RACIAL DIVERSITY AND COLLEGE CHOICE: REVISITING THE PERPETUATION OF SEGREGATION HYPOTHESIS

Since 1990, racial school segregation has been increasing for blacks and Latinos;

approximately three-quarters of blacks and Latino students attend predominantly minority high

schools (Orfield and Eaton 1996; Orfield and Lee 2007). In studying the long term effects of

desegregation, Braddock developed the perpetuation hypothesis, which argued that "racial

segregation tends to be perpetuated over stages of the life cycle and across institutional settings"

(Braddock and McPartland 1989:267). Studies examining the relationship between segregation

and college choice, consistently have found that black students who attend segregated schools

are more likely to choose predominantly black colleges than predominantly white colleges

(Braddock 1980; Wells 1995). Much of this research is based on high school cohorts from the

1970s and 1980s. There is far less known about the impact of segregation on college preferences

for non-Blacks or students graduating from high school in the current millennium. This paper

addresses the aforementioned limitations of the existing research by analyzing data from a

representative sample of 2002 Texas high school seniors in order to assess the extent to which

students' high school racial composition, apart from other factors commonly associated with

college choice, influences students' preferences for colleges with similar racial compositions.

Numerous studies have confirmed that racially heterogeneous college campuses produce

far-reaching individual (e.g., enhanced complex thinking ability) and societal (e.g., greater

engagement with social and political issues) benefits (Gurin, Nagda, and Lopez 2004; Hurtado

2007; Milem 2003). If Braddock's perpetuation hypothesis holds true with racial segregation on

the rise, then fewer and fewer students will be seeking racially diverse colleges where they could

obtain the educational benefits of diversity. Furthermore, these students of segregation will not

have access to a wider variety of job opportunities from weak ties that would have been obtained

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 1 of 34

through social networks at a more diverse college (Wells and Crain 1994). Moreover, colleges

that are seeking to create a racially heterogeneous campus will have increasing difficulty

obtaining a racially diverse applicant pool with a rise in students from racially segregated

environments who might be more accustomed to and thus more likely to attend racially

homogeneous colleges.

While less directly related to perpetuation of segregation than the desegregation studies

of the 1980s, recent research has still provided findings that suggest racial segregation is having

an effect on college preference. In an examination of California high schools, Martin, Karabel,

and Jaquez (2005) found that predominantly Latino high schools had significantly lower rates of

student applications to the UC system. However, the authors were using institutional data and

thus could not assess the effect of student-level characteristics on applications.

In a study of students attending predominantly white selective colleges and universities,

Massey (Massey 2006) found that black and Hispanic students from racially segregated

backgrounds received less academic college preparation (e.g., AP courses), lower quality

instruction, and were less prepared socially for campus life. As these findings were from students

who were attending the most selective colleges in the United States, the results might have been

bleaker with a more representative population of students not restricted by selective college

attendance--bleak enough to reduce student preference to apply to predominantly white selective

colleges.

Having a sizable applicant pool of minority students is of practical importance to

prestigious selective institutions of higher education that have been most vocal about the

compelling need for a diverse campus. However, recent findings from the THEOP data confirm

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 2 of 34

that black and Hispanic Texas seniors with qualifying academic records were less likely than

whites to apply to selective colleges (Niu, Tienda, and Cortes 2006).

Some students attending segregated schools might lack the confidence or credentials to

apply to or gain admission to prestigious selective colleges like those found in the NLSF sample.

Other students might simply prefer to attend a school with a familiar level of racial homogeneity.

Students of color are more likely to consider a predominantly minority college when suggested

or previously attended by a friend, family member, counselor, or teacher (Freeman 1999;

McDonough, Antonio, and Trent 1997). There is also a logical and practical component to

choosing a culturally homogenous college, as research has found that educational attainment for

black students and females is greater when attending institutions that enroll predominantly black

and predominantly women students, respectively (Pascarella and Terenzini 1991).

Consequently, it appears that efforts by predominantly white selective colleges to

diversify their campuses are hindered by racial segregation in two ways. Underrepresented

minority students from racially segregated backgrounds might be (1) less likely to apply due to

real or perceived limitations in academic and social preparation, (2) more inclined to choose

racially homogenous colleges due to existing ties and a potentially better record for educational

attainment.

There is, however, one notable example of how racial segregation might play a role in the

desire for integration. Through a series of interviews with 70 black students, Freeman (1999)

discovered that some students who attended predominantly African American high schools in

predominantly Black neighborhoods felt a sense of responsibility and value of sharing their

culture which prompted them to consider predominantly white institutions. While this finding

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 3 of 34

has rarely appeared in similar studies, it would serve as a valid alternative to Braddock's

perpetuation hypothesis.

This paper sets out to test Braddock's perpetuation of racial segregation hypothesis.

However, Braddock's research like most desegregation studies used percent of the high school

population that was black as the primary explanatory measure. This paper extends this test to

non-blacks in a manner that better represents multiethnic diversity of 21st century America by

using Lieberson's diversity index to measure high school and college racial composition

(Lieberson 1969). A detailed description of the Lieberson diversity index appears later in the

paper. If Braddock's perpetuation hypothesis is robust across race, then racial heterogeneity of a

student's high school will be positively associated with the racial heterogeneity of the student's

preferred first college choice, net of other school-level and individual-level effects.

DIVERSITY

Diversity is a compositional construct where individual differences in various attributes

create heterogeneity within a social unit (Jackson, May, and Whitney 1995). While the term

diversity can and often does encompass a broad range of attributes, the term diversity in this

project is limited to the proportions of racial and ethnic groups in a given high school or college

student body. Consequently, unless otherwise stated, when the word diverse or diversity appear

without a modifier, I am referring primarily to ethnoracial demographic diversity.

Research evidence highlighting the educational benefits of diversity drives the use of

diversity as a key concept for study in this paper. Demographic diversity has consistently been

found to be strongly associated with increase the frequency of positive intergroup contact

(Engberg 2007), cooperative working and problem-solving skills (Terenzini, Cabrera, Colbeck,

Bjorklund, and Parente 2001), citizenship engagement, multicultural engagement, intellectual

engagement, and academic skills (Gurin, Dey, Hurtado, and Gurin 2002). Research has also been

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 4 of 34

found to support the association between positive interracial interactions and complex thinking,

social awareness, perspective-taking skills, and self-confidence (Chang, Denson, Saenz, and

Misa 2006; Hurtado 2007). Based on the existing evidence, this paper proceeds with the

assumption that not only are there educational benefits to racial heterogeneity, but also any

diversity is preferable to any form of homogeneity.

Stanley Lieberson offered a measure that conceptualizes "diversity as the position of a

population along a homogeneity-heterogeneity continuum and describes diversity within and

between groups that are classified by one or more qualitative variables" (Lieberson 1969:851).

Lieberson's diversity index measures what proportion of the pairs would consist of students with

different racial backgrounds if all students on campus were paired together two at a time

(Lieberson 1969). In this paper, I calculate the diversity index using each of the five Census-

defined ethnic and racial groups (whites, blacks, Hispanics, Asians, and Native Americans). The

formula for the calculation is:

DVI=(2*((Xw* Xb)+(Xw* Xh)+(Xw* Xa)+(Xw* Xn)+(Xb* Xh)+(Xb* Xa)+(Xb* Xn)+(Xh* Xa)+(Xh* Xn)+(Xa* Xn))), where Xw = White, Xb = Black, Xh = Hispanic, Xa = Asian or Pacific Islander, Xn = Native American

As the likelihood of two people from a different race within a population being paired together

increases, the diversity index value increases. With five races, the maximum value of the

diversity index would be .80. That is, if every racial group on campus evenly comprised one-fifth

of the student body, then the probability of two randomly selected students having a different

race would be .80. A completely racially homogeneous campus would have a diversity index

value of 0.0 and a completely racially heterogeneous campus would have a diversity index value

of 0.80.

School desegregation studies were less interested in population diversity and

comparability across schools, as they were the effects of segregation and desegregation on

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 5 of 34

blacks. Consequently, early desegregation research tended to use percentage black as the school-

level variable of interest. While some researchers today continue to use some variation of the

proportion of a single racial group as a measure of racial composition or diversity (e.g.,

Rothman, Lipset, and Nevitte 2003), this is not valid in the context of modern multiethnic

American society. Research that lacks a measure of diversity that accounts for multiple

ethnicities does not accurately measure overall diversity nor can it accurately compare diversity

across campuses.

James Kulinski's review of campus diversity studies offers one of the best examples for

the advantages of Lieberson’s diversity index over other proportion of a single group approach:

Consider, for example, three hypothetical ethnic mixes. In the first instance, there is a very dominant white group (70 percent of the total student body) and three small minority groups, each constituting 10 percent of the total student body. In the second, white students make up 50 percent of the student body, one ethnic group constitutes 30 percent, and the other two ethnic groups each constitute 10 percent. In the final case, each group makes up a third of the student body. The probabilities of two students randomly selected from the hypothetical campuses sharing a different ethnicity are .48, .64, and .70, respectively. The index shows, correctly, more diversity on the second and third campuses than on the first. (Kuklinski 2006:107)

DATA

The analysis will use data collected from the Texas Higher Education Opportunity

Project (THEOP), a longitudinal study designed to assess the consequences of the Hopwood v.

University of Texas (1996) ruling that the University of Texas could not use race as a factor in

admissions decisions. The primary component of the THEOP was a self-administered paper and

pencil in-class student survey conducted during spring of 2002 of sophomores and seniors

enrolled in a representative sample of Texas public high schools. The sample was drawn from 62

primary sampling units randomly chosen to represent the locations of the high school-age

population in Texas. From those 62 sampling units, 108 public high schools were randomly

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 6 of 34

selected of which 98 participated, the multi-stage stratified sampling design resulted in 13,803

senior respondents (Tienda and Niu 2006).1

For the purposes of the present analysis, I impose several constraints on the original study

sample of 13,803 Texas high school seniors. First, I restrict the sample to the 8,193 seniors who

reported a first college choice preference for which college racial composition information was

obtained from the Integrated Postsecondary Education Data System (IPEDS). Second, I

restricted the sample to the 6,627 seniors who were not missing values on any variables in the

analysis. This approach to missing data, commonly referred to as listwise deletion remains the

approach least likely to result in biased parameters. Moreover, because the only cost is

efficiency, the findings--presented using the listwise deletion approach--are conservative (i.e.,

true relationships are likely more pronounced).

The best way to assess the impact of the missing values is to use several approaches to

confirm whether the findings are robust to various approaches. Following a strategy outlined by

Scott Lynch (2003) and Paul Allison (2007), I conducted identical analyses using multiple

imputation on the restricted sample of 8,193 and Heckman's two-step selection method on the

full sample of 13,803. A description of these procedures is included in the appendix along with

tables presenting results from these analyses marked with the prefix "Table A_". The findings--

presented using the listwise deletion approach--are robust across these alternative approaches to

handling missing data.

The THEOP data holds several unique advantages for this research. The data contains the

student- and school-level characteristics most often associated with college choice decisions.

Moreover, students are asked about their college choices before they were accepted, which

1 More information about the THEOP data and related research efforts can be found at the THEOP website: http://www.texastop10.princeton.edu

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 7 of 34

reduces selection bias inherent in studies of college enrollees that examine college choices

retrospectively (e.g., Bowen and Bok 1998). Most importantly, the THEOP is perhaps the only

study to collect information on student's high school racial composition and the racial

composition of the student's reported college choices.

