final is

Representation Out of Formation:
A Comparative Study of Educational Valuation in a Misrepresented Black Population in Higher
Education Institutions
By
Tarik Hasani Welch
Submitted in Partial Fulfillment of the Requirement of
Senior Independent Study for the Department of
Business Economics at
The College of Wooster
Advised by
Dr. Shu-Ling Wang
Department of Economics
March 28, 2016

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Acknowledgements
I would like simply to extend a profound gratitude to all those who have pushed, dragged,
lifted, and guided me along the way up until this point in my academic career, it is you who
deserve much of the credit for this work. Thank you to my family, close friends, distant friends,
advisors, teachers, and professors both present and past, you all have shaped me and I am proud
and grateful to have experienced time with you.

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Abstract:
This paper compares and contrasts native and immigrant populations in the National
Longitudinal Survey of Freshman (NLSF) in regards to how they value education. Specifically
noted are the background differences that can negatively or positively affect this valuation.
Based off of a number of recent studies, most notably from Massey, Mooney, Torres, and
Charles (2007), the conceptual hypothesis is that immigrant blacks value education more than
native black students given a number of key variables from other studies and the theoretical
framework of the two-period model. Results from a multiple regression show that immigrant
black students exhibit a level of valuation higher than native black students based off of a
measure of self-confidence.

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Table of Contents
1.0 Introduction
2.0. Literature Review
2.0.1. Introduction
2.1. Paul J. Taubman and Terence Wales
2.2. Robert J. Willis
2.3. Douglass S Massey, Margaret A. Mooney, Kimberly C. Torres, and Camille Z.
Charles
2.4. Jennifer Hunt
2.5. Elizabeth Raleigh and Grace Kao
2.6. Kevin J. A. Thomas
3.0. Theory
3.0.1. Theory Introduction
3.1. Two Period Model
3.1.1. Model Assumptions
3.1.2. Model Explanation
3.1.3. Lifetime Budget Constraint
3.1.4. Lifetime Budget Constraint Shift
3.1.5. Contextual Analysis
3.2. Consumption-Savings Model
3.2.1. Model Assumptions
3.2.2. Model Explanation
3.2.3. Lifetime Budget Constraint
3.2.4. Increase in r
4.0. Empirical Work
4.0.1. Model Specification
4.0.2. Variable Table
4.1. Data
4.2. Variables
4.2.1. Dependent Variable
4.2.2. Independent Variables from Studies
4.2.3. Independent Variables from Theory
4.3. Methodology
4.3.1. Heteroskedasticity
4.3.2. Multicollinearity
4.4. Regression Results and Analysis
5.0. Conclusion
6.0. Appendixes
6.1. Appendix A
6.2. Appendix B

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1.0. Introduction:
Prominent and award-winning history professor at Harvard University, Henry Lewis
Gates, while attending a Harvard black alumni gathering in 2004, observed a significance in the
makeup of the demographic of the population there. He observed that the vast majority of the
black alumni were of either Caribbean or African descent (either first generation or their
children) as apposed to Native African-American (those whose parents descend from slaves in
the U.S.). While this is just one instance, the New York Times article of reference by Sarah
Rimer and Karen B. Arenson, illuminates the existence of the issue that had needed attention and
due research. The title of the article reads, “Top Colleges take More Blacks, but Which Ones?”
As this title presumes, the topic outlays that black immigrants consistently assume a significant
percentage of the black population in selective higher education institutions in the U.S.
In this paper I intend to address this issue by taking both an economic and theoretical (in
my theory chapter) and evaluative approach (in my literature review and empirical modeling) to
determine crucial factors of native and immigrant black students that can explain a difference in
how they view/value education. It is to ask, do immigrant black students value education more
than native black students? Before this question can be answered however, one must consider the
basic questions, asking: why do more black immigrants take spots in selective higher education
than do native blacks? With a business economic approach we may conclude that selective
higher education institutions act as firms and thus operate with the thorough process of screening
and require a substantial amount of signaling when admitting new clients/students. With this the
answer may simply be that immigrant black students have better credentials, however this is
rather inconclusive and the issue delves into much more than a student’s list of credentials.

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It is given that colleges and universities go through an extensive process of advertising,
marketing, searching, and recruiting to build a diverse population, a selling point for institutions
because diversity provides students with a dynamic set of people from which to gain insight and
perspective. The dilemma, as noted in the article by Rimer and Arenson, is that in the
construction of the “black” population at selective schools, immigrant blacks are taken in at a
disproportionate rate therefore taking the spots intended for African Americans. This,
“intention,” derives from the article’s anecdote by Gates and Harvard law professor, Lani
Guinier, in their noting that the very existence of blacks in many institutions via desegregation
and affirmative action is due to the rejection of outright racism against African Americans
through Jim Crow laws and generational effects of chattel slavery. In this case Native blacks are
the “intended beneficiaries” and should therefore reflect a significant percentage of the black
population in institutions, at least proportionate to the national population.
United States census data from the year 2000 shows that black people of native parentage
comprise 11.6% of the total U.S. population while foreign born black people and black people of
foreign parentage take 0.8% and 0.5% of the total population respectively (see Table 1 in
Appendix A) (Schmidley 2000). In addition to these figures, Table 2 in Appendix A shows the
percentages of native and immigrant blacks in each type of institution via the data gathered by
the National Longitudinal Survey of Freshmen (NLSF) in 1999. This empirical evidence shows
the substantial percentage difference between native and immigrant populations in both the 10
most selective and Ivy League schools (35.6% and 40.6% immigrant) versus the populations in
all other institutions (28.7%, 29.3%, and 23.8% immigrant)(Massey, Mooney, Torres, Charles
2007). In reference to the national population statistics, the apparent inequality of admission into
higher education institutions manifests in every type of school indicated.

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The theoretical portion of the paper derives from the notion of value of education insofar
as we understand in economics that an agent will adjust their consumption when the value of an
investment increases due to a tradeoff of benefits (less consumption now is more consumption
later due to a wage differential). Based off of this idea, we can assume that a student/household
invests in education based off of the value it holds, and that a rise in value would shift
consumption further. Since we see a larger proportion of immigrant black students in selective
higher institutions we assume that immigrant blacks may value education and the future benefits
differently.
The differences in populations coupled with the steady rise in the value of education (see
Graph 1 in Appendix A) leads to the question that this paper aims to ask, do immigrant blacks
value education more than native blacks? The variables I use aim to signify much of the
differences in background/upbringing information such as parental involvement in intellectual
independence development and human capital formation due to the findings that immigrant
parents tend to place emphasis on educational attainment (Fuligini 1997, Raleigh and Kao 2010).
Another variable is the closeness of students to other races based on the relationship between
assimilation and likelihood of falling behind in school (Thomas 2009). In turn, the empirical
work and regression of the final chapter reveal the major differences that can explain a difference
in this valuation.

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2.0. Literature Review:
2.0.1. Introduction
The research for my Independent Study centers on what differences exist between
immigrant blacks and African American (native) blacks on the basis of valuation of higher
education. This specific topic bases itself in the multitude of research conducted on the necessity
and incentive of students and households to invest in education. Within this field scholars delve
into interest rates, human capital formation, access to human capital, wage inequality, education
demand, etc. These topics lead to the understanding that there are a number of determinants for
how a household is able to invest in education and further that the investment is worthwhile at
all. An economic position will solidify that an investment is effective if there is a definite benefit
in the future, however in the field of education and the idea of human capital, more factors must
be considered to confirm an investment in education (higher education).
Given that these background topics are integral to the understanding of why a household
would invest, the literature review will include two articles (first and second) in that respect
because they are crucial to the thesis of this paper. The rest will pertain directly to the topic of
immigrant versus native black issues in education. The two articles play a significant role
especially in regards to the theoretical chapter since economic gain must be at the premise of a
rationally acting agent/household’s decision to invest. The remaining articles are crucial to
understanding some of the fundamental differences between native and immigrant black people
in the U.S. Overall this body of literature aims to identify aspects of the educational investment
that either coerce them to infesting.

