Abstract
This study looks to test the impact of student loan debt on the career choices of college graduates with majors in the arts in the USA. As earnings are on average lower and more variable for arts graduates when compared to graduates of many other fields, I hypothesize that student loan debt will decrease the likelihood arts graduates will work in jobs related to their major fields of study. National Survey of College Graduates data is used to test this hypothesis. I find that for arts graduates, owing on student debt decreases the likelihood of working in jobs closely related to their major fields by over 25% and decreases the likelihood they work as artists by over 30%. For all college graduates, the negative impact of student debt on working in closely related jobs to their major fields is only 3%. Student debt may have potential distributional impacts on who works as artists, as Black and Hispanic graduates and those whose parents did not attend college are more likely to have student debt and less likely to be working in jobs closely related to their major field of study. Policies that help to alleviate the debt burden on arts graduates, like debt relief, could help to mitigate these negative distributional impacts.
Keywords: Arts, Arts majors, Student loan debt, Career choices, Creative class, National survey of college graduates
Introduction
Student loan debt is an issue that has received increasing attention in the USA in recent years. As of late 2021, the total amount of outstanding student loan debt in the USA exceeded $1.5 trillion (Hansen, 2022), and student loan forgiveness was a talking point that received major attention in the 2020 democratic primaries (Nova, 2019). In late August of 2022 the Biden administration announced a plan to forgive up to $10,000 in federal student debt for all borrowers and up to $20,000 in federal student debt for borrowers from low-income backgrounds. Borrowers also saw a pause on student loan repayments that began at the start of the COVID-19 pandemic and ran through the end of 2022 (Kanno-Youngs et al., 2022). While student loan debt is a concern of many college graduates, graduates of low earning fields, like the arts, have the potential to be greatly impacted by this debt. The spotlight on graduates of the arts grew especially bright following mainstream media attention surrounding master’s degree programs with high debt-to-earnings ratios for graduates, many of which are programs in the arts at top U.S. universities (Korn & Fuller, 2021).
Theoretical and empirical research on arts workers paint a picture of a labor market that differs in many ways from traditional labor markets. Artists are thought to be motivated in their pursuit of artistic creation (Throsby, 1994), and the nature of artistic output is such that a select few superstars may emerge with high earnings while the vast majority have earnings that are low (Rosen, 1981). The consequence in the empirical literature has been a labor market with characteristics like low average earnings (within the study sample, average yearly earnings in arts occupations is below $60,000 while average yearly earnings in non-arts occupations is over $80,000) and multiple jobholding, and for college graduates of the arts high shares working outside the arts. Works using data from the Strategic National Arts Alumni Project have found that about 60% of arts graduates work in jobs they consider to be closely related to their majors (Lindemann et al., 2012). However, works using the American Community survey find that less than a quarter work in arts occupations (Wassall & Alper, 2018). While artists may be intrinsically motivated to pursue artistic creation, financial limitations may make doing so difficult, and for college graduates, student loan debt may limit the feasibility of working in the arts even further (White, 2016).
This work looks to understand how student loan debt impacts the career choices of college graduates with degrees in the arts. Using National Survey of College Graduates (NSCG) data, I present descriptive tables and use logistic regression to empirically test for the impact of student debt on the likelihood arts graduates work in jobs closely related to their fields of study. Student debt is found to decrease the likelihood arts graduates are working in jobs closely related to their major fields by over 25%. Student debt is found to decrease the likelihood of working in an arts occupation by over 30%. Across all majors, owing on student loan debt is found to decrease the likelihood of working in jobs closely related to the major fields of study by just 3%. When asked why arts graduates are not working in closely related jobs, more than 75% report pay as a reason, and pay is reported at an even higher rate for those with student debt. Evidence is presented which also suggests that student loan debt may impact who ultimately works as an artist, as those who are white and have college-educated parents are more likely to work in closely related occupations and less likely to have borrowed student loans to attend college. Student debt relief, tuition caps, and other policies that alleviate the burden of debt on arts graduates could help to mitigate these negative impacts.
Before proceeding, it is important to call attention to the contributions of this work. Smith and Albana (2022) recently published a work looking at the relationship between student loan debt and education-job match among arts graduates using data from the Strategic National Arts Alumni Project (SNAAP). While the SNAAP is an invaluable data source for studying the careers of arts graduates, using the SNAAP comes with limitations. Notably, schools must elect to participate in the SNAAP, and as such the sample may not be representative of the broader population of arts graduates in the U.S. A key contribution of this work is in answering these questions using the NSCG, a dataset based on random sampling of U.S. college graduates. Reproducing the findings of studies that use SNAAP data with random samples of the U.S. artist workforce only strengthens the external validity of the conclusions drawn using SNAAP data. A further benefit of the NSCG is that the sample contains and primarily consists of non-arts graduates, allowing for a comparison between the two groups, which presents a second important contribution of this work. Given that models of artistic labor markets, like the work-preference model of Throsby (1994), hypothesize significant differences between artists and non-artists, empirical analyses that allow for comparisons between artists and non-artists are crucial for our understanding of artistic labor markets.
Literature
Artists and arts majors’ careers
The study of arts labor markets can be particularly interesting as artists are theorized to differ from other workers in many ways, and evidence supports this notion. The traditional approach to thinking about labor supply posits that workers face a tradeoff between labor, which leads to income for consumption, and leisure, free time available for enjoyment when not working. While this is likely an accurate depiction of the labor market for many workers, some workers, like artists, are likely to enjoy the work itself, leading to utility from working beyond that associated with the consumption from income. Throsby (1994) introduces a work preference model to try to explain the labor market decisions of artists. The model assumes that artists are motivated by the desire to create their art and want to spend as much time engaged in artistic creation as possible, recognizing though that there is some minimum level of income necessary to survive that must be obtained through work in the arts or elsewhere. Superstar (Adler, 1985; Rosen, 1981) or “winner-take-all” (Frank & Cook, 1995) markets may also explain differences in the behavior of artists relative to other workers. In the arts, a small number of superstars emerge that earn very high incomes, while most workers have low incomes. The competition to become a superstar, coupled with overconfidence—the unrealistic belief for many artists that they will be the one that becomes the star—can lead to a large artistic labor supply. An oversupply of artists is an issue that has been discussed by many authors [see Lingo and Tepper (2013) for further discussion]. The work preference and winner-take-all models would predict several differences between artistic and non-artistic labor markets like lower average earnings and higher rates of multiple jobholding.