The state of Texas is a favorable research site due to its large number of college-bound

students and diverse racial composition. The racial composition of the public elementary and

secondary schools in Texas in 2005-2006 was 45 percent Hispanic, 37 percent non-Hispanic

white, 15 percent black, and 3 percent other (Texas Education Agency 2007). Texas has had a

long history of racial residential segregation; however, it has five of the ten metropolitan areas

(El Paso, Odessa-Midland, San Antonio, Laredo, and Galveston-Texas City) that have

experienced the largest declines in residential segregation over the 1980-2000 period (U.S.

Census Bureau 2005). Consequently, there should be sufficient variance in diversity across

Texas high schools. This is confirmed by the results shown in Table 1, which uses Lieberson's

diversity index to describe the diversity of student's high schools in the THEOP sample.

Table 1. High School Diversity Index, Mean and Percentile Distribution, by Race White Black Hispanic Asian Other Native Missing Total

Mean 0.44 0.50 0.33 0.58 0.43 0.48 0.39 0.4110% 0.25 0.15 0.07 0.35 0.15 0.27 0.09 0.0925% 0.35 0.41 0.13 0.43 0.35 0.36 0.14 0.3050% 0.43 0.56 0.35 0.67 0.45 0.52 0.43 0.4375% 0.55 0.62 0.55 0.72 0.56 0.61 0.56 0.5690% 0.61 0.72 0.62 0.72 0.62 0.72 0.64 0.67

N 5,269 1,522 4,234 573 73 413 1,719 13,803Source: 2002 Texas Higher Education Opportunity Project Study of High School Seniors.

As shown in Table 1, the median diversity index is .43, which means that half of the

students attend a high school where the probability of two students randomly selected having a

different race is either greater than or less than .43. Based on median values, Asian students are

most likely to attend racially heterogeneous high schools and Hispanic students are most likely to

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 8 of 34

attend racially homogeneous (or segregated) high schools. Students who did not report their race

have a very similar high school diversity distribution as Hispanics.

Texas is also a favorable site for exploring college diversity due to Texas's wide variety

of colleges with regard to selectivity and racial composition, which is essential because 92% of

college bound high school graduates attend college in-state (Niu, Tienda, and Cortes 2006:262

fn10). Moreover, black and Hispanic students in Texas who would prefer a racially

homogeneous college campus have a fair selection of prominent Historically Black Universities

(including, Prairie View A&M and Texas Southern) and Hispanic-Serving Institutions (including

University of Texas-Pan American and University of Texas at El-Paso). The histogram shown in

Figure 1 confirms the range and variation of diversity at colleges among the reported colleges

preferred by the students in the sample.

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 9 of 34

050

010

001

500

2000

Num

ber

of

Stu

dnts

Re

port

ing

Pre

ferr

ed C

olle

ge

0 .2 .4 .6 .8College Diversity Index of College Preferred

Figure 1. Distribution of College Diversity Index Values

ANALYTICAL PLAN AND MEASURES

In an effort to test Braddock's perpetuation hypothesis, the analytical plan has been to

designed to assess the extent to which a student's high school's racial heterogeneity is associated

with the racial heterogeneity of the student's preferred first college choice, net of other school-

level and individual-level effects. In Braddock's initial study (1980), he found that black students

choosing a desegregated college was third only to high school grade point average and college

cost with regard to direct and total effects. For comparability, this study uses sequential

regression modeling as a way to assess how much variance in the racial heterogeneity of the

student's college preference can be explained by added sets of new independent variables, over

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 10 of 34

and above that explained by an earlier set.2 Table 2 describes the variables used in the analyses.

Additional information on the construction and motivation for variables are described in the text

that follows Table 2.

Table 2: Variable Descriptions for Racial Diversity and College Choice Analysis Variables Description Data Source Outcome Measure:

First Preference College Diversity Index

Diversity index of first preference college. Lieberson's diversity within a population index measures the extent to which if all students on campus were paired together two at a time, what proportion of the pairs will consist of students with different racial backgrounds (Kuklinski 2006; Lieberson 1969). DVI=(2*((Xw* Xb)+(Xw* Xh)+(Xw* Xa)+(Xw* Xn)+(Xb* Xh)+(Xb* Xa)+(Xb* Xn)+(Xh* Xa)+(Xh* Xn)+(Xa* Xn))), where Xw = White, Xb = Black, Xh = Hispanic, Xa = Asian or Pacific Islander, Xn = Native American. On a continuous scale from 0 to .80 with 0=homogeneous and .80= heterogeneous.

Survey: q50 Integrated Postsecondary Education Data System (IPEDS)

Primary High School Level Explanatory Measure (introduced in Model 1):

High School Diversity Index

Diversity index of high school. On a continuous scale from 0 to 1 with 0=homogeneous and .80= heterogeneous.

Common Core Data (CCD)

Primary Student Level Explanatory Measure -- Race (introduced in Model 2):

White "What term best describes your racial and ethnic origin?" 1=White, 0 = Not Hispanic white

Survey: q56

Black "What term best describes your racial and ethnic origin?" 1=African American/Black, 0 = Not Hispanic black

Survey: q56

Hispanic "What term best describes your racial and ethnic origin?" 1=Mexican/Mexican American/Chicano or Other Hispanic, 0 = Not Hispanic

Survey: q56

Asian "What term best describes your racial and ethnic origin?" 1=Asian or Pacific Islander, 0 = Not Asian Hispanic

Survey: q56

Native American "What term best describes your racial and ethnic origin?" 1=Native American, 0 = Not Native American

Survey: q56

Other Race "What term best describes your racial and ethnic origin?" 1=Other, 0 = Not Other

Survey: q56

Race Missing "What term best describes your racial and ethnic origin?" 1=Missing, 0 = Not Missing

Survey: q56

Other High School Level Characteristics (introduced in Model 3):

2

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 11 of 34

Variables Description Data Source Enrollment size Total campus enrollment Texas

Education Agency (TEA)

Percentage of students with college plans

School level aggregation of student responses to a college disposition question

THEOP

Feeder high school Top 20 high schools, based on the numbers of students admitted to UT-Austin and A&M are designated as feeder schools 1=Feeder, 0=Not feeder

TEA

Longhorn school Longhorn Opportunity Scholarships available for attendance at University of Texas - Austin for students graduating in Top 10% from select "underrepresented" Texas high schools 1=Longhorn, 0=Not Longhorn

THEOP

Percentage of students passing state algebra test

Percentage of students passing state algebra test TEA

Percentage of students who qualify for free or reduced lunch

Percentage of students who qualify for free or reduced lunch TEA

Other Student Level Demographic Characteristics (introduced in Model 4):

Parent with a bachelor degree

"What was the highest degree or level of school that your father or male guardian (or mother or female guardian) has completed?" 1=4-year college degree or greater, 0=Less than 4-year college degree

Survey: q67 father, q71 mother

Male "Are you male or female?" 1=male, 0=female

Survey: q55

U.S. Citizen "Are you a United States citizen" 1=Yes, 0=No/Don't know

Survey: q57d

English not always primary language

Student reported that English was NOT the primary language spoken with any one of the following: parents, guardians, siblings, relatives, or friends. 1= English NOT always primary, 0=English always primary

Survey: q59

Student Level Educational Experiences (introduced in Model 4):

Class Rank Student reported class rank (or best estimate of class rank). Ordinal scale, 10 categories: 10% to 100%

Survey: q12 or 14 (estimate)

Enrolled in College Prep Track

Student reported completing recommended (college prep) or distinguished achievement graduation plan. 1=Yes, 0=Regular (general curriculum) or Don't Know

Survey: q3

Percentage of available AP courses taken

Summation of "Which of the following (7 choices) AP courses have you taken or are you currently taking" / Summation of "Which of the following (7 choices) AP courses does your high school currently offer"

Survey: ∑(q9a…f)/ ∑(q7a...f)

Expects to attend two or four year college after high school

"What do you expect will be your primary activity in the fall after you leave high school?" 1="Taking academic courses at a two- or four-year college", 0=Other choices

Survey: q41

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 12 of 34

Variables Description Data Source College attendance encouragement from parents, teachers, and counselors

"During your senior year, have your guidance counselors, teachers, or parents/guardians encouraged you or discouraged you about going to college." Recoded to -1=Discouraged, 0=Haven't said anything, 1=Encouraged. Summation of response for guidance counselors, teachers, or parents/guardians. Divide by three. On a continuous scale from -1 to 1 with -1=Discouraged by all three and 1=Encouraged by all three

Survey: (q27+q28+q29)/3

Student Level - Factors Influencing College Choice (introduced in Model 5):

"In choosing a college or university to attend, how important to you are/were each of the following?..." 1=Not important, 2=Somewhat important, 3=Very important

Low expenses ...low expenses Survey: q49a Availability of financial aid

...availability of financial aid Survey: q49b

Athletics reputation ...athletics reputation Survey: q49c Ability to live at home ...ability to live at home Survey: q49d Ability to live away from home

...ability to live away from home Survey: q49e

Religious environment ...religious environment Survey: q49f Job placement success ...job placement success Survey: q49g Academic reputation ...academic reputation Survey: q49h Availability of desired degree program

...availability of desired degree program Survey: q49i

Ethnoracial mix of students or faculty

...ethnoracial mix of students or faculty Survey: q49j

Size ...size Survey: q49k Legacy ...legacy Survey: q49l Friends plan to attend ...friends plan to attend Survey: q49m Family connection ...family connection Survey: q49n Family opinion ...family opinion Survey: q49o Friendship with alumni ...friendship with alumni Survey: q49p

The analysis focuses on one outcome measure, racial heterogeneity of first preference

college choice. In the THEOP survey, students were asked" Please think about the

colleges/universities that you are likely to attend, and order them by your preference. For each,

enter the name and the state…" Students were provided the opportunity to list up to five colleges

or universities by their order of preference and then were asked to answer questions about each

college related to applying, admittance, financial aid and scholarships. Colleges in the preference

set were IPEDS-coded and institutional data from IPEDS, in particular enrollment statistics by

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 13 of 34

race, were collected and appended to individual records. I used these racial composition data to

construct the diversity index for each student's first preference college choice. As shown in Table

3, first preference college choice was reported for 60% of the sample. Among the first preference

colleges selected, the probability of two randomly selected students having a different race on

those campuses would be .40.

Table 3 about here

Table 3 presents the descriptive statistics for both the complete sample (N=13,803) and

the sample who provided preferred college choice information (N=8,193) to show that the

samples are very similar with differences described in the appendix and shown in Table A_4a

and Table A_4b. All of the statistically significant findings reported in this paper also appeared

when using the Heckman selection method to compensate for the differential propensities to

report a college preference. Results from the Heckman selection method are provided in Table

A_3.

Model 1, the unconditional model, includes high school diversity index as the primary

school-level explanatory variable. Diversity index, as described earlier, is an indicator of overall

campus diversity that measures the probability a randomly selected of two randomly selected

students having a different race. The diversity index is conceptually valid, comparable across

schools, and easy to interpret. The mean high school diversity index for the students in the

sample was .40.

Model 2 introduces race as a primary student-level variable. Whites comprise 53%, the

majority, of the sample reporting a preferred college choice. Hispanics comprise 28%, blacks

10%, Asians 4%, Native American <1%, other or multiracial 3%, and no response 3%.

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 14 of 34

Tabl

e 3.

Des

crip

tive

Stat

istic

s: C

ompl

ete

Sam

ple

and

Pref

erre

d C

olle

ge C

hoic

e Sa

mpl

e (S

tand

ard

devi

atio

n in

par

enth

eses

)

NM

ean

SD

Min

Max

NM

ean

SD

Min

Max

Out

com

e M

easu

re [S

tude

nt L

evel

]Fi

rst P

refe

renc

e C

olle

ge C

hoic

e R

epor

ted

13,8

03

0.60

1

(0.4

90)

01

Firs

t Pre

fere

nce

Col

lege

Div

ersi

ty In

dex

8,19

3

0.40

4

(0.1

54)

00.

