCS) scores, which converts the
Martin-Quinn ideological scores (Martin and Quinn 2002) for Supreme Court justices into
common space scores (Poole 1998), for the median justice. Thus, it is expected that as the
Supreme Court Median increases, the likelihood of a liberal vote decreases.
Panel Composition is measured as the proportion of the other panelists with an ideology
score (as determined by the Giles et al. (2001) coding strategy, which again is “flipped”) less
than zero, which is the theoretical midpoint of the common space scores. This measure varies
within cases and by each observation. For example, if a judge serves with two judges whose
common space scores are less than zero, Panel Composition takes on the value of 1; if both
judges have common space scores greater than zero, the variable has a value of 0. If one of the
remaining panelists has an ideology score greater than zero and the other’s ideology score is less
than zero, the variable is coded 0.5. While this coding strategy to capture panel effects loses the
finer details of a continuous measure of ideology, it serves as a parsimonious specification of
panel composition akin to the Sunstein et al. (2006) examination, which uses partisanship of the
appointing president. This measure does allow for both avenues of collegial influence: (1) the
overall behavior; and (2) the impact on ideology in the vote choice.
Lastly, we control for case facts in the form of a dummy variable that indicates the
presence of a Casey provision. Casey Provision is measured as a dummy variable coded 1 if a
case concerns one of the provisions discussed in Casey AND was upheld by the Court in Casey,
0 otherwise. If a government regulation on abortion concerned parental consent, medial
recordkeeping, informed consent, or a 24-hour waiting period, the variable Casey Provision was
coded 1, 0 otherwise. If the provision pertained to spousal consent, the variable was coded 0
because the Court in Casey regarded this regulation constituted an undue burden and thus fails to
comport with the Constitution. It is expected that the presence of a Casey provision will decrease
the likelihood of a liberal vote.
Analysis
We model the likelihood of a liberal vote as a function of public opinion, ideology (of the
judge, the Supreme Court, and the panel on which the judge serves), and case facts as follows:
(1) Pr(yit =1) = Φ[β0 + β1 Casey Provisionit + Β2 Supreme Court Mediant + β3 Panel
Heterogeneityit + Β4 Post-Casey + β5 Abortion Moodt + β6 Ideologyit + β7 Ideology2it
Β8 Ideologyit x Panelit + β9 Ideology x Post-Caseyit +
β10 Moodt x Ideologyit + β11 Moodt x Ideology2it]
Consistent with theory and hypotheses, we expect the marginal effect of public opinion to vary
across judge ideology. In the present case, we expect that conservatives will respond more
strongly to public opinion over abortion than liberals. This hypothesis is operationalized via
interactions between abortion mood and ideology, and mood and ideology-squared. The latter
interaction allows the moderating effect of ideology to be non-linear, rather than restricting its
functional form. There is no cost to this specification: if the moderating influence of ideology is
linear, than the quadratic specification will reduce to it.
Results
The results of our analysis are shown in Table 1. First and foremost, we find strong
evidence in favor of our key hypothesis, namely, the moderated influence of public mood on
liberal voting as a function of judge ideology. The two interactions of mood, linear and
quadratic, with judge ideology are statistically significant and substantively meaningful. As logit
coefficients are difficult to interpret substantively, and the quadratic interaction term further
complicates interpretation, we generated the predicted marginal effects of abortion mood on the
predicted probability of a liberal vote for conservative, moderate and liberal judges. In other
words, we examine the expected change in the probability of a liberal vote for a change in
abortion mood, separately for three levels of judge ideology.
These findings are reported in Figure X. The entries in this figure represent the expected
change in the probability of a liberal vote for a change in public mood from its 25th to its 75th
percentile (conservative to liberal) for judges at the 10th, 50th and 90th percentiles of ideology,
respectively. The results are largely consistent with expectations. The marginal effect of
abortion mood on the probability of a liberal vote is large and marginally significant for
conservatives only (B=.17). A change in abortion mood at the aggregate from relatively
conservative to relatively liberal increases the probability of a liberal vote for conservatives by
.17 points, or close to one-fifth of the probability scale. For moderates, the marginal effect is
insignificant, about half the size, and in the incorrect direction, while for liberals the effect is
minimal and insignificant. These effects were generated holding all other variables at their
central tendencies.7
In addition to our key hypothesis, we find support for our other expectations. First, as
expected, ideology is a more important predictor of voting behavior post-Casey than pre-Casey.
In lowering the level of scrutiny applied to abortion cases, the Supreme Court created the
possibility for greater ideological voting in the 1990s. In addition, we find that the presence of a
Casey provision decreases the probability of a liberal vote, as expected. Finally, we find a strong
and significant influence of the Supreme Court’s median on the probability of a liberal vote. As
this variable is coded in the conservative direction, a positive change in the median implies a
decrease in the probability of a liberal vote, all else equal.
