September 2, 2016
It’s now September, and in Champaign-Urbana and other cities and towns with major universities, that means the population has risen with the start of the fall semester. But how does the university population affect Champaign-Urbana’s overall statistical outlook? And how are college students counted for U.S. Census Bureau programs?
To answer the second question first, a major goal of Census programs is to count everyone where they live for the majority of the time. For students enrolled in residential colleges, that usually means in the community where their school is located, not at their family’s home address. Even if the student is at their home address at the time a Census form is completed, they should not be counted as living at that address unless they are actually a current, full-time resident there. So all total population figures, both counts and estimates, released by the U.S. Census Bureau for a given area should include the student body of any residential universities and colleges with the boundaries of that area, with some allowance for respondent error.
A large university population can impact a community’s overall statistical makeup. To start, let’s look at the university enrollment and total population. The table below shows population, enrollment, and student percentage of total population in several communities with large universities, and one community, Decatur, IL, with a similarly sized total population but with a much smaller university, for the sake of comparison.
Sources: U.S. Census Bureau; American Community Survey, 2010-2014 American Community Survey 5-Year Estimates, Table B01003; generated by CCRPC staff; using American FactFinder; (24 August 2016).; U.S. News & World Report. Higher Education. (2016). University of Illinois — Urbana-Champaign. (24 August 2016).; U.S. News & World Report. Higher Education. (2016). Indiana University — Bloomington. (24 August 2016).; U.S. News & World Report. Higher Education. (2016). Purdue University — West Lafayette. (24 August 2016).; U.S. News & World Report. Higher Education. (2016). University of Iowa. (24 August 2016).; U.S. News & World Report. Higher Education. (2016). University of Michigan — Ann Arbor. (24 August 2016).; U.S. News & World Report. Higher Education. (2016). Millikin University. (31 August 2016).; U.S. News & World Report. Higher Education. (2016). Virginia Tech. (31 August 2016).
Compared to the population percentages accounted for by the other major universities, Champaign-Urbana’s student percentage is actually relatively modest: at 36.2%, it’s a big portion of the total population, but for perspective, check out some of the other percentages. In Bloomington, IN and Lafayette, IN, students make up more than half the estimated populations of the cities. In Blacksburg, VA, Virginia Tech students account for nearly three-quarters of the estimated population. And on the other end of the spectrum, Decatur, IL, with its small university, has a student population percentage of only about 3%.
We hypothesize that the presence of these large universities will affect the statistical makeup of their communities: lower median ages and median incomes, higher poverty rates. We further hypothesize that larger student population percentages will have greater impacts. So let’s see, below, how these theories bear out.
Source: U.S. Census Bureau; American Community Survey, 2010-2014 American Community Survey 5-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (24-25 August 2016).
Compared to the national figure, all five comparison communities with large universities have lower estimated median ages, and the highest student percentages correspond with the lower estimated median ages. Bloomington, IN has the second-highest student percentage at 56.6% and the second-lowest median age of 23.5 (+/-0.2), while Blacksburg, VA has both the highest student percentage (72.3%) and the lowest median age (21.8, +/-0.2). But this trend is not consistent throughout the large university comparison communities. Lafayette, IN, home of Purdue University, has the third-highest student percentage at 55.4%, but its median age of 31.6 (+/-0.6), while lower than the national average, is the highest of the large university comparison communities. In contrast, Decatur, IL, which we predicted would not see major effects from its small university population, has a higher estimated median age than the United States as a whole.
Source: U.S. Census Bureau; American Community Survey, 2010-2014 American Community Survey 5-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (24-25 August 2016).
A low median income can be another indicator of a college or university town. Full-time students, both graduate and undergraduate, often have low household incomes, and a preponderance of student households can draw down the community-wide estimated median income.
