Latino Representation and Education: Pathways to Latino Student Performance

Abstract

The rapid growth of the Latino population in the U.S. over the past 15 years has led to a significant increase in levels of primary and secondary school enrollment rates of Latino children. Research on Latino education has demonstrated the institutional and contextual challenges faced by this increasingly significant group, but studies that link Latino representation and Latino educational performance have neglected to sort out the direct and indirect effects of representation on student achievement. The central assumption in these studies outlines a causal chain running from Latino political representation (school boards), to Latino bureaucratic representation (administrators and teachers), to Latino student performance. This study tests these theoretical assumptions by employing a path analytic model using data from 1,040 Texas school districts for the years 1997–2001 to tease out the direct and indirect effects of Latino representation on Latino student achievement. We find robust evidence of the impact of Latino political representation on Latino educational attainment in Texas, operating via a direct effect on the number of Latino administrators and teachers and an indirect effect on Latino student performance. Additionally, our results demonstrate that descriptive representation becomes substantive representation in the area of education policy for Latinos and that this relationship remains strong over time. These findings underscore the importance of school board elections and school district hiring practices on Latino student performance.

Full text

Latino Representation and Education: Pathways to Latino Student Performance
Ashley D. Ross
Ph.D. Candidate
Department of Political Science
Texas A&M University
aross@politics.tamu.edu
Stella M. Rouse
Assistant Professor
Department of Government and Politics
University of Maryland
srouse@gvpt.umd.edu
Kathleen A. Bratton
Associate Professor
Department of Political Science
Louisiana State University
bratton@lsu.edu
An earlier version of this paper was presented at the 7
th
Annual Conference on State Politics and
Policy, Austin, TX, February 23-24, 2007. We appreciate the insightful comments of Jason
Casellas, Ken Meier, the anonymous reviewers, and the editorial team at State Politics and
Policy Quarterly. We also thank Ken Meier at Texas A&M University for sharing his data for
this project.
AUTHOR INFORMATION:
Ashley D. Ross is a PhD candidate at Texas A&M University studying comparative politics and
public policy.
Stella M. Rouse is an Assistant Professor in the Department of Government and Politics at the
University of Maryland. Her research focuses on ethnic and racial politics with a special interest
on Latino representation.
Kathleen A. Bratton is Associate Professor of Political Science at Louisiana State University.
Her research and teaching interests center on state politics and policy; gender, race, ethnicity,
and politics; and legislative politics.
Abstract
1

The rapid growth of the Latino population over the past fifteen years has led to a
significant increase in levels of primary and secondary school enrollment rates of Latino
children. Research on Latino education has demonstrated the institutional and contextual
challenges faced by this increasingly significant group, but studies that link Latino representation
and Latino educational performance have neglected to empirically sort out the direct and indirect
effects of representation on student achievement. The central assumption in these studies outlines
a casual chain running from Latino political representation—school boards—to Latino
bureaucratic representation—administrators and teachers—to Latino student performance. This
study tests these theoretical assumptions by employing a path analytic model using data from
1,040 Texas school districts for the years 1997-2001 to tease out the direct and indirect effects of
Latino representation on Latino student achievement. We find robust evidence of the impact of
Latino political representation on Latino educational attainment, operating via a direct effect on
the number of Latino administrators and teachers and an indirect effect on Latino student
performance. Additionally, our results demonstrate that descriptive representation becomes
substantive representation in the area of education policy for Latinos and that this relationship
remains strong over time. These findings underscore the importance of school board elections
and school district hiring practice on Latino student performance.
Latinos are the largest and fastest growing minority group in the U.S., particularly among
children—those who have the most at stake in the education system (U.S. Census Bureau 2000;
Llagas 2003).
1
As illustrated by Figure 1, the rapid growth in the number of Latinos has resulted
in a rise in Latino enrollment at elementary and secondary schools across the nation, while
2

during the same period, enrollment rates have decreased for whites and have remained stagnant
for blacks.
<FIGURE 1 ABOUT HERE>
At the same time, the challenges faced by Latino students in education have been well-
documented. The national drop-out rate for Latino students is substantially higher than for
others, and Latino students score substantially lower than Anglo students on standardized tests
(National Center for Education Statistics 2002). Moreover, Latino students are more likely than
other students to face challenges related to immigration (Darder, Torres, and Gutierrez 1997;
Gibson 2002); most students who are classified as “limited English proficient” are Latino (Riley
and Pompa 1998).
Not surprisingly, the question of Latino student achievement has attracted considerable
scholarly attention in the last two decades. Much of the scholarly interest in the educational
outcomes of Latino students draws on research in the fields of education, policy, and public
administration (e.g. Steele 1997; Bali and Alvarez 2004; Smith and Larimer 2004). However,
because of the role that elected officials play in crafting education policy, the extant scholarship
also draws upon theories of political representation, and specifically focuses on the potential
connection between descriptive and substantive representation. In this paper, we are interested
in examining how education policy, created by school boards, influences educational
performance. Ours is the first contemporary effort to take a comprehensive approach to this
question, explicitly recognizing that the link between school boards and test scores is
substantively important—but indirect. Specifically, we model the indirect effect of political
representation on educational outcomes for Latino students, operating through the direct effects
of school board composition on administrators, teachers, and resources. Moreover, our general
3