Replication at the Aggregate: An Error-Correction Model
The results above suggest, in the case of abortion at least, a meaningful relationship
between public opinion and voting behavior amongst conservative, but not moderate or liberal,
judges at the U.S. Courts of Appeals. The models estimated above examine decision making at
the level of the individual judge. For the final empirical section of the paper, we reexamine our
hypothesis at the aggregate to assess the extent to which, and the qualitative nature of, the
relationship between ideology, public opinion, and voting behavior across time.
We first divided judges into three groups on the basis of the distribution of the ideology
variable. Judges in the first tertile were classified as “conservative,” those in the second tertile
7
To ensure that our results are not idiosyncratic to the chosen model specification, we ran an additional analysis
which trichotomized judge ideology. The pattern of results was very similar in substance and significance.
were “moderate,” and those in the highest tertile were classified as “liberal.” To operationalize
the voting behavior of each group over time, we calculated a moving proportion of liberal votes
for each group separately. This was accomplished by simply generating a 5-year moving
average of liberal votes. The estimated proportion of liberal votes for a given year is thus the
proportion of liberal votes for that group for the year in question, the two previous years, and the
two subsequent years. With this operationalization, we have data on aggregate vote proportions
for the three ideological groups from 1973 to 2005.
To assess the aggregate relationship between mood and voting behavior across
ideological groups, we estimated several error-correction models. These models are particularly
useful in allowing for the assessment of both “long-term” and “short-term” relationships between
variables. A short-term relationship would imply that a change in abortion mood from one year
to the next affects the probability of a liberal vote immediately. A long-term relationship would
imply that mood and voting behavior are in an equilibrium relationship, and thus a “shock” to the
system in the form of a change in public opinion, upsetting this balance, would induce a longterm shift in voting behavior. In other words, the shift in opinion opens a gap in the relationship
between opinion and voting which is corrected at a rate which itself is estimated by the model.
In addition to estimating the short and long-term relationship between mood and voting behavior,
we control for changes in the Supreme Court’s median. We again examine both short and longterm relationships for the median predictor. The model estimated is thus as follows:
(2) Lib. Vote Proportiont = β0 + β1 ΔSC Mediant + β2 ΔAbortion Moodt +
β4 Lib. Vote Proprtiont-1 + β5 SC Mediant-1 + β6 Abortion Moodt-1 + εt
In the error-correction model short-term effects are indicated by the coefficients on the
differenced independent variables (β1 and β2). Long-term effects are indicated by the
coefficients on the lagged independent variables (β5 and β6). The rate at which gaps in the longterm, equilibrium relationship are corrected is indicated by the coefficient on the lagged
dependent variable (β4), and is interpreted as the percentage of the gap which is corrected in each
time period. For example, a coefficient on the lagged dependent variable of .5 would indicate
that only 50% of the shock-induced gap remains after the first period, 25% after the second
period, and so on. We estimated this error-correction model for all judges combined and for each
ideological group separately. The results of these estimations are shown in Table 2. We
examine each in turn.
Looking first at the model for all judges combined, the results are mixed. First, the
model shows no short-term relationships between the proportion of liberal votes and either
abortion mood or the Supreme Court’s median. There is, in contrast, suggestive evidence of
long-term relationships between both independent variables and the proportion of liberal votes.
The coefficient for the lagged value of the Supreme Court’s median is in the expected negative
direction, and approaches significance. The coefficient for public mood is in the expected
positive direction, and also approaches significance. The coefficient on the lagged vote
proportion predictor indicates that shocks to the long-term equilibria implied by these two
coefficients decay at a rate of about 50% per period.
The mixed results for the model including all judges are a result of heterogeneous
dynamics across ideological groups. As indicated by the next three models, this heterogeneity is
highly consistent with theoretical expectations. Looking first at the model for conservative
judges, we find results which converge nicely with the individual-level model above.
Specifically, we find no short-term relationships of conservative voting behavior with either the
Supreme Court’s median or public opinion, and no long-term relationship with the median. In
contrast, we do find a long-term relationship between abortion mood and voting behavior which
is marginally significant. Consistent with the individual-level model, a liberal shift in public
opinion generates a liberal shift in the voting behavior of conservatives, and vice versa. The
coefficient on the lagged vote proportion variable indicates that the gap in the equilibrium
relationship decays at a rate of about 33% per period. Thus, the voting behavior of conservatives
adjusts to changes in the distribution of public opinion rather slowly.
