Advertisement

Race and Social Problems

, Volume 8, Issue 1, pp 42–63 | Cite as

Young Adults’ Race, Wealth, and Entrepreneurship

  • Terri FriedlineEmail author
  • Stacia West
Article

Abstract

This study explored relationships among young adults’ wealth and entrepreneurial activities with emphasis on how these relationships differed among racial and ethnic groups. Using data from the 1997 National Longitudinal Survey of Youth, results indicated that young adults’ (N = 8984) higher accumulated amounts of wealth were associated with pursuing self-employment at higher rates; however, differences emerged when the associations were explored with various types of wealth and within racial and ethnic groups. Black young adults’ greater debt and net worth were associated with their increased likelihoods of self-employment. Among Latino/a young adults, greater liquid assets and net worth were associated with increased likelihoods of self-employment. Wealth was unrelated to white young adults’ self-employment. Wealth appeared to play an outsized role in the self-employment of black and Latino/a young adults compared to that of their white counterparts. In other words, racial and ethnic minority young adults may have a heavier burden for generating their own capital to embark on entrepreneurial activities when mainstream credit markets are unresponsive or inaccessible. Policy implications are discussed.

Keywords

Young adults Entrepreneurship Self-employment Wealth Inequality 

References

  1. Audretsch, D. (2007). Entrepreneurship and economic growth. Oxford Review of Economic Policy, 23(1), 63–78. doi: 10.1093/oxrep/grm001.CrossRefGoogle Scholar
  2. Baum, S., Ma, J., & Payea, K. (2013). Education pays 2013: The benefits of higher education for individuals and society. New York, NY: The College Board, Trends in Higher Education. Retrieved from https://trends.collegeboard.org/sites/default/files/education-pays-2013-full-report.pdf.
  3. Bell, D. (2004). Silent covenants: Brown v. Board of Education and the unfulfilled hopes for racial reform. New York, NY: Oxford University Press.Google Scholar
  4. Belman, D., & Heywood, J. (1990). Union membership, union organization and the dispersion of wages. Review of Economics and Statistics, 72, 148–153.CrossRefGoogle Scholar
  5. Blanchflower, D., Levine, P., & Zimmerman, D. (2003). Discrimination in the small-business credit market. The Review of Economics and Statistics, 85(4), 930–943. doi: 10.1162/003465303772815835.CrossRefGoogle Scholar
  6. Boshara, R., Emmons, W., & Noeth, B. (2015). The demographics of wealth: How age, education, and race separate thrivers from strugglers in today’s economy. St. Louis, MO: The Federal Reserve Bank of St. Louis. Retrieved from https://www.stlouisfed.org/~/media/Files/PDFs/HFS/essays/HFS-Essay-1-2015-Race-Ethnicity-and-Wealth.pdf.
  7. Bradford, W. (2003a). The savings and credit management of low-income, low-wealth black and white families. Economic Development Quarterly, 17(1), 53–74. doi: 10.1177/0891242402239198.CrossRefGoogle Scholar
  8. Bradford, W. (2003b). The wealth dynamics for entrepreneurship for black and white families in the U.S. Review of Income and Wealth, 49(1), 89–116.CrossRefGoogle Scholar
  9. Bradford, W. (2014). The “myth” that black entrepreneurship can reduce the gap in wealth between black and white families. Economic Development Quarterly, 28(3), 254–269. doi: 10.1177/0891242414535468.CrossRefGoogle Scholar
  10. Buera, F. J. (2009). A dynamic model of entrepreneurship with borrowing constraints: Theory and evidence. Annals of Finance, 5(3–4), 443–464.CrossRefGoogle Scholar
  11. Bureau of Labor Statistics. (2012). National Longitudinal Survey of Youth 1997 Cohort, 1997–2010 (Rounds 1–14). Columbus, OH: Center for Human Resource Research, The Ohio State University.Google Scholar
  12. Bureau of Labor Statistics. (2015). Labor force statistics from the Current Population Survey. Washington, DC: United States Department of Labor, Bureau of Labor Statistics. Retrieved from http://www.bls.gov/web/empsit/cpsee_e16.htm.
  13. Card, D., & DiNardo, J. (2002). Skill-based technological change and rising wage inequality: Some problems and puzzles. Journal of Labor Economics, 20, 733–783.CrossRefGoogle Scholar