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2.1. Paul J. Taubman and Terence Wales
“The Human Capital Approach to Higher Education” from the book:
Higher Education and Earnings: College as an Investment and Screening Device (1974)
This study’s intention is to determine how and why the inclusion of education in an
agent’s life ultimately increases their lifetime income. The author conducts the research by
evaluating the existing theoretical model on human capital from Becker (1964) and further
modifies it with respect to additional assumptions pertaining to marginal production and real
wage.
In discussing the benefits of education and human capital accumulation, the economic
benefit will ultimately lead to the increased possibility of consumption in the future, however
Taubman and Wales focus on the monetary benefit solely as to not make the study too
complicated. The consumption of a household is crucial, yet it is “beyond the scope of the
present study” (Taubman and Wales 1974). Considering the monetary gain as the main benefit,
the study first defines the economic terms of “investment” and “human capital.” Though
different in their own rights, these terms are vital in this topic because both of them essentially
describe what education is. As the study’s definition of human capital shows, education is also a
means of increasing ones set of cognitive skills and affective attainment levels (Taubman and
Wales 1974). Human capital, as it is described in the study, does involve more than what
education can offer, being that education is one component to the whole of human capital. Yet,
as the article and this topic concerns, education acts as a screening device when entering the
labor market, and many higher paying occupations require this single aspect to human capital in
order for a candidate to be considered for hire (Taubman and Wales 1974). Taubman and Wales
stress the idea that ones set of skills is a major factor to how a person develops in their life. This

6
set of skills builds from birth and is formed through “genetic inheritances and is partly acquired
in the family, from friends, from formal education, and so on” (Taubman and Wales 1974). As it
pertains to jobs, a candidate will be more fit for a job if their set of skills makes them more
productive, and as apposed to the piece-rate system in which an employee gets paid according to
their productivity, most occupations and organizations pay workers by the hour and expect the
highest productivity. This expectation is reflected in the wage the worker receives. As such, the
best wage reflects the maximum amount of skills accrued and productivity a worker can manage.
The employer however pays the employee a wage less than or equal to the employee’s marginal
product, so in theory, there is an incentive to build as many skills as possible in order to have the
highest wage and income possibility.
The study points out that if an employer believes that a set of college graduate candidates
are more likely to have better and more cognitive and affective skills than a set of high school
graduates, in efforts to increase efficiency in the hiring process the employer will opt to choose
from the pool of college graduates (Taubman and Wales 1974). This screening device persists
across many occupations and many to the point where additional screens are added for masters
and doctorate degrees. The screening device is a crucial factor in education investment because
while an employer screens for the existence of education, those who may have t the necessary
cognitive and affective skills developed elsewhere from formal education, are effectively
excluded from the job opportunity due to a likely inability to invest (Taubman and Wales 1974).
To visualize this situation the study gives a simple equation where one’s skill is the dependent
variable:
Skilli=f(Ai, EDi, Pi, Xi)

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Here, Skilli is a function of Ai, a set of innate mental abilities; EDi, the amount/extent of
formal education; Pi, other innate characteristics like personality, drive, and motivation; and Xi,
all other determinants of skill (Taubman and Wales 1974). Again, in reference to the screening
issue, the cognitive and affective skills that are said to derive from EDi may come from the other
variables: Ai, Pi, and Xi. Yet, given that in today’s society many jobs require formal education,
and in particular, an undergraduate education or higher, there is a substantial incentive to invest
in education so that screening does not exclude an individual from a higher wage, higher income,
and more consumption in the future.
As it pertains to my topic, this screening tactic is what faces any individual that wishes to
increase their consumption in the future, given this generality we can assume that this dilemma
faces both native and immigrant black students and households. The need to have a college
degree is apparent for the majority of people. As this degree/signal is required to advance, it then
holds an intrinsic value. In relation to this point my study looks at how inherent differences
between immigrant and native black students and households may change how they value
education.
2.2. Robert J. Willis
“Wage Determinants: A Survey and Reinterpretation of Human Capital Earnings
Functions” (1986)
As the title aptly provides, this article aims to evaluate human capital earnings functions
however in critique of human capital investment as a primary determinant of future earnings. For
this study Willis, like Taubman and Wales, reinterprets the human capital studies from Becker
(1964, 1975), Becker and Chiswick (1966), and Mincer (1958, 1962, 1974) (Willis 1986). Willis

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introduces some of the main questions via the studies by Griliches (1977, p.1), which attempt to
answer/solve a number of questions pertaining to the problems in the estimation of the returns to
education, i.e. the coefficient ß1 in the human capital equation developed by Mincer (1974).1
In
summary Griliches asked how one is to interpret the equation and estimated coefficient and if the
coefficient is expected to be stable across multiple samples and time periods (Willis 1986).
Willis tackles this question in his study by applying that different jobs require a specific set of
skills that one gathers from innate abilities and schooling, similarly to Taubman and Wales
(1974). This way, Willis focuses on the demand side of human capital rather than the supply
side, to which much of the preceding literature and studies paid most attention.
One of Willis’ notable points is his observation that with an ability bias, one where the
innate ability of an individual positively correlates to their schooling level, the estimated rate of
return is upwardly biased. Given this finding, Willis combats the existence of bias with the
economic assumption that rational individuals choose opportunities (from those known) that are
the best for them and that schooling and post-schooling were assigned at random to individuals
with different levels of ability, thus rearing that estimates would really be unbiased due to the
experimental design (Willis 1986). Essentially this says that people will always have differing
levels of ability thus it should be given; thus, the effect of ability increasing the estimated
coefficient is inevitable. The challenging question would be to ask if there are trends in this
ability across certain populations i.e. native or immigrant black households and students.
Another important notion in his study is the distinction between private and social rates
of return based off of the work by Psacharopoulos (1973, 1981). He describes the private rate of
return as assuming that the “only cost of education is forgone earnings and that earnings are net
1
lny=ß0+ß1s+ß2x+ß3x2
+u (Willis 1986)

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of taxes” (Willis 1986). The social rate of return he describes as including the “direct cost of
schooling and uses before tax earnings” (Willis 1986). Expressing that taxes are usually
proportional to earnings, an increase in tax would then decrease the opportunity cost and benefit
by the same degree, which keeps the rate of return (private or social) the same (Willis 1986).
This point is important in that we may easily equate this hypothetical raise in taxes to a raise in
price of college (tuition) or the increase in a private or federal loan interest rate. Basic economic
theory tell us that in a perfectly competitive market the increase in price of a good would
decrease the quantity demanded of that good. With this theory in mind, a rational
individual/household would be less likely to pay for tuition when such an increase took place,
even if the rate of return is the same. The idea that future benefit is further discounted may deter
investment from households who are either reluctant to sacrifice current income for future
benefit or merely unable to pay tuition. Either way when we consider that the value of education
continues to rise (see Graph 1 in Appendix A), the dilemma that faces households when tuition
prices rise is a paramount factor in how many will choose to make educational investments.
Willis’ concluding remarks sum the empirical results of testing his modifications of the
existing human capital theories. Overall, in the context of his occupation-specific models, he
finds that his results hold significance in the theory that the return on human capital is more
dependent on the differentials in innate ability, that is, abilities that an individual does not
necessarily receive from formal schooling (Willis 1986). This result is opposed to the finding
that compensation (i.e. increased wage) for the cost of adjustment (i.e. cost of education) was the
main determinant of human capital return. In relation to my paper’s topic, the specificity and
differentials of a student’s innate ability can be a fundamental determinant of how immigrant
black students differ from native black students. This is provided that innate abilities are

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developed within the household and during the student’s upbringing, areas from which I draw
and consider variables for the empirical section of this paper.
2.3. Douglass S Massey, Margaret A. Mooney, Kimberly C. Torres, and Camille Z. Charles
“Black Immigrants and Black Natives Attending Selective Colleges and Universities in the
U.S.” (2007)
This study has been the central source for my study. While conducting my preliminary
research I had come across a number of newspaper journals and articles that referred to the
subject of native versus immigrant black populations in college, noting that the dilemma is a
generally recent issue. The majority of these articles cited this main study. And, given its
relatively recent publication, it subsequently holds a significant value to the subject of this paper.
This study’s main objective is to make a thorough comparative evaluation of immigrant
and native black students’ differences or similarities in regards to background and attendance of
higher education institutions. The study begins with a short comprehensive history of affirmative
action, influxes of immigration in the U.S., and the ensuing research thereof. The first point
addressed is that the premise of affirmative action was to serve for the generational effects of
racism in the country, for the betterment of African Americans. Not long after, the success of this
active inclusion struck a note with other marginalized demographics and others (Latinos, Asians,
women, disabled, etc) responded in a manner similar to African Americans, demanding inclusion
with respect to their own experiences of discrimination (Massey, Mooney, Torres, and Charles
2007). This suit of events evolved the affirmative action endeavor to become more broadly
oriented from the focused inclusion of African-American students to the inclusion of all
marginalized groups, toward diversity as whole (Massey, Mooney, Torres, and Charles 2007).

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The study focuses on the situation where institutions accept a significantly higher
proportion of immigrant black students (first and second generation) than native black students
in the endeavor to build the black population at schools. As noted in the introduction of this
paper, the topic of this inequality was first noted in 2004 by two of the foremost African
American intellectuals, Henry Louis Gates and Lani Gunier, while attending a Harvard Black
Alumni gathering (Massey, Mooney, Torres, and Charles 2007). From this standpoint the study
goes further to evaluate specific differences and similarities amongst the populations of native
and immigrant black students according to an empirical study.
For the empirical study, the authors used one of the more extensive data sets in recent
studies of college students. This is the National Longitudinal Survey of Freshmen (NLSF). This
dataset is so often used because of its detailed nature and the fact that it follows a large group of
students in selective higher education institutions throughout a number of years, 1999-2003. By
doing this, researchers can look at differences between how a student fared in college versus high
school and look how/if different demographics have trends. It uses a number of variables such as
household income, citizenship, GPA, etc. One of the main findings of the study is that immigrant
blacks are overrepresented more in private and highly selective institutions compared to public
institutions (see Table 2 in Appendix 1). This notion conveys that in selective colleges and
universities (those with much higher tuition than public colleges) there is a fairly large
proportion of black students of immigrant status or immigrant parents. This finding was based
off of the mere categorization of the data according to how many and to which type of college
the black population attended. The main empirical study ran lengthy regressions based on the
entirety of the background dataset that detailed parental, schooling, and general home-life
information.