finding that minority representation matters for policy outcomes that are relevant to minority
citizens has broad implications for local and state governing bodies in policy areas beyond
education.
Descriptive representation means that, "The representative does not act for others; he
'stands for' them, by virtue of a correspondence or connection between them, a resemblance or
reflection" (Pitkin 1967, p. 61). The core of political representation, however, is substantive:
"representing here means acting in the interest of the represented, in a manner responsive to
them" (Pitkin 1967, p. 209). Though Pitkin herself emphasizes the distinction between the two
forms of representation, her work has served as the foundation of rich literature that examines the
potential connection between the two, particularly with respect to the representation of women
and minorities. Despite the apparent intuitive appeal of the potential link between descriptive
and substantive representation, the findings of a broad set of empirical studies are quite mixed.
The research, taken as a whole, suggests that the strength of the link between descriptive and
substantive representation depends on several contextual factors, such as the salience of the
demographic characteristic, the salience of the policy, and the degree of control elected officials
have over the policy (e.g. Bratton and Haynie 1999; Mansbridge 1999; Meier 1993a). Bratton
and Ray (2002), for example, argue that descriptive representation matters most significantly
when policies are first being developed—that is, when elected officials have the most control
over policy development. Haynie (2000) and Preuhs (2007) point out that for descriptive
representation to translate into substantive representation, not only the overall legislative body,
but also the set of relatively powerful legislators must be descriptively representative.
Prior research has focused on the connection between descriptive representation on
school boards and substantive representation of the interests of constituents, in the form of
4

student performance. But does education policy meet the conditions for the translation of
descriptive representation into substantive representation, described above? Ethnicity and race
are salient characteristics, given the well-documented ethnic and racial differences in educational
performance. The educational performance of Latino students is clearly of interest to Latino
constituents (Martinez-Ebers, Fraga, Lopez, and Vega 2000). Indeed, the link between
representative and constituency may be even more evident in local representative institutions
than in state or national representative politics.
As we noted earlier, the one missing piece of the puzzle is discretion of the policy maker
over relevant policy. School boards are relatively small, and have direct control over education
policy.
2
Nonetheless, it is difficult for school boards to influence test scores and other measures
of educational performance, at least in the short-run (Meier and England 1984). Given that
school board members are relatively far removed from the classroom in which performance is
measured, what is the mechanism by which descriptive representation influences educational
outcomes?
The first section of the paper outlines the literature on Latino representation and Latino
student performance. The concept of representation is discussed and past findings regarding the
link between Latino representation and Latino educational outcomes are highlighted. The
second section builds an argument for presenting a path analytic model as a way to interpret
concepts of representation and to understand the effects of both political and bureaucratic factors
on Latino education. In section three we present the data and specify the models to be analyzed.
Results of the structural equation model are examined in section four. In the last section we
discuss conclusions of our analysis and offer some suggestions for future research on Latino
education using this type of modeling.
5

Previous Literature
Latino representation has been widely studied, from city councils (Shockley 1974) to
national and state legislatures (Kerr and Miller 1997; Bratton 2006) to school boards (Meier and
Stewart 1991). These works generally show that ethnic diversity in representation is associated
with the substantive representation of interests on issues that are relatively salient to Latino
citizens.
3
For example, Bratton (2006) found that Latino representatives were more likely than
their colleagues to focus on issues related to bilingual education and immigration. Using
Southwest Voter Research Initiative Scores, Kerr and Miller (1997) found that Latino members
of the U.S. House were supportive of the interests of Latino citizens.
A number of prior studies demonstrate a relationship between racial or ethnic diversity on
school boards and policy outcomes. Much of the early research focused on the relationship
between the representation of African-Americans and educational outcomes for African-
American students. Using data from urban school districts in the 1970s, Meier and England
(1984) found that a higher number of African-Americans on a school board was associated with
a variety of positive educational outcomes, including higher retention and lower suspension rates
for African-American students, a higher number of African-Americans in gifted classes, and a
lower number of African Americans in special education classes. Using a survey of a national
sample of large school districts, Stewart, England, and Meier (1989) found that the proportion of
members of the school board who were African-American was significantly associated with the
proportion of school administrators who were African-American, even after taking into account
the proportion of African-Americans in the district population. Likewise, racial composition of
school administrative staff was related to the racial composition of teaching staff. However,
racial diversity on the school board was not significantly associated with racial diversity among
6

teachers. Stewart et al. observe that this combination of findings is not surprising, given that
school boards can support efforts to recruit or promote black administrators, while at the same
time respecting the norm that they should not be involved in hiring teaching staff (p. 299-300).
4
Similar studies on Latino representation and educational outcomes suggest (but generally
do not directly test) that the connection between descriptive representation on school boards and
substantive educational outcomes is largely indirect. Using data from the late 1970s, Fraga,
Meier, and England (1986) found that the proportion of school board members who were Latino
was significantly and positively associated with higher numbers of Latino teachers. And while
Latino school board representation was not linked to Latino student performance, Latino teachers
were correlated with lower dropout and higher graduation rates of Latino students. Similarly,
Meier and Stewart (1991) found that Latino school board members were related to greater
numbers of Latino school administrators, which in turn was associated with higher numbers of
Latino teachers, which in turn was associated with positive educational outcomes for students.
More recent research has generally confirmed these paths. Scholars have found that the presence
of Latino school board members is positively associated with more Latino school administrators,
and more Latino school administrators were related to more Latino teachers, particularly in
majority-Latino districts (e.g. Leal, Martinez-Ebers, and Meier 2004), and that greater ethnic and
racial diversity on school boards, as a result of elections based on wards, contributes to more
diversity among administrators and teachers (e.g., Meier et. al. 2005).
One of the few studies that distinguishes between direct and indirect effects of minority
representation on educational attainment produced mixed findings. In a study of 64 Texas
school districts from 1976 through 1986, Polinard, Wrinkle, and Longoria (1990) find that Latino
school board representation directly influences the proportion of Latino school administrators;
7