  14. Casner-Lotto, J., & Barrington, L. (2006). Are they really ready to work? Okemos, MI: The Conference Board, Inc., the partnership for 21st century skills, corporate voices for working families, and the society for human resources management. Retrieved from http://www.p21.org/storage/documents/FINAL_REPORT_PDF09-29-06.pdf.
  15. Chatterji, A., & Seamans, R. (2012). Entrepreneurial finance, credit cards, and race. Journal of Financial Economics, 106(1), 182–195. doi: 10.1016/j.jfineco.2012.04.007.CrossRefGoogle Scholar
  16. Clifton, J. (2015). American entrepreneurship: Dead or alive? Washington, DC: GALLUP. Retrieved from http://www.gallup.com/businessjournal/180431/american-entrepreneurship-dead-alive.aspx.
  17. Collins, C. (2013). The economic context: Growing disparities in income and wealth. New England Journal of Public Policy, 24(1), 49–61.Google Scholar
  18. Cox, N. (2006). WINSOR: Stata module to Winsorize a variable. Chestnut Hill, MA: Boston College, Department of Economics. Retrieved from http://ideas.repec.org/c/boc/bocode/s361402.html#related.
  19. D’Agostino, R. B., Jr. (1998). Tutorial in biostatistics: Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Statistics in Medicine, 17, 2265–2281. doi: 10.1002/(SICI)1097-0258(19981015)17:19<2265:AID-SIM918>3.0.CO;2-B.CrossRefGoogle Scholar
  20. Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood for incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B (Methodological), 39(1), 1–38.Google Scholar
  21. Dettling, L., & Hsu, J. (2014). The state of young adults’ balance sheets: Evidence from the Survey of Consumer Finances. The Federal Reserve Bank of St. Louis Review, 96(4), 305–330.Google Scholar
  22. Elliott, W., & Lewis, M. (2015). The real college debt crisis: How student borrowing threatens financial well-being and erodes the American Dream. Santa Barbara, CA: ABC-CLIO LLC.Google Scholar
  23. Evans, D. S., & Jovanovic, B. (1989). An estimated model of entrepreneurial choice under liquidity constraints. The Journal of Political Economy, 97(4), 808–827.CrossRefGoogle Scholar
  24. Ewing Marion Kauffman Foundation. (2014). The state of entrepreneurship address. Kansas City, MO: Ewing Marion Kauffman Foundation. Retrieved from http://www.kauffman.org/~/media/kauffman_org/research%20reports%20and%20covers/2014/02/state_of_entrepreneurship_address_2014.pdf.
  25. Fairlie, R. W. (2004). Does business ownership provide a source of upward mobility for blacks and Hispanics? In D. Holtz-Eakin & H. Rosen (Eds.), Public policy and the economics of entrepreneurship (pp. 153–180). Cambridge, MA: Massachusetts Institute of Technology.Google Scholar
  26. Fairlie, R. W. (2005). Entrepreneurship and earnings among young adults from disadvantaged families. Small Business Economics, 25(3), 223–236.CrossRefGoogle Scholar
  27. Fairlie, R. W. (2011). Entrepreneurship, economic conditions, and the Great Recession. Santa Cruz, CA: University of California, Department of Economics.Google Scholar
  28. Fairlie, R. (2014). Kauffman index of entrepreneurial activity: 19962013. Kansas City, MO: Ewing Marion Kauffman Foundation. Retrieved from http://www.kauffman.org/~/media/kauffman_org/research%20reports%20and%20covers/2014/04/kiea_2014_report.pdf.
  29. Fairlie, R. W., & Krashinsky, H. A. (2012). Liquidity constraints, household wealth, and entrepreneurship revisited. Review of Income and Wealth, 58(2), 279–306.CrossRefGoogle Scholar
  30. Feagan, J., & Imani, N. (1994). Racial barriers to African American entrepreneurship: An exploratory study. Social Problems, 41(4), 562–584.CrossRefGoogle Scholar
  31. Federal Deposit Insurance Corporation. (2014). 2013 FDIC national survey of unbanked and underbanked households. Washington, DC: FDIC. Retrieved from https://www.fdic.gov/householdsurvey/2013execsumm.pdf
  32. Findlay, P., Kalleberg, A., & Warhurst, C. (2013). The challenge of job quality. Human Relations, 66(4), 441–451. doi: 10.1177/0018726713481070.CrossRefGoogle Scholar
  33. Friedline, T., & Freeman, A. (2016). The potential for savings accounts to protect young adults from unsecured debt in periods of macroeconomic stability and decline. Social Service Review, 90(1).Google Scholar