As the models predict, empirical research on the labor market for artists finds several differences between the labor market for artists and the market for other workers. These differences tend to be negative or of a precarious nature (Alacovska & Bille, 2021; Bridgstock et al., 2015). Relative to other professional workers, artists have low average incomes (Throsby, 1986; Wassall & Alper, 2018) and high levels of unemployment (Alper & Wassall, 2006; Menger, 2006). Multiple jobholding is also more common among artists (Alper & Wassall, 2000; Menger, 2006; Throsby and Peteskaya, 2017), as is self-employment (Alper & Wassall, 2006; Woronkowicz & Noonan, 2019) and short-term project-based work (Bridgstock, 2005). Artists’ motivations for self-employed work also differ from those of other workers (Feder & Woronkowicz, 2022).
The labor market for college graduates with majors in the arts, both within and outside of the United States, has also received much attention. Several studies have looked to assess whether U.S. college graduates with majors in the arts have gone on to work in the arts. One source for answering such questions is the Strategic National Arts Alumni Project (SNAAP), a survey of U.S. arts graduates. Lindemann et al. (2012) use this data and find that 57% of those employed recently report working in arts-related occupations. Among arts majors in the SNAAP data not working in the arts, Lena et al. (2014) report that the most common reasons for not working in the arts are arts jobs not being available, debt, and higher pay elsewhere. Frenette and Dowd (2020) find that being white and male are predictive of working in the arts, as is having a graduate degree in the arts. The American Community Survey (ACS), which samples a random 1% of the U.S. population yearly, has also been used to identify the share of arts graduates working in the arts. Looking at individual occupations, studies using ACS data have found that less than a quarter of arts graduates are working as artists (BFAMFAPhD, 2014; Wassall & Alper, 2018). While ACS data suggest that small shares of arts majors go on to work as artists, Paulsen et al. (2021) find that arts majors put their creative skills to good use playing big roles in entrepreneurship and innovation. Like the labor market for artists, the labor market for arts majors differs from the labor market for college graduates generally, through ways like lower average incomes (Wassall & Alper, 2018) and in how they are impacted by recessions (Paulsen, 2021). A current gap in the literature on arts majors in the U.S. is in reconciling differences between the high shares that report working in related occupations coming from SNAAP data and the low shares working as artists found using ACS data based on the National Endowment for the Arts (NEA) definition of who is an artist.
Works on the labor market for artists in Australia and other markets outside of the U.S. can help to inform our understanding of the careers of arts graduates within the U.S. Cunningham (Cunningham, 2014a, b) and the Australian Research Centre of excellence for creative industries and innovation have developed a model of measuring the creative workforce dubbed the ‘Creative Trident’ that measures creative workers in a more holistic manner than the measure coming from the NEA. In the creative trident model of measuring the creative workforce, three groups of workers are included: workers in creative occupations (artists), workers in occupations in other industries that use creative skills, and non-creatives employed in the creative industries in support occupations (Bridgstock et al., 2015). Beyond these groups, others have highlighted jobs educating creatives as common and fruitful careers for creative graduates. For music graduates in Australia and the U.K., Brook et al. (2020) find that these graduates were more than twice as likely to be working in education than in music. Interestingly, those graduates employed in education had greater levels of career satisfaction than those employed in music. Using a sample of design graduates in the Netherlands, Lavanga et al. (2021) find that only about one-third spend 100% of working time on degree-related work. Not surprisingly, degree-related income is positively associated with time spent on degree-related work. While certainly not all artists have completed an artistic education, Bille and Jensen (2018) find that for artists in Denmark, having an artistic education has a positive impact on survival in arts occupations.
Like works on the U.S. cultural workforce, scholars looking at creative workers outside the U.S. similarly find evidence that marginalized groups face barriers to success in the arts. Looking at creative graduates in the U.K., Comunian et al. (2011) find evidence of an earnings penalty for women. Looking at Britain’s cultural and creative industries, O’Brien et al. (2016) find that persons from working-class backgrounds are significantly underrepresented. For those working in the cultural and creative industries, they find evidence of earnings penalties for women, non-white workers, and those from working-class backgrounds. Using longitudinal data from Australia, Brook et al. (2021) find that women working in the cultural and creative industries were far less likely than men to be working in those industries 10 years later.
Impacts of student loan debt
Student loan debt has the potential to impact several outcomes for college graduates, including career and educational choices. Rothstein and Rouse (2011) take advantage of a natural experiment, a highly selective university implemented a ‘no loans’ policy, to test for the impact of student debt on career choices. They find that debt increases the likelihood graduates choose high salary jobs and decreases the likelihood they choose low-paid “public interest” jobs. Field (2009) examines an experiment where the student debt of law students was varied randomly and similarly finds that debt impacts career choices. Krishnan and Wang (2019) take advantage of natural experiments related to the legal treatment of student loan debt and find that student loan debt hinders entrepreneurship. Feinberg (2020) looks at data from the NSF’s survey of earned doctorates and finds that student debt is associated with a decreased likelihood of pursuing an academic career for PhDs, with larger effects within STEM fields. Regarding the relationship between student debt and educational choices, studies have identified a negative relationship between student debt and the likelihood of pursuing education beyond a bachelor’s degree (Malcom & Dowd, 2012; Zhang, 2013).
Beyond educational and career choices, student loan debt has been found to impact several other outcomes for college graduates. Student loan debt has been found to decrease the likelihood of homeownership (Cooper & Wang, 2014; Houle & Berger, 2015; Mezza et al., 2020). College graduates with student loan debt are found to delay marriage (Addo, 2014; Gicheva, 2016), and debt is associated with moving home to co-reside with parents (Dettling & Hsu, 2018). Student loan debt is also found to have a negative impact on psychological well-being, negatively impacting mental health (Walsemann et al., 2015) and life satisfaction (Kim & Chatterjee, 2019; Korankye & Kalenkoski, 2021).
Student loan debt and the arts
Few studies have looked at the impacts of student loan debt on college graduates with majors in the arts. White (2016) looks at this issue from a theoretical perspective. In looking at data on net tuition and earnings for U.S. colleges and universities, White (2016) concludes that it would be difficult for the average college graduate with an arts major to pay back student debt sufficient to cover tuition while working in an arts occupation. As such, student debt may push some arts graduates to work outside of the arts. Interventions to address this problem are posed, such as the implementation of tuition caps by arts schools, financial literacy education for arts students, and education about the broad career possibilities for arts graduates.
Using SNAAP data, a few studies have also looked at student debt in the arts empirically. Lindemann et al. (2012) use 2010 SNAAP data to assess the careers of arts graduates. Regarding student loan debt, they find a negative association between having student loan debt and the length of time arts graduates spend working as artists, driven by graduates with high levels of debt. When asked why arts graduates were pursuing work outside the arts, about 30% said debt was a reason. Using data from the 2011–2013 SNAAP surveys, Frenette and Dowd (2020) look at which factors determine whether arts graduates leave the arts. They find that high levels of debt (greater than $50,000) were a significant predictor of leaving the arts. A recent study by Smith and Albana (2022) also addresses this issue. They examine the relationship between student debt and education-job match among college graduates with bachelor’s degrees in the arts. Using SNAAP data, they present logistic regression results finding that arts graduates with $10,000 or more in student loan debt have significantly lower odds of ever having worked in an arts job following graduation. While the works using SNAAP data find that student loan debt has a negative impact on the likelihood arts graduates work in the arts, a gap in the literature which presents an opportunity to build on this existing knowledge is that no current studies use data from a random sample of arts graduates that can also allow for comparisons to non-arts graduates.
