Indebted Beginnings Read Online Free

[Gwenda Arguin]

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While student loan debt remains smaller than consumer credit debt ($4.1 trillion) or mortgage debt ($15.5 trillion), the rate of growth of student debt is alarming. Since 2006, consumer credit debt grew by about 70% and mortgage debt grew by only 24%, but student loan debt grew by 232%. Although student loan debt is just a fraction of mortgage and consumer debt, if the larger economy were to enter a serious recession, such as the current economic crisis caused by COVID-19, the rates of defaults on student debt could further weaken the financial markets.

The literature concerned with how student debt affects labor market outcomes is composed of two competing theories. The first maintains that high debt levels encourage a student be to less selective about employment (i.e., take a lower-paying job) because they are simply focused on repaying the debt. The second suggests students with more debt will seek out higher-paying but higher-risk jobs so they can more easily repay their debt. An outcome of this latter view suggests that lower-paying occupations such as teaching or law enforcement will be less attractive. The available research tends to favor the second hypothesis (Minicozzi, 2005), but results vary by level of education. The differences across individuals with student debt makes it difficult to draw broad generalizations.

While these results may suggest that our understanding of labor market outcomes is unclear, we must avoid making broad generalizations by treating all students who have debt as a homogeneous group. Based on the descriptive analysis of the Institute of Educational Sciences (2018), it is clear that not all students who have student loan debt obtained the same level of educational outcomes and those differences make it difficult, if not impossible, to draw broad generalizations about labor market outcomes.

Another element of the labor market outcome question takes the form of entrepreneurial activity (Ambrose, Cordell, and Ma, 2015; Krishnan and Wang, 2018). Not only is the creation of a new business a viable employment option, but the importance of new business formation to economic growth, particularly in rural areas, is well established in the literature (Deller, Kures, and Conroy, 2019). Baum (2015) provides three potential mechanisms that could link student debt and entrepreneurship. First, people who were inclined to start a business before assuming student debt may be deterred because of perceived success risks associated with entrepreneurship. While estimates of business survival rates vary by study, a general rule is that 50% of all new startups do not survive after five years (Deller and Conroy, 2016). Second, salary or proprietor income from new ventures is uncertain, particularly in the first few years. Without guaranteed income, former students may be unable to make debt payments or support living costs. Third, new businesses may be undercapitalized because student debt limits the ability of the potential entrepreneur to secure sufficient financing. Indeed, some have made the observation that the rapid growth in student debt levels corresponds to the national slowdown in new business formation.

The third manner in which student debt can affect the larger community is through homeownership (Cooper and Wang, 2014; Elliott and Lewis, 2015). For many communities, particularly smaller and more rural communities, the decision to purchase a home is viewed as a commitment to the community. Renters are more transient and less likely to make that commitment. Further, homeownership is important in helping rates of entrepreneurship. This comes from the commitment to the community as well as a source of potential financing for a business startup or expansion because homeownership builds wealth through equity. Xu et al. (2015) also argue that high student debt levels are a deterrent to homeownership because of the inability to secure financing as well as the desire for the person to be more footloose if alternative employment opportunities become available.

A handful of studies (e.g., Houle and Berger, 2015) challenge this conventional wisdom. Young adults who are willing to assume student debt may be taking a longer-term view surrounding the decision to purchase a home. Higher lifetime earnings potential among those with higher education outweighs the short-term burden of student debt repayment. Further, a key element of the research into this question hinges on how young adults are defined. A young adult in their early to mid 20s with student debt is different from a young adult in their early 30s.

The potential student debt crisis is a cause for concern, but it is unclear how such a crisis might impact local communities. While our research foundation is growing and finer insights are being gained, it is becoming more difficult to make broad generalizations. In essence, there is too much variation across students to make definitive statements. Debtors represent nearly every corner of demographic categories and pursue widely varying educational achievements, from associates to doctoral degrees.

New firm births buoy net job growth in rural areas (Deller, Kures, and Conroy, 2019). Therefore, threats to entrepreneurial activity through reduced access to capital and greater risk are particularly troubling for rural areas, where net job creation is overwhelmingly driven by the birth of new firms. Beyond this analysis, very little is known about student loan debt within a rural context. The aim of this analysis is to explore these differences using county level data from the U.S. Internal Revenue Service (IRS).

One of the fundamental difficulties of studying the impact of student loan debt on the community or regional economy is the lack of quality data. Unfortunately, the federal government does not consistently collect or report student loan data at the community or regional level. Most studies of student debt are based on a handful of colleges and universities that collect and make available such data on their alumni. Detailed individual data from credit reporting agencies are generally beyond the grasp of researchers.

Finally, disclosure rules apply, meaning there are no data available for the most rural communities. A mapping of the amount of student debt interest payment per return declaring such payments finds that there are large parts of the Great Plains, some of the most rural and least populated counties in the United States, where data are unavailable. Despite these limitations, the IRS data are an excellent alternative to the piecemeal college and university sourced data and the difficult-to-source credit rating agency data.

To gain additional insights into the impact of student debt on community outcomes we estimated a series of simple correlations of our proxy measure of debt on a range of community outcomes. These outcomes include the percentage of residents within the county that are owner occupied, the percentage of renters that are facing housing fiscal stress, the business birth rate as a measure of entrepreneurship, the percentage of income donated to charities and the percentage of income going into retirement accounts. The first two measures are from the American Community Survey (2017 five-year average), the business start-up rates are from Business Information Tracking Series developed by the Census Bureau, and the charity and retirement saving data are from the IRS files, from which the student debt data are drawn. Simple correlations are estimated for the full sample of counties, as well as metro, nonmetro adjacent, and nonmetro remote subsets (Table 2).

Given the current thinking around student debt, we expect to find that higher student debt leads to lower rates of home ownership and higher rates of stress in the rental market. If people with higher debt levels are excluded from the home ownership market, they are forced into the rental market, placing upward pressure on rental pricing and thus higher levels of rental stress. We also expect higher student debt to be linked to lower rates of entrepreneurship, lower rates of charitable donations, and lower rates of savings for retirement. Lower rates of entrepreneurship will place a drag on economic growth and development, lower rates of charitable donation will hinder the ability of nonprofits to provide services in the community, and lower rates of retirement saving will create greater financial stress in the long term.

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