Manajemen | Fakultas Ekonomi Universitas Maritim Raja Ali Haji 08832320109601312
Journal of Education for Business
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Race, Hispanic Ethnicity, and the Future of the
College Business Major in the United States
Karen Leppel
To cite this article: Karen Leppel (2001) Race, Hispanic Ethnicity, and the Future of the College
Business Major in the United States, Journal of Education for Business, 76:4, 209-215, DOI:
10.1080/08832320109601312
To link to this article: http://dx.doi.org/10.1080/08832320109601312
Published online: 31 Mar 2010.
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Race, Hispanic Ethnicity, and the
Future of the College Business
Major in the United States
KAREN LEPPEL
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Widener University
Chester, Pennsylvania
D
uring the 1970s and 1980s, undergraduate business education experienced great growth. While the total
number of undergraduate degrees in all
majors increased by 25% from
1970-71 to 1989-90, the number of
business majors more than doubled.
Between 1970-71 and 1987-88, bachelor’s degrees in business rose from
13.7% to 24.4%. After peaking in
1992-93, the number of business
majors started to decline, and by
1996-97 the number had fallen by
almost 12%. Business as a percentage
of bachelor’s degrees had declined to
19.3% in 1996-97 (U.S. Department of
Education, 1999b, Table 255).
Green (1992) attributed the business
major boom to several factors. First,
there was a shift in student values to
more materialistic goals. That shift was
probably due at least in part to job-market concerns triggered by the flood of
baby-boomer college graduates in the
early 1970s. Second, the increase in the
number of older students with focused
occupational concerns contributed to
the rising number of business majors.
Third, the number of minority students
earning undergraduate degrees increased at a faster rate than the overall
number of all students earning undergraduate degrees, and a disproportionate number of minority students
received business degrees. That phe-
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ABSTRACT. This article explores the
impact of race and Hispanic ethnicity
on the business major. Results of a survey show that, when other characteristics are held constant, Asians and nonHispanic Blacks are less likely and
Hispanics more likely to major in business than non-Hispanic Whites are. If,
for each demographic group, the high
school graduation rate, the percentage
of high school graduates attending 4year institutions, and the percentage of
students majoring in business remain
constant, an increase in the number of
business majors can be expected.
However, if Hispanics and non-Hispanic Blacks make socioeconomic
advances, the number of business
majors is likely to increase to a lesser
degree and may even decrease.
nomenon was probably partly the consequence of the improved business
opportunities promoted by civil rights
activism in the 1960s. Fourth, the number of undergraduate degrees earned by
foreign students grew considerably; a
large percentage of those degrees were
in business. Last, the movement of
women out of traditional female
careers, such as education, and into
business was another major contributor
to the boom.
Green (1992) suggested that the subsequent decline in the number of business majors was precipitated by several
circumstances. First, an improvement in
career opportunities and status for
teachers resulted in rising numbers of
education majors between 1986-87 and
1990-91. Second, a large proportion of
the potential population of older students already had attended college.
Third, the excesses of United States
businesses in the 1980s-including the
Savings and Loan bailout, junk bonds,
and jailing of insider traders-had
probably sullied the image of business
for students.
Numerous factors influence the
probability that students will choose a
business major. Among these factors
are race and Hispanic ethnicity. Consequently, the growing representation of
Asians, Blacks, and Hispanics in the
United States population will have an
impact on the number and proportion
of college students who choose a business major. In this article, I present
research estimating the relationship
between demographic characteristics
and choice of major. Then, using the
estimation results and projections of
the future demographic composition of
the United States population, I offer
some speculations on the future of the
business major.
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Method
Model
To predict a student’s probability of
choosing a particular field of study, I
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compared the utility level expected
from that field to the expected utilities
associated with other fields. Linear
functions were used as approximations
for indirect utility functions. For person
“a,” indirect utility associated with field
J was U, = Xa Pj + E,~, where Xa was
a vector of characteristics of the student,
pj was a set of vectors of parameters,
and E~~was a set of unobservable random error terms. To use maximum likelihood logit analysis, the random error
terms were assumed to be independent
with density function f(e) = exp(~){exp[-exp(-~)I
1.
Among the influential characteristics
were parents’ occupations. Having a
parent with the prestige associated with
a professional or executive occupation
may influence a student’s choice of
major. According to previous literature,
women are more likely to choose maledominated careers if their fathers have
high occupation levels than if their
fathers have low occupation levels (Betz
& Fitzgerald, 1987). Further, the mother’s influence as a role model is positively related to the nontraditionality of
the daughter’s college major choice
(Hackett, Esposito, & O’Halloran,
1989), and women whose mothers work
outside the home are more likely to
“aspire to higher-skill innovative and
prestigious jobs” than women whose
mothers are full-time homemakers
(Douvan, 1976).
Parents’ education can also affect
choice of major. Women are more likely
to choose male-dominated careers if
their fathers have high education levels
than if their fathers have low education
levels (Betz & Fitzgerald, 1987). In
addition, having highly educated parents
increases the probability of women
majoring in science, although it decreases the probability of men majoring in
science (Ware, Steckler, & Leserman,
1985). Further, students who are in their
family’s first generation of college attenders “are, in general, drawn to majors
that have explicit links to careers”
(Green, 1992).
How important a student thinks it is
to be very well off financially may also
affect choice of major. Students who
think financial status is very important
may be more likely to choose fields
such as business, which students per-
ceive as more lucrative. Making money
is very important to the business major
(Daymont & Andrisani, 1984).
If a student grew up in a household
with lower socioeconomic status and
less financial security, then, ceteris
paribus, that student may feel more
compelled to choose a field that is
expected to result in better job opportunities. This effect may be based both on
the student’s emotional need for financial security and on pressure from parents. Other researchers have found that
students from households with lower
socioeconomic status are more likely to
choose more lucrative fields of study
(Davies & Guppy, 1997).
In addition, general scholastic ability
may influence choice of major by determining how difficult, stressful, or
tedious the student finds the area. For
example, students with majors in science and engineering tend to have higher scores on quantitative standardized
tests (Paglin & Rufolo, 1990). In addition, brighter students have been found
to be more likely to enter more lucrative
fields (Davies & Guppy, 1997). Age
may have an impact on choice of major
as well. Older students are less likely to
enter more lucrative fields (Davies &
Guppy, 1997).
Society has traditionally encouraged
men and women to enter different
fields. Though social pressures in this
area are not as great as they have been in
the past, there is still evidence of considerable gender-related stereotyping in
job choice (Meier, 1991).
Race and Hispanic ethnicity may
also influence the student’s utility by
affecting his or her perception of the
social acceptability of the field and the
likelihood of succeeding in it. The
types of occupations chosen by Black
and White college men have been found
to differ (Slaney & Brown, 1983). Similarly, differences may occur in the
choice of college major based on race
and Hispanic ethnicity. There may also
be differences in choice of major based
on whether a student was born in the
United States. The high school dropout
rate for Hispanics is lower for those
born in the United States (National
Center for Education Statistics, 1999),
and such differences may extend to
choice of college major.
Data
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“.39
The data used in this study were
based on the 1990 survey of Beginning
Postsecondary Students (BPS). The survey was conducted by the National Center for Education Statistics (NCES) of
the U.S. Department of Education. The
survey followed a group of students
who began their postsecondary educational careers during academic year
1989-90. This research included only
students who were enrolled in courses
leading to the bachelor’s degree. Of
these students, 4,541 had complete
information on the variables examined.