730

8,19

3

0.40

4

(0

.154

)0

0.73

0

Expl

anat

ory

Mea

sure

s [H

igh

Scho

ol L

evel

]H

igh

Sch

ool D

iver

sity

Inde

x13

,803

0.

400

(0

.181

)0.

018

0.72

38,

193

0.

400

(0.1

79)

0.01

8

0.

723

Oth

er H

igh

Sch

ool C

hara

cter

istic

sE

nrol

lmen

t siz

e13

,803

1,

743

1,

046

56

5030

8,19

3

1,78

9

1,

050

56

5030

Per

cent

age

of s

tude

nts

with

col

lege

pla

ns

13,8

03

72.7

68

(22.

856)

010

08,

193

73

.648

(22.

614)

010

0Fe

eder

hig

h sc

hool

13,8

03

0.08

7

(0.2

82)

01

8,19

3

0.10

8

(0

.310

)0

1Lo

ngho

rn s

choo

l13

,803

0.

116

(0

.320

)0

18,

193

0.

105

(0.3

07)

01

Per

cent

age

of s

tude

nts

pass

ing

stat

e al

gebr

a te

st

13,8

03

33.2

23

(21.

470)

095

8,19

3

34.7

47

(2

1.63

0)0

95P

erce

ntag

e of

stu

dent

s w

ho q

ualif

y fo

r fre

e or

redu

ced

lunc

h13

,803

30

.743

(2

2.40

0)0.

993

.88,

193

29

.705

(22.

268)

0.9

93.8

Expl

anat

ory

Mea

sure

s [S

tude

nt L

evel

]R

ace

Whi

te (r

efer

ence

cat

egor

y)13

,803

0.

452

(0

.498

)0

18,

193

0.

529

(0.4

99)

01

Bla

ck13

,803

0.

092

(0

.289

)0

18,

193

0.

097

(0.2

96)

01

His

pani

c13

,803

0.

282

(0

.450

)0

18,

193

0.

275

(0.4

46)

01

Asi

an13

,803

0.

031

(0

.174

)0

18,

193

0.

038

(0.1

91)

01

Nat

ive

Am

eric

an13

,803

0.

006

(0

.074

)0

18,

193

0.

004

(0.0

66)

01

Oth

er ra

ce13

,803

0.

030

(0

.171

)0

18,

193

0.

031

(0.1

74)

01

Rac

e m

issi

ng13

,803

0.

107

(0

.310

)0

18,

193

0.

026

(0.1

58)

01

Oth

er D

emog

raph

ic C

hara

cter

istic

sP

aren

t with

a b

ache

lor's

deg

ree

11,0

97

0.40

5

(0.4

91)

01

7,45

3

0.45

9

(0

.498

)0

1M

ale

12,0

50

0.48

0

(0.5

00)

01

7,91

8

0.40

9

(0

.492

)0

1U

.S. c

itize

n12

,002

0.

936

(0

.245

)0

17,

903

0.

946

(0.2

26)

01

Eng

lish

not a

lway

s pr

imar

y la

ngua

ge12

,066

0.

212

(0

.409

)0

17,

912

0.

191

(0.3

93)

01

Edu

catio

nal E

xper

ienc

esC

lass

Ran

k P

erce

ntile

13,2

52

41.8

59

(24.

006)

1010

08,

066

35

.656

(22.

112)

1010

0E

nrol

led

in c

olle

ge p

rep

track

13,3

53

0.62

5

(0.4

84)

01

8,06

5

0.73

1

(0

.443

)0

1P

erce

ntag

e of

ava

ilabl

e A

P c

ours

es ta

ken

13,1

60

0.20

7

(0.2

94)

01

8,02

6

0.24

8

(0

.299

)0

1E

xpec

ts to

atte

nd tw

o or

four

yea

r col

lege

afte

r hig

h sc

hool

12,7

58

0.71

1

(0.4

53)

01

8,16

2

0.85

3

(0

.354

)0

1C

olle

ge a

ttend

ance

enc

oura

gem

ent f

rom

par

ents

, tea

cher

s, a

nd

coun

selo

rs12

,986

0.

833

(0

.297

)-1

18,

128

0.

883

(0.2

34)

-11

Cho

ice

Pre

fere

nces

Low

exp

ense

s11

,767

2.

249

(0

.705

)1

38,

144

2.

230

(0.6

99)

13

Ava

ilabi

lity

of fi

nanc

ial a

id11

,721

2.

449

(0

.717

)1

38,

131

2.

461

(0.7

16)

13

Ath

letic

s re

puta

tion

11,6

65

1.44

9

(0.6

76)

13

8,10

2

1.39

8

(0

.644

)1

3A

bilit

y to

live

at h

ome

11,7

07

1.79

3

(0.8

00)

13

8,13

4

1.71

0

(0

.805

)1

3A

bilit

y to

live

aw

ay fr

om h

ome

11,6

82

1.95

9

(0.7

64)

13

8,12

0

2.00

8

(0

.770

)1

3R

elig

ious

env

ironm

ent

11,5

81

1.56

4

(0.7

11)

13

8,06

5

1.56

9

(0

.713

)1

3Jo

b pl

acem

ent s

ucce

ss11

,600

2.

235

(0

.720

)1

38,

077

2.

265

(0.7

14)

13

Aca

dem

ic re

puta

tion

11,6

48

2.31

3

(0.7

03)

13

8,11

5

2.40

6

(0

.670

)1

3A

vaila

bilit

y of

des

ired

degr

ee p

rogr

am11

,649

2.

638

(0

.585

)1

38,

120

2.

708

(0.5

31)

13

Eth

nora

cial

mix

of s

tude

nts

or fa

culty

11,6

34

1.56

1

(0.7

04)

13

8,12

1

1.54

0

(0

.694

)1

3S

ize

11,6

07

1.76

2

(0.7

07)

13

8,09

7

1.81

0

(0

.707

)1

3Le

gacy

11,6

40

1.26

6

(0.5

52)

13

8,12

4

1.23

5

(0

.524

)1

3Fr

iend

s pl

an to

atte

nd11

,634

1.

493

(0

.650

)1

38,

117

1.

477

(0.6

38)

13

Fam

ily c

onne

ctio

n11

,625

1.

271

(0

.550

)1

38,

117

1.

227

(0.5

09)

13

Fam

ily o

pini

on11

,626

1.

581

(0

.685

)1

38,

117

1.

600

(0.6

88)

13

Frie

ndsh

ip w

ith a

lum

ni11

,604

1.

336

(0

.595

)1

38,

107

1.

296

(0.5

61)

13

Sou

rce:

200

2 Te

xas

Hig

her E

duca

tion

Opp

ortu

nity

Pro

ject

Stu

dy o

f Hig

h S

choo

l Sen

iors

.

Pre

ferr

ed C

olle

ge C

hoic

e A

vaila

ble

Sam

ple

Com

plet

e S

ampl

eRacial Diversity and College Choice

--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 15 of 34

Model 3 introduces other high school characteristics commonly associated with school

environment, academic quality, and educational outcomes. The variables added include

enrollment size, percentage of students at the high school who reported having plans to attend

college, percentage of students passing the Texas state algebra exam, and percentage of students

who qualify for free or reduced lunch. In addition, two Texas-specific variables were added

associated with college-going behavior. First, I added a dichotomous variable identifying

students attending one of the top 20 high schools, based on the numbers of students admitted to

the University of Texas at Austin and Texas A&M. Second, I added a dichotomous variable

identifying students attending one of the eligible "underrepresented" Texas high schools where

students who graduate in the Top 10% can receive a Longhorn opportunity Scholarship to attend

the University of Texas at Austin.

Model 4 introduces other demographic characteristics commonly associated with

educational outcomes. Dichotomous variables were added that identified whether a student had

at least one parent with a bachelor's degree or was a male. Student status as foreign-born was

available, but generation status was not as birth status of parents was not asked on the survey.

Instead of trying to assess immigration status in this manner, I chose an alternative two-prong

approach: I included U.S. citizenship because citizenship status is a requirement for admittance

to some colleges and eligibility for certain financial aid and scholarship opportunities.

Consequently, citizenship status might affect a student's preference for a college or university

that is more amenable to non-citizens. I also included a dichotomous variable to identify students

who reported that English was not the primary language spoken with any one of the following:

parents, guardians, siblings, relatives, or friends. Although the survey did not ask students to

report the other language spoken, one can assume that most of these students were likely to be

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 16 of 34

Spanish speaking. Spanish-speaking students may be more comfortable or more amenable to

attending a Hispanic Serving Institution.

Model 4 also introduces educational experience variables commonly associated with

educational outcomes. The student reported class rank by using an ordinal scale with 10

representing the Top 10% and 100 representing the Top 100% (or bottom 10%). In addition,

dichotomous variables were added that identified students who were enrolled in a college

preparatory graduation plan (as opposed to general curriculum) and students who were expecting

to attend college after high school. Students reported the availability of AP courses as well as

whether they had taken these courses. I constructed a variable that measured the percent of

available AP courses taken. I also constructed a variable to measure the combined level of

encouragement to attend college received from parents, teachers, and counselors.

Model 5 introduces variables that measure common factors that influence college choice

decisions. Students were asked to rate, on a scale of one (not important) to three (very

important), the importance of 16 factors in choosing a college or university. The factors

addressed included: low expenses, availability of financial aid, athletics reputation, ability to live

at home, ability to live away from home, religious environment, job placement success,

academic reputation, availability of desired degree program, ethnoracial mix of students or

faculty, size, legacy, friends plan to attend, family connection, family opinion, and friendship

with alumni. There is a limitation with these variables, because the cross-sectional structure of

the analysis precludes knowing whether the rated importance preceded the college search process

or whether the rated importance was influenced by the first preference college choice. Perhaps,

after a wonderful experience visiting the first preference college, a student might adjust the rated

importance of certain factors. For example, the availability of financial aid might not be very

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 17 of 34

important if one is expecting similar financial aid packages across all of your choices. However,

if one college comes through with a significant scholarship offer, then that college might

suddenly become your first choice and all other factors (e.g., distance from home, size of school,

etc.) might adjust in the respondent's mind to fit the characteristics of that college. Because of the

possible selection effect, less emphasis should be placed on the results from this model.

LIMITATIONS

The multi-stage sampling design produces individual observations (e.g., students) that are

clustered within higher-level units (e.g., high schools). Students sampled from a particular high

school interact with each other, which results in two problems: (1) it reduces the likelihood that

the sample observations from the high school are independent and (2) does not provide for the

complex error structure required for cross-level inference (Kuklinski 2006). With regard to the

first problem, standard errors are corrected for not only sampling but also clustering using Stata

10.0 survey commands designed to adjust standard errors for multi-stage survey design.

In a future draft of this paper, I plan to address the second problem by examining the

same question using multilevel sequential regression models, as a means to examine the

between-school and within-school differences. At that stage, I would be more comfortable with

making cross-level inferences (e.g., does a student's race and the high school's racial

heterogeneity interact to affect the racial heterogeneity of the student's first preference college

choice). I have avoided producing a model with or any inferences to such interactions in this

analysis due to the increased risk of coefficients achieving statistical significance when they

should not. Multilevel modeling corrects for biases in parameter estimates and provides accurate

standard errors that are unaccounted for in ordinary regression models that assume observations

are independent. More importantly, with multilevel modeling, I can draw reliable inferences

regarding the relative importance of school-level (within-schools) versus student-level (between-

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 18 of 34

schools) characteristics on the racial composition of students' college choices. (Guo and Zhao

2000).