the proportion of Latino school administrators, in turn, directly influences the proportion of
Latino teachers. Moreover, the total effect of school board representation on the proportion of
Latino teachers is enhanced by a small but significant direct effect of school board representation
on the proportion of Latino teachers. However, they find much weaker evidence of a link
between the proportion of Latino teachers and educational outcomes; while (as expected) a
higher percentage of Latino teachers was associated with the assignment of fewer Latino
students to bilingual programs, the proportion of Latino teachers was actually associated with
higher suspension rates for Latino students.
We contribute to prior knowledge by providing the first contemporary analysis to trace
the full path from descriptive representation on school boards (in this case, the proportion of
Latinos elected to the board) to substantive educational outcomes (in this case, test passage
rates). We argue that the link between school board representation and substantive outcomes is
primarily indirect: school boards influence administrators, administrators influence teachers, and
teachers influence educational outcomes. Distinguishing between the direct and indirect effect
of descriptive representation is crucial, because it helps us assess the link between descriptive
representation and substantive representation in a context where elected officials do not have
direct and immediate control over policy-making.
We note, in particular, that we incorporate all four stages of the process into our path
model: school boards, administrators, teachers, and students. In general, the last step in this
pathway from descriptive representation to substantive outcomes—the link between teachers and
student performance—is the least examined in the prior literature. Several recent studies (e.g.,
Leal, Martinez-Ebers, and Meier 2004; Meier et. al. 2005) focus primarily on the relationships
among diversity on school boards, and diversity among administrators and among teachers. Yet
8

the earlier literature was not entirely conclusive regarding the influence of teachers on student
outcomes; Polinard, Wrinkle, and Longoria (1990), for example, found mixed and relatively
weak effects of Latino teachers on Latino student performance. Student performance represents
the most "substantive" of interests considered; without changes in actual educational outcomes,
the representation of Latinos on school boards, among administrators, and among teachers can be
seen as largely symbolic. Therefore, this is a crucial part of our analysis.
In the following section, we outline a path model linking descriptive representation to
substantive outcomes.
Model Development: Mapping the Causal Links that Affect Latino Education
As discussed above, research on the determinants of Latino education policy focuses
primarily on political and bureaucratic representation. There is a general assumption in the
literature of a “top-down” process, whereby political factors affect bureaucratic elements, which
in turn influence policy outcomes and educational performance (Meier, Juenke, Wrinkle, and
Polinard 2005). Researchers often make implicit assertions about the relationship among
variables within this process. However, empirical analyses usually segregate political and
bureaucratic variables
5
, or test as direct effects what are likely indirect effects of one variable
upon another (i.e. school board influence on student achievement). These implicit assertions
often occur with little analysis or discussion about how variables in the entire process may
interact with one another. Even though regression estimates can show the significant (or
insignificant) effects of certain independent variables upon dependent variables, less is surmised
about the causal relationships of these measures.
<FIGURE 2 ABOUT HERE>
9

In Figure 2 we present a conceptual model to examine the causal connections between
political, bureaucratic, and performance variables that are hypothesized to affect Latino
educational attainment. We argue that, consistent with the concepts of representation, the “top”
point in the path analytic model is Latino political representation, as measured by school board
composition. We expect that school districts with a higher percentage of Latino students will
have more Latinos on school boards, as maintained by the concept of descriptive representation.
In turn, we expect that school boards with more Latino board members will also positively affect
the number of Latino administrators and Latino teachers in a district. Further, in line with the
theory of representative bureaucracy, which according to Meier and O’Toole, is a theory “that
considers such questions as when minority bureaucrats are likely to act in ways that benefit
minority citizens” (2006: 180), we argue that Latino administrators should also have a positive
effect on the number of Latino teachers in a district; and that Latino teachers, themselves acting
as “street level bureaucrats” (Lipsky 1980), will improve the educational attainment of Latinos.
In short, descriptive representation will lead to substantive representation (Kerr and Miller 1997;
Bratton and Haynie 1999; Swers 2000; Bratton 2006).
Of course, school districts have similar incentives and punishments for student
performance. Nonetheless, a great deal of prior empirical research has shown that race,
ethnicity, and social class are salient factors in educational outcomes. In the first two steps of
our path model (school board representation influences on administrators, administrative
representation influence on teachers), there may be a universal commitment to positive
educational outcomes—but Latino school board members and administrators may be more likely
to identify the recruitment of a diverse set of administrators and teachers as important—and may
be more effective in those recruiting efforts.
10