For the major field of study, the academic disciplines were grouped into
four areas: (a) business, (b) humanities
and social sciences, (c) science and
engineering (which included mathematics and computer science), and (d)
“other majors.” Because of small cells
for the minorities, it was necessary to
group together as “other majors” the
following fields: education, health,
vocationalhechnical, and other technical/professional.
Variables used to capture the effects
of racial and ethnic differences were
BLKNHSP (non-Hispanic Black), HISPANIC, and ASIAN. (American Indian
and Alaska Native were omitted
because of small numbers.) To capture
the effects of not being a United States
citizen, the dummy variable FOREIGN
was included. Other variables included
were gender (FEMALE), age as of 31
December 1989 (AGE), high academic
ability (HIGHACAD), whether the student believed that being very well off
financially was very important
(WELLVI), socioeconomic status percentile (SES), whether the student’s
father’s occupation was categorized as
professional or executive (DOCC),
whether the student’s mother’s occupation was categorized as professional or
executive (MOCC), and whether the
student had a parent who had attended
college (PARCOLL). The variable
HIGHACAD indicated whether the student perceived him- or herself as above
average in academic ability. This variable was used instead of Scholastic
Aptitude Test scores because SAT
scores were available for only 29% of
the respondents.
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To understand the impact of race/ethnicity on choice of major, while controlling for variation in other variables, I
performed logit analysis using the CATMOD procedure of SAS. Based on the
CATMOD specification, the values of
the categorical variable FEMALE were
1 and -1 for females and males, respectively. The values of the other categorical variables were defined similarly.
The direction and statistical significance
are interpreted analogously to the typical 1,0 dummy variable classification.
The dependent variable was the log
of the odds of choosing one field of
study over another. In this particular
context, the dependent variable
[ln(Pa/Pb)]is the logarithm of the ratio
of the probability of selecting college
field “a” to the probability of selecting
the field of business. Letting CHOICE
represent that log, the empirical specification becomes
with the three other groups, I found that
(a) the percentage of females was higher, (b) the percentage of students who
considered themselves above average
academically was lower, (c) the percentage of students who considered
financial success to be very important
was higher, and (d) the percentage of
students whose fathers had professional
or executive occupations was lower. For
the Hispanics, compared with the other
three groups, (a) the percentage of students whose mothers had professional
or executive occupations was lower,
and (b) the percentage of students with
at least one parent with some college
was lower.
The logit estimation results presented
in Table 4 are interpretable as follows.
The three parameters listed for each
variable represent the estimated coefficient of that variable-(the b in equation (1))-for the log of the odds of
choosing the humanities and social sciences relative to business, the sciences
and engineering relative to business,
TABLE 1. Percentage Distribution of Major Fields by Racial/Ethnic
Groups
Business
Humanities and
social sciences
Science and
engineering
“Other
majors”
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(1) CHOICE = b, + b, FEMALE + b,
BLKNHSP + b, ASIAN + b, HISPANIC + b, FOREIGN + b, AGE +
b, HIGHACAD + b, WELLVI + b,
SES + b,, PARCOLL + b,, DOCC +
b,, MOCC.
Males
Full sample
Non-Hispanic Whites
Non-Hispanic Blacks
Asians
Hispanics
Females
Full sample
Non-Hispanic Whites
Non-Hispanic Blacks
Asians
Hispanics
21.9
21.8
23.2
13.8
31.0
30.2
29.6
22.2
45.9
32.2
30.6
30.6
32.3
32.1
27.6
17.4
18.0
22.2
8.3
9.2
18.9
18.6
19.4
18.1
25.3
37.0
38.1
29.7
31.4
34.5
14.3
12.9
19.4
31.4
16.1
29.7
30.4
31.5
19.1
24.1
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~
Resu Its
An examination of the percentage
distribution of major fields by raciayethnic groups showed differences among
demographic groups (see Table 1). In
particular, compared with non-Hispanic
Whites, Asians were less likely to major
in business, whereas nowHispanic
Blacks and Hispanics were more likely
to major in business. In addition, nonHispanic Blacks were less likely than
non-Hispanic Whites to major in the
humanities and social sciences. Further,
Asians and non-Hispanic Blacks were
more likely than non-Hispanic Whites to
major in science and engineering.
In Table 2, I provide the means of the
independent variables for the full sample and for the four race/ethnicity subgroups. For ease of interpretation, the
categorical variables in Table 2 were
assigned values of ones and zeroes.
(Note that this specification is different
from SAS’s CATMOD specification,
which is described in Table 3.) For the
non-Hispanic Black group, compared
TABLE 2. Means of IndependentVariables, by RaciallEthnic Group
Variable
Full
sample
Non-Hispanic
Whites
Non-Hispanic
Blacks
Asians
Hispanics
0.4907
0.5000
~~
FEMALE
AGE
0.5006
18.367
0.4920
18.370
0.6250
18.333
18.238
18.506
FOREIGN
0.0 167
0.0062
0.0341
0.1449
0.0690
HIGHACAD
0.55 12
0.5632
0.3636
0.5561
0.5575
WELLVI
0.4321
0.4094
0.6629
0.5374
0.4483
PARCOLL
0.7472
0.7509
0.6970
0.8178
0.6437
DOCC
0.5457
0.5593
0.3485
0.598 1
0.4598
MOCC
0.4490
0.4579
0.3826
0.4626
0.3333
SES
77.893
79.233
66.1 17
76.383
zy
zyx
67.316
Nore. For ease of interpretation, categorical variables were assigned values of zero and one. (Thus,
the mean of 0.5006 for the full sample for FEMALE implies that 50.06% of the observations in
the sample were female.) The specification differs from S A S S CATMOD specification (see Table
3), which is used in the remainder of the article.
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TABLE 3. Definitions of the IndependentVariables Used in the Logit
Estimation
FEMALE
BLKNHSP
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dummy variable equal to 1 for females and -1 for males
dummy variable equal to I for non-Hispanic Blacks and -1 other-
wise.
ASIAN
dummy variable equal to 1 for AsiansPacific Islanders and -1 other-
wise.
HISPANIC
dummy variable equal to 1 for Hispanics and -1 for non-Hispanics
AGE
age of student as of December 31, 1989.
HIGHACAD
dummy variable equal to 1 for students who consider themselves
above average in academic ability, and -1 for students who consider
themselves average or below average in academic ability
WELLVI
dummy variable equal to 1 for students who consider it very important to be “very well off financially,” and -1 for students who consider it somewhat important or not important to be very well off financially.
DOCC
dummy variable equal to 1 for students whose father has an occupation that is classified as professional or executive, and -1 otherwise
MOCC
dummy variable equal to 1 for students whose mother has an occupation that is classified as professional or executive, and -1 otherwise
PARCOLL
dummy variable equal to 1 if at least one of the student’s parents had
some college education, and -I otherwise
SES
socioeconomic status percentile of the student’s family; a composite
continuous variable ranging from 1 to 100, and capturing parents’
occupations, things in the home (dishwasher, VCR), and family
income
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Nore. The definitions of the categorical variables given here are based on SAS’s CATMOD specification and differ from those used in Table 2.
and “other majors” relative to business,
respectively. The results for the race and
ethnicity variables are examined after
the results for the other variables.