Data
In assessing how student loan debt impacts the career choices of arts majors, I use individual level data from the 2015, 2017, and 2019 iterations of the National Survey of College Graduates (NSCG). The NSCG is a cross-sectional biennial survey of college graduates conducted by the National Science Foundation. The three iterations used in this survey were analyzed together and treated as a pooled cross section. Survey respondents answer questions related to their education, work, and demographics. Of most interest for this analysis, the NSCG asks respondents questions about the financing of their college education (National Center for Science & Engineering Statistics NCSES, 2022).
As the focus of this analysis is to analyze the relationship between student loan debt and career choices for college graduates with undergraduate degrees in the arts, the sample is restricted to individuals with bachelor’s degrees but no higher.1 Though the NSCG oversamples graduates from STEM fields, among the more than 100 undergraduate major fields included in the NSCG are four which are classified as arts majors in this study: dramatic arts; fine arts; music; and other arts majors.2 Regarding the use of student loans to finance the respondent’s undergraduate degree, the survey asks how much was borrowed and how much is still owed at the time of the survey. Rather than entering an exact dollar amount, survey respondents select a range for debt owed, starting at $0, then $1–$10,000, and continuing in increments of $10,000 until a top range of $90,000 +. For much of the analysis that follows, I construct binary variables indicating having no loans borrowed and no loans owed, where these variables take on a one if the amount borrowed or owed is $0. In assessing career choices, the primary survey question used asks respondents “To what extent was your work on your principal job related to your highest degree?” Respondents can then select “closely related”, “somewhat related”, or “not related”. For those that select “not related”, a follow-up question asks why. Additionally, I look at the detailed occupations reported by the survey respondents in assessing career choices.3
Descriptive statistics are presented in Table 1. In assessing the relationship between student loans and the career choices of arts majors, comparisons are frequently made to the full sample of college graduates, so Table 1 presents dependent and independent variable means for all majors and arts majors separately.4 Relative to the full sample of college graduates, arts majors are much less likely to work in jobs closely related to their major fields of study. For all majors this share is just over 50%, while for arts majors it is under 40%. This difference is driven by arts majors being far more likely to work in jobs unrelated to their major fields of study at over 36%. Relative to the full sample of college graduates, arts majors are more likely to have borrowed student loans to finance their undergraduate degrees and are more likely to still owe on their loans. Arts majors are more likely to be female and white and are less likely to be married or have children compared to the full sample of college graduates and are more likely to have college-educated parents.
Table 1.
Descriptive statistics
| Variable | All majors | Arts majors |
|---|---|---|
| Job closely related to major field | 50.5% | 37.9% |
| Job somewhat related to major field | 29.4% | 26.0% |
| Job unrelated to major field | 20.2% | 36.1% |
| No loans owed | 76.6% | 69.5% |
| No loans borrowed | 42.1% | 38.7% |
| Male | 58.4% | 48.3% |
| White | 62.4% | 72.2% |
| Black | 7.6% | 5.4% |
| Asian | 14.3% | 8.0% |
| Hispanic | 11.7% | 9.6% |
| Married | 69.4% | 59.7% |
| Children | 42.9% | 34.1% |
| Age | 41.7 | 40.8 |
| Mom college or higher | 37.1% | 47.5% |
| Dad college or higher | 44.9% | 54.9% |
| Observations | 109,719 | 2413 |
The most common occupations of arts majors within the sample are presented in Table 2, broken up into those whose jobs are self-reported as being “closely related”, “somewhat related”, and “not related”. The most common group of occupations for arts majors, at a share of 17.1%, is writers, editors, public relations specialists, artists, entertainers, and broadcasters. As artists are included in this group, this is not surprising. The second most common occupation is web developers, followed by occupations in management, marketing, sales, and teaching. Not surprisingly, the writers, etc., occupational grouping is also the most common occupation among those who self-reported as working in a closely related job at over 30%. Among the other common occupations reported as closely related are many teaching occupations and management occupations. Management occupations being reported closely related would align with the creative trident model of the creative industries (Cunningham 2014a; b), and researchers have found education careers to be both common and fulfilling for creative graduates (Brook et al., 2020). Surprisingly, the eighth most common group of occupations for those who self-reported as working in a closely related occupation is a group of health-related occupations.5 For those who report working in a job not closely related to their major field of study among arts graduates, common occupations include teaching, sales, management, and many service-related occupations. In reconciling some of the prior conflicting evidence on the share of arts majors working in the arts, while about 65% of arts majors self-report working in a closely or somewhat related job to their major field of study, less than 20% work in the occupational grouping that includes artists and entertainers.
Table 2.
Most common occupations for arts majors
| Rank | All arts majors | Share | Closely related | Share | Somewhat related | Share | Unrelated | Share |
|---|---|---|---|---|---|---|---|---|
| 1 | Writers, editors, PR specialists, artists, entertainers, broadcasters | 17.1% | Writers, editors, PR specialists, artists, entertainers, broadcasters | 31.7% | Writers, editors, PR specialists, artists, entertainers, broadcasters | 15.9% | Other teachers and instructors (private tutors, dance, etc.) | 8.5% |
| 2 | Web developers | 4.9% | Teachers: secondary—other subjects | 6.6% | Web developers | 7.8% | Sales–retail | 5.9% |
| 3 | Other management related occupations | 4.2% | Web developers | 5.0% | Other marketing and sales occupations | 6.2% | Other management related occupations | 5.4% |
| 4 | Other teachers and instructors (private tutors, dance, etc.) | 4.2% | Top-level managers, executives, administrators | 4.4% | Other management related occupations | 5.3% | Other marketing and sales occupations | 4.0% |
| 5 | Other marketing and sales occupations | 4.0% | Teachers: elementary | 4.4% | Other computer information science occs | 3.9% | Network and computer systems administrators | 3.6% |
| 6 | Sales–retail | 3.5% | Other computer information science occs | 3.6% | Sales–retail | 3.2% | Other health occupations | 3.6% |
| 7 | Top-level managers, executives, administrators | 3.4% | Other teachers and instructors (private tutors, dance, etc.) | 3.1% | Top-level managers, executives, administrators | 3.0% | Writers, editors, PR specialists, artists, entertainers, broadcasters | 3.4% |
| 8 | Other computer information science occupations | 3.3% | RNs, pharmacists, dieticians, therapists, physician assistants, NPs | 3.0% | Other teachers and instructors (private tutors, dance, etc.) | 3.0% | Food preparation and service | 3.4% |
| 9 | Teachers: secondary—other subjects | 3.0% | Postsecondary teachers: art, drama, and music | 2.7% | Teachers: elementary | 2.8% | Other service occupations, except health | 3.2% |
| 10 | Teachers: elementary | 2.6% | Other mid-level managers | 2.5% | Software developers: applications and systems software | 2.5% | Precision/production occupations | 3.1% |
| 10 (tie) | Other marketing and sales occs | 2.5% | Mechanical Engineers | 2.5% | Transportation and material moving occs | 3.1% | ||
| 10 (tie) | Other mid-level managers | 2.5% | ||||||
| Subtotal: | 50.0% | 69.3% | 58.6% | 47.1% |
Arts majors with a double major are excluded from calculations in this table
Empirical methodology
To empirically test for the impact of student loans on the career choices of arts majors, a series of descriptive tables are presented, followed by the estimation of logistic regressions. First, descriptive tables are presented showing the shares of arts majors working in jobs closely related to their field of study based on whether they borrowed or owe on student loans and on the level of student loan debt, comparing arts majors to the full sample of college graduates. Then, for those working in jobs that are not related to their major fields of study, descriptive tables are presented showing the self-reported reasons for working in an unrelated job.