With respect to the last step of our path model (teacher influence over student
performance), teachers clearly have an incentive to do what they can to improve test scores. At
the same time, research indicates that at least some portion of the ethnic, racial, and gender gap
in test scores can be attributed to "stereotype threat"—that children perform less well on exams
when they are concerned about confirming what they know to be negative cultural stereotypes
about their intellectual and academic abilities (Steele and Aronson 1995). Group composition—
and presumably the race, ethnicity, or gender of the teacher—can serve to contradict those
negative stereotypes, and mitigate self-doubt, thus improving educational performance.
We also assert that the number of Latino students in a district influences variables
throughout the model. We have previously mentioned the hypothesized effect of Latino students
on school board composition. In addition, we expect that an increase in the number of Latino
students will have a positive influence on the number of Latino school administrators and Latino
teachers. Similarly, an increase in Latino students should also increase the amount of
expenditures per student, and positively influence Latino educational achievement. A rise in the
number of Latino students should also cause an increase in the overall number of low income
students, since poverty is a major issue in the Latino community (Stokes 2003). In turn, we
expect that an increase in the number of low income students will negatively impact overall
student achievement.
The effect of Latino students on teacher experience is theoretically unclear. One
argument is that an increase in Latino students will lead to more experienced teachers, since it is
experienced teachers who are better equipped at tackling the wide Latino achievement gap. On
the other hand, many experienced teachers are unwilling to teach in high minority school
11

districts because of a lack of resources. To test these theoretical expectations, we employ a
structural equation model using various measures, which are discussed in the following section.
Data and Methods
Our path analysis includes 1,040 public school districts in Texas for the years 1997-2001.
The data used in this study come from a larger data set on Texas educational outcomes, the
Texas Minority Education Study (Meier 2005). These data were compiled using information
obtained from the Texas Education Agency and supplemented with both an original survey and
other supporting data sources.
6
Texas is chosen as the sample for this research because it is a
heterogeneous state with diverse school districts (Meier and O’Toole 2006). Texas also has a
large Latino population dispersed throughout the state, which makes it an excellent test case for
exploring the determinants of Latino student performance. Further, the Latino and general
population of Texas mirrors the rest of the country in terms of racial diversity, which makes the
findings of this study generalizable to many contexts across the United States.
7
The data for this study include a variety of political, bureaucratic, and achievement
measures that are commonly recognized in the literature as potential influences on Latino student
performance. Descriptive statistics for the variables used in this study can be found in Appendix
A.
To estimate the effects of Latino representation on the educational achievement of Latino
students, we focus on one specific measure of performance—standardized test scores.
Educational attainment of Latino students and students in general is measured in our model as
the percentage of students that pass the TAAS (Texas Assessment of Academic Skills). This test
is given to children every year from grades three to eight, and is a requirement for high school
graduation (Slobogin 2001). Although there are other measures of achievement, passage rates
12

for the TAAS provide a good way to gauge educational attainment throughout the careers of
students. The average Latino pass rate in Texas school districts for the years 1997-2001 is 73%
while 86% of White students passed, according to our data.
TAAS pass rates is an excellent measure of substantive representation because it not only
captures Latino educational attainment but also Latino preferences. Overall, Latinos value
education—95% of Latino parents say that it is “very important” for their children to go to
college compared to 78% of White parents that say the same (Pew 2004). And six in ten Latinos
consider standardized tests like the TAAS to be unbiased indicators of educational attainment
(Pew 2004). Therefore, both outcomes and preferences are represented in the measure of TAAS
pass rates, making it a good measure of substantive representation in the context of education.
Our first variable of interest is political representation, measured as the percentage of
Latinos serving on school boards as a total of all school board members in a district. School
boards, as the most basic units of representation, are involved in all areas of the district’s
education system. Leal et al. state that school boards, “shoulder much of the responsibility for
the quality of public education in America” (2004: 1225). Consistent with minority
representation theory and past studies (Fraga, Meier, and England 1986; Polinard, Wrinkle, and
Longoria 1990; Meier and Stewart 1991), we expect Latino school board members to positively
affect Latino representation on the administrative and teacher levels as descriptive representation
develops into substantive representation.
The theory of representative bureaucracy suggests that minority administrators and
teachers, who are at the “front lines” of implementing education policy, have a substantial effect
on the academic performance of minority students (Hess and Leal 1997; Meier, Wrinkle, and
Polinard 1999). We include two variables of bureaucratic representation in our model that
13

capture the number of Latino administrators and the number of Latino teachers which are
employed in each school district. These variables are measured as a percentage of total
administrators, and as a percentage of total teachers, respectively.
Literature on Latino education also finds that, not only the presence, but also the
experience of minority teachers can be crucial in influencing minority student achievement (e.g.,
Meier et al 1999). Therefore, our model contains a variable that measures the average years of
teacher experience. This variable should positively correlate with Latino student performance.
Scholars have also examined whether spending on education also promotes minority
student achievement; despite the intuitive appeal of such expectations, the evidence is mixed.
Studies conducted by Hanushek (1981, 1998) find a negative correlation between expenditures
and achievement; while other research has shown positive, but minimal impact from
expenditures (Wenglinsky 1997; Figlio 1998). Similarly, research on the effects of expenditures
on minority and Latino student attainment has also produced mixed results, primarily finding
mediating factors affecting a direct significant link between expenditures and achievement
(Meier et al. 1999; Leal and Hess 2000; Meier and O’Toole 2006). Our conceptual model
hypothesizes a positive link between monetary resources, and both overall student achievement
and Latino student achievement. Although there are different types of education expenditures,
our variable, “per pupil spending”, consists only of per student expenditures for instructional
purposes. As Meier and O’Toole (2006) argue, this may better tap into the direct impact of
expenditures upon Latino student performance.
As previously mentioned, poverty disproportionately affects the Latino population. Over
27 percent of Latino children live in low-income homes, and Latino poverty has been linked to
poor educational attainment (Brindis, Driscoll, Biggs, and Valderrama 2002). Therefore, we
14