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The main regression of the study tested the students’ GPA (dependent variable) against
every variable in the background dataset (independent variables). The results of the regression
suggest that there are relatively few and modest differences between the social origins of native
and immigrant blacks (Massey, Mooney, Torres, and Charles 2007). The notion that they are
relatively similar in that respect means to say that there must be another factor involved in the
overrepresentation of immigrant blacks. One of the more significant findings was that on average
immigrant parents are likely to be more educated than native black parents (Massey, Mooney,
Torres, and Charles 2007). More specifically, the findings were that black immigrant students are
more likely to have fathers who have graduated from college and/or held a higher degree, are
more likely to attend private schools, to have grown up in integrated neighborhoods, to have
more non-black friends, and to have a low susceptibility to peer pressure. This finding is
significant in that there may be an existence of an educational and motivational advantage given
the statistic, however to the contrary the study finds that once in college immigrant black
students perform at about the same level as native black students academically. These are factors
that are implicit in how the average immigrant black student is different from the native black
student. The significance is truly difficult to decipher.
My study looks at these differences again through a somewhat different model than that
used in the above article. Specifically my study does not look at all of the background variables
in relation to something such as GPA given that immigrant and native black students perform at
about the same level once in college (Massey, Mooney, Torres, and Charles 2007). The dataset
of students already has a certain level of bias in that they are all students that had been accepted
and committed to higher education, thus my study will look more specifically how certain
background variables influence each other along with integrating an economically theoretical

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aspect to the model. Massey, Mooney, Torres, and Charles gave an in depth comparative look at
both groups however it did not include much economic theory, thus in this respect my study may
well add to this topic and discussion of differences.
2.4. Jennifer Hunt
“The Impact of Immigration on the Educational Attainment of Natives” (2012)
Compared to the previous article, which noted a number of differences between native
and immigrant black students, the main objective of this article is to study how native and
immigrants are affected by each other. It outlines how either native or immigrant blacks can
influence each other in their completion of school. In the context of my study and research, this
article provides insight into how other variables such as influence may affect a student’s
educational path. From this, how they value education may very well be affected.
The article’s main study centers on the grade-high school experience of natives and
immigrants. This school experience is the first 12 years of education from ages 6-18 before a
student enters higher education (Hunt 2012). Using census data from 1940-2010, the goal of the
study was to observe how the probability of completion changes for native-born students with
the presence of immigrant students. Via the abstract, this topic is supported with the idea that
immigrant students may compete with native students for school resources and decrease the
probability of completion (Hunt 2012). At the same time there is the idea that an increase in
immigrant students would coerce native students to complete these 12 years of education. In
reality it would be true that both of these possibilities are evident, and the results of the study
have manifested this reality. Though relatively small the studies found a number of changes in
probability of graduation for native and immigrant Hispanics, native whites, and native and

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immigrant blacks. Overall the study found that immigrants as a whole had only a small negative
effect on natives’ completion (Hunt 2012). However it is significantly noted that for native
blacks the most negative effect from immigrants aged 11-17 was estimated despite it being only
a moderate change (Hunt 2012). Another important result is that on average native blacks are
more likely to attend schools with 2.7 percent more immigrants than native whites (Hunt 2012).
That the greatest immigrant effect occurs to native blacks shows that there exists a moderate
trend (Hunt 2012).
As it relates to my topic this article exemplifies that the presence of immigrants can, even
at a minute level, affect how native black students fare in terms of their graduation rate for high
school. This study is important because it adds a layer of background to the narrative that results
in the topic at hand, the representations of immigrant and native blacks in higher education. It is
without a doubt that the graduation rate plays a role in attendance of higher education
institutions, however this study does pose some lack in detail as it pertains to the topic. The study
does not separate between native and immigrant blacks, referring only to immigrant Hispanic
and white effects. I also found it unusable to mention the varying ages of immigrants and natives
as an influence to graduation rate. Having come across both ranges from 11-64 and 11-17 I
found it only necessary to consider the smaller age range, which covers most of a student’s high
school track. In relation to the background of the student, this period of schooling wherein
student can be helped or hindered, is an essential difference between immigrant and native
blacks, especially considering how the student views their own education.

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2.5. Elizabeth Raleigh and Grace Kao
“Do Immigrant Minority Parents Have More Consistent College Aspirations for Their
Children?” (2010)
As the title suggests, the parental element in the value of education is essential to how a
household may operate when investing in education for a student. We may equate aspiration with
valuation because when one aspires to achieve a goal, they can take a number of measures and
risks to achieve it. With education these risks may come in the form of debt or decreased
consumption among others. Nonetheless this article takes into account that aspirations for
education are an important precursor to actual attainment. Using extensive data from the Early
Childhood Longitudinal Study-Kindergarten Cohort (ECLS-K) the study takes tracks the college
aspiration of parents of different backgrounds, testing for consistency and stability.
It is true that on the individual household level the mere amount of money paid for tuition
to a college cannot totally determine how a household values education (though it is an important
factor). It is this aspect of the household that makes this source important to my topic since the
article focuses around more behavioral factors. Compared to the previous article by Hunt (2012),
Raleigh and Kao make a clear distinction between native and immigrant blacks, a paramount
difference as it correlates directly to the differences I aim to see in my own study. Additionally
the article makes an effort to differentiate between households that operate with two immigrant
parents and those with one immigrant parent since there is a possible difference in how they form
and perpetuate aspirations to the student.
The study’s main focus derives from its OLS regressions that test parents’ aspiration
level across multiple years against a few independent variables. The study’s time range is from
the fall of 1998 (kindergarten) to the spring of 2004 (fifth grade) (Raleigh and Kao 2010). The

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measure of “aspiration” came from the answers to a few questions on how the parents perceive
their child to fare in education. A key word mentioned was “expect” as it connects to an implicit
standard that the parent sets for their child. The significant data points would be those who
expect their child to achieve a college degree or further and keep that view consistent. The table
below shows the regression results of immigrant and native black aspirations (Raleigh and Kao
2010).
The numbers for immigrant black parents are consistently higher for most of the variables
displayed ex: parent expected child to earn a college degree, at kindergarten expected to earn a
college degree or higher, at 3rd
grade expected to earn a college degree or higher, etc. (Raleigh
and Kao 2010). It is also significant that for native black parents in this study the numbers for
aspirations for kindergarten, 3rd
, and 5th
grade decrease for each subsequent year (0.72, 0.68, and
0.67) while for immigrant black parents the numbers dip and then increase above the
kindergarten year showing an overall boost in expectations (0.92, 0.90, and 0.95) (Raleigh and

17
Kao 2010). These data points aid in the explanation of a higher aspiration for education by the
immigrant households; however, we cannot exclude the control variables that are crucial to what
may explain the low numbers of native parents. The variables: mother’s years of education,
income (10Ks), married parents, and female child, all have lower values for native parents
(Raleigh and Kao 2010). We must consider how these may play a roll in the lower numbers for
aspirations for their child. For one these control variables factor into how confident a parent may
be in themselves of their ability to motivate the child. If a parent has a limited or non-existent
experience of higher education, lower income, or is divorced or separated they may be less
optimistic about the future for not only themselves but for their child as well. The term
“optimism” is frequented in this article as an essential source for aspiration for education.
By the conclusion of this article we understand that the results of this consistent optimism
pointed in the direction to explain a “higher academic performance of children of immigrants
later in the lifecourse” (Hirschman and Wong, 1986; Kao and Tienda,1995; Fuligni, 1997).
Through this article and its findings we can further support the topic of representation in higher
education and how a parent’s role in the household pertains to education valuation.
2.6. Kevin J. A. Thomas
“Parental Characteristics and the Schooling Progress of the Children of Immigrant and
U.S. Born Blacks” (2009)
Fundamentally this article furthers the idea that the presence of parents and their
motivational characteristics can act as integral forces in pushing a student toward college (and
further representation in higher education). Differing from Raleigh and Kao (2010), Thomas
specifically focuses on the children of black immigrants rather than both the children of

18
immigrants and direct immigrant children. By making this distinction we can compare and
contrast first generation immigrant blacks and native blacks, having been raised in the same
country.
One of the main goals of this article is to explain differences between one and two parent
households and how that dynamic is different for immigrant and native households on terms of
the probability of delayed schooling. Using data from a public sample of the 2000 U.S. census
Thomas conducts a number of multiple regressions to see the significant variables that affect
students’ education tract.
These multiple regression
models test the relationship
between schooling
progress, generational
status, and parental
arrangements (Thomas
2009). The first model
controls for demographic
characteristics and the
second model controls for
family structure, size, and
income (models shown in
the table above) (Thomas
2009). The first model’s results illustrate that children born to immigrant parents (regardless of
having one or two immigrant parents) do “significantly” better than children with native parents

19
(Thomas 2009). In addition the model concludes that of all the combinations of demographics
(i.e. first or second generation, native or immigrant parents, or one or two-parent household)
second-generation children born to two immigrant black parents have the least likelihood of
delayed schooling (Thomas 2009). The results from the second model show a reduced disparity
of delayed schooling between first and second-generation children born to immigrant black
parents (Thomas 2009). Despite this reduced difference, the result from the first model remains
consistent.
The next three models differentiate between single and two-parent households and
provide additional variables about the characteristics of each spouse. The general conclusion to
these regressions is three-part; one, that children born to immigrant parents (either one or two-
parent) are less likely to experience delays in schooling, two, that educational attainment of
parents cannot explain the advantage experienced by immigrant children in lesser probability of
delayed schooling, and three, that no evidence exists of a “convergence” or influence in the
educational advancement of immigrant black children with native black children (Thomas 2009).
These findings explain a certain imperviousness to influence for immigrant black children,
however despite this consistency in these models there are likely more variables involved.
By the end of the study, Thomas concludes that a multiplier exists wherein an immigrant
parent’s motivation pertaining to better performance and lower likelihood of delayed progress
multiplies when there are two immigrant parents versus just one. This stems from the result
showing a consistent better performance from two parent immigrant households than one-parent
immigrant households. He notes further that even a student with one-parent immigrant
households have a lower likelihood of delayed progress than a student with only-native parent
households. As compared to immigrant students not born in the U.S., the study shows that U.S.

