Post on 27-Jan-2023
Parental Influence on Decisions to Attend Post-Secondary School
Parental Influence on American Youth’s Decisions to Attend Post-Secondary School
Nathan Anderson
Scott Sanders
Soc 405
Brigham Young University
Parental Influence on Decisions to Attend Post-Secondary School
Introduction
Over the past 30 years income inequality has been
increasing. The “Occupy Wall Street” movement and its anguish
toward the “1%” offers a perfect example to the ever widening
income gap and intensity around the topic. One substantial
reason for the discrepancy between incomes can be explained
through an individual’s return on their education. “In dollar
terms, 1973 college graduates earned 45 percent more than high
school graduates; by 1994 they earned 65 percent more, based on
real average hourly wages for college and high school graduates
(Baumol and Binder, 1997). As this income disparity continues to
grow, an emphasis on helping American youth attend postsecondary
school (PSS) or some form of college becomes increasingly
salient. Almost 20 years ago, President Bill Clinton, in his 1997
State of the Union address, urged Americans to enhance their
efforts in helping individuals obtain college degrees. He said,
Parental Influence on Decisions to Attend Post-Secondary School
“We must make the thirteenth and fourteenth years of education—at
least two years of college—just as universal in America by the
21st century as a high school education is today, and we must
open the doors of college to all Americans (Mathtech Inc.,
1998).” Now, 14 years into the 21st century we continue to search
for answers on how to “open the doors of college to all
Americans.” Recent research by Carnevale and Rose from the
Georgetown University Center on Education and the Workforce
(2011) found that from 1915 to 1980 the demand for college-
educated young people and the supply of college-educated young
Parental Influence on Decisions to Attend Post-Secondary School
people remained proportional to each other (3.1% growth in supply
per year to 2.9% growth in demand per year). Starting in 1990
however, the demand has begun to outpace the supply at 2.0%
growth in demand per year compared to only a 1.5% growth in
supply per year. If these trends continue, by the year 2025 the
income gap between college-educated Americans and high school
educated Americans will be 56% larger than it was in 1980 and 22%
larger than in 2010.
One of the first steps to understanding the issue of helping
Americans attend PSS is first understanding what factors
influence whether or not an individual chooses to attend college.
I propose that one factor which can have a significant effect on
an American youth’s decision to pursue PSS is the educational
achievements of their parents. Additionally, I examine the
relationship between the influence of a father attending college
versus a mother attending college can have on a child’s decision
to attend additional school.
Literature Review
Figure 1 Carnevale & Rose (2011, pg. 5-6)
Parental Influence on Decisions to Attend Post-Secondary School
Much of the research on college attendance patterns are
founded upon the “human capital” model proposed by Gary Becker.
“According to this theory, one decides to enroll in college as an
investment in future earning power (Mathtech Inc., 1998:1).” As
stated previously, individuals whom attend college have a higher
earning power which would also suggest that parents who attended
college would also have increased family incomes. This monetary
factor can aid in a young person’s college decision in a number
of ways. Cecillia Rouse (1994) found that higher family income
levels increase the probability of a high school student applying
for college. Scholars have also found that there are “persistent
patterns of stratification of college enrollments by income
(Manski, 1992, pg. 16).” Additional monetary factors such as
tuition cost, employment rates, and financial aid availability
can also have significant influences on individuals attending PSS
(Manski and Wise, 1983).
While the income in which parent’s return toward their
family may aid a child’s opportunity to continue their schooling
financially, it may be the example of increased earning power
their parents provide which makes the most significant
Parental Influence on Decisions to Attend Post-Secondary School
difference. Hossler and Maple (1993) find that parental
education levels have a stronger effect on a high school
student’s college plans than family income level. Rouse (1994)
also found that individual traits such as, parental education
levels, high school class rank, and achievement levels are of
significant importance in determining the likelihood a person
applies to college.