The estimation results showed that
foreign students were less likely to
choose humanities and social sciences
or science and engineering over business, and more likely to choose “other
majors” over business. Students from
families with higher socioeconomic status were more likely to choose humanities and social sciences over business,
and less likely to choose science and
engineering or “other majors” over
business. A “first-generation college
attended’ effect was seen; students who
had a parent who had attended college
were more likely to choose to major in
humanities and social sciences rather
than business. Students who had a par-
212
more likely to choose humanities and
social sciences or science and engineering over business and less likely to
choose “other majors” over business.
The logit estimation coefficients of
the Asian and non-Hispanic Black variables indicated that, when other variables were held constant, Asians and
non-Hispanic Blacks were less likely
than non-Hispanic Whites to choose a
business major over other fields. Hispanics, on the other hand, were more likely
than non-Hispanic Whites to choose a
business major over other fields.
The percentage of students with a
business major was slightly greater for
non-Hispanic Blacks than for non-Hispanic Whites (see Table 1). The logit
analysis indicated, however, that nonHispanic Blacks were less likely to
choose business majors. This apparent
paradox can be explained by the fact
that other characteristics related to
choice of major differed for the two
groups. More Whites than Blacks had
fathers with professional or executive
occupations, and more Whites perceived themselves as being above average in academic ability. Both of these
factors reduced the probability of
choosing a business major over either a
humanities/social
sciences
or
science/engineering major. In addition,
fewer Whites considered doing very
well financially to be very important, an
attitude that was directly related to the
odds of choosing a business major.
Also, Whites tended to have higher
socioeconomic status and a greater tendency to have a parent who had attended college than Blacks. These factors
reduced the probability of choosing
business over humanities/social sciences, but increased the odds of choosing business over science/engineering.
These findings imply that if Blacks
make socioeconomic and educational
advances, fewer of them would be
expected to major in business. The trend
is also evident in the data provided in
Table 5 . The probability of majoring in
business was higher for non-Hispanic
Blacks than for non-Hispanic Whites,
when those probabilities were evaluated
at the median characteristics for those
two groups. However, when both probabilities were evaluated at the median
characteristics for non-Hispanic Whites,
ent who had attended college were less
likely to choose science and engineering
over business. Students with fathers in
professional and executive occupations
were more likely to choose to major in
fields other than business. Students with
mothers in professional and executive
occupations were less likely to choose
science and engineering or “other
majors” over business.
Students who considered it very
important to do very well financially
were more likely to choose business
over any other category of major. The
same held for older students. Women
were more likely to choose humanities
and social sciences or “other majors”
over business and less likely to choose
science and engineering over business.
Students who considered themselves
above average in academic ability were
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the predicted probability of majoring in
business was lower for non-Hispanic
Blacks than for non-Hispanic Whites.
Compared with non-Hispanic Whites,
the percentage of students with a business major was considerably higher for
Hispanics (see Table 1). When socioeconomic status, parents’ education,
father’s occupation, and self-perceived
academic ability were examined, the
same conclusions held for Hispanics as
for non-Hispanic Blacks in comparison
TABLE 4. Multinomial Logit Estimation Results-Dependent
In[prob(field l)/prob(BUS)]
Variable:
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Fieldb
Variable
CONSTANT
FEMALE
BLKNHSP
ASIAN
HISPANIC
FOREIGN
AGE
HIGHACAD
WELLVI
SES
PARCOLL
DOCC
MOCC
with non-Hispanic Whites. Thus, if Hispanics make socioeconomic and educational advances, they too would become
less likely to major in business. However, the negative logit estimation coefficients indicated that they would remain
more likely than non-Hispanic Whites to
major in business. Again these ideas can
be seen as well by examining Table 5 .
The probability of majoring in business
was higher for Hispanics than for nonHispanic Whites, when those probabilities were evaluated at the median characteristics for those two groups. When
both probabilities were evaluated at the
median characteristics for non-Hispanic
Whites, the predicted probability of
majoring in business remained higher
for Hispanics than for non-Hispanic
Whites, but the gap was much smaller.
Relative to non-Hispanic Whites, a
lower percentage of Asian students had
a business major (see Table 1). The
characteristics of Asian students were
more similar to those of non-Hispanic
White students than were the characteristics of non-Hispanic Blacks and Hispanics. The most noteworthy discrepancy was in the percentage considering it
very important to do very well financially (53.7% for Asians versus 40.9%
for non-Hispanic Whites).
(1)
Humanities &
social sciences
0.0643
0.2245
0.2580
0.3978
-0.1606
-0.4062
-0.0142
0.1479
-0.4222
0.0082
0.0881
0.0842
0.0148
(2)
Science &
engineering
(0.1558)
(0.0136)**
(0.0291)**
(0.0347)**
(0.0357)**
(0.0572)**
(0.0054)**
(0.0137)**
(0.0139)**
(0.0010)**
(0.0179)**
(0.0164)**
(0.0144)
2.6742
-0.3095
0.3683
0.5748
-0.1305
-0.2805
-0.0907
0.3010
-0.4347
-0.0081
-0.0416
0.2220
-0.1064
(3)
“Other majors”
(0.1922)** 1.4876
(0.0154)** 0.3458
(0.0310)** 0.1229
(0.0357)** 0.1823
(0.0370)** -0.4454
(0.0552)** 0.3182
(0.0079)** -0.0538
(0.0154)** -0.1610
(0.0153)** -0.2537
(0.0010)** -0.0032
(0.0191)* -0.0740
(0.0183)** 0.0913
(0.0159)** -0.0614
(0.1544)**
(0.0149)**
(0.0303)**
(0.0379)**
(0.0422)**
(0.0491)**
(0.0056)**
(0.0149)**
(0.0150)**
(0.0010)**
(0.0184)**
(0.0178)**
(0.0158)**
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“he standard errors are in parentheses. ’There were 926 students with fields in business; 1,526 in
the humanities and social sciences; 1,019 in the sciences and engineering; and 1,070 in “other
majors.’’
*Statistically significant at the 5.00% level.
**Statistically significant at the 1.OO% level.
~~~
~~
~~
~
TABLE 5. Predicted Absolute Probabilities
Business
Males
Females
Humanities and
social sciences
Males
Females
Science and
engineering
Males
Females
“Other majors”
Males
Females
Based on median characteristics of own raciavethnic group”
Non-Hispanic Whites
Non-Hispanic Blacks
Asians
Hispanics
0.1322
0.253 1
0.1201
0.2255
0.1182
0.2072
0.1166
0.2101
0.3373
0.2480
0.2916
0.3 168
0.4723
0.3 180
0.4438
0.4625
0.4122
0.2854
0.4952
0.3858
0.1984
0.1258
0.2590
0.1936
0.1183
0.2136
0.093 1
0.07 19
0.2111
0.3491
0.1806
0.1337
0.1984
0.2600
0.2989
0.2 182
0.1183
0.0885
0.0724
0.0653
0.21 1 1
0.1694
0.1451
0.1237
Based on median characteristics of non-Hispanic Whites
Non-Hispanic Whites
Non-Hispanic Blacks
Asians
Hispanics
0.1322
0.0774
0.0562
0.1780
0.1182
0.0742
0.0564
0.1688
0.3373
0.3305
0.3 179
0.3293
0.4723
0.4965
0.4995
0.4892
0.4122
0.5036
0.5535
0.4274
“For all raciakthnic groups, predicted absolute probabilities were based on an individual who was 18 years old, was a US.citizen, had at least one parent with some college education, and had a mother who did not have a professionaUexecutive occupation. For all groups except the non-Hispanic Blacks,
the individual perceived himherself as being above average academically. For Asians and non-Hispanic Whites, the father had a professionaVexecutive
occupation; for Hispanics and non-Hispanic Blacks, the father did not. For Asians and non-Hispanic Blacks, the student considered it very important to
do very well financially; for Hispanics and non-Hispanic Whites, the student did not. For Asians and non-Hispanic Whites, the family’s socioeconomic
status was ranked at the 87th percentile; for non-Hispanic Blacks and Hispanics, the family’s socioeconomic status was at the 67th and 74th percentiles,
respectively.
