Self-employment of older Americans: do recessions matter?

Abstract

As high unemployment rates linger following the latest recession, job opportunities can be sparse, especially for older workers. This might prompt older Americans to seek out opportunities in self-employment. Alternatively, recession-related decreases in economic activity might make self-employment less attractive. Using the Health and Retirement Study, we find that unemployed respondents are more likely to enter self-employment and that these decisions are clearly affected by recessions, although the effects differ by recession and gender. Unlike men, women’s self-employment decisions are very sensitive to other sources of household income, and women are less likely to become self-employed the deeper the recession.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

Notes

  1. 1.

    Although they constitute a larger portion of the self-employed, the percentage of older workers who are self-employed has actually fallen over this time period (from 13.3 percent to 11.9 percent).

  2. 2.

    It is also possible that the payment remains the same but that payments are reduced on a per hour basis.

  3. 3.

    We measure entrepreneurship using self-employment as it is the most reliable measure available in our survey data set and is commonly used as a measure of entrepreneurship in the economics literature; for more detail on this, see Parker (2005, 2009).

  4. 4.

    As pointed out in Hurst and Lusardi (2004), the relationship between liquidity and entrepreneurship is nonlinear. The positive relationship between capital availability and entrepreneurship is found among individuals with the highest income, while this relationship is not found for the majority of households.

  5. 5.

    See table 5 in Caliendo and Kritikos (2010) for the specific results of the survey.

  6. 6.

    The entry sample includes those who report being employed in the wage and salary sector or unemployed.

  7. 7.

    Wave 5 occurred in 2000 so the variable measures the effects of a recession occurring between waves.

  8. 8.

    A potential concern for our analysis is that own unemployment status might be endogenous. For example, an individual who is contemplating starting a business might put less work effort into their wage and salary job resulting in a greater probability of being fired or laid-off. We rate this as a fairly minor concern given the structure of the HRS—survey responses are collected every 2 years, so there is a significant lag between observed own unemployment and employment status in the next survey.

  9. 9.

    Following Hurst and Lusardi (2004), we use wealth quartiles to represent the non-linearity of the relationship between wealth and the likelihood of entering self-employment. Wealth quartiles include four dummy variables. For example, the first wealth quartile variable is equal to one if a household’s wealth is in the first quartile and zero otherwise.

  10. 10.

    We strongly prefer the fixed effects model over the random effects model, as the assumption of zero correlation between included covariates and the individual-specific effect is unlikely to be met. For this reason, we estimate linear probability models instead of a random effects probit model. Results from a probit model with errors clustered at the individual level are qualitatively consistent with our linear probability results.

  11. 11.

    A probit model with standard errors clustered at the individual level produced a larger marginal effect for men (14.9 percentage points) and a smaller effect for women (9.9 percentage points), both significant at the 1 percent level.

  12. 12.

    We also test whether our decision to limit the sample to workers aged 61 or less has significant consequences for our conclusions. Given that many policy decisions are made assuming retirement at age 65, we expand our dataset to include workers who are 65 and under. Results are similar to the baseline estimates.

  13. 13.

    Results are unchanged when we add dummy variables to control for regions.

  14. 14.

    Including other income and wealth quartile variables produces results nearly identical to our baseline specification.

  15. 15.

    Note that in a linear probability model it is possible to get negative predicted probabilities.

  16. 16.

    Question worded as follows: (1) On the same scale from 0 to 100 (where 0 means absolutely no chance and 100 means absolutely certain), what are the chances that you will lose your job during the next year? (2) Suppose you were to lose your job this month. What do you think are the chances that you could find an equally good job in the same line of work within the next few months? and (3) You told us earlier that you were looking for a new job. On this 0–100 scale, what are the chances that you will find a job like the one you're looking for within the next few months?

  17. 17.

    Weighted results are generally similar and we discuss unweighted results unless otherwise noted.

  18. 18.

    Lagged variables are used for comparability to our main analysis and also to mitigate issues of simultaneity and reverse causation.

  19. 19.

    Results are presented for the male estimates only, but female estimates are similar to those presented here.

References

  1. Angrist, J. D., & Pischke, J.-S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton, NJ: Princeton University Press.

    Google Scholar 

  2. Blanchflower, D. (2000). Self-employment in OECD Countries. Labour Economics, 7(5), 471–506.

    Article  Google Scholar 

  3. Blanchflower, D., & Oswald, A. J. (1998). What makes an entrepreneur. Journal of Labor Economics, 16(1), 26–60.

    Article  Google Scholar 

  4. Bruce, D. (1999). Do husbands matter? Married women entering self-employment. Small Business Economics, 13(4), 317–329.

    Article  Google Scholar 

  5. Bruce, D. (2000). Effects of the United States tax system on transitions into self-employment. Labour Economics, 7(5), 545–574.

    Article  Google Scholar 

  6. Bruce, D. (2002). Taxes and entrepreneurial endurance: Evidence from the self-employed. National Tax Journal, 55(1), 5–24.

    Google Scholar 

  7. Bruce, D., Holtz-Eakin, D., & Quinn, J. (2000). Self-employment and labor market transitions at older ages. Working paper 2000–2013. Chestnut Hill, MA: Center for Retirement Research Boston College.

  8. Caliendo, M., & Kritikos, A. S. (2010). Start-ups by the unemployed: Characteristics, survival and direct employment effects. Small Business Economics, 35(4), 71–92.

    Article  Google Scholar 

  9. Cullen, J. B., & Gordon, R. H. (2007). Taxes and entrepreneurial risk-taking: Theory and evidence for the US. Journal of Public Economics, 91(7–8), 1479–1505.