20
born immigrant blacks have an even lower likelihood of delayed progress, the U.S. birth acting
as a positive effect. These findings support the recurring idea that the household/parents can have
a significant effect on the educational progress of a student and thus how they value education.

21
3.0. Theory
3.0.1 Theory Intro:
The goal of this study is to discover a possible difference in the educational valuation (of
higher education) between native and immigrant blacks. By planning a theoretical model here,
and based on a number of assumptions and plausible actions, this section will be useful in
mapping out a hypothetical sequence of a student investing in college. In this section I will often
identify the student as operating with their household. This distinction is based off of the
assumption that the household represents both the parents and the children, and the parents are
the primary source of funds for their children especially in the realm of higher education. Just as
much as this study is about the differences between native and immigrant students, it is also
about background differences and that greatly involves parents.
By modeling this common situation of college investment through two different two-
period models we will discover how certain economic shifts can affect the value of education for
a household and student. For these shifts this section will examine an increase in the future wage
rate and an increase in the interest rate. With both of these shifts we expect to see a change in the
household’s spending and consumption based on the tradeoff of current period consumption for
more consumption in the second period. The two student types of my study are the native black
type and the immigrant black type, however for this model situation I will make no distinction
between agents. By acting as such the model will retain an amount of transparency. The
necessity for transparency derives from the fact that we know many colleges in the U.S. actively
search for people of color to diversify their student population and I have previously stated that
in the discovery of the admissions departments have not disclosed any information on whether
there is a distinct preference for either (assuming there is for immigrant blacks). Overall, the

22
models show a situation in which an agent has to choose how much of a good they want to
consume and/or to pay tuition and attend college.
3.1. Two-Period Model:
I will use a two-period model to show how the decision of how much education and
consumption one chooses in the first period affects how much wage and affordable consumption
an agent can have in the second period. This decision will derive from how an agent approaches
their amount of consumption and education based off of the potential future wage earnings with
a college degree, the realistic valuation of earning a college degree. Paying for college in the first
period and consuming less goods will give a higher potential for goods consumption in the
second period. The agent’s tradeoff is such that they must sacrifice in the first period so that they
can have more in the second period. If they do not sacrifice in the first period, trading education
for more goods, they will pay for it in the second period by having no educational bonus via a
higher wage. In the context of the topic, the value that the agent places on the future correlates
directly to how they will value education in the first period. The value of this education will then
determine how much they are willing to spend on tuition and how much goods they are willing
to sacrifice. Simply, the amount invested should positively correlate to the college valuation of
an agent. The topic at hand is to see whether there is a difference in college valuation between
African Americans and immigrant blacks when applying to higher education. The two period
model maps how an agent is able to make the decision to invest, paying more in the first period
correlates to a higher valuation of education and only after the agent has constructed a lifetime
budget. This dynamic shows that for every person, there may exist a different value placed on
consumption versus education. There is a tradeoff of benefits for either period in the model,
more utility now and the same or less later, or less now and even more later. Given this tradeoff

23
concept, between native blacks and immigrant blacks, either will have a greater tradeoff than the
other. One will be able to trade more or less based off of a number of variables, however these
variables cannot all be shown in this model. I will test their significance in the regression model
based off of data.
3.1.1. Model Assumptions:
In researching ways to exemplify the situation in this study, I found that the two-period
consumption model was one of the most accurate in explaining the incentive of an agent to invest
as it shows the tradeoff that occurs when deciding whether or not to invest in a college degree
and additionally how much an agent is willing to spend. This tradeoff is essential to how an
agent makes the decision to invest. It is the general thought process of a student (or parent of a
student) who desires to earn a better wage in the future.
1. Education Comes from One Institution:
We do not make any distinction of options. There is only one institution of higher
education. This may be a key factor in real life since competition and elitism exist in the higher
education market both amongst students applying and amongst colleges themselves. Certain
colleges have advantages of legacy and endowment over others, factors which can affect what
jobs are available. We render all else constant with the Education.
2. Price of College is Fixed:
We assume that the tuition is one fixed price and does not accrue interest in the second
period. The agent pays only in the first period. The market for higher education is perfectly
competitive and thus does not depend on any factors of demand, shifts and shocks in the market.
Advancing the factor of tuition would have to include another factor of interest rates since many
have to borrow to afford college.

24
3. Amount of College Education is Fluid:
Since the price is just one number the amount of college you invest in is essentially a
matter of how much time you spend in college. We may simplify the amount into the
approximated number of years you spend in college.
4. College Guarantees Higher Wage:
We assume that wage is a function of the amount of college the agent invests in. Though
the benefit of college may be considered a given, there are multiple factors that can affect getting
a job and a higher paying job. Job searching takes time and money, major/specialization choice
is important significant in what jobs are available, grade earnings and GPA are factors in what
type of earnings are possible, and competition exists in the job market. By assuming that college
guarantees higher wage we eliminate the uncertainty bias that may exist in real life. Modeling
this bias would be complicated and involve more specific variables. It would take away from
showing how the basic situation evolves in the two-period model.
5. Income is Fixed in Both Periods:
The agent receives an income in both periods and incomes in both periods are an amount
that stays the same. It is an element of parental aid, assuming that the agent does not earn any
money in the first period and still receives this amount in the second period. These incomes are
separate from what the agent earns. This assumption solidifies that if an agent does not invest in
college they will have to depend on their parents’ income in the second period. In reality this
amount between the first and second period may change given the fact that the agent gets older
and many parents would be reluctant to spend the same amount of money to support the agent.
6. Two Periods Sum the Agent’s Entire Life:

25
There are only two periods in the agent’s life. The first is where he receives parental
support, consumes, and invests in education. The second is where he receives parental support,
works, and consumes. The agent dies after the second period, and there is no third period.
7. There is Only One Good Consumed in the Agent’s Life:
To simplify the situation of consumption and investment in education, there is only one
good that simply keeps the agent alive: bread. Bread is often considered a main sustaining
product, so this choice of variable is somewhat distinct however another variable of some type of
food could be used. The assumption makes it so bread is the only desire or aspiration to receive.
8. The Price of Bread is Subject to Perfect Competition:
A perfectly competitive bread market determines the price of bread in both periods. This
assumes that all firms selling bread are price takers and are thus subject to selling at the point of
equilibrium, where quantity demanded equals quantity supplied. There are no economic shifts or
external effects that can further affect the price of bread.
9. The Amount of Labor Provided is Fixed:
The second period includes a variable of labor units multiplied by an education-weighted
wage rate, an additional income after college. We want the labor to be a fixed amount since an
agent could fix the problem of not having more bread by simply working more, and that would
defeat the purpose of showing how education positively effects the amount of bread an agent can
buy in the second period.
10. The Agent Receives Utility Only From Bread:
The agent only consumes bread, thus her only source of utility is from bread. She has a
simple bread utility function: UB(B1, B2).

26
3.1.2. Model Explanation:
First, we look at the single agent, unmarked by or subject to a specific socioeconomic
class or financial standing. This is important in that it will provide transparency in the model and
show that this is a very common scenario in reality. The agent lives in two periods, the present
and future: P1 and P2. Since these two periods represent the agent’s entire life, we can assume
that the agent dies at the end of P2.
In the first period, P1, the agent has a consumption that consists of two goods: education
and bread: E and B respectively, representing their quantities. For P1 we denote these quantities
as E1 and B1. In this model, we consider E to be an investment and not so much a good, therefore
it does not have any utility for the agent. This single agent is faced with a tradeoff associated
with the two periods. Since we assume that utility only comes from bread, in order for the agent
to increase utility they must increase the amount of bread they consume. In this model education
acts as an investment from which an agent receives more income in P2. Thus there is a tradeoff
between first period education (less bread consumption) and increased second period income
(more bread consumption). This tradeoff describes an agent’s desire to increase his/her wage in
the future by obtaining a degree. Based on the assumption that college guarantees a higher wage
in the future, later in this section I will explain the function of this relationship.
There is no utility function for E since it will only be used in the first period and it does
not give utility for the agent. These two goods, education and bread, have different prices and we
will denote them as PE and PB. We know that the price of education is naturally much greater
than the price of bread, and by this we can describe the inequality with: PB<PE. Given this
assumption we can conclude that it is possible for an agent to buy and consume a higher quantity
of B1 than E1 in P1. Given the income Y1 we have the first period consumption model:

27
(1)
Y1=PEE1+PBB1
When one invests in higher education, the expectation is that they will achieve a higher
wage than they would have had they not invested. In reality there is no real multiplier for
education to wage but for this model we will assume that returns are guaranteed. We will
formulate a simple wage rate equation to exemplify this relation. We take W as the wage rate and
θ as an unknown parameter subject to the inequality θ>0. With this we have
(2)
W=θ*PEE1
Wage is a function of the price and quantity of education and the wage parameter:
W=f(θ, PE, E1). This defines the relationship between the amount of education in the first period
and the wage received in the second period. The first period education multiplies by the positive
parameter resulting in a positive relationship between education and wage. In the second period
the agent will have a job and have to supply a level of labor for which we use the variable L as
the units of labor. Now we can place the wage and labor together to create the earnings:
(3)
WL
This earning amount will be added to the second period along with income Y2. We know
that the only good in the second period is bread because the education from the first period acted
as an investment and multiplied into the wage rate. With these components we can construct the
second period consumption:
(4)
Y2+WL=PBB2

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3.1.3. Lifetime Budget Constraint:
Since there are two periods, we may expect that the agent will construct their
consumption decisions based off of both periods, their lifetime. We can model this by combining
both the first and second period budget constraints to make the lifetime budget constraint. To
begin we find the term that exists in both budget constraints. In these constraints, both PE and E1
are present (in the second period the terms exists in WL because W=θ*PEE1). We can then set
the second period budget constraint equal to one of them, PE, so that we may plug the equation
into the first period budget constraint. The resulting equation is as follows:
(5)
WL+Y2=PBB2
θ*PE*E1*L+Y2=PBB2
PE=(PBB2-Y2)/(E1Lθ)
Or
PE=((PBB2)/(E1Lθ))-((Y2)/(E1Lθ))
From here we plug in the value of PE into the first period budget constraint.
(6)
Y1=((PBB2)/(E1Lθ))-((Y2)/(E1Lθ))*E1+PBB1
And then we set the equation equal to E1:
E1=(Y1-PBB1)/((PBB2-Y2)/(E1Lθ))
E1=((Y1-PBB1)(E1Lθ)/(PBB2-Y2))
In this lifetime budget constraint E1 is a function of Y1, Y2, PE (substituted by (PBB2-
Y2)/(E1Lθ)), PB, θ, B1, and B2. Given this relationship between variables we can see how shifts in
the variables affect E1, whether it increases or decreases. When PB increases the numerator
decreases and the denominator increases thus decreasing E1 overall. We may explain this

29
decrease in E1 by understanding that the first period income must be shared between education
and bread, so if the price of bread increases and the agent desires the same utility (given that
education provides none), the agent must allocate more money for bread and less for education.
In order to evaluate what happens to E1 when PE increases we must refer to the terms with which
we substituted it in the last equation of sequence (5) and in the denominator of the second
equation of sequence (6). In both of these examples PE is (PBB2-Y2)/(E1Lθ), and since it is in the
denominator of the lifetime budget constraint in the second equation of sequence (6), if it
increases E1 decreases. We may explain this by understanding the classical economic model of
supply and demand in a perfectly competitive market. Firms selling the same goods in a specific
market are not influential enough to affect the equilibrium price, where quantity supplied (a
positive slope curve) meet quantity demanded (a negative slope curve). The theory tells us that
with an increase in price of a good, PE in this type of market, the quantity demanded, E1, will
decrease and quantity supplied subsequently decreases. In this model, if an agent has to pay more
for education in the first period that would constitute less income allocated for bread, and since
bread is the good that provides utility, an increase in PE would compromise the overall utility
maximization provided by UB(B1, B2). Given this affect of PE in decreasing E1, another variable
shift does the opposite. This is when the parameter for future wage increases. In the lifetime
budget constraint the last equation of sequence (6), the parameter θ appears in the numerator,
thus when it increases E1 increases. When θ increases, this constitutes an increase in the future
wage since θ is a multiplier for how much education an agent consumes in the first period. It is
an evaluative measure of how much value education brings to the agent in the form of increased
income in the second period, meaning more money to consume bread and receive utility. The
wage rate W directly depends on how much education an agent consumes in the first period

30
(equation (2)), thus the value of education increases when the wage/wage parameter increases.
We will see the graphical explanation of this shift further on in this chapter. Now that we have
the lifetime budget constraint, we may continue to the basic graphical representation.
On the x-axis we denote C1 for the consumption in the first period. On the y-axis we
denote C2 for the second period consumption. The budget constraint’s x-axis intercept is the
maximum amount of bread that the agent can purchase with income Y1 since this is the only
source of money in the first period. We signify this with Y1/PB. Any sacrifice in the maximum
amount of B1 consumed will directly correlate to an amount invested in E1 for the period because
the area between the origin and the x-axis intercept exemplifies the combinations of bread and
education. Since education is not necessarily consumed, we can visualize the addition of
education investment as a subtraction from the maximum amount of bread for income Y1. This
point represents the maximum amount of first period consumption if nothing were consumed
tomorrow.
The y-axis intercept represents the maximum amount of bread the agent can purchase
with the maximum amount of income in the second period. That maximum amount of income is
Y2 and WL. The amount expressed by the intercept would exist only with E1 at its maximum
amount in the first period; that is if the agent sacrifices all of her B1 for E1, consuming nothing.
For a visualization we know that since education in the first period exists as a
subtraction/tradeoff from the x-intercept bread maximum, Y1/PB, if all of Y1 is spent on E1, the
point on the graph would have to be at the origin/0 for C1 and (Y2+WL)/PB. Connecting a line
between Y1/PB on the x-axis and (Y2+WL)/PB on the y-axis we have the lifetime budget
constraint in graphic form. Just like the x-axis intercept, this point represents the maximum
amount of P2 consumption of nothing is consumed in P1.

31
Given this lifetime budget constraint and the agent’s bread utility function, UB(B1, B2),
we must expect her to maximize her lifetime utility, the most utility possible given her income.
This ultimately depends on her
bread utility function and the
indifference curves that correlate
with different levels of utility. At
any level of utility there exists an
indifference curve that contains a
number of combinations of B1 and
B2. Considering that the agent
cannot spend outside what they earn
in their lifetime, the indifference
curve should be in accord with the
lifetime budget constraint. We show
the maximum utility with the point of tangency between the indifference curve and the budget
constraint. We know this is the maximum because at lower levels of income, we can construct
parallel budget constraints and tangent indifference curves. At lower income levels the utility
maximums are lower than that of the lifetime budget constraint. Lower indifference curves’
endpoints can reach points on a higher budget constraint, meaning that at that given level of
utility, cheaper or more expensive combination of B1 and B2 exist. Given this fact, we place the
indifference curve at the furthermost point, tangent to the budget constraint, to achieve the
highest level of utility at a bargain.

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We assumed that the agent is a rational actor, and this assumption ultimately dictates how
she will make her decisions to maximize her personal economic interest, utility from bread. It is
important to note that had we not constructed a lifetime budget constraint, the agent would be
subject to two separate constraints and her utility function would be based on this premise. If the
agent had solely the first period budget constraint, no consideration or planning for the second,
and knowing that E1 does not give any utility, her utility function would be simplified to UB(B1).
We would then expect that as a rational actor, she would spend all of her Y1 income on the good
that gives her utility, bread. By adding the second budget constraint and creating a lifetime
budget constraint we allow for the agent to have the incentive to invest more on education given
her utility function that now includes both B1 and B2: UB(B1, B2).
3.1.4. Lifetime Budget Constraint Shift:
Considering the visual representation of the maximum utility for the lifetime budget
constraint, the graph shows the very basic representation of this scenario because it shows that
given both budget constraints all agents would choose the maximum utility. We really want to
model how people can maximize their bread consumption in the second period. In reality we
know that some people will spend more on education than others at the expense and sacrifice of
their first period utility, even given a lifetime budget constraint, for the further increase in bread
consumption in the second period. For reference, we can see that the point of maximum utility
for the lifetime budget constraint does not lie at the maximum amount of possible bread
consumption for period two, the y-intercept (Y2+WL)/PB. As stated before, in order to achieve
the maximum in the second period the agent must spend the entirety of Y1 on E1. This is
unrealistic because they would clearly starve in the first period; however, it is possible to model
how an agent can push toward the maximum in the second period. The model can move in a

33
manner that upwardly shifts the potential income in the second period based off of changes in the
value of a key variable in the model.
The wage rate W in the model is a function of E1. We show this with equation (2). The
positive parameter guarantees the return on investment in college. What happens if the wage rate
increases? More specifically, what happens when the parameter θ increases? The increase in the
parameter that multiplies education would in turn increase the possible income available in the
second period. This shifts the y-intercept, (Y2+WL)/PB to a higher value of (Y2+WL2)/PB. This
increase in value shifts the intercept upward making the budget constraint steeper. In other
words, the W(E1) of the y-intercept increases since W=θ*PEE1 and the negative slope has
increased. We can see that this
negative slope increase occurs in
equation (6), the higher θ increases
the denominators of the fractions
that multiply by PE. With this
increase in potential earnings, this
new budget constraint now has
points that lie further outside of the
original lifetime budget constraint.
To act in a rational manner the
agent can take advantage of this
new potential for more second
period bread consumption by changing her combination of first period B1 and E1 according to
her indifference curve. Given that the agent’s current indifference curve is tangent to the first

34
lifetime budget constraint, we can trace the indifference curve leftward and upward until it hits a
point on the new budget constraint. From this point the agent has a higher level of consumption
in the second period, a higher value on the C2 axis. Dropping the point down to the C1 axis, the
higher value in the second period consumption correlates to a lower amount of B1 and thus a
higher amount of E1. The opportunity cost of spending on B1 decreases. There is a greater
tradeoff than in the utility maximization of the first lifetime budget constraint, meaning that the
agent must sacrifice more utility in the P1 in order to gain more bread and utility in P2.
What makes this shift significant is the idea that this shift in budget constraints can be a
mental operation in reality. The increase in the parameter for wage can act as the mental
valuation of wage and education. Essentially an agent can merely believe that the wage has a
higher value for her. By viewing wage as more valuable, even if the wage parameter does not
actually increase, the agent can move to a point on the first lifetime budget constraint that is
closer to the second period maximum bread consumption. The benefit of this valuation method is
that the agent can operate from her maximum utility (her consumption correlated to the
augmented budget constraint), while the level of first period consumption would have correlated
to a lower level of utility (the upper ends of the maximum utility indifference curves for lower
incomes intercept the first lifetime budget constraint at points closer to the maximum
consumption for the second period, (Y2+WL)/PB).
Overall this model has shown how the valuation of wage can act as an incentive for more
investment in education. Further, as we consider education to be the determining variable in
future wage, the model has shown how this valuation of future wage rate can correlate to the
valuation of education, determining how much consumption one sacrifices and how much
education one invests in.