MarcWApril2001
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Speculations for the Future
The Hispanic, Asian, and non-Hispanic Black populations in the United
States are all growing more rapidly than
the non-Hispanic White population. As
indicated, the probability of majoring in
different fields varies with race and ethnicity, as well as with other important
characteristics. Consequently, changes
in the racial and ethnic composition of
the United States can be expected to
have ramifications for the distribution of
majors in higher education.
To explore some possible future
trends, I performed some calculations.
The number X of persons that are traditionally-aged (18 to 24) college business majors in 4-year institutions can be
estimated as follows: For each demographic group i, let ai equal the number
of persons aged 18 to 24, bi equal the
high school graduation rate, ci equal the
percentage of high school graduates
attending 4-year institutions, and di
equal the percentage of students majoring in business in 4-year institutions.
Then, the number of college business
majors is estimated as the sum of the
products of the four terms as shown in
equation (2) (see Figure 1).
The total number Y of persons who
are traditionally-aged college students
(all majors) in 4-year institutions can be
estimated as Y = Ci ai bi ci. To estimate
the percentage of students in 4-year
institutions who are business majors, X
was divided by Y. The demographic
groups used in the calculations were
males and females from the four
racelethnic groups discussed in previous
sections of this article: non-Hispanic
Whites, non-Hispanic Blacks, Hispanics, and Asians. (The category American
Indian, Eskimo, and Aleut, which comprises less than 1% of the United States
population, was not included.)
The numbers of persons aged 18 to 24
(the ai terms) were obtained from the
U.S. Census Bureau (see Table 6). The
high school graduation rates (bi) and the
percentage of high school graduates
attending 4-year institutions (ci) were
obtained from the U.S. Department of
Education (see Table 7). The percentage
of students in 4-year institutions majoring in business (di) was estimated from
the data set used in the current study (see
Table 1). For ai and di, gender-specific
figures were available. For bi and ci, separate figures for males and females were
not available; hence, the overall figures
for both genders combined were used.
Projections for the future of the business major were made based on the
assumptions that the patterns regarding
high school graduation rates, attendance
rates at 4-year institutions, and rates of
choosing business as a major for the
various demographic groups are stable.
The estimated percentage of students in
4-year institutions majoring in business
was expected to increase from 20.76%
in 2000 to 20.83% in 2010. The number
of business majors in 4-year institutions
was expected to increase by 253,000
from 2,088,000 in 2000 to 2,341,000 in
2010, a 12.1% increase. The increase is
a result of growing numbers of Blacks
and Hispanics in the United States and
the higher incidence of business majors
in those two groups.
The aforementioned figures were
based on constant rates used to compute
the products. However, if Hispanics and
non-Hispanic Blacks make socioeconomic advances, the total number of
students majoring in business is likely
to increase less, because the proportions
of Hispanics and non-Hispanic Blacks
majoring in business are expected to
fall. Further, the total number of students majoring in business may actually
drop because, holding other characteristics constant, non-Hispanic Blacks (and
Asians) are less likely to major in business than are non-Hispanic Whites.
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FIGURE 1. Equation (2)
the number of
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the % of students in
(2) X = C , a i b i c i d i = ~
i
4-year institutions
majoring in business
TABLE 6. Population Projections: Persons Aged 18 to 24 by RacelEthnic Groupa
2000
Males
No.
(thousands)
Non-Hispanic Whites
Non-Hispanic Blacks
Hispanics
Asians
8,969
1,896
2,067
521
zy
2010
Females
%
No.
(thousands)
66.7
14.1
15.4
3.9
8,542
1,917
1,911
533
Males
%
No.
(thousands)
%
66.2
14.9
14.8
4.1
9,598
2,229
2,705
715
63.0
14.6
17.7
4.7
Females
No.
(thousands)
9,163
2,225
233 1
7 14
YO
62.6
15.2
17.3
4.9
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~~~
"U.S. Census Bureau. (2000). (NP-Dl-A) Projections of the Resident Population by Age, Sex, Race, and Hispanic Origin: 1999-2100 (Middle Series).
Issued January 13, 2000.
214
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TABLE 7. Percentages Graduating From High School and Attending
4-Year Higher Education Institutions by Race/Ethnic Group
High school graduates
Graduating from
high school (%)”
Non-Hispanic Whites
Non-Hispanic Blacks
Hispanics
Asians
0.902
0.814
0.628
0.942
attending 4-year
higher education institutions (%)b
0.47 1
0.424
0.305
0.542
aUu.S.Department of Education, National Center for Education Statistics. (1999, November).
Dropout Rates in the United States: 1998, Table A. bU.S.Department of Education, National Center for Education Statistics. (1997,October). Access to Postsecondary Education for the 1992 High
School Graduates, Table 2.
Summary and Conclusions
This research has used a national
level data set and logit analysis to
explore the impact of race and Hispanic
ethnicity on the probability of majoring
in business. It was found that though
non-Hispanic Blacks have a higher rate
of majoring in business than non-Hispanic Whites do, when other characteristics are held constant, non-Hispanic
Blacks are actually less likely to major
in business. Hispanics are more likely to
major in business than non-Hispanic
Whites are, and Asians are less likely to
major in business than non-Hispanic
Whites are.
Those demographic differences in
major choice, coupled with increasing
representation of non-Hispanic Blacks,
Hispanics, and Asians in the U.S. popu-
lation, have implications for the future
growth of the business major. If, for
each demographic group between 2000
and 2010, the high school graduation
rate, the percentage of high school graduates attending 4-year institutions, and
the percentage of students in 4-year
institutions majoring in business remain
the same as in the 1990s, an increase in
the number of busines majors can be
expected. However, if Hispanics and
non-Hispanic Blacks make socioeconomic advances, the number of business
majors is likely to increase less and may
even decrease.
REFERENCES
higher education. Social Forces, 75, 1417-1438.
Daymont. T. N., & Andrisani, P. J. (1984). Job
preferences, college major, and the gender gap
in earnings. Journal of Human Resources. 19,
408428.
Douvan, E. (1976). The role of models in
women’s professional development Psychology of Women Quarterly, I , 5-15.
Green, K. C. (1992).After the boom: Management
majors in the 1990s. New York: McGraw-Hill.
Hackett, G., Esposito, D., & O’Halloran, M. S .
(1989). The relationship of role model influences to the career salience and educational and
career plans of college women. Journal of
Vocational Behavior, 35, 164-180.
Meier, S. T. (1991). Vocational behavior, 19881990: Vocational choice, decision-making,
career development interventions, and assessment. Journal of Vocational Behavior, 39,
131-181.
Paglin, M., & Rufolo, A. M. (1990). Heterogeneous human capital, occupational choice, and
male-female earnings differences. Journal of
Labor Economics, 8, 123-144.
Slaney, R. B., & Brown, M. T. (1983). Effects of
race and socioeconomic status on career choice
variables among college men. Journal of Vocational Behavior; 23, 257-269.