    Article  Google Scholar 

  10. Evans, D. S., & Jovanovic, B. (1989). An estimated model of entrepreneurial choice under liquidity constraints. Journal of Political Economy, 97(4), 808–827.

    Article  Google Scholar 

  11. Evans, D. S., & Leighton, L. S. (1989). Some empirical aspects of entrepreneurship. American Economic Review, 79(3), 519–535.

    Google Scholar 

  12. Evans, D. S., & Leighton, L. S. (1990). Small business formation by unemployed and employed workers. Small Business Economics, 2, 319–330.

    Article  Google Scholar 

  13. Fairlie, R. W., & Meyer, B. D. (1996). Ethnic and racial self-employment differences and possible explanations. Journal of Human Resources, 31(4), 757–793.

    Article  Google Scholar 

  14. Fairlie, R., & Robb, A. (2009). Why do female-owned businesses have lower survival rates, profits, employment, and sales, than male-owned businesses? Small Business Economics, 33(4), 397–411.

    Google Scholar 

  15. Fuchs, V. R. (1982). Self-employment and labor force participation of older males. Journal of Human Resources, 17(3), 339–357.

    Article  Google Scholar 

  16. Gurley-Calvez, T. (2011). Will tax-based health insurance reforms help the self-employed stay in business? Contemporary Economic Policy, 29(3), 441–460.

    Article  Google Scholar 

  17. Gurley-Calvez, T., Biehl, A., & Harper, K. (2009). Time-use patterns and women entrepreneurs. American Economic Review Papers and Proceedings, 99(2), 139–144.

    Article  Google Scholar 

  18. Gurley-Calvez, T., & Bruce, D. (2008). Do tax cuts promote entrepreneurial longevity? National Tax Journal, 61(2), 225–250.

    Google Scholar 

  19. Holtz-Eakin, D., Penrod, J. R., & Rosen, H. S. (1996). Health insurance and the supply of entrepreneurs. Journal of Public Economics, 62(1–2), 209–235.

    Article  Google Scholar 

  20. Hundley, G. (2001). Why women earn less than men in self-employment. Journal of Labor Research, 22(4), 817–829.

    Article  Google Scholar 

  21. Hurst, E., & Lusardi, A. (2004). Liquidity constraints, household wealth, and entrepreneurship. Journal of Political Economy, 112(2), 319–347.

    Article  Google Scholar 

  22. Kanbur, S. M. (1979). Of risk taking and the personal distribution of income. Journal of Political Economy, 87, 769–797.

    Article  Google Scholar 

  23. Kanbur, S. M. (1981). Risk taking and taxation: An alternative perspective. Journal of Public Economics, 15, 163–184.

    Article  Google Scholar 

  24. Kihstrom, R. E., & Laffont, J.-J. (1979). A general equilibrium entrepreneurial theory of firm formation based on risk aversion. Journal of Political Economy, 87, 719–749.

    Article  Google Scholar 

  25. Lombard, K. V. (2001). Female self-employment and demand for flexible, nonstandard work schedules. Economic Inquiry, 29(2), 214–217.

    Google Scholar 

  26. Manser, M. E., & Picot, G. (1999). The role of self-employment in US and Canadian job growth. Monthly Labor Review, 122, 10–25.

    Google Scholar 

  27. Parker, S. C. (1996). A time series model of self-employment under uncertainty. Economica, 63, 459–475.

    Article  Google Scholar 

  28. Parker, S. C. (2005). The economics of entrepreneurship: What we know and what we don’t. Foundations & Trends in Entrepreneurship, 1(1), 1–55.

    Article  Google Scholar 

  29. Parker, S. C. (2009). The economics of entrepreneurship. Cambridge: Cambridge University Press.

    Google Scholar 

  30. Quinn, J. (1980). Labor force participation patterns of older self-employed workers. Social Security Bulletin, 43(4), 17–28.

    Google Scholar 

  31. Robb, A., & Reedy, E. J. (2012). An overview of the Kauffman firm survey: Results from 2010 business activities. Kansas City: Ewing Marion Kauffman Foundation.

  32. Román, C., Congregado, E., & Millán, J. M. (2011). Dependent self-employment as a way to evade employment protection legislation. Small Business Economics, 37(3), 363–392.

    Article  Google Scholar 

  33. Schuetze, H. J. (2000). Taxes, economic conditions and recent trends in self-employment: A Canada–US comparison. Labour Economics, 7(5), 507–544.

    Article  Google Scholar 

  34. Wadhwa, V., Aggarwal, R., Holly, K., & Salkever, A. (2009). The anatomy of an entrepreneur: Making of a successful entrepreneur. Kansas City: Ewing Marion Kauffman Foundation.

  35. Zissimopoulos, J., & Karoly, L. A. (2007). Transitions to self-employment at older ages: The role of wealth, health, health insurance, and other factors. Labour Economics, 14, 269–295.

    Article  Google Scholar 

  36. Zissimopoulos, J., & Karoly, L. A. (2009). Labor force dynamics at older ages: Movements into self-employment for workers and nonworkers. Research on Aging, 31(1), 89–111.

    Article  Google Scholar 

Download references

Acknowledgments

We thank participants at the Small Business, Entrepreneurship, and Economic Recovery: A Focus on Job Creation and Economic Stabilization Conference for helpful comments.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Amelia M. Biehl.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Biehl, A.M., Gurley-Calvez, T. & Hill, B. Self-employment of older Americans: do recessions matter?. Small Bus Econ 42, 297–309 (2014). https://doi.org/10.1007/s11187-013-9479-7

Download citation

Keywords

  • Entrepreneurship
  • Recession
  • Older Americans
  • Economics of gender
  • Unemployment

JEL classifications

  • L26
  • J14
  • J16