control for the percentage of low income students, measured as the percentage of students who
are eligible for free or reduced lunches at school. In addition to the substantive variables that
comprise the path analytic model, we also include five dummy variables for the years 1997 -
2001 to account for the fixed effects of time upon the main explanatory measures.
We employ structural equation modeling (SEM) to test the linkages among our variables.
This technique consists of a series of regression equations which are fitted simultaneously using
maximum likelihood (ML) as the model estimator.
8
Findings
The statistical results from our path analysis are illustrated in Figure 3, which presents
only the most theoretically interesting paths; the parameter estimates are presented in Appendix
B
9
. In addition, Table 1 decomposes the path coefficients of our model into direct, indirect, and
total effects. Overall, our model supports past work in this area. A clear “top-down” process
occurs as evidenced by the direct and indirect effects running from Latino political
representation to bureaucratic representation to student performance.
One significant issue in structural equation modeling is the fit of the model with the data.
The assumptions from “absolute fix” indexes (e.g. X
2
goodness of fit test) are usually violated in
SEM. Therefore, researchers rely on “adjunct” or “incremental fit” indices to test goodness of fit.
One of the most common fit statistic used in Structural Equation Models is the Tucker-Lewis
Index (TLI).
10
With the criterion for this index ideally being above .95 (Hu and Bentler 1999), it
appears that our model fits relatively well to the data (TLI = .93).
11
<FIGURE 3 ABOUT HERE>
<TABLE 1 ABOUT HERE>
15

First, note that the number of Latino students has a large impact on the number of Latino
school board members, administrators, and teachers, as we expected. Our findings indicate that
the number of Latino students in a school district positively and significantly affects the number
of Latino representatives on school boards (path coefficient = .622), the number of Latino
administrators (path coefficient = .192), and the number of Latino teachers (path coefficient =
.113). The percentage of Latino students is also significantly associated with the percentage of
low income students (path coefficient = .474), reflecting the higher rates of poverty found in
Latino communities. Additionally, the percentage of Latino students positively influences
Latino student achievement (path coefficient = .017), but negatively influences overall student
achievement (path coefficient = -.033). Finally, the percentage of Latino students significantly
affects the amount of instructional expenditures per student, with higher levels of spending in
districts with a relatively high proportion of Latino students. The pathway between Latino
students and teacher experience is statistically insignificant.
At the same time, it is important to note that the ethnic composition of the student body
has a complex relationship with minority student achievement. Latino student population is
positively correlated with Latino representation on school boards, and among teachers and
administrators, and is directly associated with instructional spending and Latino student
achievement. All this works to elevate Latino student achievement. However, the Latino
student population is higher in less wealthy communities, and is negatively associated with
overall student achievement, which in essence counteracts the other, more positive, effects.
Therefore, the total substantive effects of Latino student population on Latino student
achievement are quite small in magnitude.
16

Second, the model supports the causal chain between political representation,
bureaucratic representation, and students. The proportion of school board members that are
Latino significantly influences the proportion of teachers that are Latino, and the TASS passage
rates of Latino students; nonetheless, by far the most powerful influence exerted by school
boards is over the proportion of administrators that are Latino. The association between school
board composition and both ethnic diversity among teachers and passage rates of Latino students
is primarily indirect, operating through their control over the administrative staff. Likewise,
administrators have a strong direct effect over teachers, and virtually no direct effect on student
scores. Teachers, acting in the role of “street level bureaucrats” have a significant and direct
impact on Latino educational performance (path coefficient = .090). This effect is larger than the
indirect effect of Latino school board representation on Latino student achievement (path
coefficient = .053), suggesting that teachers play a prominent role in the educational achievement
of Latino students.
However, here we offer an important caveat: we find that the relationship between the
proportion of Latino teachers and Latino student achievement is relatively small in magnitude.
Indeed, the total effect of Latino school board representation on Latino student achievement is of
roughly the same magnitude as the total effect of the proportion of Latino teachers on Latino
student achievement. The size of the relationship between Latino teachers and Latino students
may be a product of unit size—our measures are at the district level. Given that education
research indicates some factors that influence test performance are very immediate and situation-
specific, stronger effects might be observed if data were gathered directly from classrooms (or
even more directly, from test sites). Our finding of a significant influence of the percentage of
Latino teachers on the percentage of Latino students who pass TAAS is not a trivial finding,
17

particularly given the difficulty that policy makers and practitioners have had in reducing test
gaps. Nonetheless, the weakest link in the path between political representation and substantive
outcomes appears at the end of the pathway, in direct influences on the substantive outcome in
question (Latino student achievement.)
Third, we note that teacher experience seems to have a much more substantial overall
influence on Latino student achievement than the presence of Latino teachers; teachers with
more experience significantly affect Latino student achievement, specifically, and overall student
achievement more generally. This result differs from the findings of Meier et al. (1999) who
show that teacher experience has a positive effect on Anglo students and students overall, but a
negative effect on Latino students.
Fourth, our results demonstrate the importance of district resources on educational
performance. Per capita instructional spending significantly impacts both total student
achievement and, even after controlling for total student achievement, Latino student
achievement. Also, as expected, the relationship between low income students and overall
student achievement is negative and significant (path coefficient = -.272). Considering this
finding, in conjunction with the correlation between overall student achievement and Latino
student achievement (path coefficient =1.081), it is clear that the resources of the district are
crucial to the educational performance of all students. Unfortunately, as we pointed out above,
minorities are often concentrated in low income districts; therefore, it is evident that districts
exist with a high proportion of minority students, but without the resources to educate them.
This lends further support to the well established impact of poverty on educational outcomes for
minority students.
18