Nonetheless, I am confident that the general findings presented here should hold in light

of their strength with standard errors corrected for clustering via Stata survey commands and

robustness of results across various models accounting for missing data as shown in the appendix

tables.

Based on the existing evidence, this paper proceeds with the assumption that not only are

there educational benefits to racial heterogeneity, but also any diversity is preferable to any form

of homogeneity. Consequently, the paper uses a diversity index measure on a heterogeneity-

homogeneity scale that makes no distinctions between various forms of homogeneity. It is

feasible that some forms of racial homogeneity may be preferable to racial heterogeneity. For

example, does a black student benefit more from attending an all-white school, an all-black

school, an all-Hispanic school, or a school of equal proportioned integration? Nonetheless,

existing research has not assessed the relative strength of same-race homogeneity to different-

race homogeneity. Extended analysis in both this paper and in the larger literature on educational

benefits of diversity will be necessary to assess the extent to which any diversity is preferable to

any form of homogeneity.

FINDINGS

The racial heterogeneity of the first preference college choices of Texas high school

seniors are analyzed by estimating sequential linear regression models. The results are presented

in Table 4.

Table 4 about here

Model 1, the unconditional model, includes only high school diversity index as the

primary school-level explanatory variable. Model 1 demonstrates that the diversity index of a

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 19 of 34

Coe

fS

ES

igC

oef

SE

Sig

Coe

fS

ES

igC

oef

SE

Sig

Coe

fS

ES

igEx

plan

ator

y M

easu

res

[Hig

h Sc

hool

Lev

el]

Hig

h S

choo

l Div

ersi

ty In

dex

0.14

7(0

.031

)**

*0.

174

(0.0

26)

***

0.15

5(0

.025

)**

*0.

154

(0.0

24)

***

0.15

0(0

.025

)**

*

Oth

er H

igh

Sch

ool C

hara

cter

istic

sE

nrol

lmen

t siz

e0.

000

(0.0

00)

0.00

0(0

.000

)0.

000

(0.0

00)

Per

cent

age

of s

tude

nts

with

col

lege

pla

ns

-0.0

01(0

.000

)*

-0.0

01(0

.000

)*

0.00

0(0

.000

)Fe

eder

hig

h sc

hool

-0.0

11(0

.016

)-0

.005

(0.0

16)

-0.0

04(0

.015

)Lo

ngho

rn s

choo

l0.

062

(0.0

24)

*0.

059

(0.0

23)

*0.

056

(0.0

23)

*P

erce

ntag

e of

stu

dent

s pa

ssin

g st

ate

alge

bra

test

0.

000

(0.0

00)

0.00

0(0

.000

)0.

000

(0.0

00)

Per

cent

age

of s

tude

nts

who

qua

lify

for f

ree

or re

duce

d lu

nch

-0.0

01(0

.000

)*

-0.0

01(0

.000

)**

-0.0

01(0

.000

)**

Expl

anat

ory

Mea

sure

s [S

tude

nt L

evel

]R

ace

Whi

te (r

efer

ence

cat

egor

y)B

lack

-0.0

27(0

.013

)*

-0.0

38(0

.016

)*

-0.0

43(0

.016

)**

-0.0

40(0

.015

)*

His

pani

c0.

054

(0.0

14)

***

0.05

3(0

.012

)**

*0.

041

(0.0

11)

**0.

035

(0.0

12)

**A

sian

0.11

8(0

.012

)**

*0.

111

(0.0

11)

***

0.10

8(0

.012

)**

*0.

098

(0.0

12)

***

Nat

ive

Am

eric

an0.

041

(0.0

28)

0.04

2(0

.030

)0.

032

(0.0

31)

0.03

2(0

.033

)O

ther

race

0.01

6(0

.011

)0.

011

(0.0

12)

0.00

7(0

.012

)0.

003

(0.0

11)

Rac

e m

issi

ng0.

044

(0.0

22)

*0.

029

(0.0

20)

0.02

1(0

.021

)0.

015

(0.0

21)

Oth

er D

emog

raph

ic C

hara

cter

istic

sP

aren

t with

a b

ache

lor's

deg

ree

-0.0

28(0

.005

)**

*-0

.020

(0.0

04)

***

Mal

e0.

000

(0.0

04)

0.00

2(0

.004

)U

.S. c

itize

n-0

.011

(0.0

13)

-0.0

08(0

.012

)E

nglis

h no

t alw

ays

prim

ary

lang

uage

0.00

4(0

.009

)-0

.001

(0.0

08)

Edu

catio

nal E

xper

ienc

esC

lass

Ran

k P

erce

ntile

0.00

0(0

.000

)0.

000

(0.0

00)

Enr

olle

d in

col

lege

pre

p tra

ck-0

.008

(0.0

06)

-0.0

06(0

.005

)P

erce

ntag

e of

ava

ilabl

e A

P c

ours

es ta

ken

0.00

4(0

.011

)0.

009

(0.0

11)

Exp

ects

to a

ttend

two

or fo

ur y

ear c

olle

ge a

fter h

igh

scho

ol-0

.011

(0.0

07)

-0.0

06(0

.007

)C

olle

ge a

ttend

ance

enc

oura

gem

ent f

rom

par

ents

, tea

cher

s, a

nd c

ouns

elor

s-0

.004

(0.0

10)

-0.0

02(0

.009

)

Cho

ice

Pre

fere

nces

Low

exp

ense

s0.

010

(0.0

03)

**A

vaila

bilit

y of

fina

ncia

l aid

-0.0

11(0

.004

)**

Ath

letic

s re

puta

tion

-0.0

07(0

.004

)A

bilit

y to

live

at h

ome

0.02

0(0

.005

)**

*A

bilit

y to

live

aw

ay fr

om h

ome

0.00

2(0

.004

)R

elig

ious

env

ironm

ent

-0.0

24(0

.004

)**

*Jo

b pl

acem

ent s

ucce

ss0.

005

(0.0

03)

Aca

dem

ic re

puta

tion

-0.0

02(0

.005

)A

vaila

bilit

y of

des

ired

degr

ee p

rogr

am0.

004

(0.0

06)

Eth

nora

cial

mix

of s

tude

nts

or fa

culty

0.01

2(0

.005

)*

Siz

e-0

.004

(0.0

03)

Lega

cy-0

.012

(0.0

06)

*Fr

iend

s pl

an to

atte

nd-0

.004

(0.0

05)

Fam

ily c

onne

ctio

n-0

.004

(0.0

05)

Fam

ily o

pini

on-0

.003

(0.0

03)

Frie

ndsh

ip w

ith a

lum

ni-0

.005

(0.0

05)

Con

stan

t0.

344

(0.0

15)

***

0.31

5(0

.012

)**

*0.

355

(0.0

27)

***

0.39

7(0

.034

)**

*0.

408

(0.0

39)

***

F-S

tatis

tic (A

djus

ted

Wal

d Te

st F

or C

ompl

ex S

urve

y D

ata)

22.3

0

22

.85

4.74

4.

61

8.99

M

odel

Deg

rees

of F

reed

om1

6

6

9

16

Des

ign

Deg

rees

of F

reed

om52

52

52

52

52

Pr>

F0.

000

0.00

00.

001

0.00

00.

000

R2

0.03

00.

078

0.09

80.

109

0.14

4C

hang

e in

R2

0.04

80.

020

0.01

10.

036

Sou

rce:

200

2 Te

xas

Hig

her E

duca

tion

Opp

ortu

nity

Pro

ject

Stu

dy o

f Hig

h S

choo

l Sen

iors

.N

=6,6

27 --

Mis

sing

val

ues

are

hand

led

usin

g lis

twis

e de

letio

n*p

<.0

5 **

p<.

01 *

** p

<.00

1 (tw

o-ta

iled

test

s)

Tabl

e 4.

Coe

ffici

ents

from

the

Line

ar R

egre

ssio

n of

Sel

ecte

d Ex

plan

ator

y Va

riabl

es o

n th

e D

iver

sity

Inde

x of

Stu

dent

's P

refe

rred

Firs

t Col

lege

Cho

ice,

Lis

twis

e D

elet

ion,

N=6

,627

(St

anda

rd e

rror

s in

par

enth

eses

)M

odel

1M

odel

2M

odel

3M

odel

4M

odel

5

Draft Date: 08/04/08 DRAFT: DO NOT CITE Page 20 of 34

student’s high school is positively associated with the diversity index of the student’s preferred

first college choice. Texas high school students from more racially heterogeneous high schools

are more likely to prefer attending more racially diverse colleges and students from more racially

homogeneous high schools are more likely to prefer more racially homogeneous colleges.

Model 2 introduces race as a primary student-level variable. The inclusion of race

increases the effect of high school diversity and improves the percent of the variance explained

in Model 1 by 160 percent (Change in R2 of current / R2 of previous model). Relative to white

students, black students are more likely to prefer less diverse colleges while Hispanic, Asian, and

unreported race students are more likely to prefer colleges that are more diverse. The finding for

students who do not report race will disappear in later models.

Model 3 introduces other high school characteristics. The addition of other high school

characteristics reduces the effect of high school diversity relative to Model 2, but by no means

eliminates it. The coefficient for high school diversity is still greater than it was in Model 1, the

unconditional model. Model 3 improves the percent of the variance explained in Model 2 by 25

percent. The impact of race on the racial heterogeneity of preferred college choice largely

remains; however, students who did not report their race are no longer statistically different from

white students. Three of the high school characteristics produce direct effects on the racial

heterogeneity of preferred college choice. As the percent of students planning to attend college

from a student’s high school increases, the diversity index of college preference decreases;

however, this finding will disappear in the final model. Attending a Longhorn high school (i.e.,

economically disadvantaged and historically underserved high school eligible for guaranteed

scholarship money to attend UT-Austin, the state flagship college) increases the diversity index

of the student’s preferred college choice. As the percent of economically disadvantaged (students

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 21 of 34

who qualify for free or reduced lunch) at a student’s high school increases, the diversity index of

college preference decreases.

Model 4 introduces other demographic characteristics and educational experience

variables. Relationships previously reported in Model 3 are unchanged with the addition of these

variables. Model 4 improves the percent of the variance explained in Model 3 by only 11

percent. Moreover, among the nine variables added to the model, only parent's education has a

direct effect. Having a parent with a bachelor’s degree reduces the diversity index of the

student’s preferred college choice.

Model 5 introduces variables that measure common factors that influence college choice

decisions. As mentioned earlier, due to the cross-sectional nature of this analysis, it is impossible

to assess how much of the rated importance may have been influenced by the first preference

college choice. Therefore, these results should be interpreted with greater caution. With the

addition of these variables, relationships previously reported in Model 4 are unchanged with the

exception of the loss of significance in the previous direct effect of the school-level variable that

measured the percentage of students with college attendance plans. Model 5 improves the

percent of the variance explained in Model 3 by 33 percent. Among the common factors that

influence college choice, direct effects were found with six of the sixteen factors. Three variables

had positive associations with diversity of college choice: low expenses, ability to attend a

college close to home, and ethnoracial mix of the students or faculty. Three variables had

negative associations with diversity of college choice: availability of financial aid, religious

environment, and family attends or attended the college.

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 22 of 34

DISCUSSION3

Braddock's perpetuation hypothesis is supported; racial heterogeneity of a student's high

school is positively associated with the racial heterogeneity of the student's preferred first college

choice, net of other school-level and individual-level effects. Based on the changes in variance

explained, there does appear to be a strong direct effect of race on the racial heterogeneity of the

student's preferred first college. Further analysis is needed to assess whether or not there is an

interaction effect between race and high school diversity. While this could be done using the

present analytical scheme, as mentioned earlier, inference between school-level and student-level

variables would be prone to Type I error (false positive) using traditional regression models.

