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STATE JUDICIAL SELECTION SYSTEM AND THE ETHNIC, RACIAL, AND GENDER
DIVERSITY OF THE BENCH
Helen Bass
Honors Undergraduate Thesis, Economics
April 29, 2016

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STATE JUDICIAL SELECTION SYSTEM AND THE ETHNIC, RACIAL, AND GENDER
DIVERSITY OF THE BENCH
ABSTRACT
This paper utilizes data from 2010 to investigate the effect of judicial selection system on
the diversity of state court judges at the trial, appellate, and supreme court level. That the
judicial population represent the voting population has long been considered a necessary goal,
and many have claimed that particular systems favor nontraditional candidates more than others.
Similar to previous work in this area, the presence of female and minority attorneys seems the
single largest factor determining the diversity of state judges at all three court levels. Building
onto past work, a state’s exposure to a particular selection system, measured in years, is
investigated. However, the addition of this measure confounds any clear indications of
differential effects of particular selection systems. The unclear results of this study, in
conjunction with the results of previous works, call for a longitudinal look at the effect of
selection system on judicial diversity, utilizing data collected over time. A study of this nature
could take advantage of the data collected regarding judicial diversity from as far back as 1985.

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INTRODUCTION
The selection of state judges takes on five main forms in the US—each state decides on a
judicial selection system for each level of court. In partisan election systems, judges are selected
by popular vote with their political party listed on the ballot. In nonpartisan election systems,
judges’ political parties are prohibited from the ballot. In executive appointment systems, the
governor holds the authority to appointment judges, though their appointments often must be
approved by the legislature. In legislative appointment systems, the legislature holds both
appointment and approval power. In merit selection systems, an informed and balanced
committee—often composed of attorneys, retired justices, public officials, and lay persons—
submits nominations, the governor appoints from the nominations submitted, and the legislature
approves the appointment.
The efficacy of different selection systems has long been a topic of debate. At the time of
their founding, most states utilized executive appointment systems and lifetime judicial terms.
With the Jacksonian era came the inclination that the “will of the people” play a more deciding
role in government, and many states adopted partisan election systems. Many of these states
would later shift to non-partisan election as fear grew that party influences were dominating the
public sphere. In the early nineteenth century, momentum for an informed and unbiased judicial
selection method led states to consider merit selection—a system first adopted by Missouri in
1940 (Reddick 2008).
Movements for various judicial selection systems have been accompanied by challenging
questions for state judiciaries. Though election systems capitalize on democratic ideals, there are
doubts that the public is well-informed of judicial candidates or even current state justices. A

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2003 survey of public perceptions of the judiciary concluded that the courts “do not appear to
weigh heavily on the public mind (Rott, Hansen, Mott & Grimes 2003).” Merit selection
certainly provides for informed decision-making, but many argue that political and legal elites
hold too much power in this system (Hurwitz & Lanier 2001). This theme—balancing public
input with informed and fair selection—has been recurrent in the judicial selection debate and
salient in subsidiary discussions.
More recently, the ethnic, racial, and gender diversity of judges has entered the academic
and legal realm as a necessary consideration for a fair and balanced judiciary. Those in favor of
merit selection have suggested that informed committees would be more likely to favor non-
traditional candidates and that the political connections required for campaigning in election
systems would eliminate their chances besides. Those in favor of election systems have argued
that merit selection committees, almost always partially comprised of legal elites, would stick to
traditional candidates and, in doing so, maintain the status quo (as cited in Hurwitz & Lanier
2001).
Following a statistical report released by the Fund for Modern Courts and an early series
of papers authored by Nicholas Alozie beginning in the 1980’s, not a small amount of academic
literature has empirically investigated the connection between selection system and judicial
diversity (Fund for Modern Courts 1985, Alozie 1988). Alozie addressed the diversity of the
bench by creating separate analyses for female, African American or Black, and Hispanic or
Latino state judges based on a state’s judicial candidate pool, demographic of voters, and judicial
selection system. These analyses were followed by similar work utilizing more recent data and
featuring additional controls such as executive ideology, public ideology, level of court (trial,

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appellate, or supreme), and size of court (number of seats at each level) (Hurwitz & Lanier 2003,
Reddick et. al 2009, Williams 2007).
The results of these studies have afforded some clarity to the judicial selection debate,
though the effect of selection system on diversity remains uncertain. Alozie’s papers from the
late 1980’s found that judicial selection was not significantly related to the presence of female or
African American or Black judges on state courts, though there was some evidence that partisan
election systems benefited Hispanic candidates in areas with a high population of Hispanic
voters. A 2001 paper released by the American Judicature Society found that between 1985 and
1999, “selection method does not seem to be associated with the diversity characteristics of those
selected for the bench (Hurwitz & Lanier 2001).” A 2007 paper released in Social Science
Quarterly suggested that “nonpartisan elections increase women’s representation on trial courts”
and that merit selection slightly repressed female representation at the appellate level (Williams
2007). However, another paper released by the American Judicature Society in 2009 found that
a disproportionate quantity of minority and female judges were appointed via merit selection.
The inconsistent results of past literature have left room for future work investigating the
connection between diversity of the bench and judicial selection system. The regression analysis
in this study takes a form similar to that of Nicholas Alozie’s 1988 paper, “Black Representation
on State Judiciaries.” In his paper, black representation on state courts is regressed on state
selection system in an OLS model, controlling for black lawyers and voters by state. In a series
of companion papers, Alozie repeats this model for female and Hispanic judges. Though some
of the literature following the publication of Alozie’s papers has grouped all minority judges
together, there is evidence that different minority groups achieve judicial office in slightly
different ways (Alozie 1990). In keeping with Alozie’s work, I separate analyses based on