Logistic regressions are then estimated to test for the impact of having borrowed or still owing on student loans on working in jobs closely related to the major fields of study, controlling for observables. These regressions take the form:
where Closely Related, No Loans Borrowed, and No Loans Owed are binary variables and X is a vector of demographic and education-related control variables. Demographic controls include age and age-squared, and binary variables indicating being male, Black, Asian, Hispanic, other race/ethnicity, married, an interaction of male and married, whether the spouse works full-time (if married), having children, mother’s highest degree being bachelor’s or higher, father’s highest degree being bachelor’s or higher, and regional geographic indicators.6 Educational controls include years since graduation, and binary variables indicating being a double major, indicators for major field of study, and Carnegie classifications of undergraduate institution graduated from as liberal arts, research, comprehensive, doctoral granting, arts institution, or other.7 For the sample of arts majors, similar regressions are also estimated where the dependent variable is a binary variable which takes on a one if the individual’s occupation is in the writers, etc. grouping which includes artists and entertainers.
I hypothesize that student loan debt will have a negative impact on the likelihood that college graduates with majors in the arts will be working in jobs closely related to their major fields of study. For college graduates generally, I hypothesize that there will be little relationship between student loan debt and career choices. Relative to graduates of other fields, arts majors have earnings that are lower and less consistent, and are more likely to hold multiple jobs (Wassall & Alper, 2018). While for graduates of many fields the highest paying job may be one that is closely related to the major field, making debt unlikely to impact which job they take, for many arts majors it may be possible to find work outside of the arts that pays better. The work preference model of Throsby (1994) is useful in understanding how student loans may enter the career decisions of arts graduates. The federal student loan system in the U.S. requires that borrowers make consistent minimum payments monthly based on the amount of debt owed. For those arts graduates with student loan debt, these payments raise the minimum necessary income threshold for survival and require some income consistency. For some share of graduates, this is likely to push them into primary occupations outside the arts that have pay that is higher, more consistent, or both.
Results
Shares of individuals working in jobs closely related to their major fields of study by major and student debt are presented in Table 3. The first column presents the share working in a closely related job for all majors, the second column presents the share for all arts majors (both those with a single major and those with a double major), and the last column presents the share for single arts majors only. Among all majors, about 50% are working in jobs closely related to their major fields of study, and this does not vary much based on student loan status. However, among those have debt they still owe, those with more than $50,000 owed are about 4% points less likely to be working in a job closely related to their major field. Student loans have more sizeable impacts on the likelihood arts majors are working in closely related jobs. While over 39% of arts majors that do not owe student debt are working in jobs closely related to their major fields of study, that number is under 35% for those who do, a 12% difference [(39.4–34.6)/39.4]. Among arts majors that owe on student debt, those with $50,000 or more owed are about 17% [(31.7–38.3)/38.3] less likely to be working in closely related jobs than those with less than $50,000. These differences are even larger when double majors are excluded. For single majors in the arts, owing on student loan debt is associated with about a 17% difference in the likelihood of working in a closely related job, and the difference among those with debt between those with more than $50,000 and those with $50,000 or less is over 20%.
Table 3.
Share working in closely related occupations and student loans
| Grouping | All majors | Arts majors | Single arts majors |
|---|---|---|---|
| Borrowed student loans | 50.9% | 37.4% | 37.0% |
| No loans borrowed | 49.8% | 38.7% | 37.5% |
| Still owes student loans | 49.1% | 34.6% | 32.4% |
| No loans owed | 50.8% | 39.4% | 39.3% |
| Owes less than $50,000 | 50.6% | 38.3% | 37.7% |
| More than $50,000 owed | 46.7% | 31.7% | 29.7% |
| Observations | 109,719 | 2413 | 1724 |
Table 4 is like Table 3, but with separate columns for each of the four individual arts major fields. There are notable differences in the shares working in closely related occupations by arts major field, with dramatic arts majors being the least likely to work in closely related jobs. There are also considerable differences in the effect of owing on student loans on the likelihood of working in closely related jobs by arts major field. For dramatic arts majors, those who still owe on their student loans are more than 40% less likely to be working in closely related jobs than those who do not have outstanding student loan balances. For fine arts majors, this difference is only about 6%. While the data cannot tell us with certainty why this difference across arts majors occurs, within the context of the Throsby (1994) model, the effect may be especially large for dramatic arts majors as their incomes are likely to be among the most variable of the arts fields.
Table 4.
Share working in closely related occupations and student loans—by arts major type
| Grouping | Dramatic arts | Fine arts | Music | Other arts majors |
|---|---|---|---|---|
| Borrowed Student loans | 21.2% | 34.9% | 36.2% | 42.3% |
| No loans borrowed | 24.6% | 35.7% | 37.0% | 42.4% |
| Still owes student loans | 15.4% | 33.7% | 30.6% | 36.5% |
| No loans owed | 26.5% | 35.9% | 38.3% | 45.1% |
| Observations | 182 | 520 | 276 | 746 |
For those college graduates working in jobs self-reported as not related to their major fields of study, the NSCG asks why they are not. Respondents can choose one or more options among the following: career change; working conditions; family; location; jobs not available; pay; and other reasons. Table 5 presents the share of respondents selecting each of these reasons for all majors, arts majors, single arts majors, and single arts majors with loans owed. For college graduates in all majors not working in jobs related to their major fields, the most selected reason why is pay, followed by working conditions, and then by location. While these are also the most common reasons for arts majors, arts majors are much more likely to report pay as a reason for not working in related jobs. While 66.3% of all majors report pay as a reason to not be working in jobs related to their majors, 74.5% of arts majors do. For single arts majors, this is slightly higher at 75%. For single arts majors with loans owed, this share is even higher at 78.6%. Collectively, the importance of pay as a reason for not working in a job related to their major fields for arts majors supports the hypothesis that student loan debt impacts the career choices of college graduates with majors in the arts.