While most of the studies I have reviewed here provide a
correlation of a child’s college enrollment and parental
education levels, much of the research is becoming dated and may
not reflect current trends in contemporary America. Additionally,
one area of study that requires further explanation is if the
relationship of a father who attended PSS has a greater influence
on their child than if their mother attended PSS. In one study
conducted by Kohn, Manski, and Mundel (1976) they distinguish
between mother’s and father’s education levels but found
conflicting results. Utilizing two subsamples of surveys from two
different states, Kohn and team found that in one subset a
father’s education level had a greater effect on the likelihood
of college attendance, while the other subsample showed a
Parental Influence on Decisions to Attend Post-Secondary School
mother’s education level having a greater effect. I will further
explore this question by analyzing the moderating effect in which
parent’s education level, father’s education level, and mother’s
education level each play on a child’s PSS decision respectively
(See Figure 2). I hypothesize, in common with previous research
that an increase in parent’s education will result in an increase
likelihood of a high school senior choosing to attend at least
two years of college. I also hypothesize that a father who
attended college will have a greater influence on whether or not
a child attends college than if the mother attended college.
Figure 2
+High
SchoolSenior
AttendCollege
Parents/FathersCollege
Parental Influence on Decisions to Attend Post-Secondary School
Method
Sample
Because much of the research on this topic comes from sample
sets which are more than 15 years old, it was important that I
used a sample population from a recent data collection. I
accomplished this by selecting a data set from 2010, one of the
most recent made publicly available on 12th-grade students. My
sample set comes from the Monitoring the Future: A Continuing Study of
American Youth (12th-Grade Survey), 2010. This survey was conducted by a
team from the University of Michigan and is conducted on an
annual basis.
The data collection comprises of high school students during
the spring of their senior year. The surveys were distributed to
approximately 130 public and private schools and contain more
than 13,000 respondents. Schools were selected based upon
geographic location and area population density. In areas of high
population density more than one school was included in the
sampling design. 350 seniors were selected either by randomly
Parental Influence on Decisions to Attend Post-Secondary School
sampling classrooms or by some other random method that is
convenient for the school and judged unbiased.
One limitation to the data is that youth who have dropped
out of school prior to their senior year of high school were not
surveyed. This excludes a relatively small portion of the age
cohort, between 11 and 20 percent, but is of importance as this
group is likely not to pursue PSS and thus, if included could
adjust statistical conclusions.
Variables
The first variable, my dependent variable, “collegeplan”
comes from three survey questions. Each question read, “Suppose
you could do just what you’d like and nothing stood in your way.
How many of the following things would you want to do? (mark all
that apply)” Each question was then followed by one of the three
following answer choices, “Graduate from a two-year college
program”, “Graduate from a four-year college program”, “Attend
graduate or professional school after college”, asking the
respondents to either mark YES or NO. I took this data and
combined these questions into one variable in order to provide a
Parental Influence on Decisions to Attend Post-Secondary School
simple metric showing if the student “Planned to attend college,
YES or NO.” Because I was most concerned with whether or not the
student plans to attend any form of college and not how much
college they plan to receive, I created a dichotomous variable
with values of 0 (No) and 1 (Yes).
The main explanatory variables comprise from survey results
regarding parents’ education. Developed from questions asking
students to mark the highest level of education their father and
mother completed, ranging from high school dropout to graduate
school degree, I then recoded the variables in one of three ways.
The first way was to create a dichotomous variable for both
father’s education (feduc) and mother’s education level (meduc)
with values of 0 (no college) or 1 (attended college). For the
purposes of bivariate analysis I combined the father’s education
variable and the mother’s education variable into one variable
called pteduc. Again, as I explained with the variable
collegeplan, for the first research question I am concerned with
whether or not a parent attended college rather than how much
college any specific parent completed. To estimate the second
research question, the influence of a father’s education as
Parental Influence on Decisions to Attend Post-Secondary School
compared to a mother’s education on a child’s decision to attend
PSS, I created a variable separating the amount of college
education received for a mother or father individually. These
education levels ranged from “No College”, “Started College”,
“Four Year Degree”, and “Grad School”.
Finally, a number of control variables were included as a
part of the model. The first set of control variables included
demographic variables such as sex, race, (coded as separate dummy
variables White (0) Black (1) and White (0) Hispanic (1)), and
urban or rural home environment. The second set of control
variables was associated to school achievement, including the
students current G.P.A and Self-Intelligence, a variable
comprised from a question asking the student to rate how
intelligent he or she felt they were compared to their fellow
peers. One limitation to this study may be that no control for
family income is included in the model. This is because no data
was obtained through the survey on this topic.