35
Considering the context, this theoretical framework showcases the situation in which the
native or immigrant black household invests in higher education. When the wage parameter
increases the value of education increases as well given that having a degree increases the
probability of gaining more income, consumption, and utility post-higher education. In this case
we expect the households (native and immigrant) will invest more in education based on the
increasing value of education (see Graph 1 in Appendix A). Results from the NSLF dataset
coupled with U.S. census data from 2000 relay that immigrant blacks makeup a significantly
higher relative proportion of the black population at higher education institutions than do native
blacks (Massey, Mooney, Torres, Charles 2007, Schmidley 2000). Thus based off of this two-
period model, immigrant blacks value education more than native blacks. The empirical chapter
will test the significance of multiple variables to accept or reject this conceptual hypothesis.
3.2. Consumption-Savings Model:
The consumption-savings model is a variation of the two-period model that shows specifically
how the decision to save or borrow in the first period affects potential wealth in the second
period. In this model we consider the borrowing to be for education. Based on this model,
borrowing for education involves a tradeoff for second period consumption in that borrowing
more in the first period reduces income in the second period due to an interest rate. The agent
must pay back in the second period what she borrowed in the first period with interest,
decreasing income, consumption, and utility for the second period. An increase in distinction is
crucial because it shows that if an agent saves more in the first period, they will have more
wealth in the second period. Given these effects the consumption-savings model is effective in

36
showing how education investment affect how agents value education, the central point of
measure for this study’s topic about immigrant and native blacks in higher education. Based on a
rising value of education (see Graph 1 in Appendix A) and the previous model we expect an
agent to invest more, thus this consumption savings model shows a situation where an agent
would be less inclined to invest.
3.2.1 Model Assumptions:
Agent’s Wealth Represents Parental Income:
We assume that the agent’s wealth in the first period is comprised of support from her
parents or guardians. We assume this because we will assume that she does not have a job before
and during college.
Tax Has Been Omitted:
We assume that tax is neither a necessary nor important factor to the model and what the
model represents in light of education investment.
Specific Goods Have Been Omitted:
We assume that the consumption variable summarizes how the agent spends her income,
thus we do not require the complication of prices and quantities of goods.
Utility Function is Unspecific and General:
Since specific goods have been omitted, the utility of the agent derives from a general
consumption of goods. By this we denote the lifetime utility function as U1.
Two Periods Sum the Agent’s Entire Life:
The agent lives for only two periods: the first where she saves and consumes, and the
second where she consumes. The agent dies after the second period.

37
Y1 is Equal to Y2:
The incomes for the first and second period are the same amount. This assumption
solidifies the concept that an agent may wish to increase consumption past what is automatically
given (parents’ incomes).
3.2.2. Model Explanation:
We can begin by establishing that in the first period an agent receives an income of Y1
and can either save or borrow to decrease or increase their consumption in the first period. When
an agent saves their income decreases by r. if they do not save r=0. With this we can construct a
first period budget constraint:
(7)
C1+S=Y1
When an agent borrows they have negative savings, inferring that instead of an agent taking
funds away from their income to have a positive savings, an agent does the opposite/negative of
that and adds more funds to increase first period consumption. In the equation (7) with a negative
savings, separating out C1 results in an increased income, which subsequently increases C1:
(8)
C1-S=Y1
C1=Y1+S
In the second period an agent receives an income of Y2. If the agent saved in the first period their
second period consumption C2 increases by the amount saved with interest, which we represent
with r. We can then construct a second period budget constraint:
(9)
C2=Y2+S(1+r)

38
If the agent borrowed in the first period, a negative savings, their second period consumption
would decrease having to pay back what they borrowed in the first period with interest (interest
rate r), decreasing their second period income of Y2.
(10)
C2=Y2+S(1+r)
C2-S(1+r)=Y2
3.2.3. Lifetime Budget Constraint:
In order to create the lifetime budget constraint we first set the second budget constraint
equal to the value that repeats in both budget constraints. In this case it is S, therefore:
(11)
C2=Y2+S(1+r)
S=(C2-Y2)/(1+r)
To get the lifetime budget constraint we plug in this S value for the S value in the first period
budget constraint:
(12)
C1+(C2-Y2)/(1+r)=Y1
Rearranging terms will result in the following arrangement for the equation:
(13)
C1+(C2/(1+r))=Y1+(Y2/(1+r))
The terms on the left of the equation describe the present value of lifetime consumption and the
terms on the right of the equation describe the present value of lifetime income. We understand
them as such because they include both the first period consumption/income and the second
period consumption/income discounted by (1+r), which shows the value in the present period.

39
The “present value” also correlates to the form of the equation, having been of the first period
budget constraint (7) before substituting S.
The x-axis variable is the current/first period consumption C1 and the y-axis variable is
the future/second period consumption C2. Deriving from the first period budget constraint, the
terms on the right of the lifetime budget constraint represents the present lifetime value of
income. This can also be defined as the first period consumption if nothing were consumed
tomorrow. We can show this by eliminating C2 from the lifetime budget constraint, giving us:
(14)
C1=Y1+(Y2/(1+r))
This value of C1 is the maximum amount that an agent can consume in the first period. Thus, on
the x-axis this represents the x-axis intercept. Essentially this is the entire amount of Y1 along
with the present value of Y2 (Y2 discounted by (1+r)). To find the y-axis intercept we can
conduct the equation in the same way, considering that eliminating C1 and setting the lifetime
budget constraint to C2 we would have the future value of lifetime income.
(15)
C2/(1+r)=Y1+Y2/(1+r)
C2=Y1(1+r)+(Y2(1+r))/(1+r)
C2=Y1(1+r)+Y2
This value of C2 represents the maximum amount an agent can consume in the second period i.e.
the amount that an agent could consume if nothing is consumed in the first period. This amount
is the entire Y1 with interest along with Y2.
By reconfiguring the equation from (10) into a simple linear equation (y=mx+b) we may
verify the above y-intercept and find the slope of the lifetime budget constraint. We begin by
making all equal to the y-axis term, C2.

40
(16)
C1+(C2/(1+r))=Y1+(Y2/(1+r))
C2/(1+r)=Y1+(Y2/(1+r))-C1
C2=(1+r)Y1+Y2-(1+r)C1
Looking at the resulting equation and recalling that m represents the slope in y=mx+b, we
can see that –(1+r) is the slope, multiplying by the x-axis term C1. If then we recall that b
represents the y-axis intercept, we see that (1+r)Y1+Y2 is the y-axis intercept for the lifetime
budget constraint, verifying the previous finding.
From our assumptions we know that the agent has a utility function of U1 that
corresponds to the agent receiving utility from the consumption of any good. The curve derives
all of the possible consumption combinations for that specific level of utility. In order for the
agent to achieve the maximum utility, she must choose the indifference curve that offers the most
utility that she can afford given her lifetime budget constraint. Subsequently, the maximum
utility received will define a situation where the agent spends all of her Y1 on consumption and
does not save nor borrow. Saving would increase her second period consumption and borrowing
would decrease the second period possible consumption. With no savings nor borrowing from
the first period, the agent does not have any additional amount to increase consumption nor any
amount to pay back and decrease consumption making the two periods unequal. Thus, for each
period, spending only income Y1 and Y2 maximizes lifetime consumption, compromising for
neither period. By the assumption that the utility function corresponds to consumption of any
good, we may draw an indifference curve (U1) tangent to the point where Y1 and Y2 convene.
They meet at a point that, given the assumption that both Y1 and Y2 are the same amount,
maximizes lifetime utility and consumption. This point is what we call the endowment point, the
point at which no borrowing or savings occurs. At this point we draw the furthermost

41
indifference curve tangent to the lifetime budget constraint, a curve wherein there is one
consumption combination
that reaches the lifetime
budget constraint. The
other combinations of this
indifference curve lie
outside of the agent’s
lifetime budget constraint
i.e. the agent cannot afford
them.
In this model, in
order for the agent to
consume more goods than what Y2 can purchase in the second period, the agent must sacrifice an
amount of her Y1. This amount acts as an investment, a tradeoff for goods in the first period for
gain in possible consumption in the second period. This cannot happen without a shift in value of
a variable within the model.
3.2.4. Increase in r:
What would happen to an agent’s first and second period consumptions if r increased?
Since we know r defines the payback of what the agent borrows in the first period, an increase in
r automatically increases that amount. Further, since we know that r also defines the interest rate
of savings, an increase in r correlates to an increase in possible gain in the second period. We can
show this graphically by seeing what directly happens to the x and y-axis intercepts and the slope
with this change. We can define the increased r as:

42
(17)
r2
Since we know that the slope is -(1+r), increasing r to r2 makes the slope decrease to a
more negative slope:
(18)
-(1+r2)
For the x-axis intercept in sequence (14), r is in the denominator. If r increases to r2, C1 decreases
since Y2 adds to a smaller amount. The decreased intercept now looks as such:
(19)
C1=Y1+(Y2/(1+r2))
For the y-axis intercept in sequence (15), (1+r) multiplies with Y1 and adds to Y2. If r
increases to r2, Y1 multiplies by a greater amount, (1+r2), increasing C2.
(20)
C2=Y1(1+r2)+Y2
The increase in r decreases the x-axis intercept and increases the y-axis intercept. since at
the endowment point, an agent neither saves nor borrows, they are not affected by any change in
r that would decrease or increase first or second period consumption/income. Given this
unchanged value, the budget
constraint with an increased r must
go through the same endowment
point where the value of Y1 meets
the value of Y2.
Based on the previous
model we would expect a
household to invest in education

43
given its value in providing more income in the second period. In this model the household must
borrow to attend school, an action that decreases income in the second period due to paying back
the borrowed funds for tuition in the first period. Since we know the tradeoff for first period
borrowing is a decreased second period income, and a decreased income means less consumption
of goods and utility, the indifference curve must then shift to maximize the utility at that point.
Borrowing for more than Y1 and then consuming less in the second period derives a point on the
new lifetime budget constraint. From this point, a tangent indifference curve signifies that at the
point, the maximum amount of utility can be obtained for that level. This new indifference curve
we will represent as U2. Tracing U2 to where it meets U1, this point represents the level of
borrowing where the household would enjoy a higher U1 utility given the U2 curve consumption
options. This point is outside the second lifetime budget constraint and, tracing a line to the x-
axis, would require a decreased amount of borrowing. We show all of these points within the
graph to the left.
Overall this model has exemplified a situation wherein the borrowing for education relays
a decreased second period income for a household to consume and gain utility. An increase in
the interest rate shows that a household would borrow even less.
3.2.5. Contextual Analysis:
In reference to the main topic and previous model, this consumption savings model
shows a situation wherein a native or immigrant black household may be less inclined to invest
in education. The previous model and research conducted by Avery and Turner (2012) had
shown that with an increasing value of education households would be inclined to invest in
education. This model provides an additional condition/variable of borrowing interest rate.

44
College tuition continually increases in price and there is increase in the amount of borrowing for
tuition in the U.S., two factors that would make increased borrowing an option and/or obstacle
for many households (see Graph 2 and Table 3 in Appendix A) (U.S. Department of Education
2015) (Avery and Turner 2012). Given the disproportion of immigrant and native black students
in higher education, this interest rate variable provides a possible insight to deterrence to
investment for native black households (Massey, Mooney, Torres, Charles 2007).

45
4.0. Empirical Work
4.0.1. Model Specification
The empirical work for this study is in the form of an OLS multiple-variable linear
regression. Through the research for this paper, multiple studies have conducted similar
regression models i.e. Massey, Mooney, Torres, and Charles (2007) and Thomas (2009). Given
this frequency, this regression is an appropriate way to test the hypothesis whether immigrant
blacks value education more than native blacks.
This type of regression tests a number of independent variables to try and explain a
relationship to a dependent variable. In a multiple regression the independent x variables are
those by which the dependent variable is affected. If this regression model were more simple, i.e.
only one independent variable and one dependent variable, then the results could be easily
graphed in a scatter plot style and we may see if there is a line of best fit. The multivariate linear
regression is not so simple to graph due to the many independent variables, complicating the
feasibility of showing an x-axis and thus we do not often see it modeled in such a way. I
introduce these points in anticipation of the presentation of the results of this study, which I will
display with tables that show the values of the results rather than a graph.
(1)
Confid=ß0+ß1Humcap+ß2Intind+ß3Mindist+ß4Wsocdist+ß5Fwagegrad+ß6Intchangeloan+E
Confid=f(Humcap, Intind, Mindist, Wsocdist, Fwagegrad, Intchangeloan)

46
4.0.2. Variable Table:
Variable Number Variable Name Definition Sign Justification/Function
Dependent
Variable
Confid Measure of a
student’s
confidence that
they will complete
college or farther
(graduate,
doctorate)
Valuation of
educational investment
1. Humcap Measure of how
much parents
have cultivated a
child’s human
capital
+ Human Capital,
variable determinant of
future wage
2. Intind Measure of how
much parents
have cultivated a
child’s intellectual
independence
+ Variable determinant of
future wage
3. Mindist Measure of
closeness/distance
to minority
classmates
+/- Performance
determinant
4. Wsocdist Measure of
closeness/distance
to white
classmates
+ Performance
determinant
5. Fwagegrad Dummy variable
whether student
graduates and
receives wage rate
premium (2003)
+ Education value
determinant
6. Intchangeloan Semester amount
($) of loan aid for
a student times
the increase in
federal loan
interest rate
- Borrowing/savings
determinant

47
4.1. Data:
As previously mentioned, the data used for this study comes from an extensive panel
dataset that followed a number of students over multiple years, from before freshman year of
college to senior year. By its extensive nature the National Longitudinal Survey of Freshmen
goes into detail about the specific demographics of each student, detailing their home life,
upbringing, high school culture, friends, environment, etc. All of these details are given through
numerical scores rather than continuous, because the data derives from survey results from the
students answering from a scale of least to greatest with 0-4, 1-5, or 0-10. Another important
factor to the organization of the data is that each variable displayed is a score that compiles the
answers of questions that are related to the variable name. In other words the student was asked
small number of related survey questions and then the results from those questions were
compiled to make the final score for the variable that describes the questions. An example is the
variable of Quality of Teaching; for a maximum final score of 14, the questions are Teacher
Interest 0-3, Teacher Preparation 0-3, Fairness of Discipline 0-3, and Felt Encouraged to think
Independently 0-5. It is by this criterion that the variables in the regression are defined, and I will
further explain each of the variables I use.
The goal of my study is to test if there is a significant difference between native and
immigrant black students in how they value education given the context of a higher proportion of
immigrant black students in selective higher education institutions. I used the extensive variety
of background data from one of the first sets of NLSF data (Wave 1) to conduct this regression.
This dataset comprises all of the personal data that explains each case’s personality profile, the
variables that describe his/her upbringing with respect to their parents, high school life,
neighborhood, exposure to negativity, and preliminary education experience. Based on the

48
research I conducted I am able to specify a number of variables from the NLSF dataset that could
best explain a difference between native and immigrant black students since the data contained in
this section of Wave 1 describes the nature of the students’ pre-college and personal life, the
information by which natives and immigrants differentiate outside of their skin color. Rooted in
this study is of course the subject of race/skin color. The subject is relevant because of the
agenda of higher education create a population of diversity, however as this study has detailed, a
dilemma arises because of the lack of differentiation between black students in the admissions,
and representation is disproportionate. This empirical regression thus aims to isolate differences
between native and immigrant black students, noting that how students view their education
(valuation) can and may be a significant factor in a student in respect to achieving a higher
education.
For this study, the data was sorted to solely the black population, and further separated
between immigrant black students (those with one or two immigrant black parents, or are
immigrant born) and native black students (those with two native black parents). There were 752
observations of native black students and 299 observations of immigrant black students.
4.2. Variables:
4.2.1. Dependent Variable:
Since the end result is to see if there is a difference in how native and immigrant black
students value education, the response variable must embody this idea of placing value on
education. Based in the field of educational economics, the studies conducted by Filippin and
Paccagnella (2012) outline a student’s crucial factors to economic outcomes. The article,
“Family Background, Self-Confidence, and Economic Outcomes” characterizes the role that self-
confidence plays in how people choose tasks. According to the study, people tend to choose

49
tasks (opportunities, risks, investments, etc) based on perceived ability, and this ability derives
from a person’s level of self-confidence. In addition to these points, the study notes that a
person’s socio-economic and family background affect both innate abilities and a person’s
perception of those abilities. Concluding that an “intergenerational transmission of beliefs” is the
main factor in the passing of major differences through generations, I found that this study was
crucial in supporting my effort to test for major differences between native and immigrant black
students in regards to how view their education. From their study, Filippin and Paccagnella
establish that a person’s upbringing (as a factor of early human capital formation) can affect their
set of beliefs about their ability, i.e. their self confidence; and, as noted in the study, self-
confidence holds a key role in a person’s decisions about investment in education. These points
point to the conclusion that self-confidence could be an effective measure of how a student
values their education, thus it is a possible response variable for the regression model in my
study.
We may now see self-confidence as a measure of the belief in one’s own ability to
perform or succeed. With respect to a specific opportunity, self-confidence relays the level of
belief that success can come from that opportunity. Within the context of this study, the
opportunity is a college career and, based off of the discussion in the theoretical section, the
college career is an investment. In this case, the educational investment depends heavily on the
belief in one’s own ability to succeed and achieve a higher wage by the end of college. Referring
to the theoretical models, I showed that a student/household would value education based on
promise of a future wage. This promise was a mathematical function, multiplying the amount of
first period education by a post-college wage rate. In reality, paying for college is only the initial
part of the value of college. Realistically the determinants of the profitability of one’s

