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Managing Factors That Correlate to High Cohort Default Rate at Public 2-Year Community Colleges in Michigan

DOI: 10.4236/jfrm.2023.124018, PP. 328-365

Keywords: Michigan, Student Loan Debt, National Data, Federal Financial Aid, Variables Affecting Student Loan Default, Repayment, Age, Gender, Ethnicity/Race

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Abstract:

Community colleges serve more than a considerable proportion of Americans who could not otherwise attend colleges by providing access to fulfill their educational goals. Many of the students enrolled in the institutions look to the federal government to finance their educational expenses by obtaining federally guaranteed student loans. The borrowers who default on their student loans cut across race, gender, and age, with Blacks and Hispanic American males more likely to default. The research problem addressed in this quantitative correlational study was the high cohort default rates at 26 public 2-year community colleges in Michigan. The high cohort default rates present problems to the institutions’ ability to generate revenue to meet educational budgets. The purpose of this quantitative correlational study was to identify variables associated with student loan default in the 26 public 2-year community colleges in Michigan. The study was guided by the conceptual framework of the student-institution fit model, focusing on individual student attributes and institution-level variables that accounted for the willingness to repay behavior. A quantitative methodology with a nonexperimental design was used to address the research questions. Secondary data were extracted from the National Student Loan Data System and the Integrated Postsecondary Education Data System. The results for all the research questions showed that the assumptions of normality, homoscedasticity, and absence of multicollinearity tests were met, and null hypotheses were not rejected. The study’s findings showed that institution-level factors did not significantly predict student loan default among borrowers but rather individual characteristics. I recommended future research to explore default patterns among borrowers in public 2-year community colleges after the COVID-19 crisis in terms of federal government policies that could result in a recommendation for practice for institutions. The practice recommendations included institutions developing a financial aid education and outreach program, a default prevention guide, and special attention to students eligible for Pell Grants.

References

[1]  Addo, F. R., Houle, J. N., & Simon, D. (2016). Young, Black, and Still in the Red: Parental Wealth, Race, and Student Loan Debt. Race and Social Problems, 8, 64-76.
https://doi.org/10.1007/s12552-016-9162-0
[2]  Akers, B., & Chingos, M. (2016). The Game of Loans: The Rhetoric and Reality of Student Debt. Princeton University Press.
https://doi.org/10.1515/9781400883271
[3]  Anderson, T. (2017). More than 1.1 Million Borrowers Defaulted on Their Federal Student Loans Last Year. CNBC.
https://www.cnbc.com/2017/03/14/more-than-11-million-borrowers-defaulted-on-their-federal-student-loans-last-year.html
[4]  Bailey, T., & Smith, J. S. (2016). When College Students Start Behind. The Century Foundation.
[5]  Baker, A. R., Andrews, B. D., & McDaniel, A. (2017). The Impact of Student Loans on College Access, Completion, and Returns. Sociology Compass, 11, e12480.
https://doi.org/10.1111/soc4.12480
[6]  Banks, T., & Dohy, J. (2019). Mitigating Barriers to Persistence: A Review of Efforts to Improve Retention and Graduation Rates for Student of Color in Higher Education. Higher Education Studies, 9, 118-131.
https://doi.org/10.5539/hes.v9n1p118
[7]  Barone, S., Steiner, M., & Teszler, N. (2005). Multivariate Analysis of Student Loan Defaulters at Texas A&M University. Texas Guaranteed Research and Analytical Services.
[8]  Barr, J. (2020). The Impact of Organizational Structure at Multi-Campus Community Colleges on Student Access, Equity, and Completion. Doctoral Dissertation, University of Maryland University College.