U.S. Census Bureau. (2000). (NP-DI-A)Pmjections of the resident population by age,sex,
race, and Hispanic origin: 1999-2100 (Middle
Series). Issued January 13, 2000. Washington,
DC: Author.
U.S. Department of Education, National Center
for Education Statistics. (1997).Access to postsecondary education for the 1992 high school
graduates (Table 2). Washington, DC: Author.
U.S. Department of Education, National Center
for Education Statistics. (1998). Dropout rates
in the United States: 1998. Washington, DC:
Author.
U S . Department of Education, National Center
for Education Statistics. (1999a). Digest of education statistics. Washington, DC: Author.
U.S. Department of Education, National Center
for Education Statistics. (1999b).Dropout rates
in the United States: 1998 (Table A). Washington, DC: Author
Ware, N. C., Steckler, N. A., & Leserman, J.
(1985). Undergraduate women: Who chooses a
science major? Journal of Higher Education,
56. 73-84.
zyxwvu
Betz, N., & Fitzgerald, L. F. (1987). The career
psychology of women. Orlando, FL:Academic
Press.
Davies, S., & Guppy, N. (1997). Fields of study,
college selectivity, and student inequalities in
MarcWApril2001
215
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Race, Hispanic Ethnicity, and the Future of the
College Business Major in the United States
Karen Leppel
To cite this article: Karen Leppel (2001) Race, Hispanic Ethnicity, and the Future of the College
Business Major in the United States, Journal of Education for Business, 76:4, 209-215, DOI:
10.1080/08832320109601312
To link to this article: http://dx.doi.org/10.1080/08832320109601312
Published online: 31 Mar 2010.
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Race, Hispanic Ethnicity, and the
Future of the College Business
Major in the United States
KAREN LEPPEL
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Widener University
Chester, Pennsylvania
D
uring the 1970s and 1980s, undergraduate business education experienced great growth. While the total
number of undergraduate degrees in all
majors increased by 25% from
1970-71 to 1989-90, the number of
business majors more than doubled.
Between 1970-71 and 1987-88, bachelor’s degrees in business rose from
13.7% to 24.4%. After peaking in
1992-93, the number of business
majors started to decline, and by
1996-97 the number had fallen by
almost 12%. Business as a percentage
of bachelor’s degrees had declined to
19.3% in 1996-97 (U.S. Department of
Education, 1999b, Table 255).
Green (1992) attributed the business
major boom to several factors. First,
there was a shift in student values to
more materialistic goals. That shift was
probably due at least in part to job-market concerns triggered by the flood of
baby-boomer college graduates in the
early 1970s. Second, the increase in the
number of older students with focused
occupational concerns contributed to
the rising number of business majors.
Third, the number of minority students
earning undergraduate degrees increased at a faster rate than the overall
number of all students earning undergraduate degrees, and a disproportionate number of minority students
received business degrees. That phe-
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ABSTRACT. This article explores the
impact of race and Hispanic ethnicity
on the business major. Results of a survey show that, when other characteristics are held constant, Asians and nonHispanic Blacks are less likely and
Hispanics more likely to major in business than non-Hispanic Whites are. If,
for each demographic group, the high
school graduation rate, the percentage
of high school graduates attending 4year institutions, and the percentage of
students majoring in business remain
constant, an increase in the number of
business majors can be expected.
However, if Hispanics and non-Hispanic Blacks make socioeconomic
advances, the number of business
majors is likely to increase to a lesser
degree and may even decrease.
nomenon was probably partly the consequence of the improved business
opportunities promoted by civil rights
activism in the 1960s. Fourth, the number of undergraduate degrees earned by
foreign students grew considerably; a
large percentage of those degrees were
in business. Last, the movement of
women out of traditional female
careers, such as education, and into
business was another major contributor
to the boom.
Green (1992) suggested that the subsequent decline in the number of business majors was precipitated by several
circumstances. First, an improvement in
career opportunities and status for
teachers resulted in rising numbers of
education majors between 1986-87 and
1990-91. Second, a large proportion of
the potential population of older students already had attended college.
Third, the excesses of United States
businesses in the 1980s-including the
Savings and Loan bailout, junk bonds,
and jailing of insider traders-had
probably sullied the image of business
for students.
Numerous factors influence the
probability that students will choose a
business major. Among these factors
are race and Hispanic ethnicity. Consequently, the growing representation of
Asians, Blacks, and Hispanics in the
United States population will have an
impact on the number and proportion
of college students who choose a business major. In this article, I present
research estimating the relationship
between demographic characteristics
and choice of major. Then, using the
estimation results and projections of
the future demographic composition of
the United States population, I offer
some speculations on the future of the
business major.
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Method
Model
To predict a student’s probability of
choosing a particular field of study, I
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209
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compared the utility level expected
from that field to the expected utilities
associated with other fields. Linear
functions were used as approximations
for indirect utility functions. For person
“a,” indirect utility associated with field
J was U, = Xa Pj + E,~, where Xa was
a vector of characteristics of the student,
pj was a set of vectors of parameters,
and E~~was a set of unobservable random error terms. To use maximum likelihood logit analysis, the random error
terms were assumed to be independent
with density function f(e) = exp(~){exp[-exp(-~)I
1.
Among the influential characteristics
were parents’ occupations. Having a
parent with the prestige associated with
a professional or executive occupation
may influence a student’s choice of
major. According to previous literature,
women are more likely to choose maledominated careers if their fathers have
high occupation levels than if their
fathers have low occupation levels (Betz
& Fitzgerald, 1987). Further, the mother’s influence as a role model is positively related to the nontraditionality of
the daughter’s college major choice
(Hackett, Esposito, & O’Halloran,
1989), and women whose mothers work
outside the home are more likely to
“aspire to higher-skill innovative and
prestigious jobs” than women whose
mothers are full-time homemakers
(Douvan, 1976).
Parents’ education can also affect
choice of major. Women are more likely
to choose male-dominated careers if
their fathers have high education levels
than if their fathers have low education
levels (Betz & Fitzgerald, 1987). In
addition, having highly educated parents
increases the probability of women
majoring in science, although it decreases the probability of men majoring in
science (Ware, Steckler, & Leserman,
1985). Further, students who are in their
family’s first generation of college attenders “are, in general, drawn to majors
that have explicit links to careers”
(Green, 1992).
How important a student thinks it is
to be very well off financially may also
affect choice of major. Students who
think financial status is very important
may be more likely to choose fields
such as business, which students per-
ceive as more lucrative. Making money
is very important to the business major
(Daymont & Andrisani, 1984).
If a student grew up in a household
with lower socioeconomic status and
less financial security, then, ceteris
paribus, that student may feel more
compelled to choose a field that is
expected to result in better job opportunities. This effect may be based both on
the student’s emotional need for financial security and on pressure from parents. Other researchers have found that
students from households with lower
socioeconomic status are more likely to
choose more lucrative fields of study
(Davies & Guppy, 1997).
In addition, general scholastic ability
may influence choice of major by determining how difficult, stressful, or
tedious the student finds the area. For
example, students with majors in science and engineering tend to have higher scores on quantitative standardized
tests (Paglin & Rufolo, 1990). In addition, brighter students have been found
to be more likely to enter more lucrative
fields (Davies & Guppy, 1997). Age
may have an impact on choice of major
as well. Older students are less likely to
enter more lucrative fields (Davies &
Guppy, 1997).