The models for moderates and liberals show results very different from that of
conservatives, as implied by the individual-level models above. With respect to moderates, we
find no short-term relationships with liberal vote proportion, but a long-term relationship with
the Supreme Court’s median which is marginally significant (significant with a one-tailed test).
Importantly, however, the long-term relationship with public opinion does not approach
significance. Similarly, we find no short or long-term relationship of voting behavior to public
opinion amongst liberals. We do, however, find both a short and a long-term relationship of this
group’s decision making to the Supreme Court’s median. The long-term portion of the
relationship shows decay in shock-induced gaps of about 75% per period. Thus, the relationship
between liberal voting and the ideology of the Supreme Court is quite close.
Overall, the results of this second analysis are highly consistent with the individual-level
results above, as well as with theoretical expectations. Conservatives respond to changes in
public opinion over abortion, voting in line with their ideological interests when possible, and
reverting to a more liberal voting record when opinion is out of step with preferences. On the
other hand, moderates and liberals show no relationship with public opinion, but instead respond
to changes in the ideological composition of the High Court.
Conclusion
This paper examines whether and to what degree public opinion directly influences the
choices judges make at the U.S. Courts of Appeals. As the courts directly below the Supreme
Court within the judicial hierarchy, circuit court jurists first and foremost are responsible for
adjudicating cases consistently with precedent established by the justices. Along with the
additional protections of life tenure and a lack of electoral accountability, this role of circuit
court jurists should decrease the impact of public opinion as a constraint. Rather, we
hypothesized that popular sentiment should function as an additional tool that reinforces judges’
policy preferences. In short, we believe that public opinion’s potential influence is conditional on
the legal context and the policy preferences of judges deciding any particular case.
This is especially the case for conservative judges. When judicial discretion is low, public
opinion should matter little unless it serves to advance the policy-making goals of circuit court
judges. When the legal context (i.e., the compelling interest test) and public opinion went
against policy preferences, we see conservative jurists voting counter to expectations derived
from the attitudinal model. What is most striking about the results is that it appears conservative
jurists did indeed follow public opinion to defy the strict scrutiny standard established under Roe.
These judges, even when judicial discretion is low, made decisions that closely followed public
opinion, which was headed in the conservative direction, to begin making decisions that restrict
the right to an abortion.
When judicial discretion is high, we observe two phenomena in abortion cases. There are
judges that vote in accordance with their policy preferences. Liberals vote liberally and
moderates behave like moderates. The behavior of conservatives is slightly different.
Conservative jurists, who are free to vote in accordance with their policy preferences under a
lower standard of adjudication, are significantly affected by popular sentiment. Yet, what is even
more striking, as confirmed by the moving window analysis, is the suggestion that the decisionmaking of these jurists moves with the ebb and flow of popular sentiment. Rather than just
voting ideologically and therefore conservatively, these judges appear to adjust decision-making
in accordance with the changes in public opinion. We rest our explanation of the phenomena on
the extralegal context facing appellate court judges in abortion cases. To generalize these
findings, the lesson we draw from these patterns of results is that public opinion is important to
judges insofar as it is one of several strategic concerns; along with the composition and
preferences of the Supreme Court and the coordinate branches, judges balance against their
desire to vote their own policy preferences.
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Cases Cited
Akron v. Akron Center for Reproductive Health, 462 U.S. 416 (1983).
Barenblatt v. United States, 252 F.2d 129 (D.C. Cir. 1958).
Doe v. Bolton, 410 U.S. 179 (1973).
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APPENDIX A. QUESTION SELECTION
Sources
Questions were obtained from two main sources: (1) searches completed on ipoll.com (Roper
Center) and the National Elections Survey cumulative file. We opted to only use survey
questions from polls conducted by certain sources. They are as follows: (1) ABC; (2)
ANES/NES; (3) Associated Press; (4) CBS; (5) CNN; (6) Fox News; (7) GSS; (8) Harris; (9)
LA Times; (10) NY Times; (11) Pew; (12) Roper; and (13) Time Yankelvich.
Questions
In order for question to be included in the sample, they had to pertain to abortion with a clear
ideological direction, which means responses had to be identifiable on a liberal (less
restrictive) and conservative (more restrictive) dimension. Thus, questions regarding
importance or salience of abortion as an issue would not be included in the sample.
Furthermore, questions that allowed respondents to choose “No Opinion” were also not
included in the sample.
Priming
Questions had to be about abstract restrictions on abortion. Questions with proper nouns (i.e.,
specific candidates, political parties, states, politicians, bills or laws) were not included in the
sample. For example, a question that asked if respondents supported President Clinton’s
position on a piece of legislation would were not included in this sample. Any questions that
make specific mention of dates were also not included.