[9]  Baum, S. (2016). Trends in Student Aid 2016. In Trends in Higher Education Series.
https://research.collegeboard.org/media/pdf/trends-student-aid-2016-full-report.pdf
[10]  Belfield, C. R. (2013). Student Loans and Repayment Rates: The Role of For-Profit Colleges. Research in Higher Education, 54, 1-29.
https://doi.org/10.1007/s11162-012-9268-1
[11]  Bipartisan Policy Center (2021). Income-Driven Plans. U.S. Department of Education Office of Federal Student Aid.
https://bipartisanpolicy.org/
[12]  Blagg, K. (2018). Underwater on Student Loan Debt: Understanding Consumer Credit and Student Loan Default. Research Report, Urban Institute.
https://www.urban.org/sites/default/files/publication/98884/underwater_on_student_debt_0.pdf
[13]  Bryman, A., & Bell, E. (2015). Business Research Method (4th ed.). Oxford University Press.
[14]  Cabrera, A. F., Nora, A., & Castañeda, M. B. (1992). The Role of Finances in the Persistence Process: A Structural Model. Research in Higher Education, 33, 571-593.
https://doi.org/10.1007/BF00973759
[15]  Callender, C., & Mason, G. (2017). Does Student Loan Debt Deter Higher Education Participation? New Evidence from England. The Annals of the American Academy of Political and Social Science, 671, 20-48.
https://doi.org/10.1177/0002716217696041
[16]  Campbell, C., & Hillman, N. H. (2015). A Closer Look at the Trillion: Borrowing, Repayment, and Default at Iowa’s Community Colleges. Association of Community College Trustees.
https://www.acct.org/product/closer-look-trillion-borrowing-repayment-and-default-iowas-community-colleges-2015
[17]  Campbell, C., & Love, L. (2017). Lost in the Trillion: A Three-State Comparison of Community College Borrowing and Default. The Association of Community College Trustees.
[18]  Canche, M. S. G. (2020). Community College Students Who Attained a 4-Year Degree Accrued Lower Student Loan Debt than 4-Year Entrants over 2 Decades: Is a 10 Percent Debt Accumulation Reduction Worth the Added “Risk”? If So, for Whom? Research in Higher Education, 61, 871-915.
https://doi.org/10.1007/s11162-019-09565-9
[19]  Castonguay, A. (2019). An Economic Analysis of Student Loan Default. Master’s Dissertation, University of Maine.
https://digitalcommons.library.umaine.edu/etd/2965/#:~:text=
https%3A//digitalcommons.library.umaine.edu/etd/2965
[20]  Chamberlain, L. (2019). Student Loan Default Prevention and Management Practices at Mississippi Community College and Junior Colleges. Doctoral Dissertations, University of Southern Mississippi.
https://aquila.usm.edu/dissertations
[21]  Charles, K. D., Sheaff, S., Woods, J., & Downey, L. (2016). Decreasing Your Student Loan Cohort Default Rate: Leading a College-Wide Change Initiative at Mohave Community College. Community College Journal of Research and Practice, 40, 597-606.
https://doi.org/10.1080/10668926.2015.1125814
[22]  Chen, X., & Simone, S. (2016). Remedial Course-Taking at U.S. Public 2 and 4-Year Institutions: Scope, Experiences, and Outcomes. National Center for Education Statistics.
https://nces.ed.gov/pubs2016/2016405.pdf
[23]  Chrisman, D. E. (2015). Multiple Realities: Characteristics of Loan Defaulters at a Two-Year Public Institution. Community College Review, 27, 16-32.
https://doi.org/10.1177/009155210002700402
[24]  Clayton, K., Wessel, R. D., McAtee, J., & Knight, W. E. (2019). KEY Careers: Increasing Retention and Graduation Rates with Career Interventions. Journal of Career Development, 46, 435-439.
https://doi.org/10.1177/0894845318763972
[25]  Congressional Research Service (2020). The Higher Education Act (HEA): A Primer.
https://sgp.fas.org/crs/misc/R43351.pdf
[26]  Creswell, J. W. (2014). Research Design: Quantitative, Qualitative, and Mixed Methods Approaches. Sage.
[27]  Creswell, J. W., & Creswell, J. D. (2017). Qualitative Methods. Research Design: Qualitative, Quantitative, and Mixed Methods Approach. Sage.
[28]  Dillon, E., & Smiles, R. V. (2010). Lowering Student Loan Default Rates: What One Consortium of Historically Black Institutions Did to Succeed. Education Sector Reports.