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ethnic, racial, and gender characteristics of judges. I detract from Alozie’s model by dropping
the control variable for proportion of minority voters for each state from the regressions. The
high multicollinearity between proportion of minority lawyers and proportion of minority voters
by state could have potentially disrupted the results of the models. I add to his work in four
ways, the first of which being a simple update using data from 2010.
Next, I test for court level-specific effects by breaking down each state observation for
the different levels of court: trial, appellate, and supreme. Empirical analysis has found that the
effect of selection methods varies across the different level of courts (Williams 2007, Reddick et.
al 2010). However, it is not uncommon for all judges of one state to be grouped together when
studying the effect of selection system and diversity of the bench.
In order to examine the effect of a selection method over time, I include an ‘exposure’
variable which controls for the amount of time, measured in years, passed following the adoption
of a particular selection system. While some courts have utilized the same selection system for
over a century, some have only recently adopted a new selection mechanism. The adoption of a
particular selection mechanism could have important institutional effects over time (i.e.
campaign mechanisms).
Finally, I use a structural estimation model (SEM) to examine the inter-court effects of
diversity and selection method. It seems common knowledge in the legal field that “trial courts
often serve as a training ground for appellate seats (Williams 2007),” making the pool of trial
court judges relevant to the diversity of appellate judges. The SEM tables in this paper utilize
female and minority lawyers as a candidate pool for the trial court, and trial judges as a candidate
pool for the appellate level.

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DATA & METHODS
Data for this study came from two sources, and the data from both sources was collected
for the year 2010. Data for minority and female state judges, state selection system, and history
of state selection system reforms were taken from the National Center for State Court’s Judicial
Selection in the States website.1
Data for female and minority lawyers was taken from the US
Census Bureau.2
Using this data, I present four sections of regressions, separated by judge demographic.
These four demographic sections are separate analyses specific to all minority judges, African
American or Black judges, Hispanic or Latino judges, and female judges. The dependent
variable in each regression is the proportion of minority, African American or Black, Hispanic or
Latino, or female judges in relation to all judges by state and specific court level. For example,
the mean of the dependent variable in the female-specific regressions for trial courts is equal to
.225. This simply means that, on average, female trial judges make up 22.5% of all trial judges
on state courts.
This dependent variable is regressed on the type of selection system specific to each state
and court level. Because so few states use either legislative or executive appointment, I combine
the two selection systems into a single ‘elite appointment’ category, reducing the categories of
1
Data for female/minority state judges, selection system, and exposure to selection system by
state and level of court can be found at the National Center for State Court’s “Judicial Selection
in the States” website under the sections for “Diversity of the Bench”, “Methods of Judicial
Selection”, and “Altering Selection Methods”, respectively. It is important to note that some
judges are selected by informal, interim mechanisms which may be different than the official
selection method of the given state and court level. No estimate was found for the number or
proportion of judges selected informally. This introduces error into the regressions in this study.
2
Data was taken from the US Census Bureau’s American Community Survey using 2006-2010
5-year estimates. For black lawyers, individuals that cited “Black or African American Alone” as
well as individuals that cited “White and Black or African American” were included in the data.

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selection system to four (Hurwitz & Lanier 2008). These four selection system categories are
represented in the regressions as dichotomous variables. A state with a partisan election system
at the trial level will have an observation of ‘1’ for the partisan election dummy variable at the
trial level, and an observation of ‘0’ for the other selection system variables at that level. In
order to create the “exposure” variable, I take the log of the number of years since a system has
been adopted and multiply it by the selection system dummy variables.
I include one control variable in the regressions. This is a continuous variable for the
proportion of female (FL), African American or Black (BL), Hispanic or Latino (HL), or
minority lawyers among all lawyers, by state (ML).3
This control variable has been the most
prominent determinant of judicial diversity in previous literature (Alozie 1988, 1990; Hurwitz &
Lanier 2003; Reddick et. al 2009;Williams 2007).
I evaluate each of the four demographic groups with two separate analyses: one set of
Ordinary Least Squares (OLS) regressions and two structural equation models (SEM). I begin
each OLS table by regressing the proportion of female/minority judges on proportion
female/minority lawyers alone. In the second column of the table, I include the selection system
dummies (without the exposure-selection variable) into the regression. In the third column, I
regress proportion female/minority judges on female/minority lawyers, selection system, and the
exposure-selection variables. The partisan election dummy variable was omitted to avoid
multicollinearity. Below is an example of the OLS regressions for female trial judges:
(1) FJti = b0 + b1FLi + u
(2) FJti = b0 + b1FLi + b2NEti + b3MSti + b4Eti + u
3
A complete list of variable symbols can be found in Appendix I at the end of the paper. Appendix II contains the
regression equations, and Appendix III contains the results of the regressions.

