Washington, DC, July 20, 2021
For the past 14 years, Sallie Mae’s How America Pays for College report has surveyed college students and parents of undergraduate students about their attitudes toward higher education and how they are paying for it. The research examines families’ attitudes toward the value of a college education, as well as their key considerations about what school to attend and how to pay for that education.
Despite the pandemic, American families continued to value and invest in higher education, in large part due to their belief that college yields new opportunities and higher earnings, and is integral to the American Dream.
The pandemic did not change how families approached covering the cost of college. Despite a 12% decrease in reported education costs for AY 2020–21, families used\ tried-and-true strategies and relied on sources of funding in similar ways as reported in previous years of How America Pays for College.
The proportion of families applying for federal financial aid by submitting the FAFSA® decreased again this year. The top reason for not applying is a perception that they wouldn’t qualify for any aid. Similarly, many students didn’t apply for scholarships because they didn’t think they’d receive one. Exploring and addressing families’ rationales for not taking advantage of these funding sources may encourage them to apply and not miss out on valuable free aid. Many families used borrowed funds to bridge the gap between the college bill and money that they won’t have to repay. This year, there’s an increase in the proportion of families who are reporting that they are making education loan payments while the student is still in school. This strategy will help many families get a jump start on paying down their college debt.
Cost remains a critical consideration for the majority of families when they select the school their student will attend. However, fewer than half of families are discussing anticipated outcomes of education: the total cost of education, the need for education beyond undergraduate to achieve career goals, or the starting salaries for the student’s selected field of study. As more information and tools become available, we encourage families to consider these factors as they begin their college journeys.
One of the major changes in the education experience brought on by the pandemic is online learning. Even though most students are eager to get back to campus, many, particularly from Black and Hispanic families, are embracing this new learning mode. The pandemic may serve as a catalyst for innovation to enhance how colleges and universities deliver education to the many communities they serve, and it may be a driving force in creating more equity in higher education.
For additional analysis, visit Salle Mae.
About this Study
Sallie Mae has again partnered with Ipsos, a global to conduct this study. How America Pays for College 2021 reflects the results of online interviews Ipsos conducted, in English, with:
- 985 parents of children ages 18-24 enrolled as undergraduate students
- 1,000 undergraduate students ages 18-24
The research was fielded between April 8 and May 4, 2021.
Dollar and proportional amounts in this report are averages that reflect composite representations intended to illustrate how the “typical” family pays for college. The composite is a computed formula that spreads individual responses across all survey respondents.
Low-income households are defined as those with annual income of less than $35,000; middle-income as those with annual income from $35,000 to less than $100,000; and high-income as those with annual income of $100,000 or more. Geographic regions discussed mirror those used by the U.S. Census Bureau.
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The sample for this study was randomly drawn from Ipsos’ online panel, partner online panel sources, and “river” sampling and does not rely on a population frame in the traditional sense. Ipsos uses fixed sample targets, unique to the study, in drawing sample. The sample design was a disproportionate stratified sample of parents of college students and college students. After a sample has been obtained, Ipsos calibrates respondent characteristics to be representative of the U.S. Population using standard procedures such as raking-ratio adjustments. The source of these population targets is 2016 American Community Survey data. The sample was stratified by additional variables, such as region and student enrollment status.
To correct for the disproportionate stratified sample, both samples were weighted using a statistical technique called raking, in which all of the population marginal profiles of interest are replicated in the sample. The sample of parents was weighted by gender, age, race/ethnicity, region, education and by college information (region, size and type). The sample of students was weighted by gender, age, race/ethnicity, region, and by college information (region, size and type). All of the demographic profiles used for both parents and students in the weights were sourced from the Current Population Survey (CPS). The National Center for Educational Statistics provided additional data for the college information weights.
Bayesian Credibility Intervals
The calculation of credibility intervals assumes that Y has a binomial distribution conditioned on the parameter θ\, i.e., Y|θ~Bin(n,θ), where n is the size of our sample. In this setting, Y counts the number of “yes”, or “1”, observed in the sample, so that the sample mean (y ̅) is a natural estimate of the true population proportion θ. This model is often called the likelihood function, and it is a standard concept in both the Bayesian and the Classical framework. The Bayesian 1 statistics combines both the prior distribution and the likelihood function to create a posterior distribution. The posterior distribution represents our opinion about which are the plausible values for θ adjusted after observing the sample data. In reality, the posterior distribution is one’s knowledge base updated using the latest survey information. For the prior and likelihood functions specified here, the posterior distribution is also a beta distribution (π(θ/y)~β(y+a,n-y+b)), but with updated hyper-parameters.
Our credibility interval for θ is based on this posterior distribution. As mentioned above, these intervals represent our belief about which are the most plausible values for θ given our updated knowledge base. There are different ways to calculate these intervals based on π(θ/y). Since we want only one measure of precision for all variables in the survey, analogous to what is done within the Classical framework, we will compute the largest possible credibility interval for any observed sample. The worst case occurs when we assume that a=1 and b=1 and y=n/2. Using a simple approximation of the posterior by the normal distribution, the 95% credibility interval is given by, approximately 2.5.
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