Table 5.
Reasons for not working in a job related to major field
| Reasons | All majors | Arts majors | Single arts majors | Single arts majors with loans owed |
|---|---|---|---|---|
| Career change | 44.0% | 46.8% | 46.0% | 46.0% |
| Working conditions | 54.3% | 55.6% | 56.0% | 58.9% |
| Family | 25.4% | 25.7% | 26.2% | 23.2% |
| Location | 52.4% | 54.6% | 54.8% | 55.8% |
| Jobs not available | 32.8% | 43.1% | 44.3% | 55.4% |
| Pay | 66.3% | 74.5% | 75.0% | 78.6% |
| Other reasons | 9.7% | 8.3% | 8.3% | 8.0% |
| Observations | 22,109 | 870 | 648 | 224 |
The sample is restricted to those who self-report working in a job not related to their major field
Table 6 presents reasons for not working in jobs related to their major field for arts majors separately by individual major field. For each of the four arts majors, pay is again the most selected reason for working in jobs not related to the major fields. There is some heterogeneity across majors, with dramatic arts the highest at 86.1% and other arts majors the lowest at 74.4%. Dramatic arts having the highest share of respondents reporting pay as a reason for not working in jobs related to the major field is consistent with the results of Table 4 showing that dramatic arts majors are most affected by having student loan debt.
Table 6.
Reasons for not working in a job related to major field—by arts major type
| Reasons | Dramatic arts | Fine arts | Music | Other arts majors |
|---|---|---|---|---|
| Career change | 41.7% | 44.6% | 45.5% | 48.9% |
| Working conditions | 66.7% | 61.5% | 60.6% | 53.3% |
| Family | 30.6% | 29.2% | 21.2% | 16.7% |
| Location | 47.2% | 66.2% | 45.5% | 55.6% |
| Jobs not available | 47.2% | 66.2% | 48.5% | 53.3% |
| Pay | 86.1% | 76.9% | 84.8% | 74.4% |
| Other reasons | 2.8% | 7.7% | 3.0% | 12.2% |
| Observations | 36 | 65 | 33 | 90 |
The sample is restricted to single majors who self-report working in a job not related to their major field
Logistic regression results testing for the impact of student loans on the career choices of arts majors are presented in Table 7. The first two columns present logistic regression results for all majors, where the dependent variable is a binary variable which takes on a 1 if the individual is working in a job closely related to their major field of study. The first regression includes both single and double majors, while the second regression includes only single majors. In either case, controlling for demographic and educational characteristics, having no loans borrowed has a small negative impact on working in closely related jobs, while having no loans owed has a small positive impact. The third and fourth regressions are restricted to arts majors, where the third regression includes both single and double majors and the fourth regression is restricted to only single majors. For arts majors, having no loans borrowed has an insignificant impact on working in closely related jobs. Having no loans owed has a large, positive, and significant impact on the likelihood of working in closely related jobs, with a larger effect for single majors. As the share of arts majors overall working in closely related jobs is around 37%, having no loans owed increases the likelihood of working in a closely related job by over 25% (10.7% points) relative to the mean for all arts majors and almost 35% (13.8% points) for single arts majors. The final two columns of Table 7 present logistic regression results for arts majors where the dependent variable is a binary variable that takes on a 1 if the individual is working in the writers, etc. occupational category which includes artists and entertainers. Here having no loans borrowed is found to have an insignificant impact on working in an arts occupation, while having no loans owed increases the likelihood by a large, significant margin (about 30% relative to the mean). These results provide further support for the hypothesis that student loans have an impact on the career choices of arts majors but little impact on the careers choices of college graduates generally.
Table 7.
Logit regression: dependent variables are binaries for whether working in a closely related or arts occupation
| Variable | Closely related | Closely related | Closely related | Closely related | Arts occupation | Arts occupation |
|---|---|---|---|---|---|---|
| Sample | All majors | All single majors | Arts majors | Single arts majors | Arts majors | Single arts majors |
| No loans borrowed | − 0.011*** (0.005) | − 0.014*** (0.005) | − 0.036 (0.033) | − 0.042 (0.038) | − 0.006 (0.020) | − 0.005 (0.023) |
| No loans owed | 0.012*** (0.006) | 0.015*** (0.006) | 0.107*** (0.035) | 0.138*** (0.039) | 0.039** (0.021) | 0.039** (0.023) |
| Dep. Var. mean | 50.5% | 51.1% | 37.9% | 37.2% | 12.7% | 14.2% |
| Pseudo R-squared | 0.091 | 0.097 | 0.065 | 0.050 | 0.083 | 0.069 |
| Observations | 109,719 | 94,462 | 2413 | 1724 | 2705 | 2072 |
Coefficient estimates reported are marginal effects estimated at means. Standard errors are in parenthesis
***Indicates p < 0.01, **indicates p < 0.05
Demographic characteristics and student debt in the arts
Institutional contexts related to student loan debt in the U.S. have made this issue rise to prominence in recent years. Between 2007 and 2020, student loan debt more than doubled as a share of GDP (Hansen, 2022). One factor driving this increase in debt is increases in college tuition. Adjusting for inflation, tuition rates rose 180% between 1980 and 2020 in the U.S. (McGurran, 2022). During the post-great recession period the U.S. has also seen significant drops in state funding for higher education (Mitchell at al., 2019). In light of these contexts, it is likely the case that student loan debt has been a challenge affecting more recent graduates the most. Within the sample of arts graduates, nearly 70% of those who graduated within 10 years of completing the NSCG took out student loans to pay for their undergraduate degrees. That number is less than 50% for those who completed the survey more than 20 years after finishing their undergraduate degree. Appendix Table 9 tests for the possibility that student loans had differential impacts on different cohorts of arts graduates. Given the institutional context of increasing student debt over time, it is not surprising to see that the impact of student loan debt on career choices is large and statistically significant for recent arts graduates, but smaller and insignificant for more distant graduates.
Table 9.