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(3) FJti = b0 + b1FLi + b2NEti + b3MSti + b4Eti + b5EXNEti + b6EXMSti + b7EXEti +
b8EXPETi + u
Following the OLS table for each level of court, I include the results of a two-step SEM
table. The dependent variable of the first level of this model is the proportion of female/minority
judges among all judges at the trial level, controlling for female/minority lawyers. The
dependent variable in the second level of this model is the proportion of female/minority judges
at the appellate level, including female/minority trial judges and minority voters as independent
variables but removing female/minority lawyers from the regression. I execute this model
twice—once with the exposure-selection variables and once without. The SEM for female
judges is as follows:
(I) a. FJti = b0 + b1FLi + b2NEti + b3MSti + b4Eti + u
b. FJai = b0 + b1FJti + b2NEai + b3MSai + b4Eai + u
(II) a.FJti =b0 +b1FLi +b2NEti +b3MSti +b4Eti +b5EXNEti +b6EXMSti +b7EXEti +b8EXPETi +u
b. FJai = b0 + b0FJti + b0NEai + b0MSai + b0Eai + b0EXNEai + b0EXMSai + b0EXEai + u
Judicial representation and selection system are specific not only to the state but the level
of court as well. Thus, each state has three potential observation points for the year 2010: at the
trial, appellate, and supreme court levels. However, some states do not have all three levels of
court, most often lacking an appellate court system. In some states, judicial selection system for
a single court level changes by county or city. In each case, the observation was dropped. This
brought the total number of observations to 47 at the trial level, 39 at the appellate level, and 48
at the supreme court level. When the exposure variable was introduced, uncertain information
on state court reform dropped the number of observations to 46 at the trial level, 37 at the

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appellate level, and 47 at the supreme court level. The SEM table suffered from inconsistencies
in the data set, bringing the total number of observations from 34 to 36 for those models.
RESULTS
The first set of OLS regressions (Table 1) investigates the presence of female justices at
each level of state court. In these regressions and in those following, the dummy variable for
partisan election is dropped for multicollinearity. At the trial level (FJt), only the variable for the
proportion of female lawyers in a state (FL) remains positive and significant throughout all three
regressions. Further, the coefficient for this variable hovers around 1.0, meaning that the model
would predict a one percent increase in FL in a state to translate into a one percent increase in
FJt. Without including the exposure variable in the regression (Column (2)), the coefficient for
elite appointment is both negative and statistically significant, predicting an eleven percent drop
in FJt for states with elite appointment, relative to partisan election. The coefficients of the
remaining selection methods are both positive, though relatively small and statistically
insignificant. However, once the exposure variables are included in the regression (Column (3)),
the elite selection variable drops in significance. Besides FL, only one variable in Column (3)
holds statistical significance—the exposure variable for nonpartisan election is both positive and
significant.
At the appellate level, the coefficient for FL is neither positive nor significant in any of
the three regressions. This is consistent with the hypotheses that the factors affecting female
representation at the trial level differ from the factors affecting representation at the appellate
level (FJa) (Williams 2007). No other variables quite reach statistical significance in any of the

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columns. However, the coefficient for merit selection is quite large, predicting an eleven percent
decrease in FJa in states with merit selection at the appellate level, given that the average FJa
falls at thirty percent. With a p-value of .105 and only thirty-seven available observations, the
coefficient certainly begs for further investigation.
Though the coefficient for proportion of FL is positive throughout all three supreme court
OLS regressions (FJs), it comes close to approaching statistical significance only in Column (3)
(p-value of .156). None of the coefficients are significant in Columns (1) or (2), but the dummy
variable for merit selection is positive and significant at the ten percent level in Column (3),
where the exposure variables are included. However, it should be noted that the R-squared value
drops substantially in both the appellate and supreme court OLS regressions in comparison to the
trial court section.
The SEM table (Part I), which examines the inter-court effects on female representation
at the trial and appellate level, mimics much of the results from the separate OLS regressions.
With and without the exposure variable included, the proportion of female lawyers in a state is
positively correlated with the proportion of female trial judges, though the effect is larger in
magnitude in the SEM table. In Part I, the elite appointment dummy variable is negative and
significant at the trial level, and the merit selection dummy variable is negative and significant at
the appellate level. In Part II, the exposure-nonpartisan election variable is positive and
significant (at the ten percent level) for trial courts, but no variable is significant at the appellate
level. These results mimic Columns (2) and (3) for the trial and appellate OLS models. The
SEM table adds to the OLS models by examining the effect of the proportion of female judges at
the trial level on the proportion of female judges at the appellate level. In both Part I and Part II,