Society has traditionally encouraged
men and women to enter different
fields. Though social pressures in this
area are not as great as they have been in
the past, there is still evidence of considerable gender-related stereotyping in
job choice (Meier, 1991).
Race and Hispanic ethnicity may
also influence the student’s utility by
affecting his or her perception of the
social acceptability of the field and the
likelihood of succeeding in it. The
types of occupations chosen by Black
and White college men have been found
to differ (Slaney & Brown, 1983). Similarly, differences may occur in the
choice of college major based on race
and Hispanic ethnicity. There may also
be differences in choice of major based
on whether a student was born in the
United States. The high school dropout
rate for Hispanics is lower for those
born in the United States (National
Center for Education Statistics, 1999),
and such differences may extend to
choice of college major.
Data
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“.39
The data used in this study were
based on the 1990 survey of Beginning
Postsecondary Students (BPS). The survey was conducted by the National Center for Education Statistics (NCES) of
the U.S. Department of Education. The
survey followed a group of students
who began their postsecondary educational careers during academic year
1989-90. This research included only
students who were enrolled in courses
leading to the bachelor’s degree. Of
these students, 4,541 had complete
information on the variables examined.
For the major field of study, the academic disciplines were grouped into
four areas: (a) business, (b) humanities
and social sciences, (c) science and
engineering (which included mathematics and computer science), and (d)
“other majors.” Because of small cells
for the minorities, it was necessary to
group together as “other majors” the
following fields: education, health,
vocationalhechnical, and other technical/professional.
Variables used to capture the effects
of racial and ethnic differences were
BLKNHSP (non-Hispanic Black), HISPANIC, and ASIAN. (American Indian
and Alaska Native were omitted
because of small numbers.) To capture
the effects of not being a United States
citizen, the dummy variable FOREIGN
was included. Other variables included
were gender (FEMALE), age as of 31
December 1989 (AGE), high academic
ability (HIGHACAD), whether the student believed that being very well off
financially was very important
(WELLVI), socioeconomic status percentile (SES), whether the student’s
father’s occupation was categorized as
professional or executive (DOCC),
whether the student’s mother’s occupation was categorized as professional or
executive (MOCC), and whether the
student had a parent who had attended
college (PARCOLL). The variable
HIGHACAD indicated whether the student perceived him- or herself as above
average in academic ability. This variable was used instead of Scholastic
Aptitude Test scores because SAT
scores were available for only 29% of
the respondents.
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To understand the impact of race/ethnicity on choice of major, while controlling for variation in other variables, I
performed logit analysis using the CATMOD procedure of SAS. Based on the
CATMOD specification, the values of
the categorical variable FEMALE were
1 and -1 for females and males, respectively. The values of the other categorical variables were defined similarly.
The direction and statistical significance
are interpreted analogously to the typical 1,0 dummy variable classification.
The dependent variable was the log
of the odds of choosing one field of
study over another. In this particular
context, the dependent variable
[ln(Pa/Pb)]is the logarithm of the ratio
of the probability of selecting college
field “a” to the probability of selecting
the field of business. Letting CHOICE
represent that log, the empirical specification becomes
with the three other groups, I found that
(a) the percentage of females was higher, (b) the percentage of students who
considered themselves above average
academically was lower, (c) the percentage of students who considered
financial success to be very important
was higher, and (d) the percentage of
students whose fathers had professional
or executive occupations was lower. For
the Hispanics, compared with the other
three groups, (a) the percentage of students whose mothers had professional
or executive occupations was lower,
and (b) the percentage of students with
at least one parent with some college
was lower.
The logit estimation results presented
in Table 4 are interpretable as follows.
The three parameters listed for each
variable represent the estimated coefficient of that variable-(the b in equation (1))-for the log of the odds of
choosing the humanities and social sciences relative to business, the sciences
and engineering relative to business,
TABLE 1. Percentage Distribution of Major Fields by Racial/Ethnic
Groups
Business
Humanities and
social sciences
Science and
engineering
“Other
majors”
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(1) CHOICE = b, + b, FEMALE + b,
BLKNHSP + b, ASIAN + b, HISPANIC + b, FOREIGN + b, AGE +
b, HIGHACAD + b, WELLVI + b,
SES + b,, PARCOLL + b,, DOCC +
b,, MOCC.
Males
Full sample
Non-Hispanic Whites
Non-Hispanic Blacks
Asians
Hispanics
Females
Full sample
Non-Hispanic Whites
Non-Hispanic Blacks
Asians
Hispanics
21.9
21.8
23.2
13.8
31.0
30.2
29.6
22.2
45.9
32.2
30.6
30.6
32.3
32.1
27.6
17.4
18.0
22.2
8.3
9.2
18.9
18.6
19.4
18.1
25.3
37.0
38.1
29.7
31.4
34.5
14.3
12.9
19.4
31.4
16.1
29.7
30.4
31.5
19.1
24.1
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~
Resu Its
An examination of the percentage
distribution of major fields by raciayethnic groups showed differences among
demographic groups (see Table 1). In
particular, compared with non-Hispanic
Whites, Asians were less likely to major
in business, whereas nowHispanic
Blacks and Hispanics were more likely
to major in business. In addition, nonHispanic Blacks were less likely than
non-Hispanic Whites to major in the
humanities and social sciences. Further,
Asians and non-Hispanic Blacks were
more likely than non-Hispanic Whites to
major in science and engineering.
In Table 2, I provide the means of the
independent variables for the full sample and for the four race/ethnicity subgroups. For ease of interpretation, the
categorical variables in Table 2 were
assigned values of ones and zeroes.
(Note that this specification is different
from SAS’s CATMOD specification,
which is described in Table 3.) For the
non-Hispanic Black group, compared
TABLE 2. Means of IndependentVariables, by RaciallEthnic Group
Variable
Full
sample
Non-Hispanic
Whites
Non-Hispanic
Blacks
Asians
Hispanics
0.4907
0.5000
~~
FEMALE
AGE
0.5006
18.367
0.4920
18.370
0.6250
18.333
18.238
18.506
FOREIGN
0.0 167
0.0062
0.0341
0.1449
0.0690
HIGHACAD
0.55 12
0.5632
0.3636
0.5561
0.5575
WELLVI
0.4321
0.4094
0.6629
0.5374
0.4483
PARCOLL
0.7472
0.7509
0.6970
0.8178
0.6437
DOCC
0.5457
0.5593
0.3485
0.598 1
0.4598
MOCC
0.4490
0.4579
0.3826
0.4626
0.3333
SES
77.893
79.233
66.1 17
76.383
zy
zyx
67.316
Nore. For ease of interpretation, categorical variables were assigned values of zero and one. (Thus,
the mean of 0.5006 for the full sample for FEMALE implies that 50.06% of the observations in
the sample were female.) The specification differs from S A S S CATMOD specification (see Table
3), which is used in the remainder of the article.
MarcWApril2001
211
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TABLE 3. Definitions of the IndependentVariables Used in the Logit
Estimation
FEMALE
BLKNHSP
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dummy variable equal to 1 for females and -1 for males
dummy variable equal to I for non-Hispanic Blacks and -1 other-
wise.
ASIAN
dummy variable equal to 1 for AsiansPacific Islanders and -1 other-
wise.
HISPANIC
dummy variable equal to 1 for Hispanics and -1 for non-Hispanics
AGE
age of student as of December 31, 1989.