Missing Data
Parental Influence on Decisions to Attend Post-Secondary School
Because my dataset surveyed more than 13,000 respondents
missing data is present as would be expected from a sample this
vast. However, due to the large sampling population the number of
missing cases was low, (approximately 8-15%) compared to the
total number of respondents. This allowed me to remove the
missing cases from my variables and still have a sufficient
number (12,000-11,000 cases) of valid data to run my statistical
test. In order to ensure that the results would be significant
across a generalized population, I compared missing data across
various racial groups as well as age and did not find any
systematic patterns of missing data.
Analysis
Statistical tests used to develop my conclusions involved a
series of cross tabulations with accompanying chi test and
logistic regression analysis. For my analysis of collegeplan and
pteduc I ran a cross tabulation because both variables were
categorical. This allowed me to gain percentages on the
likelihood of a student attending PSS. I also ran a chi test with
Parental Influence on Decisions to Attend Post-Secondary School
this tabulation to induce statistical significance from the
results.
The effects of the explanatory variables were estimated by
using a logistic regression. Because the dependent variable was
categorical and dichotomous, logistic regression allowed for
accurate regression outputs. The explanatory variables were
tested through a series of nested models, beginning with
demographic variables, followed by adding education achievement
variables and finally father’s college attendance and mother’s
college attendance were added over the final two nested models
respectively. Odds ratios were used to compare the effect of the
explanatory variable on the dependent variable.
When comparing father’s education level to mother’s
education level and their respective influence on a child’s
college decision, I did choose to utilizing a linear fit line to
present how an increase over the four levels of education (No
college, Started College, etc.) results in a change of mother and
fathers influence across levels. Cross tabulations as well
logistic regression we also used to help explain this question.
STAT 13 was used to calculate the statistical test.
Parental Influence on Decisions to Attend Post-Secondary School
Results
Table 1
AnticipatedPlan After High
School
Parents Attended College
No Yes TotalNo Plan to Attend
PSS or College824
11.08%327
5.57%1,1518.65%
Plan on AttendingPSS or College
6,61388.92%
5,54994.43%
12,16291.35%
Total 7,437100%
5,876100%
13,313100%
Table 1 shows the results of a cross tabulation between
collegeplan or anticipated college enrollment and pteduc or
parents actual college attendance. 11% or 824 of 13,313 student
respondents plan to follow their parent’s example and not attend
college. That contrasts with 5.5% or 327 students who plan on not
continuing their schooling even when one of their parents has
gone on to college before them. Additionally, students who do
have at least one parent who has attended college are six percent
more likely to plan on attending PSS than those students who have
no parent who has attended college. These statistics were
statistically significant according to the accompanying chi
Parental Influence on Decisions to Attend Post-Secondary School
squared test at a p value of .000 allowing for the rejection of
the null hypothesis and assuming the change is not a result of
chance.
The four nested logistic regression models are summarized in
Table 2. Each nested model was significant at a p value of .000.
Significant results were found for both primary independent
variables, father’s education and mother’s education, while
controlling for sex, race, urban/rural, G.P.A., and perceived
self-intelligence. The results indicate that a student whose
father attended at least some PSS is 1.53 times more likely to
attend PSS than a student who did not have a father attend
college. Similarly, there is a 1.51 times increased likelihood
that a student will attend college if their mother previously
attended college. These findings support the previous literature
on the topic and my first hypothesis that a student whose parents
attend college is more inclined to follow their parent’s example
and also attend college. Another significant result, which
requires additional research outside the scope of this article,
is the significantly increased likelihood of a female planning on
college than a male student.
Parental Influence on Decisions to Attend Post-Secondary School
Table 2 Odds Ration of American Youth’s College Plans
Variable Model 1 Model 2 Model 3 Model 4Demographics
Female 2.4*** 2.3*** 2.4*** 2.46***Black .71*** .91 .93 .91
Hispanic .936 1.26** 1.44** 1.56***Rural/Urban 1.13*** 1.1*** 1.1*** 1.1***
AchievementGPA 1.22*** 1.2*** 1.2***
Self-Intelligence 1.36*** 1.33*** 1.32***
ParentsEducationFather Educ. 1.77*** 1.53***Mother Educ. 1.51***
The results from nested model number four show a slight
positive association that a father’s college attendance has a
greater influence on a child’s college plan than a mother’s
college attendance. Additional tests in an effort to find
additional support for my second hypothesis, a father’s education
will have a greater influence on a youth’s decision to attend PSS
than a mother’s education, are consistent with the findings from
this regression analysis. The percentages gathered from a cross
tabulation, as presented in Figure 3 show that if a father did
not go to college than their son or daughter has an 11.73% chance
Parental Influence on Decisions to Attend Post-Secondary School
of not going to college as well, verses 11.7% change of a child
not going if their mother did not go.