Logit regression: closely related regressions by graduation cohort
| Variable | Closely related | Closely related | Closely related |
|---|---|---|---|
| Sample |
Single arts majors 0–10 years since graduation |
Single arts majors 11–20 years since graduation |
Single arts majors 21 + years since graduation |
| No loans borrowed | − 0.144** (0.068) | 0.057 (0.080) | − 0.053 (0.069) |
| No loans owed | 0.262*** (0.063) | 0.049 (0.080) | 0.036 (0.116) |
| Dep. Var. mean | 42.2% | 36.9% | 31.5% |
| Pseudo R-squared | 0.073 | 0.104 | 0.060 |
| Observations | 688 | 459 | 575 |
Coefficient estimates reported are marginal effects estimated at means. Standard errors are in parenthesis
***Indicates p < 0.01, **indicates p < 0.05
As not all college graduates are equally affected by student loan debt, the finding of an impact of student loan debt on the career choices of college graduates with majors in the arts has potential distributional impacts on who ends up working as artists. Table 8 presents demographic characteristics for single arts majors working in closely related and unrelated occupations to their major fields of study, and for those who did and did not borrow student loans to attend college. Those working in closely related jobs are more likely to be male, white, and have highly educated parents. Those who borrowed are more likely to be Black or Hispanic and are less likely to have college-educated parents. These results suggest that student loan debt may also have an impact on who ultimately becomes artists, potentially in such a way that the college graduates who go on to work in the arts are less diverse than arts graduates overall. These findings are largely in-line with the literature on inequities in the arts, notably O’Brien et al. (2016) which finds that those from working-class backgrounds in Britain are less likely to be working in the cultural and creative industries.
Table 8.
Demographics, occupation relatedness, and loan borrowing for arts majors
| Variable | Closely related | Unrelated | No loans borrowed | Loans borrowed |
|---|---|---|---|---|
| Male | 53.5% | 50.3% | 44.9% | 49.1% |
| White | 75.4% | 72.8% | 76.8% | 72.8% |
| Black | 3.6% | 6.3% | 1.9% | 6.4% |
| Asian | 7.0% | 6.6% | 11.0% | 6.0% |
| Hispanic | 9.7% | 10.0% | 6.9% | 10.0% |
| Mom college or higher | 47.0% | 42.9% | 49.5% | 41.7% |
| Dad college or higher | 54.0% | 49.8% | 56.6% | 47.8% |
| Observations | 641 | 648 | 827 | 1245 |
Arts majors with a double major are excluded
Conclusions
This paper assesses the impact of student loan debt on the career choices of college graduates with majors in the arts. As average earnings for many arts occupations are notably lower than earnings for college graduates overall, the career choices of arts majors have the potential to be strongly impacted relative to college graduates with majors in other fields. Using National Survey of College Graduates data, this paper presents descriptive tables and regression results testing for the impact of student debt on the likelihood arts graduates work in jobs closely related to their fields of study, and in jobs in the arts, with comparisons made to graduates of non-arts fields. This study finds that owing on student loan debt decreases the likelihood arts graduates are working in jobs closely related to their major fields of study by over 25% and decreases the likelihood of working in an arts occupation by over 30%, with impacts driven most prominently by recent graduates. For all college graduates, owing on student loan debt decreases the likelihood of working in jobs closely related to their major fields of study by less than 3%. College graduates with majors in the arts are more likely to report pay as a reason for not working in closely related jobs than graduates of other majors, and those with debt owed are even more likely to report pay as a reason. Heterogeneity in the impact of debt across arts major fields is also found. Taken collectively, student debt is found to have a differential negative impact on the likelihood arts majors are working in jobs closely related to their major fields of study.
While the evidence presented supports the hypothesis that student loan debt decreases the likelihood arts majors are working in jobs related to their major fields, it is not fair to assume that working outside the arts is always an unwanted outcome. The NSCG questionnaire does not directly ask respondents whether they want to be working in jobs related to their major fields of study. Some presented evidence would suggest that arts majors working in unrelated jobs would like to be working in the arts, such as pay being the most selected reason for working in an unrelated job for arts majors, selected at a higher share than for other majors. Additionally, there’s little reason to believe that those who have debt, and those from less advantaged backgrounds, would be more likely to not want to work in the arts. However, researchers have highlighted rewarding roles for arts graduates in education occupations (Brook et al., 2020). A growing body of work has looked at the role arts majors play in entrepreneurship and innovation. Recent special issues in the journals Small Business Economics and Journal of Cultural Economics have focused on the role of entrepreneurship and innovation in the arts (Noonan, 2021; Woronkowicz, 2021). Entrepreneurship education in arts programs is on the rise (Essig & Guevara, 2016; White, 2013), and arts majors play a significant role in jobs and industries that are entrepreneurial and innovative (Paulsen et al., 2021). As such, it is possible that some share of arts majors enters or leaves college intending to work outside the arts in education or in entrepreneurial or innovation intensive roles that take advantage of the arts skillset.
There are several policies that could be implemented at program, university, and government levels that could help to alleviate the burden of student debt on arts graduates. Given that arts graduates who ultimately go on to work in closely related occupations are more likely to be white, male, and have college education parents, policies that alleviate the debt burden for arts graduates could help to make the arts more equitable by making careers in the arts more financially viable for those from marginalized populations. As suggested by White (2016), universities or arts programs could take actions like capping tuition, expanding aid, and helping students see broader possibilities for putting their arts training to work. Beyond actions that colleges and universities can take, several government policies could alleviate the burden of debt for arts graduates, such as student debt forgiveness, increases in grant and scholarship financial aid support, and reduced or lower cost public colleges and universities. Such policies could be designed to affect all college graduates, or potentially targeted toward graduates of the arts or other lowering earning fields. Given that the Biden administration has implemented a plan for student loan forgiveness, this opens the door to future empirical analyses testing for policy’s impact on the careers of arts graduates. As pay is reported as the most common reason arts graduates are not working in the arts, it is possible that low pay in the arts is the true problem, rather than student loan debt. If the problem is pay, programs that guarantee income, like the intermittence de spectacle program in France, could help to alleviate the burden of debt on artists (Beardsley & Kheriji-Watts, 2021). Though situated in the North American context, the findings and policy recommendations of this work can have implications beyond the labor market for arts majors in the U.S. as social policy in other countries also impacts artists.
The findings of this study are limited in several ways. As the NSCG has a focus on STEM fields, the full breadth of arts majors available in surveys like the ACS and SNAAP were not given as options, which limited the ability to look at the impact of student debt on individual art majors. The NSCG also does not make available the respondent’s institution of higher education. To speak with stronger causal language about the impact of student debt on the career choices of arts majors, researchers would benefit from the availability of more detailed covariates or panel data. There are many additional possibilities for future research on this topic, such as looking at the intersection of student debt and economic conditions at graduation on career choices of arts majors.
Appendix
See Table 9.