HIGHACAD
dummy variable equal to 1 for students who consider themselves
above average in academic ability, and -1 for students who consider
themselves average or below average in academic ability
WELLVI
dummy variable equal to 1 for students who consider it very important to be “very well off financially,” and -1 for students who consider it somewhat important or not important to be very well off financially.
DOCC
dummy variable equal to 1 for students whose father has an occupation that is classified as professional or executive, and -1 otherwise
MOCC
dummy variable equal to 1 for students whose mother has an occupation that is classified as professional or executive, and -1 otherwise
PARCOLL
dummy variable equal to 1 if at least one of the student’s parents had
some college education, and -I otherwise
SES
socioeconomic status percentile of the student’s family; a composite
continuous variable ranging from 1 to 100, and capturing parents’
occupations, things in the home (dishwasher, VCR), and family
income
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Nore. The definitions of the categorical variables given here are based on SAS’s CATMOD specification and differ from those used in Table 2.
and “other majors” relative to business,
respectively. The results for the race and
ethnicity variables are examined after
the results for the other variables.
The estimation results showed that
foreign students were less likely to
choose humanities and social sciences
or science and engineering over business, and more likely to choose “other
majors” over business. Students from
families with higher socioeconomic status were more likely to choose humanities and social sciences over business,
and less likely to choose science and
engineering or “other majors” over
business. A “first-generation college
attended’ effect was seen; students who
had a parent who had attended college
were more likely to choose to major in
humanities and social sciences rather
than business. Students who had a par-
212
more likely to choose humanities and
social sciences or science and engineering over business and less likely to
choose “other majors” over business.
The logit estimation coefficients of
the Asian and non-Hispanic Black variables indicated that, when other variables were held constant, Asians and
non-Hispanic Blacks were less likely
than non-Hispanic Whites to choose a
business major over other fields. Hispanics, on the other hand, were more likely
than non-Hispanic Whites to choose a
business major over other fields.
The percentage of students with a
business major was slightly greater for
non-Hispanic Blacks than for non-Hispanic Whites (see Table 1). The logit
analysis indicated, however, that nonHispanic Blacks were less likely to
choose business majors. This apparent
paradox can be explained by the fact
that other characteristics related to
choice of major differed for the two
groups. More Whites than Blacks had
fathers with professional or executive
occupations, and more Whites perceived themselves as being above average in academic ability. Both of these
factors reduced the probability of
choosing a business major over either a
humanities/social
sciences
or
science/engineering major. In addition,
fewer Whites considered doing very
well financially to be very important, an
attitude that was directly related to the
odds of choosing a business major.
Also, Whites tended to have higher
socioeconomic status and a greater tendency to have a parent who had attended college than Blacks. These factors
reduced the probability of choosing
business over humanities/social sciences, but increased the odds of choosing business over science/engineering.
These findings imply that if Blacks
make socioeconomic and educational
advances, fewer of them would be
expected to major in business. The trend
is also evident in the data provided in
Table 5 . The probability of majoring in
business was higher for non-Hispanic
Blacks than for non-Hispanic Whites,
when those probabilities were evaluated
at the median characteristics for those
two groups. However, when both probabilities were evaluated at the median
characteristics for non-Hispanic Whites,
ent who had attended college were less
likely to choose science and engineering
over business. Students with fathers in
professional and executive occupations
were more likely to choose to major in
fields other than business. Students with
mothers in professional and executive
occupations were less likely to choose
science and engineering or “other
majors” over business.
Students who considered it very
important to do very well financially
were more likely to choose business
over any other category of major. The
same held for older students. Women
were more likely to choose humanities
and social sciences or “other majors”
over business and less likely to choose
science and engineering over business.
Students who considered themselves
above average in academic ability were
zyxw
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the predicted probability of majoring in
business was lower for non-Hispanic
Blacks than for non-Hispanic Whites.
Compared with non-Hispanic Whites,
the percentage of students with a business major was considerably higher for
Hispanics (see Table 1). When socioeconomic status, parents’ education,
father’s occupation, and self-perceived
academic ability were examined, the
same conclusions held for Hispanics as
for non-Hispanic Blacks in comparison
TABLE 4. Multinomial Logit Estimation Results-Dependent
In[prob(field l)/prob(BUS)]
Variable:
zyxwvutsrqp
Fieldb
Variable
CONSTANT
FEMALE
BLKNHSP
ASIAN
HISPANIC
FOREIGN
AGE
HIGHACAD
WELLVI
SES
PARCOLL
DOCC
MOCC
with non-Hispanic Whites. Thus, if Hispanics make socioeconomic and educational advances, they too would become
less likely to major in business. However, the negative logit estimation coefficients indicated that they would remain
more likely than non-Hispanic Whites to
major in business. Again these ideas can
be seen as well by examining Table 5 .
The probability of majoring in business
was higher for Hispanics than for nonHispanic Whites, when those probabilities were evaluated at the median characteristics for those two groups. When
both probabilities were evaluated at the
median characteristics for non-Hispanic
Whites, the predicted probability of
majoring in business remained higher
for Hispanics than for non-Hispanic
Whites, but the gap was much smaller.
Relative to non-Hispanic Whites, a
lower percentage of Asian students had
a business major (see Table 1). The
characteristics of Asian students were
more similar to those of non-Hispanic
White students than were the characteristics of non-Hispanic Blacks and Hispanics. The most noteworthy discrepancy was in the percentage considering it
very important to do very well financially (53.7% for Asians versus 40.9%
for non-Hispanic Whites).
(1)
Humanities &
social sciences
0.0643
0.2245
0.2580
0.3978
-0.1606
-0.4062
-0.0142
0.1479
-0.4222
0.0082
0.0881
0.0842
0.0148
(2)
Science &
engineering
(0.1558)
(0.0136)**
(0.0291)**
(0.0347)**
(0.0357)**
(0.0572)**
(0.0054)**
(0.0137)**
(0.0139)**
(0.0010)**
(0.0179)**
(0.0164)**
(0.0144)
2.6742
-0.3095
0.3683
0.5748
-0.1305
-0.2805
-0.0907
0.3010
-0.4347
-0.0081
-0.0416
0.2220
-0.1064
(3)
“Other majors”
(0.1922)** 1.4876
(0.0154)** 0.3458
(0.0310)** 0.1229
(0.0357)** 0.1823
(0.0370)** -0.4454
(0.0552)** 0.3182
(0.0079)** -0.0538
(0.0154)** -0.1610
(0.0153)** -0.2537
(0.0010)** -0.0032
(0.0191)* -0.0740
(0.0183)** 0.0913
(0.0159)** -0.0614
(0.1544)**
(0.0149)**
(0.0303)**
(0.0379)**
(0.0422)**
(0.0491)**
(0.0056)**
(0.0149)**
(0.0150)**
(0.0010)**
(0.0184)**
(0.0178)**
(0.0158)**
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zy
zyxwvut
zyxwvut
“he standard errors are in parentheses. ’There were 926 students with fields in business; 1,526 in
the humanities and social sciences; 1,019 in the sciences and engineering; and 1,070 in “other
majors.’’
*Statistically significant at the 5.00% level.