Similarly, any questions that attempted to ask a respondent about their preferences for
themselves or for their family members in particular situations were not included in the
sample. For example, a question would not be included if a given question prompted a
respondent as follows: “Should your daughter get an abortion…”
Subpopulations
Questions with subpopulations were removed if the subpopulation was not randomly
selected. Several examples include, but are not limited to: (1) asked of only of a particular
subgroup such as registered voters, only women or only blacks; or (2) asked of individuals
who responded in a particular way to a previous question.
A full list of all the items used in the estimation is available upon request.
APPENDIX B. CODING STRATEGY FOR NESTING OF ABORTION QUESTIONS
Frame of the survey question was coded as follows:
1 (access) = if the question pertained to the general access for abortions, including locations,
difficulty and bans on abortion in the abstract.
2 (viability) = if the question pertained to the developmental stage of the fetus, the progress
of the pregnancy as it advances towards term, the specific stage of pregnancy such as
trimester or viability of the fetus.
3 (parent) = if the question pertained to parental consent restrictions on abortion.
4 (doctor) = if the question pertained to the choice of the doctor or the woman seeking the
abortion as well as whether or not the abortion decision was to be left to the doctor, the
woman or both.
5 (constitution) = if the question pertained to whether there should be a constitutional
amendment banning some, any or all aspects of the abortion procedure.
6 (life) = if the question pertained to the life and/or physical health exception.
7 (informed) = if the question pertained to informed consent restrictions on abortion.
8 (spouse) = if the question pertained to spousal consent restrictions on abortion.
9 (partial) = if the question pertained to partial-birth/late term abortions. There must be a
specific mention of either the procedure (e.g., D&X) or the use of “partial-birth” or “lateterm.” If the question only mentioned time or stage of pregnancy, it was coded as 2.
10 (defect) = if the question pertained to general or specific birth defects or fetal health.
11 (economic) = if the question pertained to economic motivations for the abortion decision,
which also include private financial support and private insurance coverage.
12 (morality) = if the question pertained to the moral aspects of abortion, which include
perceptions of whether or not abortions are morally wrong.
13 (consequences) = if the question pertained to the (un)intended consequences of abortion
being illegal.
14 (rape) = if the question pertained to rape and/or incest exceptions to abortion.
15 (unwanted) = if the question pertained to whether the pregnancy was unwanted or where
the abortion decision is balanced some other reason not listed above or below.
16 (government) = if the question pertained to government funding of abortions.
17 (unmarried) = if the question pertained to unmarried or single women seeking abortions.
18 (control) = if the question pertained to abortion used as a birth control method
19 (gag) = if the question pertained to the gag rule, which are restrictions on the discussion of
abortion by public or private medical practitioners.
20 (education) = if the question pertained to the education of abortions in schools.
21 (pill) = if the question pertained to the abortion pill or RU-486.
22 (mental) = if the question pertained to the mental health of the woman seeking the
abortion.
23 (waiting) = if the question pertained to waiting period restrictions on abortion.
APPENDIX C. ESTIMATION OF ABORTION MOOD
To generate the abortion mood series we adapt the basic Item Response Theory (IRT)
framework to the dynamic case of estimating aggregate opinion over time. In the general case,
the researcher possesses data for N units (a sample from the population of interest) on K items.
The observed response for unit j on item k is assumed to be a function of the item-specific
difficulty (αk) and discrimination (βk) parameters, and the unit’s value on a latent trait (θj)
assumed to underlie the covariances amongst the various items as follows:
(1) yijk = αk + βkθj + εijk
εijk ~ N(0, τ)
The general case assumes that the θj are independently drawn from a normal distribution,
typically with a mean and variance fixed to zero and one respectively to identify the model. This
latter assumption of independence fails in the present case, as the θj are not exchangeable given
that the unit identifiers denote the temporal sequence of the series, and units closer together in
time are related by some evolutionary process. This process must then be integrated into the
estimation procedure itself. Our model assumes that the series represents a “random walk”
process such that the value of θ for a given time point is a function of (1) the previous time
point’s value and (2) some random disturbance:
(2) θt = θt-1 + δt
δt ~ N(0, Δt),
where Δt is known as the evolution variance, set a priori by the researcher, which serves to
“smooth” the θt over time (see Martin and Quinn 2002; West and Harrison 1997). In essence,
this equation serves as a prior density for the θt, with prior mean equal to the previous period’s
value of θ and prior variance determining the degree of smoothing. Larger values of the prior
variance represent a more diffuse prior, and thus less pooling of the estimated value of θt to the
previous period’s value. At one extreme, an infinite variance implies no smoothing. At the other
extreme, a prior variance of zero implies a series which is constant over time. The ratio of the
evolution variance to the variance of the “observation equation,” equation (1) above, determines
the degree of smoothing for a given model.