  34. Friedline, T., Johnson, P., & Hughes, R. (2014). Toward healthy balance sheets: Are savings accounts a gateway to young adults’ asset diversification and accumulation? Federal Reserve Bank of St. Louis Review, 96(4), 359–389.Google Scholar
  35. Friedline, T., & Rauktis, M. (2014). Young people are the front lines of financial inclusion: A review of 45 years of research. Journal of Consumer Affairs, 48(3), 535–602. doi: 10.1111/joca.12050.CrossRefGoogle Scholar
  36. Friedline, T., & Song, H. (2013). Accumulating assets, debts in young adulthood: Children as potential future investors. Children and Youth Services Review, 35(9), 1486–1502. doi: 10.1016/j.childyouth.2013.05.013.CrossRefGoogle Scholar
  37. Fry, R. (2014). Young adults, student debt and economic well-being. Washington, DC: Pew Research Center. Retrieved from http://www.pewsocialtrends.org/2014/05/14/young-adults-student-debt-and-economic-well-being/
  38. Goodman, M., Sands, A., & Coley, R. (2015). America’s skills challenge: Millennials and the future. Princeton, NJ: Educational Testing Service, Center for Research on Human Capital and Education. Retrieved from http://www.ets.org/s/research/30079/asc-millennials-and-the-future.pdf.
  39. Guo, S., & Fraser, W. M. (2010). Propensity score analysis: Statistical methods and applications. Thousand Oaks, CA: Sage.Google Scholar
  40. Hipple, S. (2010). Self-employment in the United States. Washington, DC: Bureau of Labor Statistics. Retrieved from http://www.bls.gov/opub/mlr/2010/09/art2full.pdf.
  41. Holtz-Eakin, D., Rosen, H., & Weathers, R. (2000). Horatio Alger meets the mobility tables. Small Business Economics, 14(4), 243–274.CrossRefGoogle Scholar
  42. Houle, J. (2013). Disparities in debt: Parents’ socioeconomic resources and young adult student loan debt. Sociology of Education, Online First,. doi: 10.1177/0038040713512213.Google Scholar
  43. Houle, J., & Berger, L. (2014). Is student loan debt discouraging home buying among young adults? Hanover, NH: Dartmouth College. Retrieved from http://www.cfpbmonitor.com/files/2014/06/Is_Student_Loan_Debt_Discouraging_Home_Buying_Among_Young_Adults1.pdf.
  44. Hurst, E., & Lusardi, A. (2004). Liquidity constraints, household wealth, and entrepreneurship. Journal of Political Economy, 112(2), 319–347.CrossRefGoogle Scholar
  45. Institute for Local Self-Reliance. (2014). Access to capital for local businesses. Washington, DC: Institute for Local Self-Reliance. Retrieved from http://ilsr.org/rule/financing-local-businesses/.
  46. Kim, P. H., Aldrich, H. E., & Keister, L. A. (2006). Access (not) denied: The impact of financial, human, and cultural capital on entrepreneurial entry in the United States. Small Business Economics, 27(1), 5–22.CrossRefGoogle Scholar
  47. King, G., & Zeng, L. (2001). Logistic regression in rare events data. Political Analysis, 9, 137–163. Retrieved from http://gking.harvard.edu/gking/files/abs/0s-abs.shtml.
  48. Köllinger, P., & Minniti, M. (2006). Not for lack of trying: American entrepreneurship in black and white. Small Business Economics, 27(1), 59–79. doi: 10.1007/s11187-006-0019-6.CrossRefGoogle Scholar
  49. Krogstad, J. M. (2015). 114th Congress is most diverse ever. Washington, DC: Pew Research Center. Retrieved from http://www.pewresearch.org/fact-tank/2015/01/12/114th-congress-is-most-diverse-ever/.
  50. Krogstad, J. M., & Fry, R. (2012). More Hispanics, blacks enrolling in college, but lag in bachelor’s degrees. Washington, DC: Pew Research Center. Retrieved from http://www.pewresearch.org/fact-tank/2014/04/24/more-hispanics-blacks-enrolling-in-college-but-lag-in-bachelors-degrees/.
  51. Levy, F., & Kochan, T. (2012). Addressing the problem of stagnant wages. Comparative Economic Studies, 54, 739–764. doi: 10.1057/ces.2012.28.CrossRefGoogle Scholar
  52. Lusardi, A., Schneider, D., & Tufano, P. (2011). Financially fragile households: Evidence and implications (NBER Working Paper No. 17072). Cambridge, MA: National Bureau of Economic Research.Google Scholar
  53. Lynn, L., & Salzman, H. (2010). The globalization of technology development: Implications for US skills policy. In D. Finegold, M. Gatta, H. Salzman, & S. Schurman (Eds.), Transforming the US workforce development system: Lessons from research and practice (pp. 57–86). Ithaca, NY: Cornell University Press/ILR Press Book.Google Scholar