50
educational investment are more related to one’s personal ability to take advantage of the
resources and perform to a high level. It is for this reason that I consider self-confidence as a
proper measure of how native black and immigrant black students value education. According to
Filippin and Paccagnella their backgrounds and upbringings are the major determinants of
shaping their beliefs about one’s own abilities, thus, connecting to the topic, this self confidence
would correlate to one’s belief in their abilities to succeed in college. This idea may also well
equate to a common concept in business economics: NPV or Net Present Value. This term
defines how we determine if an investment is worthwhile to make i.e. if it is profitable or not. In
this study we consider education to be an investment, however due to its nature, its benefit
cannot be mathematically calculated with an equation like financial investments can. The
formula will just aid in the comprehension of the concept in the context of education. The
formula for the NPV is as follows: NPV= Present Value of Benefit – Present Value of Cost.
Relating these terms to education, we may equate the present value of the benefit of education as
the student’s realistic view of her own future success after college, a projection of the best
possibilities. In this sense, self-confidence is an essential component to a student’s NPV of
education since their success heavily depends on their own actions. Belief in that action and how
they will conduct themselves is the assurance of their success.
The NLSF dataset subsequently has a variable labeled as the “index of respondent’s self-
confidence” and abbreviated as confid. This self-confidence variable is a measure of a specific
student’s belief about how far they will go in college and/or higher education (as some expect
further education past undergraduate). The variable itself is a summation of four different
questions that range from 0 to 10 creating a maximum range from 0 to 40. Since this section of
the data is a part of the background dataset in Wave 1, the student answered the question at the

51
beginning of their first year in college. The four questions are as follows: [what is the] likelihood
of finishing two years? … Likelihood of graduating from college? … Likelihood of post-
graduate education? and … Likelihood of finishing grad/prof degree? The score from 0 to 10
represents the student’s level of belief, the range correlates to a student who feels very unlikely
to very likely about heir ability to complete their education. A student with a self-confidence
score of 40 would be one who has strong beliefs about their ability to strive through
undergraduate, post-grad, and a graduate career. A student with a self-confidence score of 0
would be one who has weak to no belief that they will finish any school at all.
4.2.2. Independent Variables from Studies:
1. Humcap: Human Capital Formation
The independent variables must be those that can explain a difference in how native and
immigrant black students value education, and based off of the explanation of the dependent
variable, self-confidence, some of these variables are the differing background and upbringing
information that can affect the student’s formation of beliefs about their ability and profitability
of their education investment.
A substantial amount of studies in the realm of education and economic outcomes take
human capital into consideration. The bulk of studies note that human capital is one of the
essential factors in wage determination, educational outcomes, and economic success. We may
define it as a person’s stock of traits, knowledge, information, networks, connections, etc. that
aid in gaining economic value. Essentially human capital is someone’s intangible set of assets
that benefit financially. Most notoriously, Becker (1975) explains the importance of human
capital in context of education due to the accumulation of knowledge within public and private
institutions. He concludes that the difference in one’s human capital formation (having more or

52
having less) is a major factor in the persistence of income inequality. Considering this viewpoint
in the context of one’s upbringing, as previously noted, they are both decisive in forming how a
person makes decisions and succeeds in the course of their life. In support of this notion it is
important that when we think of human capital, we must not isolate educational institutions as
the sole provider of human capital. In the context of this study, one’s upbringing and family
background can be just as important a source of human capital as from an institution. The
economic literature regarding human capital and parents has centered on the human capital
investment framework, which is in terms of parents’ financial resources, and investment demand
i.e. correlating the wealth of the family, investment in education, and differences in educational
outcomes (Thomas 2009, Willis 1986). From this research we derive the independent variable
from the NLSF dataset, humcap.
This variable is an index of multiple measures of parental tactics to develop human
capital in the child’s upbringing. This variable is also comprised of three different periods of the
student’s life: at age 6, 13, and 18. This provides a dynamic range for the index variable
humcap. The majority of the measures are from 0-4 correlating to never/always or strongly
disagree/strongly agree. The other few measures are dummy variables from 0-1, which will be
signified. The measures are as follows: (age 6) parents read to the student (never-always),
parents helped with homework (never-always), parents took the student to the library (never-
always), parents put the student in summer school (dummy), parents put the student in summer
educational camp (dummy), parents put student in summer enrichment program (dummy), (age
13) parents helped with homework (never-always), parents took the student to the library (never-
always), parents put the student in a summer educational camp (dummy), parent participated in
PTA (never-always), (age 18) parents checked homework (never-always), parents helped with

53
homework (never-always), parents met with the student’s teachers (never-always), parents read
daily newspaper (never-always), parents read Sunday newspaper (never-very often), parents read
the weekly newspaper (never-very often), mother pushed the student to do their best (strongly
disagree-strongly agree), mother helped with schoolwork (strongly disagree-strongly agree),
mother encouraged the student when got poor grades (strongly disagree-strongly agree), father
pushed the student to do their best (strongly disagree-strongly agree), father helped with
schoolwork (strongly disagree-strongly agree), and father encouraged the student when got poor
grades (strongly disagree-strongly agree). The maximum score possible is 104 and the minimum
is 0.
2. Intind: Intellectual Independence
Via its definition, human capital can be understood as the culmination of many different
inputs, not solely the knowledge gained from school based on family income. However, in light
of the traditional economic sense of the term, Thomas (2009) finds that black children born to
immigrant parents are less likely to fall behind in school than black children born to native
parents. Additionally, Thomas (2009) finds that children born to the wealthiest immigrant black
parents fare better academically in the second generation than in the first, and children born to
poorer immigrant black parents fare better in the first generation than in the second. These
findings about immigrant black human capital refute the significance of parents’ finance and
ability to provide opportunities for their children in education since the poorer households would
automatically be ruled out as not able to succeed further. Through Thomas (2009) we see that
poorer first generation immigrant blacks do better than wealthier second generation. From this
we may conclude that wealth effects are not always consistent in terms of human capital, and as
Thomas’ study further concludes, factors of success can be developed within the household

54
based on a relation between parental characteristics/traits and the socio-economic status of the
household (Thomas 2009). These traits and characteristics are some of what this study aims to
see within the populations of native and immigrant black students in the NLSF dataset.
Another study by Raleigh and Kao (2010) addresses this similar topic of immigrant and
native parental traits with regards to education. This study specifically focuses on the educational
aspirations of parents for their children. Parents’ aspiration essentially defines how profitable
parents expect their children to be in their educational endeavors, how far they want them to go
and how proficient. On this topic Thomas (2009) concludes that there exists an overall advantage
in immigrants, noting that many studies have shown evidence that both immigrant parents and
children desire high educational attainment (Fuligini 1997). Raleigh and Kao (2010) sustain this
finding in the conclusion that immigrant parents are more optimistic about the educational path
of their children than native parents. With these findings about the effects of parental
encouragement we can derive an appropriate independent variable from the NLSF dataset for the
regression model. The variable most appropriate to fit the research was intind, a measure of how
much parents develop their child to think independently.
As with the previous independent variable, intind is an index of multiple measures of
parental tactics and behavior in the student’s upbringing. The same 0-4 range and three age
periods apply. The measures are as follows: (age 6) parents checked the student’s homework
(never-always), parents rewarded the student for good grades (never-always), (age 13) parents
checked the student’s homework (never-always), parents rewarded the student for good grades
(never-always), (age 18) mother thought the student should give in on arguments (strongly agree-
strongly disagree), mother pushed the student to think independently (strongly disagree-strongly
agree), mother explained reasons for decisions (strongly disagree-strongly agree), mother

55
thought the student should not argue with adults (strongly agree-strongly disagree), mother
thought she was always right (strongly agree-strongly disagree), mother told the student that they
would understand as an adult (strongly agree-strongly disagree), father thought the student
should give in on arguments (strongly agree-strongly disagree), father pushed the student to think
independently (strongly disagree-strongly agree), father explained reasons for decisions (strongly
disagree-strongly agree), father thought the student should not argue with adults (strongly agree-
strongly disagree), father thought he was always right (strongly agree-strongly disagree), and
father told the student that they would understand as an adult (strongly agree-strongly disagree).
When we think about intellectual independence, these measures relay the idea that a productive
higher education student must be focused while at the same able to think independently to
develop their own ideas, applying a self-reflection or self-critique. Given this idea these
measures in the NLSF variable are accurate in encompassing what it means to be intellectually
independent. A parent checking homework and encouraging good grades we may easily infer as
a push for the student to work harder and focus more. The parental behavior regarding the
student/child’s opinion and ability to voice said opinion, impart a practice for a child to rear a
sense of self worth in that their ideas are not shut down but encouraged. In education, expressing
one’s ideas and being focused are essential. In this case these measures of intellectual
independence can either help or hurt a student’s self-confidence about education, our measure for
how a student may value education.
3/4. Mindist and Wsocdist: Distance to Minorities, Distance to Whites
Hunt (2012) and Thomas (2009) both discuss the interactive effects on the probability of
completing a 12-year education and the likelihood of delayed schooling, respectively. This
derives from the interaction between immigrant students and native students. Hunt (2012) finds

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