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this effect is not statistically significant. The R-squared values of the SEM table are higher than
those of the OLS models at the trial and appellate levels.
In the trial (BJt), appellate (BJa), and supreme court (BJs) OLS analyses for African
American or Black judges, only the proportion of black lawyers (BL) shows a statistically
significant relationship to the proportion of black judges. The relationship between these
variables is larger than a one-to-one ratio. For a one percent increase in BL, the model
approximately predicts a 1.4 percent increase in BJt. This ratio is even higher at the appellate
and supreme court level. However, none of the coefficients for the selection dummy variables or
the exposure-selection variables show significance.
Similar to the OLS regressions, Part I and II of the SEM tables showed a positive and
statistically significant relationship between BL and BJt. Unlike the results of the SEM table for
female justices, BJt was positively and significantly correlated with BJa. In Part II, the merit
selection exposure variable was negative and significant at the ten percent level, but no other
selection system variables were significant in either Part I or II.
The proportion of Hispanic or Latino lawyers (HL) by state remained positive and
significant throughout the OLS regressions for Hispanic or Latino judges (HJt, HJa, and HJs).
This variable shows a particularly high coefficient at the supreme court level, predicting 2.24
percent increase in judicial representation for a one percent increase in HL. In Column (3) of the
appellate level regressions (HJa), the nonpartisan election, merit selection, and elite appointment
dummy variables all have negative and statistically significant coefficients relative to partisan
election, but so is the exposure variable for partisan election negative and significant. These
conflicting results seem to suggest that, overall, the selection-related variables do not have

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coefficients significantly different from zero. However, an F-test failed to show that, held in
conjunction, the coefficients were not significantly different from zero. At the supreme court
level (HJs), only the HL variable holds significance.
In Part I and Part II of the SEM table, HL is positively and significantly correlated with
HJt, and HJt with HJa. In Part I, none of the selection system dummy variables are significant.
At the trial level and with the exposure-selection variables included in the regression, the
nonpartisan election, merit selection, and elite appointment dummy variables all show positive
and significant coefficients relative to partisan election, though the exposure variable for partisan
election is positive and significant as well. The appellate section of Part II shows negative and
significant coefficients on the nonpartisan election, merit selection, and elite appointment
dummy variables relative to partisan election, but the exposure variable for partisan election is
negative as well. These conflicting results seem to suggest that, overall, the selection-related
variables do not have coefficients significantly different from zero. However, an F-test failed to
show that, held in conjunction, the coefficients were not significantly different from zero.
In the minority OLS regressions, the variable for proportion of minority lawyers (ML)
maintains a positive and significant coefficient through all three court levels. In Column (2) of
the trial level regressions (MJt), the merit selection dummy variable is both positive and
significant. This variable maintains its sign and significance in Column (3), but the dummy
variables for nonpartisan election and elite appointment as well as the exposure variable for
partisan election become positive and significant as well. These conflicting results seem to
suggest that, overall, the selection-related variables do not have coefficients significantly
different from zero. However, an F-test failed to show that, held in conjunction, the coefficients
were not significantly different from zero. This same issue is apparent in Column (3) of the

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appellate regression (MJa). In the supreme court Column (2) regressions (MJs), the nonpartisan
election, merit selection, and elite selection variables are all negative relative to partisan election.
However, these coefficients switch signs and drop in significance when the exposure variables
are included in Column (3), and the exposure variable for partisan election is positive.
Throughout the SEM table for minority judges, ML is positively and significantly
correlated with MJt, and MJt with MJa. In Part I, only the merit selection dummy variable at the
trial level holds significance outside of the ML and MJt variables. At the trial level and with the
exposure-selection variables included in the regression, the nonpartisan election, merit selection,
and elite appointment variables are all positive and significant relative to partisan election,
though the exposure variable for partisan election is positive and significant as well. At the
appellate level, the same variables all hold significance, though they also switch signs. These
conflicting results seem to suggest that, overall, the selection-related variables do not have
coefficients significantly different from zero. However, an F-test failed to show that, held in
conjunction, the coefficients were not significantly different from zero.
DISCUSSION
The results for the female OLS models support the hypothesis that the female attorney
population of a state is a more significant determinant of trial court judges than judges at the
appellate or supreme level. At the trial level, female attorney representation holds a one-to-one
ratio with female representation on the state trial benches. However, unlike past predictions, the
SEM tables do not show that female judges at the trial level are correlated to female
representation on the appellate benches (Williams 2007, Tokarz 1986). Overall, the r-squared

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value for the female-only regressions was very low in comparison with the other three regression
sections—approaching zero for the appellate and supreme court regressions. This seems to
suggest that there are other variables significantly affecting female representation. The results
do not clearly show that any selection system favors or disfavors female representation at any
level of court. This is in opposition to the findings of Margaret Williams’s 2007 paper
published in Social Science quarterly, in which she describes nonpartisan election as favorable to
female candidates at the appellate level.
The results suggest that the presence of African American or Black attorneys has a
positive influence on African American or Black judges at all three court levels. The ratio
between African American or Black lawyers and judges is larger than a one-to-one ratio at all
three levels of court. The results also show a positive relationship between African American or
Black trial judges and their appellate counterparts in the SEM tables, showing that states with a
high BJt value also have a higher BJa value. However, no selection system stands out as
favoring these judicial candidates. Much of these results mimic those of Alozie’s findings using
data from 1985 (Alozie 1988).
Like the results for African American or Black judges, Hispanic or Latino attorney
presence (HL) holds a positive and significant relationship to the presence of Hispanic or Latino
judges at all three levels of court. This relationship is strongest at the supreme court level—a
one percent increase in HL roughly corresponds to a 2.2 percent increase in HJs. In addition, the
SEM tables show that states with high HJt values, on average, have higher HJa values. Also
similar to the results for African American or Black judges is the fact that no selection system
stands out as favoring these judicial candidates.