Figure 3
Father Did Not Go Mother Did Not Go11.00%
11.10%
11.20%
11.30%
11.40%
11.50%
11.60%
11.70%
11.80%
11.90%
12.00%
Likelihood Child Will Not Attend
College
Parental Influence on Decisions to Attend Post-Secondary School
Figure 4
Father went to college Mother Went to college90.00%
92.00%
94.00%
96.00%
98.00%
100.00%
Like
liho
od Chi
ld W
ill
Atte
nd
Coll
ege
Figure 5
Parental Influence on Decisions to Attend Post-Secondary School
The results in Figure 4 also show a very slight change in
the likelihood a child will attend college based on a mother’s
verses father’s education. Figure 5 may help explain this slight
relationship by graphically representing the increase likelihood
of a child’s college attendance across the various levels of
education between a father and mother. The linear fit lines
remain almost even until “Four-Year Degree” in which a slight
separation is visible between mothers and fathers.
Finally, using the same control variables as in the logistic
regression models previously presented, but replacing feduc and
meduc (dichotomous variables) with variables taking into account
the level of college education obtained, the correlation
coefficients of the regression model indicate that a one unit
increase in the level of college education received for a father
results in a .18 change in the dependent variable, while a
mother’s increase in level of college education reports a
coefficient of .17. Both of these coefficients we statistically
significant at a p value of .000. The results from this and the
previous statistical tests find mild support for the second
hypothesis.
Parental Influence on Decisions to Attend Post-Secondary School
Conclusion
The scope of this paper has covered two basic questions
regarding influences that may “open the door” to American youth
in attending PSS. The first question was: How does a parent’s
college education moderate whether or not their child will
progress on after high school and pursue higher education. In
response to this question I have concluded that there is strong
statistical evidence that my hypothesis was correct in stating
that an increase in parental education has a positive effect on
the likelihood a child will attend college. This finding can lend
support to the Human Capital Theory in that youth may recognize
the benefits of a college education for their parents and choose
to similarly invest in their own human capital by attending PSS.
The second question researched analyzed whether or not a
father’s education obtainment has more influence on a child’s
education choice. Utilizing data from the 2010 Monitoring the Future
Survey, I found that there is indeed a slight positive correlation
that a father’s college attendance has more influence than a
Parental Influence on Decisions to Attend Post-Secondary School
mother’s college attendance, particularly if the father went on
to obtain a four-year degree.
The conclusions made from this study present one finding,
parental education, important in helping all Americans make
college a universal part of their educational experience. I
recommend, with support from this research on how parents’
education influences a child decision to go to college, that
parents, high school counselors, scholars, legislators, college
admissions departments, and other persons of prominent position
should provide special emphasis toward potential first generation
college students to ensure that in coming years the demand for
employees with higher education does not overly exceed the supply
of persons with a college degree.
Parental Influence on Decisions to Attend Post-Secondary School
References
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Policy, 7th edition, Fort Worth: The Dryden Press, 1997.
Carnevale, A., & Rose, S. (2011, June 26). The Undereducated
American. The Undereducated American. Retrieved April 17, 2014,
from http://cew.georgetown.edu/undereducated
Hossler, Don, and Maple, Sue. “Being Undecided about
Postsecondary Education.” Review of Higher Education 16:285
(1993).
Manski, Charles F. “Income and Higher Education.” Focus 14(3):14
(1992).
Manski, Charles F., and Wise, David A. College Choice in America.
Cambridge, Mass: Harvard University Press, 1983.
Mathtech, Inc., “Financial Aid Enrollment.” Ed.gov, 1998
http://www2.ed.gov/offices/OUS/PES/finaid/enroll98.pdf
Rouse, Cecilia Elena. “What to Do after High School: The Two-Year
versus Four-Year College Enrollment Decision.” In Choices and
Consequences: Contemporary Policy Issues in Education, Ronald G.
Ehrenberg, ed. Ithaca, NY: ILR Press, 1994