These types of questions would have to be explored using multilevel models (e.g., hierarchical

linear modeling).

With racial segregation on the rise and Braddock's perpetuation hypothesis holding across

race in a modern context, fewer students will seek racially diverse colleges where they could

obtain the educational benefits of diversity. Moreover, these students will begin a lifetime of

self-perpetuating segregation from segregated high schools to racially homogeneous colleges to

racially homogeneous jobs and racially homogeneous neighborhoods. One notable negative

relationship from this analysis is that high school diversity index is lower for black students

relative to white students. These results are particularly disturbing on top of the perpetuation

hypothesis. There is very little disagreement over the consequences of racial isolation:

production of underclass communities, family disruption, higher rates of crime victimization,

increased mortality, lower educational standards, and increased welfare dependence (Collins and

Williams 1999; Massey 1990; Massey, Condran, and Denton 1987; Peterson and Krivo 1999).

3 One puzzling finding unaddressed in this discussion is that the high school diversity index of first preference college choices decreases for students who have at least one parent with a bachelor's degree relative to parents without a bachelor's degree. As shown in Table 2, 46% of the students had at least one parent with a bachelor's degree. Further analysis and research is needed to assess what may be driving this result.

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 23 of 34

Breaking the cycle of segregation that begins in the high schools just recently became

more difficult. In a 2007 decision, commonly referred to as Parents v. Seattle, the U.S. Supreme

Court prohibited the use of race as the sole factor in order to integrate public schools and

declined to recognize racial balancing as a compelling state interest.

While some view this decision as an official end to the desegregation era (post Brown v.

Board of Education), the holding opinion authored by Associate Justice Anthony Kennedy,

affirmed that schools have a compelling interest in avoiding racial isolation and achieving a

diverse student population. While the race of an individual student cannot be the sole factor,

Kennedy noted, "School boards may pursue the goal of bringing together students of diverse

backgrounds and races through other means, including strategic site selection of new schools;

drawing attendance zones with general recognition of the demographics of neighborhoods;

allocating resources for special programs; recruiting students and faculty in a targeted fashion;

and tracking enrollments, performance, and other statistics by race. These mechanisms are race

conscious but do not lead to different treatment based on a classification that tells each student he

or she is to be defined by race" (Parents Involved in Community Schools v. Seattle School

District No.1 et al.2007).

The findings from this study highlight the increasing need of communities and school

districts to consider demographic diversity of neighborhoods (and schools) in planning as a way

to both avoid racial isolation and achieve student diversity. In addition, this study also highlights

a measure, the diversity index that is race conscious, yet could withstand the scrutiny of the

current legal holding.

The findings also suggest mechanisms for breaking the cycle that can be implemented by

colleges and state governments. Attending a Longhorn high school increased the diversity index

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 24 of 34

of the student’s preferred college choice. On the other hand, as the percent of economically

disadvantaged at a student’s high school increases, the diversity index of college preference

decreased. Because Longhorn schools represent a select group of high schools that have higher

than average levels of economic disadvantage, these dual findings suggest that attending a

Longhorn schools has a very powerful effect on preferring a college with more racial

heterogeneity than students attending economically segregated high schools that are not eligible

for the Longhorn scholarship to attend UT-Austin. As shown in Table 2, the importance of

financial aid availability was the second highest rated factor influencing college choice. Making

college affordable for the racially and economically segregated would be a vital step in breaking

the cycle of segregation.

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 25 of 34

REFERENCES

Allison, Paul. 2007. "Missing Data: A 2-Day Course on Modern Methods for Handling Missing

Data." Princeton, NJ. Bowen, William G. and Derek Curtis Bok. 1998. The Shape of the River: Long-Term

Consequences of Considering Race in College and University Admissions. Princeton, NJ: Princeton University Press.

Braddock, Jomills Henry, II. 1980. "The Perpetuation of Segregation across Levels of Education: A Behavioral Assessment of the Contact-Hypothesis." Sociology of Education 53:178-186.

Braddock, Jomills Henry, II and James M. McPartland. 1989. "Social-Psychological Processes That Perpetuate Racial Segregation: The Relationship Between School and Employment Desegregation." Journal of Black Studies 19:267-289.

Chang, Mitchell J., Nida Denson, Victor Saenz, and Kimberly Misa. 2006. "The Educational Benefits of Sustaining Cross-Racial Interaction among Undergraduates." Journal of Higher Education 77:430-455.

Collins, Chiquita A. and David R. Williams. 1999. "Segregation and Mortality: The Deadly Effects of Racism?" Sociological Forum 14:495-523.

Engberg, Mark E. 2007. "Educating the Workforce for the 21st Century: A Cross-Disciplinary Analysis of the Impact of the Undergraduate Experience on Students Development of a Pluralistic Orientation." Research in Higher Education 48:283-317.

Freeman, Kassie. 1999. "HBCs or PWIs? African American High School Students' Consideration of Higher Education Institution Types " The Review of Higher Education 23:91-106.

Guo, Guang and Hongxin Zhao. 2000. "Multilevel Modeling for Binary Data." Annual Review of Sociology 26:441-462.

Gurin, Patricia, Eric L. Dey, Sylvia Hurtado, and Gerald Gurin. 2002. "Diversity and Higher Education: Theory and Impact on Educational Outcomes." Harvard Educational Review 72:330-336.

Gurin, Patricia, Biren A. Nagda, and Gretchen E. Lopez. 2004. "The Benefits of Diversity in Education for Democratic Citizenship." The Journal of Social Issues 60:17.

Hopwood v. University of Texas. 1996. "78 F. 3d 932 5th Cir." edited by U.S. Court of Appeals for the 5th Circuit: Federal Reporter.

Hurtado, Sylvia. 2007. "Linking Diversity with the Educational and Civic Missions of Higher Education." Review of Higher Education 30:185.

Jackson, Susan E., Karen E. May, and Kristina Whitney. 1995. "Understanding the dynamics of diversity in decision-making teams." Pp. 204-261 in Team effectiveness and decision making in organizations, edited by E. S. R. A. Guzzo, and Associates. San Francisco, CA: Jossey-Bass.

Kuklinski, James H. 2006. "Review: The Scientific Study of Campus Diversity and Students' Educational Outcomes." Public Opinion Quarterly 70:99-120.

Lieberson, Stanley. 1969. "Measuring Population Diversity." American Sociological Review, 34:850-862.

Lynch, Scott. 2003, "Missing Data (Soc 504)", Retrieved 23 July 2008, (http://www.princeton.edu/~slynch/SOC_504/missingdata.pdf).

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 26 of 34

Martin, Isaac, Jerome Karabel, and Sean W. Jaquez. 2005. "High School Segregation and Access to the University of California." Educational Policy 19:308-330.

Massey, Douglas S. 1990. "American Apartheid: Segregation and the Making of the Underclass." American Journal of Sociology 96:329-357.

—. 2006. "Social Background and Academic Performance Differentials: White and Minority Students at Selective Colleges." American Law and Economics Review 8:390-409.

Massey, Douglas S., Gretchen A. Condran, and Nancy A. Denton. 1987. "The Effect of Residential Segregation on Black Social and Economic Well-Being." Social Forces 66:29-56.

McDonough, Patricia M., Anthony Lising Antonio, and James W. Trent. 1997. "Black Students, Black Colleges: An African American College Choice Model." Journal for a Just and Caring Education 3:9-36.

Milem, Jeffrey F. 2003. "Educational Benefits of Diversity: Evidence from Multiple Sectors." Pp. 126-169 in Compelling Interest: Examining the Evidence on Racial Dynamics in Colleges and Universities, edited by M. J. Chang, D. Witt, J. Jones, and K. Hakuta. Stanford, CA: Stanford Education, an imprint of Stanford University Press.

Niu, Sunny Xinchun, Marta Tienda, and Kalena Cortes. 2006. "College selectivity and the Texas top 10% law." Economics of Education Review 25:259-272.

Orfield, Gary and Susan E. Eaton. 1996. Dismantling Desegregation. The Quiet Reversal of Brown v. Board of Education. New York, NY: The New Press.

Orfield, Gary and Chungmei Lee. 2007, "Historic Reversals, Accelerating Resegregation, and the Need for New Integration Strategies" A report of the Civil Rights Project, Retrieved (http://www.civilrightsproject.ucla.edu/research/deseg/reversals_reseg_need.pdf).

Pascarella, Ernest and Patrick Terenzini. 1991. How College Affects Students: Findings and Insights from Twenty Years of Research. San Francisco, CA: Jossey-Bass.

Peterson, Ruth D. and Lauren J. Krivo. 1999. "Racial Segregation, the Concentration of Disadvantage, and Black and White Homicide Victimization." Sociological Forum 14:465-493.

Rothman, Stanley, Seymour Martin Lipset, and Neil Nevitte. 2003. "Racial diversity reconsidered." Public Interest:25-38.

Terenzini, Patrick T., Alberto F. Cabrera, Carol L. Colbeck, Stefani A. Bjorklund, and John M. Parente. 2001. "Racial and Ethnic Diversity in the Classroom: Does It Promote Student Learning?" Journal of Higher Education 72:509-531.

Texas Education Agency. 2007, "Enrollment in Texas Public Schools 2005-06", Retrieved 6 May 2007, (http://www.tea.state.tx.us/research/pdfs/enrollment_2005-06.pdf).

Tienda, Marta and Sunny Xinchu Niu. 2006. "Flagships, Feeders, and the Texas Top 10% Law: A Test of the "Brain Drain" Hypothesis." Journal of Higher Education 77:712-739.

U.S. Census Bureau. 2005, "Chapter 6: Residential Segregation of Hispanics or Latinos: 1980 to 2000", Retrieved 6 May 2006, (http://www.census.gov/hhes/www/housing/housing_patterns/ch6.html).

U.S. Supreme Court. 2007. "Parents Involved in Community Schools v. Seattle School District No.1 et al." in 551 U.S. "No. 05-908 in Press": United States Reports.

Wells, Amy Stuart. 1995. "Reexamining social science research on school desegregation: Long-versus short-term effects." Teachers College Record 96:691-706.

Wells, Amy Stuart and Robert L. Crain. 1994. "Perpetuation Theory and the Long-Term Effects of School Desegregation." Review of Educational Research 64:531-555.

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 27 of 34

APPENDIX

The best way to assess the impact of the missing values is to use several approaches to

confirm whether the findings are robust to various approaches. To this end, I also conducted

identical analyses using multiple imputation on the restricted sample of 8,193 (see Table A_1)

and on the full senior sample of 13,803 (see Table A_2). Multiple imputation adjusts for the

downward bias that hotdecking and regression-based imputation produce, its key drawback is

that it assumes the data are missing at random.

If missingness on reported college preference is a function of reported college preference

(e.g., persons who do not intend to go to college do not report a college preference), then the data

are not missing at random. While the data is likely missing at random for the restricted sample, it

is most certainly not among the full senior sample. To this end, I use the Nobel Prize winning

Heckman selection method for imputing missing values that are not missing at random. This

method compensates for the differential propensities to report a college preference and reduces

the likelihood of biased parameters that would arise using multiple imputation or other

imputation approaches. The results from this approach are presented in Table A_3.