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The proportion of minority lawyers in a state is positively and significantly correlated
with minority judicial representation on all three levels of court, hovering near a one-to-one ratio
in both the OLS and SEM results. However, the results regarding election system are unclear.
Any results that appear when the selection system dummy variables are included are confounded
by the addition of the exposure variables.
The overall results regarding female/minority judicial representation and selection system
are unclear, and the inclusion of the exposure variable extinguishes any clarity that might have
been. These conflicting and inconsistent results call for a longitudinal study which examines the
effect of selection systems over time. Not only is the number of observations limited in a cross-
sectional study, but such a format also misses the natural experiments created by the
implementation of different selection systems over time. A longitudinal study would have the
potential to ferret out state-specific effects which could be influencing the results of cross-
sectional studies. Additionally, there is practical potential for a study of this caliber, as data on
female and minority justices and lawyers stretches back to at least 1985.

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Appendix I: Variable Key
s, a, t Court level label for selection method variables (PE, NE, MS, E) and
percent female/minority judges (FJ, BJ, HJ, MJ). Supreme court
variables labeled with ‘s’; appellate court variables labeled with ‘a’,
trials court variables labeled with ‘t’.
PEx Partisan election of judges, by state and court level (x will be an s, a,
or t for the level of court)
NEx Nonpartisan election of judges, by state and court level (x will be an s,
a, or t for the level of court)
MSx Merit selection of judges, by state and court level (x will be an s, a, or
t for the level of court)
FJx Percent female state judges among all state judges, by state and court
level (x will be an s, a, or t for the level of court)
BJx Percent African American/Black state judges among all state judges,
by state and court level (x will be an s, a, or t for the level of court)
HJx Percent Hispanic or Latino state judges among all state judges, by
state and court level (x will be an s, a, or t for the level of court)
MJx Percent racial/ethnic minority judges among all judges in the state, by
state and court level (x will be an s, a, or t for the level of court)
FL Percent female lawyers among all lawyers, by state
BL Percent African American/black lawyers among all lawyers, by state
HL Percent Hispanic or Latino lawyers among all lawyers, by state
ML Percent minority lawyers among all lawyers, by state

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Appendix II: Equations
Female trial court judges:
(1) FJti = b0 + b1FLi + u
(2) FJti = b0 + b1FLi + b2NEti + b3MSti + b4Eti + u
(3) FJti = b0 + b1FLi + b2NEti + b3MSti + b4Eti + b5EXNEti + b6EXMSti + b7EXEti +
b8EXPEti + u
Female appellate court judges:
(1) FJai = b0 + b1FLi + u
(2) FJai = b0 + b1FLi + b2NEai + b3MSai + b4Eai + u
(3) FJai = b0 + b1FLi + b2NEai + b3MSai + b4Eai + b5EXNEai + b6EXMSai + b7EXEai +
b8EXPEai + u
Female supreme court judges:
(1) FJsi = b0 + b1FLi + u
(2) FJsi = b0 + b1FLi + b2NEsi + b3MSsi + b4Esi + u
(3) FJsi = b0 + b1FLi + b2NEsi + b3MSsi + b4Esi + b5EXNEsi + b6EXMSsi + b7EXEsi +
b8EXPEsi + u
African American or Black trial court judges:
(1) BJti = b0 + b1BLi + u
(2) BJti = b0 + b1BLi + b2NEti + b3MSti + b4Eti + u
(3) BJti = b0 + b1BLi + b2NEti + b3MSti + b4Eti + b5EXNEti + b6EXMSti + b7EXEti +
b8EXPEti + u

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African American or Black appellate court judges:
(1) BJai = b0 + b1BLi + u
(2) BJai = b0 + b1BLi + b2NEai + b3MSai + b4Eai + u
(3) BJai = b0 + b1BLi + b2NEai + b3MSai + b4Eai + b5EXNEai + b6EXMSai + b7EXEai +
b8EXPEai + u
African American or Black supreme court judges:
(1) BJsi = b0 + b1BLi + u
(2) BJsi = b0 + b1BLi + b2NEsi + b3MSsi + b4Esi + u
(3) BJsi = b0 + b1BLi + b2NEsi + b3MSsi + b4Esi + b5EXNEsi + b6EXMSsi + b7EXEsi +
b8EXPEsi + u
Hispanic or Latino trial court judges:
(1) HJti = b0 + b1HLi + u
(2) HJti = b0 + b1HLi + b2NEti + b3MSti + b4Eti + u
(3) HJti = b0 + b1HLi + b2NEti + b3MSti + b4Eti + b5EXNEti + b6EXMSti + b7EXEti +
b8EXPEti + u
Hispanic or Latino appellate court judges:
(1) HJai = b0 + b1HLi + u
(2) HJai = b0 + b1HLi + b2NEai + b3MSai + b4Eai + u
(3) HJai = b0 + b1HLi + b2NEai + b3MSai + b4Eai + b5EXNEai + b6EXMSai + b7EXEai +
b8EXPEai + u
Hispanic or Latino supreme court judges:

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(1) HJsi = b0 + b1HLi + u
(2) HJsi = b0 + b1HLi + b2NEsi + b3MSsi + b4Esi + u
(3) HJsi = b0 + b1HLi + b2NEsi + b3MSsi + b4Esi + b5EXNEsi + b6EXMSsi + b7EXEsi +
b8EXPEsi + u
Minority trial court judges:
(1) MJti = b0 + b1MLi + u
(2) MJti = b0 + b1MLi + b2NEti + b3MSti + b4Eti + u
(3) MJti = b0 + b1MLi + b2NEti + b3MSti + b4Eti + b5EXNEti + b6EXMSti + b7EXEti +
b8EXPEti + u
Minority appellate court judges:
(1) MJai = b0 + b1MLi + u
(2) MJai = b0 + b1MLi + b2NEai + b3MSai + b4Eai + u
(3) MJai = b0 + b1MLi + b2NEai + b3MSai + b4Eai + b5EXNEai + b6EXMSai + b7EXEai +
b8EXPEai + u
Minority supreme court judges:
(1) MJsi = b0 + b1MLi + u
(2) MJsi = b0 + b1MLi + b2NEsi + b3MSsi + b4Esi + u
(3) MJsi = b0 + b1MLi + b2NEsi + b3MSsi + b4Esi + b5EXNEsi + b6EXMSsi + b7EXEsi +
b8EXPEsi + u

Figures significant at the 10% level denoted with *, at the 5% level denoted with **, at the 1% level denoted with ***
Appendix II: Results
Dependent Variable: Female state judges as a proportion of all state judges, by level of court
Trial Appellate Supreme
(1) (2) (3) (1) (2) (3) (1) (2) (3)
Intercept -0.08 -0.104 -0.067 0.389* 0.371 0.042 0.53 0.063 -0.475
(0.101) (0.094) (0.213) (.230) (0.239) (0.583) (.217) (0.235) (0.454)
Proportion Female Lawyers 0.969*** 1.102*** 0.94*** -0.265 -0.011 -0.063 0.837 0.778 1.07
(0.319) -0.296 -0.316 (0.718) (0.721) (0.081) (.689) (1.07) (0.740)
Nonpartisan Election - 0.019 -0.162 - -0.0128 0.0326 - 0.025 0.281
(0.026) (0.193) (0.0725) (0.053) (0.066) (0.416)
Merit Selection - 0.029 -0.029 - -0.115 0.0489 - -0.002 0.78
(0.027) (0.21) (0.0687) (0.545) (0.62) (0.447)
Elite Appointment - -0.11** -0.168 - -0.08 -0.04 - 0.001 0.69
-0.043 (0.255) (0.091) (0.58) (0.094) (0.539)
Exposure* Nonpartisan
Election
- - -0.041 - - 0.002 - - 0.046
(0.021) (0.065) (0.05)
Exposure* Merit Selection - - 0.012 - - 0.046 - - -0.91
(.031) (0.067) (0.069)
Exposure*Elite Selection - - 0.011 - - 0.073 - - -0.056
(.044) (0.079) (0.089)
Exposure* Partisan Election
- - -0.003 - - 0.075 - - 0.098
(0.031) (0.101) (0.078)
R-Squared 0.1611 0.3575 0.4181 0.1362 0.1821 0.0304 0.0323 0.1391
Adj. R-Squared 0.1437 0.2963 0.2923 0.0346 -0.0516 0.0098 -0.0578 -0.0421
Observations 50 47 46 40 39 37 49 48 47