[29]  Dynarski, S. (2016). The Trouble with Student Loans? Low Earnings, Not High Debt. Brookings Institution.
https://www.brookings.edu/research/the-trouble-with-student-loans-low-earnings-not-high-debt
[30]  Dynarski, S. (2018). Susan Dynarski Testifies on Student Loans before U.S. Senate HELP Committee.
https://fordschool.umich.edu/news/2018/dynarski-testifies-student-loans-us-senate-help-committee
[31]  Edmiston, K. D., Brooks, L., & Shepelwich, S. (2013). Student Loans: Overview and Issues. Federal Reserve Bank of Kansas City Research Working Paper, 12-05.
https://doi.org/10.2139/ssrn.2137243
[32]  Elliott, W., & Rauscher, E. (2018). When Does My Future Begin? Student Debt and Intragenerational Mobility. Sociology Mind, 8, 175-201.
https://doi.org/10.4236/sm.2018.82015
[33]  Farrugia, P., Petrisor, B. A., Farrokhyar, F., & Bhandari, M. (2010). Practical Tips for Surgical Research: Research Questions, Hypotheses, and Objectives. Canadian Journal of Surgery, 53, 278-281.
[34]  Flint, T. A. (1997). Predicting Student Loan Defaults. The Journal of Higher Education, 68, 322-354.
https://doi.org/10.1080/00221546.1997.11778986
[35]  Friedman, Z. (2021). Student Loan Debt Statistics in 2021: A Record $1.7 Trillion. Forbes.
https://www.forbes.com/sites/zackfriedman/2021/02/20/student-loan-debt-statistics-in-2021-a-record-17-trillion/?sh=170df9fd1431
[36]  Galloway, F. J., & Swail, W. S. (1999). Institutional Retention Strategies at Historically Black Colleges and Universities and Their Effects on Cohort Default Rates: 1997-1995. Monograph Series.
[37]  Ganem, N. M., & Manasse, M. (2011). The Relationship between Scholarships and Student Success: An Art and Design Case Study. Education Research International, 2011, Article ID: 743120.
https://doi.org/10.1155/2011/743120
[38]  Goodell, J. W. (2016). Do For-Profit Universities Induce Bad Student Loans? The Quarterly Review of Economics and Finance, 61, 173-184.
https://doi.org/10.1016/j.qref.2016.02.003
[39]  Gross, J. P. K., Cekie, O., Hossler, D., & Hillman, N. (2009). What Matters in Student Loan Default? A Review of the Research Literature. Journal of Student Financial Aid, 39, 19-29.
https://doi.org/10.55504/0884-9153.1032
[40]  Harrast, S. A. (2004). Undergraduate Borrowing: A Study of Debtor Students and Their Ability to Retire Undergraduate Loans. Journal of Student Financial Aid, 34, 21-37.
https://doi.org/10.55504/0884-9153.1081
[41]  Head, B. A. (2019). Understanding Community College Student Perception of Success beyond Traditional Measures of Persistence and Degree Attainment. The University of Alabama.
http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:13809265
[42]  Hepworth, D., Littlepage, B., & Hancock, K. (2018). Factors Influencing University Student Academic Success. Educational Research Quarterly, 42, 45-61.
[43]  Herr, E., & Burt, L. (2005). Predicting Student Loan Default for the University of Texas at Austin. Journal of Student Financial Aid, 36, 34-52.
https://doi.org/10.55504/0884-9153.1072
[44]  Hillman, N. W. (2015). Cohort Default Rates: Predicting the Probability of Federal Sanctions. Educational Policy, 29, 559-582.
https://doi.org/10.1177/0895904813510772
[45]  Hinton-Smith, T. (2016). Negotiating the Risk of Debt-Financed Higher Education: The Experience of Lone Parent Student. British Educational Research Journal, 42, 207-222.
https://doi.org/10.1002/berj.3201
[46]  Hordosy, R., Clark, T., & Vickers, D. (2018). Lower-Income Students and the Double Deficit of Part-Time Work: Undergraduate Experiences of Finance, Studying and Employability. Journal of Education and Work, 31, 353-365.
https://doi.org/10.1080/13639080.2018.1498068
[47]  Inge, B. (2017). Factors Associated with Federal Student Loan Default among Borrowers in a Statewide System of Community and Technical Colleges. Doctoral Dissertation, University of Louisville.