The relationship between community-wide median income and student population percentage shows itself in much the same way as the median age relationship. Four of the university comparison communities have estimated median incomes below the national estimate. Bloomington, IN and Blacksburg, VA, with the two highest student percentages, have the two lowest estimated median incomes of the analyzed group. Lafayette, with the third-highest student percentage, has an estimated median income lower than the national figure, but not nearly as low as Bloomington, IN’s, despite their similar student percentages. Ann Arbor, MI has an estimated median income slightly higher than the national estimate. This goes against our first hypothesis – that a large student percentage will lead to a lower estimated median income – but not necessarily against our second, that a smaller student percentage will has lesser impacts than a larger one, since Ann Arbor’s student percentage is the lowest of the large university comparison communities. Decatur, IL’s estimated median income is lower than the national estimate – and very similar to Lafayette, IN’s, despite their very different student percentages.
Source: U.S. Census Bureau; American Community Survey, 2010-2014 American Community Survey 5-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (24-25 August 2016).
Poverty rate can be a complicated measure in any community, with or without a large college or university, because a community’s entire population is not necessarily measured when poverty is calculated. The Census Bureau’s list of “People Whose Poverty Status Cannot Be Determined” includes people in the following living situations: “institutional group quarters (such as prisons or nursing homes),” “college dormitories,” “military barracks,” “living situations without conventional housing (and who are not in shelters),” and “unrelated individuals under age 15.”
For the purposes of this blog post, the relevant group on that list is residents of college dormitories. Regardless of their level of income, residents of college dorms are not counted toward the poverty rate. This means that, although a large student population can have an effect on a community’s poverty rate, assuming that a segment of that population lives off-campus, the effect is less than it would have been if poverty calculations included dorm residents.
The poverty rates of Champaign, Urbana, and all five comparison communities with large universities are above the national rate: some, like Ann Arbor, MI’s 22.6% (+/-1.2) and Lafayette, IN’s 20.4% (+/-1.8) are relatively close to the national rate, while others, like Urbana’s 36.0% (+/-2.5), Bloomington, IN’s 39.0% (+/-1.5), and Blacksburg, VA’s 46.3% (+/-2.7) are more than double the national rate of 15.6% (+/-0.1). Bloomington and Blacksburg continue to carry our second hypothesis: they’re communities with larger student percentages showing the predicted impacts to a greater degree. But Lafayette undermines it again: with a very similar student percentage to Bloomington’s, it shows the predicted impact much less. And Decatur complicates the comparisons further, with its low student percentage and an estimated poverty rate that is also above the national estimate.
At this point, our first hypothesis is holding up for the most part, but our second is looking unsteady – and that’s because correlation does not imply causation. We can reasonably say that large universities and their student populations have some impact on the overall statistical makeup of the communities in which they’re located. But they’re not the only factor. Yes, a large student population can draw down the median age by forming a disproportionately large population of young adults. But a community with a high birth rate and a disproportionately large number of young children could have a similarly low median age. So, possibly, could a community in which a large percentage of the late middle-aged or elderly population had chosen to retire elsewhere and moved away, affecting the median age via absence. A large university is definitely not the only plausible reason for such a trend.
We could also present lists of alternate causes for lower estimated median incomes and higher poverty rates. They can often appear with large universities, and sometimes communities with larger universities have lower estimated median ages and incomes and higher poverty rates than communities with smaller ones. But high poverty rates, low estimated median incomes, and low estimated median ages also appear in communities without large universities, in all different degrees and combinations, because there are other factors at play.
The takeaway from this post? If a community with a large university has one of those statistical hallmarks, the student population can be said to account for some of it. But we can’t make sound, generalized predictions about a community’s estimated median age, estimated median income, or poverty rate based solely on whether or not there’s a university there, or attribute these factors solely to a university’s statistical impact. It’s not that simple.
*A brief public service announcement: we realize that our two datasets are not from the same year. The American Community Survey data is from the 2010-2014 5-Year Estimates dataset, and the university enrollment data, from U.S. News & World Report’s College Rankings and Reviews, is all dated 2016. This is a clear case of “do as we say, not as we do” – for the purposes of a loose analysis, we’re making the assumptions that enrollment at these universities has neither doubled nor seriously dropped in the last two years, and that the items taken from the ACS for each of these geographies have also made no hugely dramatic shifts. But don’t take the analysis in this post as having serious statistical rigor (it doesn’t), and if you’re attempting an analysis with serious statistical rigor, make sure your data periods match up.
 U.S. Census Bureau. (2016). “How the Census Bureau Measures Poverty.” (Accessed 29 August 2016).