**Statistically significant at the 1.OO% level.
~~~
~~
~~
~
TABLE 5. Predicted Absolute Probabilities
Business
Males
Females
Humanities and
social sciences
Males
Females
Science and
engineering
Males
Females
“Other majors”
Males
Females
Based on median characteristics of own raciavethnic group”
Non-Hispanic Whites
Non-Hispanic Blacks
Asians
Hispanics
0.1322
0.253 1
0.1201
0.2255
0.1182
0.2072
0.1166
0.2101
0.3373
0.2480
0.2916
0.3 168
0.4723
0.3 180
0.4438
0.4625
0.4122
0.2854
0.4952
0.3858
0.1984
0.1258
0.2590
0.1936
0.1183
0.2136
0.093 1
0.07 19
0.2111
0.3491
0.1806
0.1337
0.1984
0.2600
0.2989
0.2 182
0.1183
0.0885
0.0724
0.0653
0.21 1 1
0.1694
0.1451
0.1237
Based on median characteristics of non-Hispanic Whites
Non-Hispanic Whites
Non-Hispanic Blacks
Asians
Hispanics
0.1322
0.0774
0.0562
0.1780
0.1182
0.0742
0.0564
0.1688
0.3373
0.3305
0.3 179
0.3293
0.4723
0.4965
0.4995
0.4892
0.4122
0.5036
0.5535
0.4274
“For all raciakthnic groups, predicted absolute probabilities were based on an individual who was 18 years old, was a US.citizen, had at least one parent with some college education, and had a mother who did not have a professionaUexecutive occupation. For all groups except the non-Hispanic Blacks,
the individual perceived himherself as being above average academically. For Asians and non-Hispanic Whites, the father had a professionaVexecutive
occupation; for Hispanics and non-Hispanic Blacks, the father did not. For Asians and non-Hispanic Blacks, the student considered it very important to
do very well financially; for Hispanics and non-Hispanic Whites, the student did not. For Asians and non-Hispanic Whites, the family’s socioeconomic
status was ranked at the 87th percentile; for non-Hispanic Blacks and Hispanics, the family’s socioeconomic status was at the 67th and 74th percentiles,
respectively.
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Speculations for the Future
The Hispanic, Asian, and non-Hispanic Black populations in the United
States are all growing more rapidly than
the non-Hispanic White population. As
indicated, the probability of majoring in
different fields varies with race and ethnicity, as well as with other important
characteristics. Consequently, changes
in the racial and ethnic composition of
the United States can be expected to
have ramifications for the distribution of
majors in higher education.
To explore some possible future
trends, I performed some calculations.
The number X of persons that are traditionally-aged (18 to 24) college business majors in 4-year institutions can be
estimated as follows: For each demographic group i, let ai equal the number
of persons aged 18 to 24, bi equal the
high school graduation rate, ci equal the
percentage of high school graduates
attending 4-year institutions, and di
equal the percentage of students majoring in business in 4-year institutions.
Then, the number of college business
majors is estimated as the sum of the
products of the four terms as shown in
equation (2) (see Figure 1).
The total number Y of persons who
are traditionally-aged college students
(all majors) in 4-year institutions can be
estimated as Y = Ci ai bi ci. To estimate
the percentage of students in 4-year
institutions who are business majors, X
was divided by Y. The demographic
groups used in the calculations were
males and females from the four
racelethnic groups discussed in previous
sections of this article: non-Hispanic
Whites, non-Hispanic Blacks, Hispanics, and Asians. (The category American
Indian, Eskimo, and Aleut, which comprises less than 1% of the United States
population, was not included.)
The numbers of persons aged 18 to 24
(the ai terms) were obtained from the
U.S. Census Bureau (see Table 6). The
high school graduation rates (bi) and the
percentage of high school graduates
attending 4-year institutions (ci) were
obtained from the U.S. Department of
Education (see Table 7). The percentage
of students in 4-year institutions majoring in business (di) was estimated from
the data set used in the current study (see
Table 1). For ai and di, gender-specific
figures were available. For bi and ci, separate figures for males and females were
not available; hence, the overall figures
for both genders combined were used.
Projections for the future of the business major were made based on the
assumptions that the patterns regarding
high school graduation rates, attendance
rates at 4-year institutions, and rates of
choosing business as a major for the
various demographic groups are stable.
The estimated percentage of students in
4-year institutions majoring in business
was expected to increase from 20.76%
in 2000 to 20.83% in 2010. The number
of business majors in 4-year institutions
was expected to increase by 253,000
from 2,088,000 in 2000 to 2,341,000 in
2010, a 12.1% increase. The increase is
a result of growing numbers of Blacks
and Hispanics in the United States and
the higher incidence of business majors
in those two groups.
The aforementioned figures were
based on constant rates used to compute
the products. However, if Hispanics and
non-Hispanic Blacks make socioeconomic advances, the total number of
students majoring in business is likely
to increase less, because the proportions
of Hispanics and non-Hispanic Blacks
majoring in business are expected to
fall. Further, the total number of students majoring in business may actually
drop because, holding other characteristics constant, non-Hispanic Blacks (and
Asians) are less likely to major in business than are non-Hispanic Whites.
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FIGURE 1. Equation (2)
the number of
zyxw
the % of students in
(2) X = C , a i b i c i d i = ~
i
4-year institutions
majoring in business
TABLE 6. Population Projections: Persons Aged 18 to 24 by RacelEthnic Groupa
2000
Males
No.
(thousands)
Non-Hispanic Whites
Non-Hispanic Blacks
Hispanics
Asians
8,969
1,896
2,067
521
zy
2010
Females
%
No.
(thousands)
66.7
14.1
15.4
3.9
8,542
1,917
1,911
533
Males
%
No.
(thousands)
%
66.2
14.9
14.8
4.1
9,598
2,229
2,705
715
63.0
14.6
17.7
4.7
Females
No.
(thousands)
9,163
2,225
233 1
7 14
YO
62.6
15.2
17.3
4.9
zyxwvutsr
~~~
"U.S. Census Bureau. (2000). (NP-Dl-A) Projections of the Resident Population by Age, Sex, Race, and Hispanic Origin: 1999-2100 (Middle Series).
Issued January 13, 2000.
214
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TABLE 7. Percentages Graduating From High School and Attending
4-Year Higher Education Institutions by Race/Ethnic Group
High school graduates
Graduating from
high school (%)”
Non-Hispanic Whites
Non-Hispanic Blacks
Hispanics
Asians
0.902
0.814
0.628
0.942
attending 4-year
higher education institutions (%)b
0.47 1
0.424
0.305
0.542
aUu.S.Department of Education, National Center for Education Statistics. (1999, November).
Dropout Rates in the United States: 1998, Table A. bU.S.Department of Education, National Center for Education Statistics. (1997,October). Access to Postsecondary Education for the 1992 High
School Graduates, Table 2.
Summary and Conclusions
This research has used a national
level data set and logit analysis to
explore the impact of race and Hispanic
ethnicity on the probability of majoring
in business. It was found that though
non-Hispanic Blacks have a higher rate
of majoring in business than non-Hispanic Whites do, when other characteristics are held constant, non-Hispanic
Blacks are actually less likely to major
in business. Hispanics are more likely to
major in business than non-Hispanic
Whites are, and Asians are less likely to
major in business than non-Hispanic
Whites are.
Those demographic differences in
major choice, coupled with increasing
representation of non-Hispanic Blacks,
Hispanics, and Asians in the U.S. popu-
lation, have implications for the future
growth of the business major. If, for
each demographic group between 2000
and 2010, the high school graduation
rate, the percentage of high school graduates attending 4-year institutions, and
the percentage of students in 4-year
institutions majoring in business remain
the same as in the 1990s, an increase in
the number of busines majors can be
expected. However, if Hispanics and
non-Hispanic Blacks make socioeconomic advances, the number of business
majors is likely to increase less and may
even decrease.
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