Funding
Not applicable.
Availability of data and material
All data used in this study come from publicly available sources.
Code availability
Not Applicable.
Declarations
Conflicts of interest
Not applicable.
Footnotes
Those with an advanced degree may or may not have that degree in the arts, which is likely to impact whether they work in a related occupation. While an analysis of graduates with advanced degree in the arts would also be valuable, the share of arts graduates with advanced degrees in the NSCG is of much smaller sample size, limiting the possibility for a fruitful analysis of those graduates.
The ACS and SNAAP include more detailed art major categories than the four given in the NSCG.
When asked to report about their principal job, multiple jobholders are asked to report the job for which they work the most hours. The survey does not report information on other jobs the employee may hold.
The full sample consists of 109,719 observations, with 37,100 from 2015, 33,963 from 2017, and 38,65 from 2019. Among arts majors, there were 2,413 observations in total, with 780 from 2015, 771 from 2017, and 862 from 2019.
While the survey does not give researchers the specific job title for workers within this group of occupations, it is possibly the case that arts graduates who report these occupations as closely related may work as art or music therapists.
These indicators are binary variables corresponding to the U.S. region of the respondent, where respondents are grouped into multistate regions like New England region, Middle Atlantic region, etc.
The name of the institution attended is not made available to researchers.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- Addo, F. R. (2014). Debt, cohabitation, and marriage in young adulthood. Demography,51, 1677–1701. 10.1007/s13524-014-0333-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Adler, M. (1985). Stardom and talent. The American Economic Review,75(1), 208–212. [Google Scholar]
- Alacovska, A., & Bille, T. (2021). A heterodox re-reading of creative work: The diverse economies of Danish visual artists. Work, Employment and Society,35(6), 1053–1072. 10.1177/0950017020958328 [Google Scholar]
- Alper, N. O., & Wassall, G. H. (2000). More than once in a blue moon: Multiple jobholdings by American artists. National Endowment for the Arts.
- Alper, N. O., & Wassall, G. H. (2006). Artists’ careers and their labor markets. Handbook of the Economics of Art and Culture,1, 813–864. [Google Scholar]
- Beardsley, E., & Kheriji-Watts, K. (2021). In France, performing artists are guaranteed unemployment income. NPR.
- BFAMFAPhD. (2014). Artists report back: A national study on the lives of arts graduates and working artists. http://bfamfaphd.com/#artists-report-back
- Bille, T., & Jensen, S. (2018). Artistic education matters: Survival in the arts occupations. Journal of Cultural Economics,42, 23–43. 10.1007/s10824-016-9278-5 [Google Scholar]
- Bridgstock, R. (2005). Australian artists, starving and well-nourished: What can we learn from the prototypical protean career? Australian Journal of Career Development,53(1), 40–47. 10.1177/103841620501400307 [Google Scholar]
- Bridgstock, R., Goldsmith, B., Rodgers, J., & Hearn, G. (2015). Creative graduate pathways within and beyond the creative industries. Journal of Education and Work,28(4), 333–345. 10.1080/13639080.2014.997682 [Google Scholar]
- Brook, S., Comunian, R., Jewell, S., & Lee, J. Y. (2020). More than a day job, a fair job: Music graduate employment in education. Music Education Research,22(5), 541–554. 10.1080/14613808.2020.1840539 [Google Scholar]
- Brook, S., Lee, J., & Park, S. (2021). Selection and survival in the field of cultural production: A longitudinal study of the Australian census. Cultural Trends,30(4), 303–320. 10.1080/09548963.2021.1874820 [Google Scholar]
- Comunian, R., Faggian, A., & Jewell, S. (2011). Winning and losing in the creative industries: An analysis of creative graduates’ career opportunities across creative disciplines. Cultural Trends,20(3–4), 291–308. 10.1080/09548963.2011.589710 [Google Scholar]
- Cooper, D., & Wang, J. C. (2014). Student Loan Debt and Economic Outcomes. Current Policy Perspectives. Federal Reserve Bank of Boston, 14–7, 1–37.
- Cunningham, S. (2014a). Creative labour and its discontents: A reappraisal. In G. Hearn, R. Bridgstock, B. Goldsmith, & J. Rodgers (Eds.), Creative work beyond the creative industries: Innovation, employment and education (pp. 25–46). Edward Elgar
- Cunningham, S. (2014b). Hidden innovation: Policy, industry and the creative sector. Lexington Books/Rowman and Littlefield.
- Dettling, L. J., & Hsu, J. W. (2018). Returning to the nest: Debt and parental co-residence among young adults. Labour Economics,54, 225–236. 10.1016/j.labeco.2017.12.006 [Google Scholar]
- Essig, L., & Guevara, J. (2016). A landscape of arts entrepreneur-ship in US higher education. In Alliance for the arts in research universities:1–67. https://herbergerinstitute.asu.edu/sites/default/files/a_landscape_of_arts_entrepreneurship_in_us_higher_education_0.pdf
- Feder, T., & Woronkowicz, J. (2022). Reluctantly independent: motivations for self-employed artistic work. Journal of Cultural Economic. 10.1007/s10824-022-09464-5 [Google Scholar]
- Feinberg, R. M. (2020). Is an academic career a luxury good? Student debt and the under- representation of minorities. Economics Bulletin,40(4), 2964–2977. [Google Scholar]
- Field, E. (2009). Educational debt burden and career choice: Evidence from a financial aid experiment at NYU law school. American Economic Journal: Applied Economics,1(1), 1–21. 10.1257/app.1.1.1 [Google Scholar]
- Frank, R. H., & Cook, P. J. (1995). The winner-take-all society. The Free Press.
- Frenette, A. & Dowd, T. J. (2020). Careers in the Arts: Who Stays and Who Leaves? SNAAP Special Report 1–36. https://snaaparts.org/findings/reports/careers-in-the-arts-who-stays-and-who-leaves
- Gicheva, D. (2016). Student loans or marriage? A look at the highly educated. Economics of Education Review,53, 207–216. 10.1016/j.econedurev.2016.04.006 [Google Scholar]
- Hansen, M. (2022). Student loan debt statistics. In Education data initiative.https://educationdata.org/student-loan-debt-statistics
- Houle, J. N., & Berger, L. (2015). Is student loan debt discouraging homeownership among young adults? Social Service Review,89(4), 589–621. 10.1086/684587 [Google Scholar]
- Kanno-Youngs, Z., Cowley, S., & Tankersley, J. (2022). Biden to cancel $10,000 in student debt; low-income students are eligible for more. New York Times.