Out of curiosity, I wanted to examine the impact of the variables in the present analysis

on the likelihood of reporting a college preference. For this analysis, I simply replaced college

diversity index as the outcome measure with a dichotomous variable identifying whether a

student reported a college preference. The results from this approach are presented in Table

A_4a (coefficients) and Table A_4b (odds ratios). Using listwise deletion, there is no relation

between high school racial diversity and reporting a college preference in an unconditional

model (model 1) or a model that includes race (model 2). When school-level characteristics are

added (model 3), however, a negative relationship develops between high school racial

heterogeneity and reporting a college preference that is maintained through the remaining

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 28 of 34

models. The model is strongest (F=90.02) when the student-level demographic and educational

experience variables are added (model 4). Any racial differences in reporting a college

preference were eliminated in model 4 after controlling for other demographics and educational

experiences. With the exception of language, all of the non-race student-level variables in the

analysis had a direct effect on reporting a college preference. The only school-level variable with

a direct effect on reporting a college preference is attending a feeder high school.

Appendix Tables (Table A_1) about here

Appendix Tables (Table A_2) about here

Appendix Tables (Table A_3) about here

Appendix Tables (Table A_4a) about here

Appendix Tables (Table A_4b) about here

Racial Diversity and College Choice--DRAFT: NOT FOR CITATION OR REPRODUCTION WITHOUT AUTHOR'S CONSENT--

Donnell Butler, djbutler@princeton.edu

Draft Date: 08/04/08 Page 29 of 34

Coe

fS

ES

igC

oef

SE

Sig

Coe

fS

ES

igC

oef

SE

Sig

Coe

fS

ES

igEx

plan

ator

y M

easu

res

[Hig

h Sc

hool

Lev

el]

Hig

h S

choo

l Div

ersi

ty In

dex

0.15

7(0

.033

)**

*0.

179

(0.0

28)

***

0.15

7(0

.027

)**

*0.

154

(0.0

26)

***

0.15

1(0

.026

)**

*

Oth

er H

igh

Sch

ool C

hara

cter

istic

sE

nrol

lmen

t siz

e0.

000

(0.0

00)

0.00

0(0

.000

)0.

000

(0.0

00)

Per

cent

age

of s

tude

nts

with

col

lege

pla

ns

-0.0

01(0

.000

)*

-0.0

01(0

.000

)*

-0.0

01(0

.000

)*

Feed

er h

igh

scho

ol-0

.014

(0.0

17)

-0.0

08(0

.018

)-0

.005

(0.0

16)

Long

horn

sch

ool

0.06

5(0

.024

)**

0.06

0(0

.023

)*

0.05

8(0

.023

)*

Per

cent

age

of s

tude

nts

pass

ing

stat

e al

gebr

a te

st

0.00

0(0

.000

)0.

000

(0.0

00)

0.00

0(0

.000

)P

erce

ntag

e of

stu

dent

s w

ho q

ualif

y fo

r fre

e or

redu

ced

lunc

h-0

.001

(0.0

00)

*-0

.001

(0.0

00)

**-0

.001

(0.0

00)

**

Expl

anat

ory

Mea

sure

s [S

tude

nt L

evel

]R

ace

Whi

te (r

efer

ence

cat

egor

y)B

lack

-0.0

27(0

.011

)*

-0.0

36(0

.013

)**

-0.0

41(0

.014

)**

-0.0

38(0

.013

)*

His

pani

c0.

046

(0.0

14)

**0.

046

(0.0

11)

***

0.03

7(0

.010

)**

0.03

1(0

.011

)**

Asi

an0.

120

(0.0

12)

***

0.11

5(0

.011

)**

*0.

116

(0.0

11)

***

0.10

8(0

.010

)**

*N

ativ

e A

mer

ican

0.05

0(0

.021

)*

0.04

7(0

.022

)0.

040

(0.0

23)

0.04

0(0

.024

)O

ther

race

0.01

4(0

.010

)0.

009

(0.0

10)

0.00

6(0

.010

)0.

004

(0.0

10)

Rac

e m

issi

ng0.

033

(0.0

12)

**0.

033

(0.0

12)

**0.

027

(0.0

12)

*0.

025

(0.0

11)

Oth

er D

emog

raph

ic C

hara

cter

istic

sP

aren

t with

a b

ache

lor's

deg

ree

-0.0

29(0

.006

)**

*-0

.021

(0.0

05)

***

Mal

e-0

.002

(0.0

05)

-0.0

01(0

.005

)U

.S. c

itize

n-0

.002

(0.0

11)

0.00

1(0

.011

)E

nglis

h no

t alw

ays

prim

ary

lang

uage

0.00

0(0

.008

)-0

.005

(0.0

07)

Edu

catio

nal E

xper

ienc

esC

lass

Ran

k P

erce

ntile

0.00

0(0

.000

)0.

000

(0.0

00)

Enr

olle

d in

col

lege

pre

p tra

ck-0

.010

(0.0

05)

-0.0

06(0

.005

)P

erce

ntag

e of

ava

ilabl

e A

P c

ours

es ta

ken

-0.0

01(0

.010

)0.

005

(0.0

09)

Exp

ects

to a

ttend

two

or fo

ur y

ear c

olle

ge a

fter h

igh

scho

ol-0

.008

(0.0

06)

-0.0

04(0

.006

)C

olle

ge a

ttend

ance

enc

oura

gem

ent f

rom

par

ents

, tea

cher

s, a

nd c

ouns

elor

s-0

.007

(0.0

09)

-0.0

03(0

.009

)

Cho

ice

Pre

fere

nces

Low

exp

ense

s0.

010

(0.0

03)

**A

vaila

bilit

y of

fina

ncia

l aid

-0.0

10(0

.003

)**

Ath

letic

s re

puta

tion

-0.0

02(0

.004

)A

bilit

y to

live

at h

ome

0.01

8(0

.005

)**

*A

bilit

y to

live

aw

ay fr

om h

ome

0.00

1(0

.004

)R

elig

ious

env

ironm

ent

-0.0

25(0

.003

)**

*Jo

b pl

acem

ent s

ucce

ss0.

007

(0.0

03)

Aca

dem

ic re

puta

tion

-0.0

03(0

.004

)A

vaila

bilit

y of

des

ired

degr

ee p

rogr

am0.

003

(0.0

05)

Eth

nora

cial

mix

of s

tude

nts

or fa

culty

0.01

0(0

.004

)*

Siz

e-0

.006

(0.0

04)

Lega

cy-0

.011

(0.0

05)

*Fr

iend

s pl

an to

atte

nd-0

.003

(0.0

04)

Fam

ily c

onne

ctio

n-0

.005

(0.0

05)

Fam

ily o

pini

on-0

.008

(0.0

03)

*Fr

iend

ship

with

alu

mni

0.00

0(0

.006

)

Con

stan

t0.

341

(0.0

17)

***

0.31

7(0

.013

)**

*0.

367

(0.0

31)

***

0.40

4(0

.038

)**

*0.

419

(0.0

36)

***

Sou

rce:

200

2 Te

xas

Hig

her E

duca

tion

Opp

ortu

nity

Pro

ject

Stu

dy o

f Hig

h S

choo

l Sen

iors

.N

=8,1

93 --

Mis

sing

val

ues

are

hand

led

usin

g m

ultip

le im

puta

tion

*p <

.05

** p

<.01

***

p<.

001

(two-

taile

d te

sts)

Tabl

e A

_1. C

oeffi

cien

ts fr

om th

e Li

near

Reg

ress

ion

of S

elec

ted

Expl

anat

ory

Varia

bles

on

the

Div

ersi

ty In

dex

of S

tude

nt's

Pre

ferr

ed F

irst C

olle

ge C

hoic

e, M

ultip

le Im

puta

tion,

N=8

,193

(St

anda

rd e

rror

s in

par

enth

eses

)M

odel

1M

odel

2M

odel

3M

odel

4M

odel

5

Draft Date: 08/04/08 DRAFT: DO NOT CITE Page 30 of 34

Coe

fS

ES

igC

oef

SE

Sig

Coe

fS

ES

igC

oef

SE

Sig

Coe

fS

ES

igEx

plan

ator

y M

easu

res

[Hig

h Sc

hool

Lev

el]

Hig

h S

choo

l Div

ersi

ty In

dex

0.17

3(0

.030

)**

*0.

192

(0.0

26)

***

0.17

1(0

.023

)**

*0.

168

(0.0

22)

***

0.16

5(0

.023

)**

*

Oth

er H

igh

Sch

ool C

hara

cter

istic

sE

nrol

lmen

t siz

e0.

000

(0.0

00)

*0.

000

(0.0

00)

**0.

000

(0.0

00)

**P

erce

ntag

e of

stu

dent

s w

ith c

olle

ge p

lans

-0

.001

(0.0

00)

*-0

.001

(0.0

00)

**-0

.001

(0.0

00)

**Fe

eder

hig

h sc

hool

-0.0

14(0

.016

)-0

.007

(0.0

17)

-0.0

07(0

.016

)Lo

ngho

rn s

choo

l0.

059

(0.0

14)

*0.

056

(0.0

13)

***

0.05

3(0

.013

)*

Per

cent

age

of s

tude

nts

pass

ing

stat

e al

gebr

a te

st

0.00

0(0

.000

)*

0.00

0(0

.000

)*

0.00

0(0

.000

)*

Per

cent

age

of s

tude

nts

who

qua

lify

for f

ree

or re

duce

d lu

nch

-0.0

01(0

.000

)*

-0.0

01(0

.000

)**

-0.0

01(0

.000

)**

Expl

anat

ory

Mea

sure

s [S

tude

nt L

evel

]R

ace

Whi

te (r

efer

ence

cat

egor

y)B

lack

-0.0

32(0

.009

)*

-0.0

42(0

.010

)**

*-0

.045

(0.0

10)

**-0

.041

(0.0

10)

*H

ispa

nic

0.04

9(0

.011

)**

*0.

044

(0.0

08)

***

0.03

6(0

.009

)**

0.03

0(0

.009

)**

Asi

an0.

126

(0.0

15)

***

0.11

6(0

.013

)**

*0.

118

(0.0

13)

***

0.10

8(0

.013

)**

*N

ativ

e A

mer

ican

0.03

6(0

.029

)0.

037

(0.0

29)

0.03

0(0

.029

)0.

031

(0.0

29)

Oth

er ra

ce0.

022

(0.0

15)

0.01

6(0

.015

)0.

014

(0.0

15)

0.01

1(0

.014

)R

ace

mis

sing

0.01

8(0

.021

)0.

019

(0.0

20)

0.01

4(0

.020

)0.

013

(0.0

19)

Oth

er D

emog

raph

ic C

hara

cter

istic

sP

aren

t with

a b

ache

lor's

deg

ree

-0.0

28(0

.005

)**

*-0

.020

(0.0

05)

***

Mal

e-0

.002

(0.0

09)

0.00

1(0

.009

)U

.S. c

itize

n-0

.001

(0.0

10)

0.00

0(0

.010

)E

nglis

h no

t alw

ays

prim

ary

lang

uage

0.00

0(0

.007

)-0

.002

(0.0

06)

Edu

catio

nal E

xper

ienc

esC

lass

Ran

k P

erce

ntile

0.00

0(0

.000

)0.

000

(0.0

00)

Enr

olle

d in

col

lege

pre

p tra

ck-0

.005

(0.0

07)

-0.0

03(0

.007

)P

erce

ntag

e of

ava

ilabl

e A

P c

ours

es ta

ken

0.00

0(0

.009

)0.

008

(0.0

09)

Exp

ects

to a

ttend

two

or fo

ur y

ear c

olle

ge a

fter h

igh

scho

ol-0

.003

(0.0

08)

0.00

0(0

.009

)C

olle

ge a

ttend

ance

enc

oura

gem

ent f

rom

par

ents

, tea

cher

s, a

nd c

ouns

elor

s-0

.003

(0.0

08)

-0.0

05(0

.007

)

Cho

ice

Pre

fere

nces

Low

exp

ense

s0.