Finally, we find that time (fixed effects) has an inconsistent impact on the main
explanatory variables. Time is significant only for Latino student enrollment, for the years 1999-
2001, and Latino school board members, for the years 1998 and 2000, indicating that Latino
enrollment and hiring practices were distinct in these years.
In sum, the findings demonstrate descriptive representation—the presence of Latinos in
representative government—has a powerful (albeit largely indirect) effect on substantive policy
outcomes of interest to the Latino community. The election of Latino school board members is
significantly related to the number of Latino administrators, which is associated with the number
of Latino teachers. In turn, the number of Latino teachers influences Latino student
performance. Our results provide more support for the “top-down” argument of Latino
representation and student performance and offer evidence over time of the translation of
descriptive representation to substantive representation.
12
Conclusion
Past research on Latino representation and Latino educational performance has not
empirically sorted out the direct and indirect effects of representation and student achievement.
The central assumption in these studies outlines a casual chain running from Latino political
representation—school boards—to Latino bureaucratic representation—administrators and
teachers—to Latino student performance. Our results support this argument with a path analytic
model and show the direct and indirect effects of Latino political and bureaucratic representation
on Latino student performance.
Furthermore, we find that descriptive representation is significantly linked to substantive
representation in the area of education policy for Latinos, and that this relationship is relatively
consistent over time. The strongest link between the presence of Latinos and educational
19

outcomes appears to be the relationship between the ethnic composition of the school board and
the ethnic composition of administrators. This is not surprising, given the high degree of direct
control that school boards have over administrators. While we do find a link between the
presence of Latino teachers and minority student achievement, that link is less pronounced,
which is in keeping with the significant but limited influence that teachers have over educational
outcomes. That is, our findings support a model of descriptive representation that emphasizes
stronger links when policymakers have a relatively high degree of discretion over policy
outcomes.
Not only does our model contribute to the body of literature on Latino representation and
education, it underscores the importance of school board elections and school district hiring
practices. Latino political representation directly and substantially affects the numbers of Latino
administrators and teachers. Therefore, policies such as ward elections that promote the
representation of Latinos may be one way to effectively promote minority student achievement
(Leal, Martinez-Ebers, Meier 2004; Meier, Juenke, Wrinkle, and Polinard, 2005). Likewise, the
recruitment of Latino administrators and teachers—particularly teachers with experience — in
districts with sizeable Latino student populations may improve educational outcomes, as
suggested by our findings.
Although this study enhances our understanding of the effect of Latino representation on
Latino policy, specifically educational outcomes, there are some limitations that should be
addressed in future work. First, the model may need refinement in its specification. Past studies
have asserted an interactive effect between Latino school board members and teachers in
influencing Latino student performance (Polinard, Wrinkle, and Longoria 1990). In general,
given our findings regarding the significant but relatively weak relationship between the
20

presence of Latino teachers and student performance, more research should be done examining
the conditions under which the diversity in teaching staff can contribute to student achievement
across groups of students. Second, additional dependent variables should be tested. Analyses of
Latino representation have employed measures of class assignments (gifted, bilingual, mentally-
challenged), drop out rates/graduation rates, and disciplinary actions in determining the effects of
political and bureaucratic representation on Latino student performance. More research should
be done to examine the political, social, and bureaucratic factors that influence a broad set of
achievement measures. And third, future research should examine these issues for other
demographic groups (e.g., women, African Americans), as well as examining how the diversity
among Latinos may influence the relationships that connect political representation to
substantive educational outcomes.
Beyond education policy, our study has broad implications for Latino politics. While here
we focus on school boards, this type of analysis can be applied to other representational settings
and in other policy arenas. In particular, the literature on the link between the descriptive and
substantive representation of Latinos has been somewhat inconclusive. An approach that looks at
policy outcomes rather than voting records and that disentangles both the direct and the indirect
effects of representation on those policy outcomes may go a long way toward reconciling these
discrepancies. As the Latino population continues to grow, states offer a uniquely appropriate
setting to observe how these demographic changes translate into changes in representation,
policy implementation, and policy outcomes. Our findings indicate that minority representation
matters for minority policy, and this should be explored further for other minority groups across
multiple policy areas. In particular, a similar analysis of African American student achievement
is warranted. African Americans encounter similar obstacles as Latinos in educational
21

attainment. Therefore, it is important to develop a causal model that looks at how the relationship
between descriptive and substantive representation impacts black education outcomes.
Even though the value of educational attainment is axiomatic in our society, it is clear
that the paths that translate political and bureaucratic actions into student performance remain far
from simple. This study provides a path analytic model designed to sort out these relationships.
Our results reveal a more comprehensive explanation of how both direct and indirect measures
affect Latino education policy. Future research should explore how this process can be altered to
provide more tangible and successful outcomes for educationally challenged minority groups.
Appendices
Appendix A
Descriptive Statistics, Independent and Dependent Variables
Variable
N
Mean
SD
Min.
Max.
% Latino Students
5,204
27.64
26.70
0
100
% Latino SB Members
5,188
9.40
21.11
0
100
% Latino Administrators
5,194
8.85
21.94
0
100
% Latino Teachers
5,204
8.61
18.56
0
100
Avg. Teacher Experience
5,204
11.93
2.31
.80
20.70
Instructional Expenditures
per student
5,199
3,502.53
940.77
1,169
15,537
% Latinos that Pass TAAS
4,722
73.07
12.95
0
100
% All Students that Pass
TAAS
5,201
80.69
9.77
26.7
100
% Low Income
5,204
47.04
19.26
0
100
1997
5,207
.20
.40
0
1
1998
5,207
.20
.40
0
1
22