We estimate our model via the Gibbs sampler in the software package WinBUGS. We
assume standard priors for the item-specific parameters as follows:
(3) αk ~ N(µα, τα)
βk ~ N(µβ, τβ),
with uninformative priors for the µ and τ.
We assume a random-walk process for the θt as follows:
(4) θt ~ N(θt-1, Δt) for t = 2, …, T.
Since there is no period “0”, we give the value of θ for the first period a diffuse normal prior,
with a mean of zero. As described above, the value of the evolution variance must be fixed a
priori by the researcher, and determines the level of smoothing of values of the latent factor over
time. We follow Martin and Quinn (2002), and set the value to approximately one-tenth of the
variance of the observation equation. We estimated the model with alternative values of the
evolution variance, and the basic contours of the series over time remained the same.
Substituting estimates from these alternatives into the models estimated in the paper did not
fundamentally alter our results.
We identified the model by fixing the value of the discrimination parameter for item 1
(β1) to “1.” This ensures that higher values of the latent factor indicate a more pro-abortion
orientation in the aggregate (because observations on item 1 represent the ratio of liberal to
liberal plus conservative responses), and guarantees a single posterior with non-negligible mass
for each θt. The model was run for 100,000 iterations after a 50,000 iteration burn-in period.
Standard diagnostics indicated convergence of all parameters to their posterior distributions.
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1975
1973
APPENDIX D. COMPARISON TO ALTERNATIVE ESTIMATION PROCEDURES
A. Dynamic IRT Model
.100
.050
.000
-.050
-.100
-.150
-.200
B. General Social Survey
0.71
0.69
0.67
0.65
0.63
0.61
0.59
0.57
0.55
C. Stimson’s (1991) Algorithm
0.65
0.6
0.55
0.5
0.45
0.4
0.35
Table 1. Results for Judge-Level Voting Behavior
_____________________________________________
Variable
B
SE
p
_____________________________________________
Casey Provision
-.22
.11
.04
SC Median
-1.88
.64
.00
Panel Heterogeneity
.33
.32
.30
Post-Casey
-.55
.24
.02
Abortion Mood
Ideology
Ideology^2
5.64
-1.92
1.88
2.81
.99
.87
.05
.05
.03
Ideology X Panel Het.
Ideology X Post-Casey
Ideology X Mood
Ideology^2 X Mood
-.51
.83
-29.68
27.35
.51
.43
13.15
13.05
.32
.05
.02
.04
.68
.30
.02
Constant
Pseudo R^2
.03
N
613
_____________________________________________
Notes: Entries are probit coefficients and standard
errors.
Table 2. Results for Error-Correction Models
______________________________________________________________________________________
All Judges
Conservatives
Moderates
Liberals
_______________
________________ _______________
______________
B
SE
p
B
SE
p
B
SE
p
B
SE
p
______________________________________________________________________________________
Differenced Variables
SC Median
Mood
-.15
.27
.24
.24
.54
.26
.03
.31
.46
.44
.95
.48
-.38
.21
.29
.31
.20
.51
-.35
.26
.16
.25
.04
.31
SC Median
Mood
Vote Proportion
-.26
.31
-.50
.17
.20
.18
.14
.13
.01
-.12
.56
-.33
.22
.34
.11
.58
.11
.01
-.32
-.13
-.42
.18
.21
.15
.10
.53
.01
-.33
.25
-.75
.11
.23
.17
.01
.29
.01
Constant
.30
.11
.01
.20
.07
.01
.25
.09
.01
.46
.10
.01
Lagged Variables
R^2
.28
.16
.27
.42
N
32
32
32
32
______________________________________________________________________________________
Notes: Entries are OLS coefficients and robust standard errors.
Figure 1. Abortion Mood, 1973-2005
1973
1977
1981
1985
1989
1993
1997
Notes: Estimates from dynamic item response model.
2001
2005
Figure 2. Marginal Effect of Abortion Mood across Ideology
Marginal Effect of Abortion Mood
.35
.25
.15
.17
.05
.02
-.05
-.09
-.15
-.25
Conservative
Moderate
Liberal
Notes: Entries represent the predicted change in the probability of a
liberal vote for a change in abortion mood from its 25th to its 75th percentile.
Extended lines are 95% confidence intervals. “Conservatives,” “Moderates,”
and “Liberals” correspond with the 10th, 50th and 95th percentiles of ideology
respectively.