[48]  Ionescu, A. F., & Ionescu, A. M. (2014). The Interplay between Student Loans and Credit Card Debt: Implications for Default in the Great Recession.
https://www.federalreserve.gov/econres/feds/the-interplay-between-student-loans-and-credit-card-debt-implications-for-default-in-the-great-recession.htm
https://doi.org/10.2139/ssrn.2399182
[49]  Ionescu, F., & Simpson, N. (2016). Default Risk and Private Student Loans: Implications for Higher Education Policies. Journal of Economic Dynamics & Control, 64, 119-147.
https://doi.org/10.1016/j.jedc.2015.12.003
[50]  Ishitani, T. T., & McKitrick, S. A. (2016). Are Student Loan Default Rates Linked to Institutional Capacity? Journal of Student Financial Aid, 46, 17-37.
https://doi.org/10.55504/0884-9153.1557
[51]  Jaquette, O., & Hillman, N. W. (2015). Paying for Default: Change over Time in the Share of Federal Financial Aid Sent to Institutions with High Student Loan Default Rates. Journal of Student Financial Aid, 45, Article 2.
https://ir.library.louisville.edu/jsfa/vol45/iss1/2
https://doi.org/10.55504/0884-9153.1543
[52]  Kelchen, R. (2019). Do High Cohort Default Rates Affect Student Living Allowances and Debt Burdens? An Empirical Analysis. Journal of Student Financial Aid, 49, Article 3.
https://ir.library.louisville.edu/jsfa/vol49/iss1/3
https://doi.org/10.55504/0884-9153.1648
[53]  Knapp, L. G., & Seaks, T. G. (1992). An Analysis of the Probability of Default on Federally Guaranteed Student Loans. The Review of Economics and Statistics, 74, 404-411.
https://doi.org/10.2307/2109484
[54]  Kool, T. G., & Seaks, T. G. (2021). Evaluation of the Macro and Micro Economic Factors Affecting the Financial Energy of Households. Energies, 14, Article 3512.
https://doi.org/10.3390/en14123512
[55]  Lochner, L. J., & Monge-Naranjo, A. (2015). Default and Repayment among Baccalaureate Degree Earners. In B. Hershbein, & K. M. Hollenbeck (Eds.), Student Loans and the Dynamics of Debt (pp. 235-286). W.E. Upjohn Institute for Employment Research.
https://doi.org/10.17848/9780880994873.ch8
[56]  Lochner, L., Stinebrickner, T., & Suleymanoglu, U. (2013). Analysis of the CSLP Student Loan Defaulter Survey and Client Satisfaction Surveys. University of Western Ontario, CIBC Center for Human Capital and Productivity.
https://economic.uwo.ca/cibc/workingpapers_docs/docs/wp2013/Lochner_Stinebrickner_Suleymanoglu03.pdf
[57]  Looney, A., & Yannelis, C. (2015). A Crisis in Student Loans? How Changes in the Characteristics of Borrowers and in the Institutions They Attended Contributed to Rising Loan Defaults. Brookings Papers on Economic Activity, 2, 1-89.
https://doi.org/10.1353/eca.2015.0003
[58]  Luna-Torres, M., McKinney, L., Horn, C., & Jones, S. (2018). Understanding Loan Use and Debt Burden among Low-Income and Minority Students at a Large Urban Community College. Journal of Student Financial Aid, 48, Article 2.
https://doi.org/10.55504/0884-9153.1619
[59]  McKinney, L., Gross, J. P. K., & Inge, B. (2014). Understanding Federal Loan Borrowing, Repayment, and Default among Community College Students. In The Annual Meeting of the Association for the Study of Higher Education.
[60]  McKinney, L., Gross, J. P., Burridge, A., Inge, B., & Williams, A. (2021). Understanding Loan Default among Community College Students. Community College Review, 49, 314-342.
https://doi.org/10.1177/00915521211001467
[61]  McKinney, L., Novak, H., & Hagedorn, L. S. (2016). Borrowing among Academically Underprepared Students: Facilitating Success or Perpetuating Inequity at the Community College? Greater Texas Foundation.