1999
5,207
.20
.40
0
1
2000
5,207
.20
.40
0
1
2001
5,207
.20
.40
0
1
23

Appendix B
Structural Equation Model: Matrix of Regression Results (Parameter Estimates)
Variables
Latino
Student
s
Latino
SB
Mem.
Latino
Admins
Latino
Teacher
s
Avg.
Teacher
Exp.
Per
Pupil
Spendi
ng
Latinos
Pass
TAAS
Student
s
Pass
TAAS
Low
Income
Latino
Students
______
0.622*
(0.005)
0.192*
(0.007)
0.113*
(0.004)
-0.002
(0.001)
3.179*
(0.357)
0.017*
(0.007)
-0.033*
(0.007)
0.474*
(0.006)
Latino SB
Mem.
0.622*
(0.000)
______
0.656*
(0.009)
0.209*
(0.006)
_____
_____
.039*
(.011)
_____
_____
Latino
Admins
0.192*
(0.007)
0.656*
(0.009)
_____
0.489*
(0.006)
_____
_____
.008
(.013)
_____
_____
Latino
Teachers
0.113*
(0.004)
0.209*
(0.006)
0.489*
(0.006)
_____
_____
_____
0.090*
(0.018)
_____
_____
Avg.
Teacher Exp
-0.002
(0.001)
______
______
_____
_____
_____
0.163*
(0.049)
0.842*
(0.059)
_____
Per Pupil
Spending
3.179*
(0.357)
______
______
_____
_____
_____
0.001*
(0.000)
0.005*
(0.000)
_____
Latinos
Pass TAAS
0.025*
(0.007)
______
______
0.129*
(0.010)
0.165*
(0.049)
0.001*
(0.000)
_____
1.081*
(0.008)
_____
Students
Pass TAAS
-0.033*
(0.007)
______
______
_____
0.842*
(0.059)
0.005*
(0.000)
1.083*
(0.008)
_____
-0.272*
(0.010)
Low
Income
0.474*
(0.006)
______
______
_____
_____
_____
_____
-0.272*
(0.010)
_____
Y97
1.098
(0.876)
-0.855
(0.439)
0.480
(0.379)
_____
_____
_____
_____
_____
_____
Y98
1.558
(0.876)
-1.103*
(0.439)
0.627
(0.380)
_____
_____
_____
_____
_____
_____
Y99
2.040*
(0.877)
-0.817
(0.440)
0.354
(0.380)
_____
_____
_____
_____
_____
_____
Y00
2.553*
(0.877)
-0.998*
(0.440)
0.558
(0.380)
_____
_____
_____
_____
_____
_____
Y01
3.223*
(0.877)
-0.595
(0.440)
-0.065
(0.380)
_____
_____
_____
_____
_____
_____
24

Appendix C
Alternative Analyses
We conducted a set of alternative analyses, using fixed effect cross-sectional time series
models, to examine how changes in diversity among school board officials, administrators, and
teachers influenced changes in test scores. The results from these alternative analyses support
the path model presented in this paper. When controlling for initial levels of diversity on school
boards, among administrators, and among students, in addition to our other control variables,
changes in Latino proportion of school board members over a two-year period was positively
associated with changes in the Latino proportion of administrators. When controlling for initial
levels of diversity among administrators, teachers, and students, as well as our other control
variables, changes in the Latino proportion of administrators over a two-year period was
positively associated with changes in the Latino proportion of teachers. And, when controlling
for initial test scores, and diversity among teachers and students, as well as our other control
variables, changes in Latino proportion of teachers over a two-year period was positively
associated with changes in test scores. We note that changes in the ethnic composition of the
teaching staff appear to have a more powerful effect on changes in test scores than our path
model indicated, at least relative to the other factors of Latino representation on the school board
and the ethnic composition of the administrative staff. However, as in the findings presented in
the paper, the relationship between changes in the percentage of Latino teachers and changes in
Latino passage rates is much smaller than the relationship between changes in teacher experience
and changes in Latino passage rates.
We also observe that the influence of Latino school board representation on the ethnic
composition of administrative staff is significant regardless of the time lag considered (two
years, three years, four years, or five years). The same is true of the influence of the ethnic
25

composition of administrative staff on the ethnic composition of teaching staff. However,
changes in the proportion of Latino teachers significantly influence changes in test scores only
across a two-year period. This is consistent with educational research (e.g. Aronson et al. 1999)
that indicates that test scores respond to relatively immediate, situation-specific factors.
We also tested for non-linear relationships in alternative OLS models. The OLS results
indicate that Latino representation on school boards had a positive effect on the percentage of
Latino administrators—but that this effect was less evident in districts where Latino
administrators made up a relatively high proportion of administrators. Likewise, the percentage
of Latino teachers was positively associated with Latino passage rates, but the effect was less
evident in districts with a relatively high proportion of Latino teachers.
The results for the cross-sectional time series analyses examining the influence of
changes in school board composition, and changes in the composition of administrative and
teaching staff, showed no evidence of significant non-linear effects. This makes sense, given
that change should predict change in a relatively linear fashion.
Our control variables (such as instructional spending, financial resources within the
population, and teacher experience) address the possibility that our results are an artifact of the
likelihood that districts with a more educated Latino labor force (and thus more Latino teachers)
are generally those where Latino students perform well on basic skills exams. However, to
further examine these relationships, we also conducted additional alternative cross-sectional
panel analyses, which analyze the effect of gains in representation separately from the effect of
losses. We find that across two-year periods, gains in Latino representation on school boards
leads to increases in the percentage of administrators who are Latino, which in turn leads to gains
in the percentage of teachers who are Latino, which in turn leads to an increase in Latino test
26