Dependent Variable: African American or Black state judges as a proportion of all state judges, by level of court
(1) (2) (3) (1) (2) (3) (1) (2) (3)
Intercept 0.005 0.002 0.054 0.017 -0.007 0.002 -0.004 -0.012 -0.19
(0.007) (0.12 (.085) (0.15) (0.032) (0.209) (0.016) (0.03)
Proportion African
American/Black Lawyers
1.29*** 1.37*** 1.41*** 1.67*** 1.68*** 1.66*** 1.69*** 1.69*** 2.03***
(0.144) (0.153) (0.18) (.294) (0.323) (0.373) (0.352) (0.395) (0.17)
Nonpartisan Election
- -0.009 -0.0648 - 0.03 0.018 - -0.001 0.001
(0.013) (0.102) (0.033) (0.248) (0.032) (0.222)
Merit Selection - 0.016 -0.45 - 0.028) 0.0163 - 0.012 0.262
(0.134) (0.103) 0.032) (243) (0.032) (0.212)
Executive Appointment
- -0.006 -0.169 - 0.024 -0.077 - 0.054 0.213
(0.022) (0.132) (0.041) (0.264) (0.045) (0.269)
Election
- - 0 - - 0.0001 - - 0.039
(.012) (0.031) (0.29)
Exposure* Merit Selection
- - 0.002 - - -0.036 - - 0.043
(0.015) (0.03) (0.033)
Exposure*Elite Selection
- - 0.026 - - 0.022 - - 0
(0.023) (0.036) (0.044)
- - -0.011 - - -0.002 - - 0.036
(0.018) (0.046) (0.038)
R-Squared 0.6246 0.6631 0.6763 0.4588 0.4636 0.4867 0.327 0.3528 0.439
Adj. R-Squared 0.6167 0.631 0.6063 0.4446 0.4005 0.34 0.3127 0.2925 0.3208
Observations 50 47 46 40 39 37 49 48 47

Dependent Variable: Hispanic or Latino state judges as a proportion of all state judges, by level of court
(1) (2) (3) (1) (2) (3) (1) (2) (3)
Intercept -0.003 -0.001 -0.14 -0.015 -0.01 0.624 -0.032 -0.038 0.002
(0.004) (0.008) (0.66) (0.01) (0.028) (0.251) (2.24) (0.023) (0.170)
Proportion Hispanic/Latino
Lawyers
.623*** 0.634*** 0.759*** 1.4*** 1.415*** 0.823** 2.24*** 2.259*** 2.224***
(0.073) (0.081) (0.1) (.186) (0.218) (0.325) (.204) (0.227) (0.287)
- -0.005 0.116 - 0.005 -0.596** - -0.007 -0.009
(0.008) (0.07) (0.030) (0.261) (0.025) (0.188)
Merit Selection - 0.003 0.116 - -0.018 -0.68** - 0.012 -0.048
(0.009) (0.073) (0.027) (0.252) (0.024) (0.198)
Elite Appointment - -0.009 0.16* - -
(0.014) (0.088) 0.004 0.68** 0.03 -0.044
(0.036) (0.283) (0.035) (0.234)
Election
- - 0.003 - - -0.006 - - -0.008
(0.006) (0.022) (0.019)
Exposure* Merit Selection - - 0.005 - - 0.012 - - 0.007
(0.009) (0.023) (0.026)
Exposure*Elite Appointment - - -0.008 - - 0.015 - - 0.008
(0.013) (0.027) (0.034)
Exposure* Partisan Election - - 0.028 - - -0.128 - - -0.007
(0.013) (0.050) (0.035)
R-Squared 0.6134 0.6269 0.6807 0.5979 0.617 0.695 0.7487 0.7302 0.7321
Adj. R-Squared 0.3052 0.5905 0.6097 0.5874 0.572 0.6078 0.7127 0.7051 0.6757
Observations 49 46 45 40 39 37 49 48 47

Dependent Variable: Minority state judges as a proportion of all state judges, by level of court
(1) (2) (3) (1) (2) (3) (1) (2) (3)
Intercept -0.022 -0.0314 -0.289** 0.039** 0.048 0.534** -0.01 0.102
(0.13 (0.02) (0.139) 0.019 (0.039) (0.239) (0.038) (0.068)
Proportion Minority Lawyers
1.05*** 1.08*** 1.12*** 0.878*** 0.88*** 0.749*** 1.86*** 1.3*** 1.3***
(.098) (0.092) (.094) (.132) (.0.137) (0.144) (.297) (.30) (0.317)
- -0.019 0.3* - 0.002 -0.37 - -0.168** 0.374
(.021) (0.153) (0.039) (.261) (0.072) (0.467)
Merit Selection - 0.047 0.33* - -0.013 -0.323 - -0.115* 0.103
(.164) (0.037) (0.261) (0.069) (0.515)
Elite Appointment - 0.001 0.304 - -0.005 -0.578* - -0.056 0.48
(0.035) (.202) (0.049) -0.287 (0.102) (0.605)
Election
- - -0.16 - - -0.023 - - -0.01
(0.017) (0.032) (0.056)
Exposure* Merit Selection
- - 0.008 - - -0.041 - - 0.076
(0.24) (0.032) (0.079)
Exposure*Elite Appointment
- - -0.012 - - 0.024 - - -0.007
(.035) (0.038) (0.01)
- - 0.053* - - 0.102* - - 0.111
(.028) (.05) (0.088)
R-Squared 0.7036 0.7784 0.8045 0.5364 0.5627 0.6419 0.3172 0.4012 0.4392
Adj. R-Squared 0.6975 0.7573 0.7622 0.5242 0.5112 0.5396 0.3026 0.3455 0.3212
Observations 50 47 46 40 39 37 49 48 47