[62]  McVicar, B. (2017). Michigan Student Loan Default Rate on the Rise. Michigan Live.
https://www.mlive.com/news/2017/09/michigans_student_loan_default.html#
[63]  Mezza, A. A., & Sommer, K. (2015). A Trillion-Dollar Question: What Predicts Student Loan Delinquencies? Finance and Economics Discussions, 95, 1-47.
https://doi.org/10.17016/feds.2015.098
[64]  Millea, M., Wills, R., Elder, A., & Molina, D. (2018). What Matters in College Student Success? Determinants of College Retention and Graduation Rates. Education, 138, 309-322.
[65]  Millian, R. P., Zarifa, D., & Seward, B. (2021). Paying Back Student Loans: Demographic, Human Capital, and Other Correlates of Defaults and Repayment Difficulty. Higher Education Quarterly, 75, 77-97.
[66]  Montalto, C. P., Phillips, E. L., McDaniel, A., & Baker, A. R. (2019). College Student Financial Wellness: Student Loans and Beyond. Journal of Family & Economic Issues, 40, 3-21.
https://doi.org/10.1007/s10834-018-9593-4
[67]  Mueller, H. M., & Yannelis, C. (2019). Reducing Barriers to Enrollment in Federal Student Loan Repayment Plans: Evidence from the Navient Field Experiment.
https://cmepr.gmu.edu/wp-content/uploads/2019/08/MuellerYannelis.pdf
[68]  National Center for Education Statistics (2023). Your Primary Source for Information on U.S. Colleges, Universities, and Technical and Vocational Institutions.
[69]  Nyahende, V. R. (2013). The Influence of Students’ Loan Borrowers’ Characteristics on Default Rate in Tanzania. Higher Education Studies, 3, 26-49.
https://doi.org/10.5539/hes.v3n4p26
[70]  Odle, T. K., Lee, J. C., & Gentile, S. P. (2021). Do Promise Programs Reduce Student Loans? Evidence from Tennessee Promise. The Journal of Higher Education, 92, 847-876.
https://doi.org/10.1080/00221546.2021.1888674
[71]  Park, H. (2013). An Introduction to Logistic Regression: From Basic Concepts to Interpretation with Particular Attention to the Nursing Domain. Journal of Korean Academy of Nursing, 43, 154-164.
https://doi.org/10.4040/jkan.2013.43.2.154
[72]  Perna, L. W., Kvaal, J., & Ruiz, R. (2017). Understanding Student Debt: Implications for Federal Policy and Future Research. The Annals of the American Academy of Political and Social Sciences, 671, 270-286.
https://doi.org/10.1177/0002716217704002
[73]  Pew Research (2019). Institutional Eligibility for Participation in Title IV Student Financial Aid Programs. Congressional Research Service, R43159.
https://crsreports.congress.gov
[74]  Podgursky, M., Ehlert, M., Monroe, R., Watson, D., & Wittstruck, J. (2002). Student Loan Defaults and Enrollment Persistence. Journal of Student Financial Aid, 32, 27-42.
https://doi.org/10.55504/0884-9153.1184
[75]  Price, D. V., & Tovar, E. (2014). Student Engagement and Institutional Graduation Rates: Identifying High-Impact Educational Practices for Community Colleges. Community College Journal of Research and Practice, 39, 766-782.
https://doi.org/10.1080/10668926.2012.719481
[76]  Princeton Review (2021). A Test Used by Most Higher Institutions to Make Admissions Decisions. The Princeton Review.
https://www.princetonreview.com/college/act-information
[77]  Sampson, J. P., Hooley, T., & Marriot, J. (2011). Fostering College and Career Readiness: How Career Development Activities in Schools Impact on Graduation Rates and Students’ Life Success. International Center for Guidance Studies.