scores. Most interestingly, the reverse pattern is observed for reductions in Latino
representation—when Latino representation drops, the percentage of Latino administrators
drops, the percentage of Latino teachers drops, and Latino scores drop .Given that there is little
reason to believe that a smaller Latino population would equate a less educated Latino
population, this suggests that the relationships we find are indeed due to the involvement of
Latinos in education policy, rather than to community demographics.
Table C1 present the results from the alternative analyses predicting change across two-
year intervals. The full set of alternative analyses is available from the authors.
27

Table C1. Influences on Change in % Latino Administrators, % Latino Teachers, % Latino Passing TAAS
Change, % Latino
Administrators
Change, % Latino
Teachers
Change, % Latino Pass
TAAS
Change, % Latino Teachers
.153
*
(.052)
Change, % Latino Administrators
.023
*
(.004)
-.006
(.017)
Change, % Latino School Board Rep.
.093
*
(.013)
.001
(.004)
.045
*
(.017)
Change, Low Income
-.019
(.012)
-.011
*
(.004)
.016
(.017)
Change, % Latino Students
.073
*
(.039)
.029
*
(.013)
-.268
*
(.061)
Change, Instructional Spending
.104
(.162)
.036
(.056)
.165
(.266)
Change, Teacher Experience
.064
(.054)
-.070
*
(.019)
.293
*
(.088)
Change, Overall Passage Rates
.604
*
(.018)
Lagged % Latino School Board Rep
.080
*
(.016)
-.001
(.006)
.067
*
(.021)
Lagged % Latino Administrators
-1.018
*
(.014)
.053
*
(.006)
.027
(.026)
Lagged % Latino Students
.069
(.042)
.021
(.014)
-.390
*
(.065)
Lagged % Latino Teachers
-.793
*
(.013)
.268
*
(.066)
Lagged % Latino Pass TAAS
-.832
*
(.012)
1995
-.661
*
(.291)
-1.140
(.101)
-27.074
*
(.605)
1996
-.618
*
(.277)
-.864
(.096)
-21.887
*
(.525)
1997
-.614
*
(.272)
-.604
(.094)
-15.368
*
(.481)
1998
-.376
(.265)
-.354
(.091)
-9.163
*
(.432)
1999
-.282
(.257)
-.211
(.088)
-4.673
*
(.379)
2000
.071
(.252)
-.099
(.086)
-2.330
*
(.357)
Constant
6.451
*
(1.220)
6.176
*
(.428)
72.857
*
(2.412)
Sample Size
7,185
7,184
Groups
1,038
1,038
Within R
2
.48
.40
Notes: * p≤ .05, one tailed test. Standard errors in parenthesis. Change measured across two year intervals.
28

Endnotes
1
Most scholarly work that references people of Spanish origin use the terms “Hispanic” and
“Latino” interchangeably. For purposes of uniformity we use the term “Latino” in this paper.
2
Scholars have, of course, debated whether school boards effectively control education policy.
Chubb and Moe (1990) argue that as democratic institutions facing a multitude of competing
demands, school boards are rendered ineffective in their attempts to respond to demands for
quality. Smith and Meier (1994) and Meier, Polinard and Wrinkle (2000) argue that school
bureaucracies grow in response to poor student performance, and that bureaucracies respond by
reducing class sizes and increasing staff.
3
Descriptive representation is often referred to as “passive representation” and substantive
representation is also labeled as “active representation” in the Latino education literature (Meier
and Stewart 1991; Meier and O’Toole 2006).
4
See also Meier, Stewart, and England (1991).
5
See Polinard et al. 1990 and Meier and O’Toole (2006) as exceptions.
6
The only variable included in this data set not directly obtained from the Texas Education
Agency is the “percent Latinos on school boards” (school board ethnicity) measure. This variable
was created using government Census data of school boards, information from the Texas
Association of School Boards and annual compilations of the National Association of Latino
Elected Officials (NALEO). The data was also supplemented by phone surveys. For more details
on how this variable was constructed, see Meier and O’Toole 2006.
29

7
Scholars have observed that there may be resistance to knowledge gained through single-state
studies. However, as Nicholson-Crotty and Meier (2002) observe, "the unique characteristics of
a state may make it a particularly desirable venue in which to test a theory" (p. 414). They also
note that data sets drawn from single states can enhance internal and construct validity, while
still preserving the rich information levels of large sample sizes.
8
Maximum Likelihood is the standard method of estimating free parameters in structural
equation modeling (Hoyle and Panter 1995), and is appropriate over other regression estimators
when there are missing variables, as is the case with our study.
9
Appendix B presents the structural equation model in a matrix format, illustrating the
coefficient values for each pair of relevant variables in the regression analysis.
10
For more information on fit criteria, see Hu and Bentler (1999).
11
One factor driving down the TLI measure may be the inclusion of time fixed effects. We ran
the model without the yearly dummy variables and the TLI is .99.
12
We perform a number of alternative analyses, to examine whether changes in our independent
variables are associated with changes in our dependent variables (and to examine whether
increases in representation have different effects than decreases in representation.), and to
examine the effect of non-linear effects. These analyses, described in Appendix C, generally
support our path model findings.
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