Female Judges - SEM Results
PART I: PART II:
Dependent Variable: FJt Dependent Variable: FJt
Intercept -0.216** Intercept 0.304***
(0.101) (0.218)
FL 1.378*** FL 1.249***
(0.313) (0.326)
NEt 0.012 NEt 0.012
(0.025) (0.187)
MSt 0.013 MSt 0.166
(0.027) (0.214)
Et -0.133*** Et 0.005
(0.046) (0.235)
Dependent Variable: FJa EXNEt 0.032
Intercept 0.294*** (0.019)
(0.117) EXMSt 0.034
FJt 0.323 (0.032)
(0.452) EXEt -0.002
NEa -0.007 (0.039)
(0.068) EXPEt 0.027
MSa -0.123 (0.035)
(0.066) Dependent Variable: FJa
Ea -0.037 Intercept 0.045
(0.099) (0.414)
R-Squared 0.4448 FJt -0.117
Adj. R-Squared 0.1743 (0.488)
Observations 36 NEa 0.373
(0.478)
Ea 0.238
(0.544)
EXNEa -0.009
(0.070)
EXMSa 0.053
(0.060)
EXEa -0.017
(0.088)
EXPEa 0.076
(0.086)
R-Squared 0.5131
Adj. R-Squared 0.1719
Observations 34

African American or Black Judges - SEM Results
PART I: PART II:
Dependent Variable: BJt Dependent Variable: BJt
Intercept 0 Intercept 0.03
(0.014) (0.094)
BL 1.403*** BL 1.459***
(0.174) (0.198)
NEt -0.005 NEt -0.061
(0.014) (0.112)
MSt 0.013 MSt -0.082
(0.015) (0.118)
Et -0.005 Et -0.153
(0.025) (0.135)
Dependent Variable: BJa EXNEt 0.005
Intercept -0.006 (0.012)
(0.035) EXMSt 0.016
BJt 1.123*** (0.018)
(0.250) EXEt 0.028
NEa 0.043 (0.022)
(0.034) EXPEt -0.007
MSa 0.024 (0.020)
(0.033) Dependent Variable: HJa
Ea 0.020 Intercept -0.040
(0.046) (0.193)
R-Squared 0.6524 BJt 1.132***
Adj. R-
Squared 0.3785
(0.240)
Observations 36 NEa 0.100
(0.224)
Ea -0.015
(0.261)
EXNEa -0.005
(0.028)
EXMSa -0.052
(0.028)
EXEa 0.023
(0.042)
EXPEa 0.007
(0.042)
R-Squared 0.6736
Adj. R-
Squared 0.4395
Observations 34

Hispanic or Latino - SEM Results
PART I: PART II:
Dependent Variable: HJt Dependent Variable: HJt
Intercept 0.003 Intercept -0.310***
(0.008) (0.100)
HL 0.622*** HL 0.966***
(0.087) (0.130)
NEt -0.010 NEt 0.271***
(0.008) (0.098)
MSt 0.003 MSt 0.273***
(0.008) (0.100)
Et -0.017 Et 0.340***
(0.014) (0.113)
Dependent Variable: HJa EXNEt 0.006
Intercept -0.024 (0.006)
(0.039) EXMSt 0.009
HJt 2.434*** (0.010)
(0.544) EXEt -0.011***
NEa 0.033 (0.013)
(0.043) EXPEt 0.06***
MSa 0.003 (0.019)
(0.008) Dependent Variable: MJa
Ea -0.017 Intercept 0.879***
(0.014) (0.158)
R-Squared 0.6218 HJt 0.967***
Adj. R-Squared 0.0592 (0.309)
Observations 35 NEa -0.823***
(0.176)
Ea -0.879***
(0.204)
EXNEa -0.010
(0.020)
EXMSa 0.004
(0.021)
EXEa 0***
(0.032)
EXPEa -0.181***
(0.033)
R-Squared
Adj. R-Squared
Observations

Minority Judges - SEM Results
PART I: PART II:
Dependent Variable: MJt Dependent Variable: MJt
Intercept -0.034 Intercept -0.488***
(0.022) (0.152)
ML 1.102*** ML 1.176***
(0.097) (0.097)
NEt -0.011 NEt 0.453***
(0.022) (0.160)
MSt 0.050** MSt 0.521***
(0.023) (0.177)
Et -0.002 Et 0.513***
(0.040) (0.203)
Dependent Variable: MJa EXNEt -0.004
Intercept 0.077** (0.016)
(0.040) EXMSt -0.005
MJt 0.785*** (0.027)
(0.1331) EXEt -0.018
NEa 0.009 (0.033)
(0.042) EXPEt 0.091***
MSa -0.037 (0.030)
(0.039) Dependent Variable: MJa
Ea -0.010 Intercept 0.881***
(0.056) (0.202)
R-Squared 0.7886 MJt 0.600***
Adj. R-Squared 0.3955 (0.104)
Observations 36 NEa -0.702***
(0.227)
MSa -0.637***
(0.232)
Ea -0.906***
(0.270)
EXNEa -0.023
(0.029)
EXMSa -0.044
(0.029)
EXEa 0.029
(0.044)
EXPEa -0.169***
(0.043)
R-Squared 0.8344
Adj. R-Squared 0.6326
Observations 34

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