007

(0.0

05)

Ava

ilabi

lity

of fi

nanc

ial a

id-0

.006

(0.0

03)

**A

thle

tics

repu

tatio

n-0

.006

(0.0

04)

Abi

lity

to li

ve a

t hom

e0.

019

(0.0

04)

***

Abi

lity

to li

ve a

way

from

hom

e0.

000

(0.0

04)

Rel

igio

us e

nviro

nmen

t-0

.024

(0.0

03)

***

Job

plac

emen

t suc

cess

0.00

8(0

.004

)A

cade

mic

repu

tatio

n-0

.001

(0.0

04)

Ava

ilabi

lity

of d

esire

d de

gree

pro

gram

0.00

1(0

.006

)E

thno

raci

al m

ix o

f stu

dent

s or

facu

lty0.

011

(0.0

04)

*S

ize

-0.0

03(0

.003

)Le

gacy

-0.0

10(0

.005

)Fr

iend

s pl

an to

atte

nd-0

.001

(0.0

04)

Fam

ily c

onne

ctio

n-0

.007

(0.0

06)

Fam

ily o

pini

on-0

.006

(0.0

05)

Frie

ndsh

ip w

ith a

lum

ni-0

.004

(0.0

06)

Con

stan

t0.

337

(0.0

15)

***

0.31

2(0

.013

)**

*0.

345

(0.0

25)

***

0.36

3(0

.032

)**

*0.

378

(0.0

33)

***

Sou

rce:

200

2 Te

xas

Hig

her E

duca

tion

Opp

ortu

nity

Pro

ject

Stu

dy o

f Hig

h S

choo

l Sen

iors

.N

=13,

803

-- M

issi

ng v

alue

s ar

e ha

ndle

d us

ing

mul

tiple

impu

tatio

n*p

<.0

5 **

p<.

01 *

** p

<.00

1 (tw

o-ta

iled

test

s)

Tabl

e A

_2. C

oeffi

cien

ts fr

om th

e Li

near

Reg

ress

ion

of S

elec

ted

Expl

anat

ory

Varia

bles

on

the

Div

ersi

ty In

dex

of S

tude

nt's

Pre

ferr

ed F

irst C

olle

ge C

hoic

e, M

ultip

le Im

puta

tion,

N=1

3,80

3 (S

tand

ard

erro

rs in

par

enth

eses

)M

odel

1M

odel

2M

odel

3M

odel

4M

odel

5

Draft Date: 08/04/08 DRAFT: DO NOT CITE Page 31 of 34

Coe

fS

ES

igC

oef

SE

Sig

Coe

fS

ES

igC

oef

SE

Sig

Coe

fS

ES

igEx

plan

ator

y M

easu

res

[Hig

h Sc

hool

Lev

el]

Hig

h S

choo

l Div

ersi

ty In

dex

0.15

7(0

.033

)**

*0.

179

(0.0

28)

***

0.15

7(0

.027

)**

*0.

153

(0.0

24)

***

0.15

0(0

.025

)**

*

Oth

er H

igh

Sch

ool C

hara

cter

istic

sE

nrol

lmen

t siz

e0.

000

(0.0

00)

0.00

0(0

.000

)*

0.00

0(0

.000

)P

erce

ntag

e of

stu

dent

s w

ith c

olle

ge p

lans

-0

.001

(0.0

00)

*-0

.001

(0.0

00)

*0.

000

(0.0

00)

Feed

er h

igh

scho

ol-0

.014

(0.0

17)

-0.0

05(0

.017

)-0

.004

(0.0

15)

Long

horn

sch

ool

0.06

5(0

.024

)**

0.05

6(0

.023

)*

0.05

6(0

.023

)*

Per

cent

age

of s

tude

nts

pass

ing

stat

e al

gebr

a te

st

0.00

0(0

.000

)0.

000

(0.0

00)

0.00

0(0

.000

)P

erce

ntag

e of

stu

dent

s w

ho q

ualif

y fo

r fre

e or

redu

ced

lunc

h-0

.001

(0.0

00)

*-0

.001

(0.0

00)

**-0

.001

(0.0

00)

**

Expl

anat

ory

Mea

sure

s [S

tude

nt L

evel

]R

ace

Whi

te (r

efer

ence

cat

egor

y)B

lack

-0.0

27(0

.011

)*

-0.0

37(0

.013

)**

-0.0

44(0

.016

)**

-0.0

40(0

.015

)*

His

pani

c0.

046

(0.0

14)

**0.

046

(0.0

11)

***

0.03

9(0

.011

)**

0.03

5(0

.012

)**

Asi

an0.

121

(0.0

12)

***

0.11

5(0

.011

)**

*0.

110

(0.0

11)

***

0.09

8(0

.012

)**

*N

ativ

e A

mer

ican

0.04

9(0

.021

)*

0.04

7(0

.022

)*

0.03

4(0

.029

)0.

032

(0.0

33)

Oth

er ra

ce0.

013

(0.0

10)

0.00

9(0

.010

)0.

007

(0.0

12)

0.00

3(0

.011

)R

ace

mis

sing

0.03

1(0

.013

)*

0.02

9(0

.012

)*

0.01

9(0

.022

)0.

016

(0.0

21)

Oth

er D

emog

raph

ic C

hara

cter

istic

sP

aren

t with

a b

ache

lor's

deg

ree

-0.0

29(0

.005

)**

*-0

.020

(0.0

04)

***

Mal

e-0

.001

(0.0

04)

0.00

2(0

.004

)U

.S. c

itize

n-0

.010

(0.0

13)

-0.0

09(0

.012

)E

nglis

h no

t alw

ays

prim

ary

lang

uage

0.00

1(0

.008

)-0

.001

(0.0

08)

Edu

catio

nal E

xper

ienc

esC

lass

Ran

k P

erce

ntile

0.00

0(0

.000

)0.

000

(0.0

00)

Enr

olle

d in

col

lege

pre

p tra

ck-0

.009

(0.0

05)

-0.0

06(0

.005

)P

erce

ntag

e of

ava

ilabl

e A

P c

ours

es ta

ken

0.00

3(0

.011

)0.

008

(0.0

11)

Exp

ects

to a

ttend

two

or fo

ur y

ear c

olle

ge a

fter h

igh

scho

ol-0

.012

(0.0

09)

-0.0

10(0

.008

)C

olle

ge a

ttend

ance

enc

oura

gem

ent f

rom

par

ents

, tea

cher

s, a

nd c

ouns

elor

s-0

.004

(0.0

09)

-0.0

02(0

.009

)

Cho

ice

Pre

fere

nces

Low

exp

ense

s0.

010

(0.0

03)

**A

vaila

bilit

y of

fina

ncia

l aid

-0.0

11(0

.003

)**

Ath

letic

s re

puta

tion

-0.0

07(0

.004

)A

bilit

y to

live

at h

ome

0.02

0(0

.005

)**

*A

bilit

y to

live

aw

ay fr

om h

ome

0.00

2(0

.004

)R

elig

ious

env

ironm

ent

-0.0

24(0

.003

)**

*Jo

b pl

acem

ent s

ucce

ss0.

005

(0.0

03)

Aca

dem

ic re

puta

tion

-0.0

02(0

.005

)A

vaila

bilit

y of

des

ired

degr

ee p

rogr

am0.

004

(0.0

06)

Eth

nora

cial

mix

of s

tude

nts

or fa

culty

0.01

2(0

.005

)*

Siz

e-0

.004

(0.0

03)

Lega

cy-0

.012

(0.0

06)

*Fr

iend

s pl

an to

atte

nd-0

.004

(0.0

05)

Fam

ily c

onne

ctio

n-0

.004

(0.0

05)

Fam

ily o

pini

on-0

.003

(0.0

03)

Frie

ndsh

ip w

ith a

lum

ni-0

.005

(0.0

05)

Con

stan

t0.

337

(0.0

15)

***

0.31

4(0

.013

)**

*0.

363

(0.0

31)

***

0.39

8(0

.033

)**

*0.

414

(0.0

40)

***

N13

,803

13

,803

13,8

03

12

,500

12,2

37

F-

Sta

tistic

(Adj

uste

d W

ald

Test

For

Com

plex

Sur

vey

Dat

a)22

.32

22

.94

17.9

2

17

.49

32.9

0

M

odel

Deg

rees

of F

reed

om1

6

6

9

9

Des

ign

Deg

rees

of F

reed

om52

52

52

52

52

P

r>F

0.00

00.

000

0.00

00.

000

0.00

0

Sou

rce:

200

2 Te

xas

Hig

her E

duca

tion

Opp

ortu

nity

Pro

ject

Stu

dy o

f Hig

h S

choo

l Sen

iors

.N

=13,

803

-- M

issi

ng v

alue

s ar

e ha

ndle

d us

ing

heck

man

sel

ecte

d m

etho

d*p

<.0

5 **

p<.

01 *

** p

<.00

1 (tw

o-ta

iled

test

s)

Tabl

e A

_3. C

oeffi

cien

ts fr

om th

e Li

near

Reg

ress

ion

of S

elec

ted

Expl

anat

ory

Varia

bles

on

the

Div

ersi

ty In

dex

of S

tude

nt's

Pre

ferr

ed F

irst C

olle

ge C

hoic

e, H

eckm

an S

elec

tion

Met

hod,

N=1

3,80

3 (S

tand

ard

erro

rs in

par

enth

eses

)M

odel

1M

odel

2M

odel

3M

odel

4M

odel

5

Draft Date: 08/04/08 DRAFT: DO NOT CITE Page 32 of 34

Coe

f.S

ES

igC

oef.

SE

Sig

Coe

f.S

ES

igC

oef.

SE

Sig

Coe

f.S

ES

igEx

plan

ator

y M

easu

res

[Hig

h Sc

hool

Lev

el]

Hig

h S

choo

l Div

ersi

ty In

dex

-0.1

91(0

.294

)-0

.523

(0.2

74)

-0.6

21(0

.287

)*

-0.5

58(0

.259

)*

-0.5

39(0

.250

)*

Oth

er H

igh

Sch

ool C

hara

cter

istic

sE

nrol

lmen

t siz

e0.

000

(0.0

00)

0.00

0(0

.000

)0.

000

(0.0

00)

Per

cent

age

of s

tude

nts

with

col

lege

pla

ns

0.00

0(0

.003

)0.

000

(0.0

03)

0.00

0(0

.003

)Fe

eder

hig

h sc

hool

0.55

5(0

.185

)**

0.39

9(0

.100

)**

*0.

217

(0.0

86)

*Lo

ngho

rn s

choo

l-0

.341

(0.2

88)

-0.1

87(0

.291

)-0

.213

(0.2

69)

Per

cent

age

of s

tude

nts

pass

ing

stat

e al

gebr

a te

st

0.00

3(0

.003

)0.

003

(0.0

02)

0.00

2(0

.002

)P

erce

ntag

e of

stu

dent

s w

ho q

ualif

y fo

r fre

e or

redu

ced

lunc

h0.

002

(0.0

03)

0.00

0(0

.003

)0.

002

(0.0

03)

Expl

anat

ory

Mea

sure

s [S

tude

nt L

evel

]R

ace

Whi

te (r

efer

ence

cat

egor

y)B

lack

-0.2

03(0

.131

)-0

.090

(0.1

45)

0.09

3(0

.152

)0.

133

(0.1

35)

His

pani

c-0

.565

(0.0

92)

***

-0.5

06(0

.099

)**

*-0

.056

(0.1

18)

-0.0

03(0

.113

)A

sian

0.14

2(0

.188

)0.