  54. Mishel, L., Bivens, J., Gould, E., & Shierholz, H. (2012). The state of working America (12th ed.). Ithaca, NY: Cornell University Press.Google Scholar
  55. Oliver, M., & Shapiro, T. (2006). Black wealth/white wealth: A new perspective on racial inequality. New York, NY: Taylor and Francis Group.Google Scholar
  56. Paulsen, D., Platt, M., Huettel, S., & Brannon, E. (2012). From risk-seeking to risk-averse: The development of economic risk preference from childhood to adulthood. Frontiers in Psychology, 3(313), 1–6. doi: 10.3389/fpsyg.2012.00313.Google Scholar
  57. Piketty, T. (2014). Capital in the twenty-first century. Cambridge, MA: Belknap Press.CrossRefGoogle Scholar
  58. Price, D. (2004). Borrowing inequality: Race, class, and student loans. Boulder, CO: Lynne Rienner Publishers.Google Scholar
  59. Rose, R. A., & Fraser, M. W. (2008). A simplified framework for using multiple imputation in social work research. Social Work Research, 32(3), 171–178. doi: 10.1093/swr/32.3.171.CrossRefGoogle Scholar
  60. Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York, NY: Wiley.CrossRefGoogle Scholar
  61. Ryan, B. (2014). Starved of financing, new businesses are in decline. Washington, DC: GALLUP. Retrieved from http://www.gallup.com/businessjournal/175499/starved-financing-new-businesses-decline.aspx.
  62. Shapiro, T., Meschede, T., & Osoro, S. (2013). The roots of the widening racial wealth gap: Explaining the blackwhite economic divide. Waltham, MA: Brandeis University, Institute on Assets and Social Policy. Retrieved from http://iasp.brandeis.edu/pdfs/Author/shapiro-thomas-m/racialwealthgapbrief.pdf.
  63. Sironi, M., & Furstenberg, F. (2012). Trends in the economic independence of young adults in the United States: 1973–2007. Population and Development Review, 38(4), 609–630.CrossRefGoogle Scholar
  64. Sullivan, L., Meschede, T., Dietrich, L., Shapiro, T., Traub, A., Ruetschlin, C., et al. (2014). The racial wealth gap: Why policy matters. New York, NY: Demos. Retrieved from http://www.demos.org/sites/default/files/publications/RacialWealthGap_1.pdf.
  65. Taylor, P., Kochhar, R., Fry, R., Velasco, G., & Motel, S. (2011). Wealth gaps rise to record highs between whites, blacks, and Hispanics. Washington, DC: Pew Research Center. Retrieved from http://www.pewsocialtrends.org/files/2011/07/SDT-Wealth-Report_7-26-11_FINAL.pdf.
  66. Tomz, M., King, G., & Zeng, L. (2003). ReLogit: Rare events logistic regression. Journal of Statistical Software, 8(2), 137–163.Google Scholar
  67. US Department of Labor. (2014). Employment and unemployment among youth summary. Washington, DC: US Department of Labor, Bureau of Labor Statistics. Retrieved from http://www.bls.gov/news.release/youth.nr0.htm.
  68. US Small Business Administration. (2013). Small business lending in the United States, 2012. Washington, DC: US Small Business Administration, Office of Advocacy. Retrieved from https://www.sba.gov/sites/default/files/files/sbl_12study.pdf.
  69. van Stel, A., Carree, M., & Thurik, R. (2005). The effect of entrepreneurial activity on national economic growth. Small Business Economics, 24(3), 311–321. doi: 10.1007/s11187-005-1996-6.CrossRefGoogle Scholar
  70. Vowels, S. (2015). Economic impact report: The effects of NMSDC certified minority businesses enterprises on the U.S. economy. Retrieved from http://www.nmsdc.org/wp-content/uploads/Economic_Impact_Report_FINAL.pdf.
  71. Wennekers, S., & Thurik, R. (1999). Linking entrepreneurship and economic growth. Small Business Economics, 13(1), 27–56. doi: 10.1023/A:1008063200484.CrossRefGoogle Scholar
  72. Western, B., & Rosenfeld, J. (2011). Unions, norms, and the rise in US wage inequality. American Sociological Review, 76(4), 513–537. doi: 10.1177/0003122411414817.CrossRefGoogle Scholar
  73. Winograd, M., & Hais, M. (2014). How Millennials could upend Wall Street and corporate America. Washington, DC: Brookings Institution, Governance Studies. Retrieved from http://www.brookings.edu/~/media/research/files/papers/2014/05/millennials%20wall%20st/brookings_winogradv5.pdf.

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.School of Social WelfareUniversity of KansasLawrenceUSA
  2. 2.School of Social WelfareUniversity of KansasLawrenceUSA

Personalised recommendations