[78]  Sattelmeyer, S., Denten, B., Spencer, O., Remedios, J., Williams, R., & Willson, C. (2019). Student Loan System Presents Repayment Challenges. Borrowers at Risk of Default and Delinquency Need Flexibility and Targeted, Timely Support. Pew Charitable Trusts Report.
https://www.pewtrusts.org/en/research-and-analysis/reports/2019/11/student-loan-system-presents-repayment-challenges
[79]  Saunders, M., Lewis, P., & Thornhill, A. (2007). Research Methods for Business Students (4th ed.). Prentice-Hall.
[80]  Scott-Clayton, J., & Li, J. (2016). Black-White Disparity in Student Loan Debt More than Triples after Graduation: Evidence Speaks Reports. The Brookings Institution.
[81]  Sekaran, U., & Bougie, R. (2016). Quantitative Data Analysis: Hypothesis Testing 300. In Research Methods for Business: A Skill Building Approach (7th ed., pp. 300-331). Wiley.
[82]  Seyedian, M., & Yi, T. D. (2011). Improving Financial Literacy of College Students: A Cross-Sectional Analysis. College Student Journal, 45, 177-189.
[83]  Steiner, M., & Barone, S. (2014). Detecting Early Signs of Default Risk at Austin Community College. Texas Guaranteed Research and Analytical Services.
[84]  Stoddard, C., Urban, C., & Schmeiser, M. D. (2018). College Financing Choices and Academic Performance. Journal of Consumer Affairs, 52, 540-561.
https://doi.org/10.1111/joca.12175
[85]  TICAS (2019). Driving Down Fault: How to Strengthen the Cohort Default Rate to Further Reduce Federal Student Loan Default Risk. The Institute for College Access and Success.
https://ticas.org/wp-content/uploads/2019/11/Driving-Down-Default.pdf
[86]  Tudor, T. R. (2018). Fully Integrating Academic Advising with Career Coaching to Increase Student Retention, Graduation Rates and Future Job Satisfaction: An Industry Approach. Industry and Higher Education, 32, 73-79.
https://doi.org/10.1177/0950422218759928
[87]  U.S. Department of Education (2016). Student Loan Delinquency and Default. U.S. Department of Education Office of Federal Student Loan Aid.
[88]  U.S. Department of Education (2019). National Student Loan Data System.
[89]  U.S. Department of Education (2021). FY2018 Official 3-Year Default Rates.
[90]  Volkwein, F. J., Szelest, B. P., Cabrera, A. F., & Napierski-Pracl, M. R. (1998). Factors Associated with Student Loan Default among Different Racial and Ethnic Groups. The Journal of Higher Education, 69, 206-237.
https://doi.org/10.2307/2649206
[91]  Volkwein, J. F., & Szelest, B. P. (1995). Individual and Campus Characteristics Associated with Student Loan Default. Research in Higher Education, 36, 41-72.
https://doi.org/10.1007/BF02207766
[92]  Webber, K. L., & Rogers, S. L. (2014). Student Loan Default: Do Characteristics of Four-Year Institutions Contribute to the Puzzle? Journal of Student Financial Aid, 44, Article 2.
https://doi.org/10.55504/0884-9153.1541
[93]  Westfall, P. H., & Henning, K. S. S. (2013). Texts in Statistical Science. Understanding Advanced Statistical Methods. Taylor & Francis.
https://doi.org/10.1201/b14398
[94]  White, H. (1980). A Heteroscedasticity-Consistent Covariance Estimator and a Direct Test for Heteroscedasticity. Econometrica, 14, 817-838.
https://doi.org/10.2307/1912934
[95]  Wilcox, L. (1991). Evaluating the Impact of Financial Aid on Student Recruitment and Retention. New Directions for Institutional Research, 1991, 47-60.
https://doi.org/10.1002/ir.37019917006
[96]  Wilkinson, R. B., Taylor, J. S., Peterson, A., & Machado-Taylor, M. D. (2007). A Practical Guide to Strategic Enrollment Management Planning.
https://files.eric.ed.gov/fulltext/ED499875.pdf
[97]  Woo, J. H. (2002). Factors Affecting the Probability of Default: Student Loans in California. Journal of Student Financial Aid, 32, 5-23.
https://doi.org/10.55504/0884-9153.1179

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