074

(0.1

64)

-0.1

21(0

.153

)-0

.065

(0.1

71)

Nat

ive

Am

eric

an-0

.911

(0.3

71)

*-0

.850

(0.3

55)

*-0

.441

(0.2

99)

-0.4

28(0

.298

)O

ther

race

-0.2

85(0

.198

)-0

.289

(0.2

02)

-0.0

93(0

.220

)-0

.092

(0.2

25)

Rac

e m

issi

ng-0

.316

(0.4

33)

-0.2

73(0

.499

)-0

.040

(0.4

52)

0.00

9(0

.387

)

Oth

er D

emog

raph

ic C

hara

cter

istic

sP

aren

t with

a b

ache

lor's

deg

ree

0.29

2(0

.107

)**

0.23

4(0

.108

)*

Mal

e-0

.515

(0.0

93)

***

-0.4

04(0

.087

)**

*U

.S. c

itize

n0.

252

(0.1

26)

*0.

179

(0.1

23)

Eng

lish

not a

lway

s pr

imar

y la

ngua

ge-0

.142

(0.0

88)

-0.1

13(0

.084

)

Edu

catio

nal E

xper

ienc

e sC

lass

Ran

k P

erce

ntile

-0.0

15(0

.003

)**

*-0

.012

(0.0

03)

***

Enr

olle

d in

col

lege

pre

p tra

ck0.

512

(0.1

06)

***

0.40

8(0

.110

)**

*P

erce

ntag

e of

ava

ilabl

e A

P c

ours

es ta

ken

0.39

5(0

.195

)*

0.23

7(0

.194

)E

xpec

ts to

atte

nd tw

o or

four

yea

r col

lege

afte

r hig

h sc

hool

1.28

0(0

.087

)**

*1.

215

(0.0

95)

***

Col

lege

atte

ndan

ce e

ncou

rage

men

t fro

m p

aren

ts, t

each

ers,

and

cou

nsel

ors

0.74

8(0

.148

)**

*0.

608

(0.1

59)

***

Cho

ice

Pre

fere

nce s

Low

exp

ense

s-0

.199

(0.1

08)

Ava

ilabi

lity

of fi

nanc

ial a

id0.

171

(0.0

56)

**A

thle

tics

repu

tatio

n-0

.215

(0.0

84)

*A

bilit

y to

live

at h

ome

-0.1

84(0

.042

)**

*A

bilit

y to

live

aw

ay fr

om h

ome

0.15

7(0

.060

)*

Rel

igio

us e

nviro

nmen

t-0

.001

(0.0

95)

Job

plac

emen

t suc

cess

-0.0

33(0

.078

)A

cade

mic

repu

tatio

n0.

226

(0.0

61)

**A

vaila

bilit

y of

des

ired

degr

ee p

rogr

am0.

233

(0.0

87)

*E

thno

raci

al m

ix o

f stu

dent

s or

facu

lty-0

.170

(0.0

67)

Siz

e0.

249

(0.0

68)

**Le

gacy

-0.0

83(0

.085

)Fr

iend

s pl

an to

atte

nd0.

073

(0.0

79)

Fam

ily c

onne

ctio

n-0

.291

(0.1

04)

**Fa

mily

opi

nion

0.24

4(0

.089

)**

Frie

ndsh

ip w

ith a

lum

ni-0

.186

(0.0

69)

**

Con

stan

t1.

171

(0.1

33)

***

1.51

4(0

.132

)**

*1.

207

(0.2

87)

***

-0.2

15(0

.351

)-0

.627

(0.3

48)

F-S

tatis

tic (A

djus

ted

Wal

d Te

st F

or C

ompl

ex S

urve

y D

ata)

0.42

7.

36

2.40

90

.02

20.5

5

M

odel

Deg

rees

of F

reed

om1

6

6

9

16

Des

ign

Deg

rees

of F

reed

om52

52

52

52

52

Pr>

F0.

519

0.00

00.

042

0.00

00.

000

Sou

rce:

200

2 Te

xas

Hig

her E

duca

tion

Opp

ortu

nity

Pro

ject

Stu

dy o

f Hig

h S

choo

l Sen

iors

.N

=8,9

09 --

Mis

sing

val

ues

are

hand

led

usin

g lis

twis

e de

letio

n*p

<.0

5 **

p<.

01 *

** p

<.00

1 (tw

o-ta

iled

test

s)

Tabl

e A

_4a.

Coe

ffici

ents

from

the

Logi

stic

Reg

ress

ion

of S

elec

ted

Expl

anat

ory

Varia

bles

on

Stud

ent R

epor

ting

a Pr

efer

red

Firs

t Col

lege

Cho

ice,

Lis

twis

e D

elet

ion,

N=8

,909

(St

anda

rd e

rror

s in

par

enth

eses

)M

odel

1M

odel

2M

odel

3M

odel

4M

odel

5

Draft Date: 08/04/08 DRAFT: DO NOT CITE Page 33 of 34

Odd

s R

atio

S

ES

ig O

dds

Rat

io

SE

Sig

Odd

s R

atio

S

ES

ig O

dds

Rat

io

SE

Sig

Odd

s R

atio

S

ES

igEx

plan

ator

y M

easu

res

[Hig

h Sc

hool

Lev

el]

Hig

h S

choo

l Div

ersi

ty In

dex

0.82

6(0

.243

)0.

593

(0.1

63)

0.53

7(0

.154

)*

0.57

2(0

.148

)*

0.58

3(0

.146

)*

Oth

er H

igh

Sch

ool C

hara

cter

istic

sE

nrol

lmen

t siz

e1.

000

(0.0

00)

1.00

0(0

.000

)1.

000

(0.0

00)

Per

cent

age

of s

tude

nts

with

col

lege

pla

ns

1.00

0(0

.003

)1.

000

(0.0

03)

1.00

0(0

.003

)Fe

eder

hig

h sc

hool

1.74

2(0

.323

)**

1.49

0(0

.150

)**

*1.

243

(0.1

07)

*Lo

ngho

rn s

choo

l0.

711

(0.2

05)

0.83

0(0

.241

)0.

808

(0.2

17)

Per

cent

age

of s

tude

nts

pass

ing

stat

e al

gebr

a te

st

1.00

3(0

.003

)1.

003

(0.0

02)

1.00

2(0

.002

)P

erce

ntag

e of

stu

dent

s w

ho q

ualif

y fo

r fre

e or

redu

ced

lunc

h1.

002

(0.0

03)

1.00

0(0

.003

)1.

002

(0.0

03)

Expl

anat

ory

Mea

sure

s [S

tude

nt L

evel

]R

ace

Whi

te (r

efer

ence

cat

egor

y)B

lack

0.81

6(0

.107

)0.

914

(0.1

32)

1.09

8(0

.166

)1.

142

(0.1

54)

His

pani

c0.

569

(0.0

52)

***

0.60

3(0

.060

)**

*0.

946

(0.1

12)

0.99

7(0

.113

)A

sian

1.15

2(0

.217

)1.

077

(0.1

76)

0.88

6(0

.136

)0.

937

(0.1

60)

Nat

ive

Am

eric

an0.

402

(0.1

49)

*0.

427

(0.1

52)

*0.

644

(0.1

92)

0.65

2(0

.194

)O

ther

race

0.75

2(0

.149

)0.

749

(0.1

51)

0.91

1(0

.201

)0.

912

(0.2

05)

Rac

e m

issi

ng0.

729

(0.3

16)

0.76

1(0

.380

)0.

961

(0.4

34)

1.00

9(0

.390

)

Oth

er D

emog

raph

ic C

hara

cter

istic

sP

aren

t with

a b

ache

lor's

deg

ree

1.34

0(0

.143

)**

1.26

4(0

.136

)*

Mal

e0.

597

(0.0

56)

***

0.66

8(0

.058

)**

*U

.S. c

itize

n1.

287

(0.1

62)

*1.

197

(0.1

48)

Eng

lish

not a

lway

s pr

imar

y la

ngua

ge0.

867

(0.0

77)

0.89

3(0

.075

)

Edu

catio

nal E

xper

ienc

e sC

lass

Ran

k P

erce

ntile

0.98

5(0

.003

)**

*0.

988

(0.0

03)

***

Enr

olle

d in

col

lege

pre

p tra

ck1.

669

(0.1

76)

***

1.50

3(0

.165

)**

*P

erce

ntag

e of

ava

ilabl

e A

P c

ours

es ta

ken

1.48

5(0

.289

)*

1.26

7(0

.246

)E

xpec

ts to

atte

nd tw

o or

four

yea

r col

lege

afte

r hig

h sc

hool

3.59

7(0

.313

)**

*3.

370

(0.3

19)

***

Col

lege

atte

ndan

ce e

ncou

rage

men

t fro

m p

aren

ts, t

each

ers,

and

cou

nsel

ors

2.11

2(0

.313

)**

*1.

837

(0.2

93)

***

Cho

ice

Pre

fere

nce s

Low

exp

ense

s0.

820

(0.0

89)

Ava

ilabi

lity

of fi

nanc

ial a

id1.

186

(0.0

67)

**A

thle

tics

repu

tatio

n0.

806

(0.0

68)

*A

bilit

y to

live

at h

ome

0.83

2(0

.035

)**

*A

bilit

y to

live

aw

ay fr

om h

ome

1.17

0(0

.070

)*

Rel

igio

us e

nviro

nmen

t0.

999

(0.0

95)

Job

plac

emen

t suc

cess

0.96

8(0

.075

)A

cade

mic

repu

tatio

n1.

254

(0.0

77)

**A

vaila

bilit

y of

des

ired

degr

ee p

rogr

am1.

263

(0.1

10)

*E

thno

raci

al m

ix o

f stu

dent

s or

facu

lty0.

844

(0.0

56)

Siz

e1.

283

(0.0

87)

**Le

gacy

0.92

0(0

.079

)Fr

iend

s pl

an to

atte

nd1.

076

(0.0

85)

Fam

ily c

onne

ctio

n0.

748

(0.0

78)

**Fa

mily

opi

nion

1.27

6(0

.114

)**

Frie

ndsh

ip w

ith a

lum

ni0.

830

(0.0

57)

**

F-S

tatis

tic (A

djus

ted

Wal

d Te

st F

or C

ompl

ex S

urve

y D

ata)

0.42

7.

36

2.40

90

.02

20.5

5

M

odel

Deg

rees

of F

reed

om1

6

6

9

16

Des

ign

Deg

rees

of F

reed

om52

52

52

52

52

Pr>

F0.

519

0.00

00.

042

0.00

00.

000

Sou

rce:

200

2 Te

xas

Hig

her E

duca

tion

Opp

ortu

nity

Pro

ject

Stu

dy o

f Hig

h S

choo

l Sen

iors

.N

=8,9

09 --

Mis

sing

val

ues

are

hand

led

usin

g lis

twis

e de

letio

n*p

<.0

5 **

p<.

01 *

** p

<.00

1 (tw

o-ta

iled

test

s)

Tabl

e A

_4b.

Odd

s R

atio

s fr

om th

e Lo

gist

ic R

egre

ssio

n of

Sel

ecte

d Ex

plan

ator

y Va

riabl

es o

n St

uden

t Rep

ortin

g a

Pref

erre

d Fi

rst C

olle

ge C

hoic

e, L

istw

ise

Del

etio

n, N

=8,9

09 (

Stan

dard

err

ors

in p

aren

thes

es)

Mod

el 1

Mod

el 2

Mod

el 3

Mod

el 4

Mod

el 5

Draft Date: 08/04/08 DRAFT: DO NOT CITE Page 34 of 34