- Kim, J., & Chatterjee, S. (2019). Student loans, health, and life satisfaction of US households: Evidence from a panel study. Journal of Family and Economic Issues,40, 36–50. 10.1007/s10834-018-9594-3 [Google Scholar]
- Korankye, T., & Kalenkoski, C. M. (2021). The effect of households’ student debt on life satisfaction. Journal of Family and Economic Issues,42, 757–772. 10.1007/s10834-021-09753-9 [Google Scholar]
- Korn, M., & Fuller, A. (2021). ‘Financially hobbled for life’: The Elite master's degrees that don’t pay off. The Wall Street Journal. https://www.wsj.com/articles/financially-hobbled-for-life-the-elite-masters-degrees-that-dont-pay-off-11625752773
- Krishnan, K., & Wang, P. (2019). The cost of financing education: Can student debt hinder entrepreneurship? Management Science,65(10), 4522–4554. 10.1287/mnsc.2017/2995 [Google Scholar]
- Lavanga, M., Martorana, M. F., Loots, E., & Nieboer, E. (2021). Designed for the job? An empirical study on the determinants of design graduates’ work choices. Cultural Trends,30(4), 321–337. 10.1080/09548963.2021.1951599 [Google Scholar]
- Lena, J. C., Gaskill, S., Houghton, R. F., Lambert, A. D., Miller, A. L., & Tepper, S. J. (2014). Making it work: The education and employment of recent arts graduates, SNAAP annual report 2014. Center for Postsecondary Research, Indiana University, School of Education.
- Lindemann, D. J., Tepper, S. J., Gaskill, S., Jones, S. D., Kuh, G. D., Lambert, A. D., Lena, J., Miller, A. L., Park, K., Rudolph, E. B., & Vanderwerp, L. (2012). Painting with broader strokes: Reassessing the value of an arts education. Indiana University and Vanderbilt University, Strategic National Arts Alumni Project.
- Lingo, E. L., & Tepper, S. J. (2013). Looking back, looking forward: Arts-based careers and creative work. Work and Occupations,40(4), 337–363. 10.1177/0730888413505229 [Google Scholar]
- Malcom, L. E., & Dowd, A. C. (2012). The impact of undergraduate debt on the graduate school enrollment of STEM baccalaureates. The Review of Higher Education,35(2), 265–305. 10.1353/rhe.2012.0007 [Google Scholar]
- Mcgurran, B. (2022). College tuition inflation: Compare the cost of college over time. Forbes.
- Menger, P. M. (2006). Artistic labor markets: Contingent work, excess supply and occupational risk management. Handbook of the Economics of Art and Culture,1, 765–811. [Google Scholar]
- Mezza, A., Ringo, D., Sherlund, S., & Sommer, K. (2020). Student loans and homeownership. Journal of Labor Economics,38(1), 215–260. 10.1086/704609 [Google Scholar]
- Mitchell, M., Leachman, M., & M. Saenz. (2019). State higher education funding cuts have pushed costs to students, worsened inequality. In Center on Budget and policy priorities.https://www.cbpp.org/research/state-budget-and-tax/state-higher-education-funding-cuts-have-pushed-costs-to-students
- National Center for Science and Engineering Statistics NCSES. (2022). National Survey of College Graduates: Survey Description. In Public use documentation. https://www.nsf.gov/statistics/srvygrads/#top
- Noonan, D. S. (2021). Arts and cultural entrepreneurship. Small Business Economics,57, 635–638. 10.1007/s11187-020-00415-y [Google Scholar]
- Nova, A. (2019). Where the 2020 Democratic candidates stand on student debt. In CNBC.https://www.cnbc.com/2019/09/21/what-the-2020-candidates-are-proposing-to-do-about-student-debt.html
- O’Brien, D., Laurison, D., Miles, A., & Friedman, S. (2016). Are the creative industries meritocratic? An analysis of the 2014 British labour force survey. Cultural Trends,25(2), 116–131. 10.1080/09548963.2016.1170943 [Google Scholar]
- Paulsen, R. J. (2021). Arts majors and the great recession: A cross-sectional analysis of educational choices and employment outcomes. Journal of Cultural Economics. 10.1007/s10824-021-09430-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Paulsen, R. J., Alper, N., & Wassall, G. (2021). Arts majors as entrepreneurs and innovators. Small Business Economics,57, 639–652. 10.1007/s11187-020-00416-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rosen, S. (1981). The economics of superstars. The American Economic Review,71(5), 845–858. [Google Scholar]
- Rothstein, J., & Rouse, C. E. (2011). Constrained after college: Student loans and early-career occupational choices. Journal of Public Economics,95, 149–163. 10.1016/j.pubeco.2010.09.015 [Google Scholar]
- Smith, K. N., & Albana, H. F. (2022). When debt deters: Student loans as a predictor of education-job match among arts bachelor’s graduates. Journal of Career Development. 10.1177/08948453221118030 [Google Scholar]
- Throsby, D. & Petetskaya, K. (2017). Marking art work: An economic study of professional artists in Australia. In Australia council for the arts.https://www.australiacouncil.gov.au/research/making-art-work/
- Throsby, D. (1986). Occupational and employment characteristics of artists. Policy and Planning Division, Australia Council.
- Throsby, D. (1994). A work-preference model of artist behaviour. In A. Peacock & I. Rizzo (Eds.), Cultural economics and cultural policies. Springer.
- Walsemann, K. M., Gee, G. C., & Gentile, D. (2015). Sick of our loans: Student borrowings and the mental health of young adults in the United States. Social Science & Medicine,124, 85–93. 10.1016/j.socscimed.2014.11.027 [DOI] [PubMed] [Google Scholar]
- Wassall, G. & Alper, N. (2018). The importance of a college major in the arts to artistic success. In National endowment for the arts working paper. https://www.arts.gov/sites/default/files/Research-Art-Works-Northeastern-rev.pdf
- White, J. C. (2013). Barriers to recognizing arts entrepreneurship education as essential to professional arts training. Artivate: A Journal of Entrepreneurship in the Arts,2(3), 28–39. [Google Scholar]
- White, J. C. (2016). Arts students in debt: Concerns, consequences, and interventions. Arts Education Policy Review,117(1), 55–64. 10.1080/10632913.2014.954088 [Google Scholar]
- Woronkowicz, J. (2021). Arts, entrepreneurship, and innovation. Journal of Cultural Economics,45, 519–526. 10.1007/s10824-021-09432-5 [Google Scholar]
- Woronkowicz, J., & Noonan, D. S. (2019). Who goes freelance? The determinants of self- employment for artists. Entrepreneurship Theory and Practice,43(4), 651–672. 10.1177/1042258717728067 [Google Scholar]
- Zhang, L. (2013). Effects of college educational debt on graduate school attendance and early career and lifestyle choices. Education Economics,21(2), 154–175. 10.1080/09645292.2010.545204 [Google Scholar]
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Data Availability Statement
All data used in this study come from publicly available sources.
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