Welfare Reform and Labor Force Exit by Young, Low-Skilled Single Males


While the labor market woes of low-skilled male workers in the United States over the past several decades have been well documented, the academic literature identifying causal factors leading to declines in labor force participation (LFP) by young, low-skilled males remains scant. To address this gap, I use the timing and characteristics of welfare-reform policies implemented during the 1990s and fixed-effects, instrumental variable regression modeling to show that policies seeking to increase LFP rates for low-skilled single mothers inadvertently led to labor force exit by young, low-skilled single males. Using data from the Current Population Survey and a bundle of work inducements enacted by states throughout the 1990s as exogenous variation in a quasi-experimental design, I find that the roughly 10 percentage point increase in LFP for low-skilled single mothers facilitated by welfare reform resulted in a statistically significant 2.8 percentage point decline in LFP for young, low-skilled single males. After conducting a series of robustness checks, I conclude that this result is driven entirely by white males, who responded to welfare-reform policies with a 3.7 percentage point decline in labor supply. Young black males, as well as other groups of potentially affected workers, appear to be uninfluenced by the labor supply response of less-educated single mothers to welfare reform. Impacts on young, single white males are large and economically significant, suggesting that nearly 150,000 males departed the formal labor market in response to directed welfare-reform policies.

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

Fig. 1
Fig. 2
Fig. 3


  1. 1.

    In particular, the decline of married, two-biological-parent households has been tied to a host of other issues, including the reduced role of low-skilled men in the family life of their biological children, the increase in the number of complex families, and the various challenges and impacts associated with child support payments.

  2. 2.

    In this analysis, low-skilled workers are defined as those individuals with an educational level of high school diploma or less. Furthermore, the terms “low-skilled” and “less-educated” will be used interchangeably and “high school diplomas” include both traditional and general equivalency diplomas.

  3. 3.

    As is common in the literature, in this article, I concentrate on LFP rather than employment. LFP is arguably a more accurate depiction of labor supply because it captures the intent to provide labor. Employment, on the other hand, can be based on a number of factors outside the individual’s control, especially the demand for labor.

  4. 4.

    The general decline in LFP rates for low-skilled males since the early 1980s has been documented very thoroughly by Holzer and various colleagues. In Holzer and Offner (2006), they report declines in labor supply for young, less-educated white males from approximately 92 % in 1979 to roughly 87 % in 2000. Correspondingly, rates for black males have dropped from roughly 82 % to 70 % over the same time period. In Holzer et al. (2005), the authors report that at least half of the decline in employment among less-educated black males can be attributed to increases in incarceration rates and stronger child support enforcement laws.

  5. 5.

    Recent estimates of the scale of the illicit drug trade in the United States indicate that it is a highly lucrative industry which is estimated to produce up to $150 billion in revenue each year (Bagley 2012; United Nations Office on Drugs and Crime 2012). Given this scope, it does not seem unreasonable to contend that low-skilled males are more likely than other groups to enter these illegal professions given that they have fewer employment options.

  6. 6.

    Scholars have noted their skepticism regarding whether low-skilled men and women compete in the same labor markets (Blank 2002; Blank and Gelbach 2006). However, there is seemingly enough overlap in some low-skilled sectors, such as fast-food services, custodial services, and security and retail jobs, for this supposition. For example, Card and Krueger (1994) claimed that fast-food franchises are a leading employer of low-wage workers, and low-skilled workers of either gender seem equally qualified for these entry-level positions.

  7. 7.

    A positive relationship could indicate peer effects, whereby the welfare-reform work inducements create positive spillovers in the form of increased LFP for applicable males residing within the household or the community.

  8. 8.

    The state dummy variables account for time-invariant unobserved factors that influence historical LFP rates in a particular state. The year, quarter, and year-quarter fixed effects control for omitted factors that impact labor supply rates in all states during a particular period. In addition, the quarterly variables account for seasonality in the LFP rates for young males. The CPS considers university-bound males on summer break (i.e., those between their last year of high school and first year of college) as potential labor force participants. During the summer months, this influx of short-term labor drives down the LFP rate for single males aged 16–29.

  9. 9.

    Other instruments were considered in this analysis but were excluded because of their weak predictive power.

  10. 10.

    In some states this ratio changed well before the implementation of either an AFDC waiver or their state-level TANF program. For example, New York implemented its TANF program in November 1997, but the LFP rates for single mothers in that state increased markedly before this point—presumably because of the large increases in the federal EITC beginning in 1994.

  11. 11.

    The vast majority of CPS data used in this analysis come from the IPUMS-CPS database (Flood et al. 2015).

  12. 12.

    These periods are identified with vertical lines in the forthcoming figures.

  13. 13.

    Upcoming modeling is not sensitive to the choice of using single mothers aged 16–44. Models using single mothers aged 16–30 produce very similar estimates.

  14. 14.

    As previously mentioned, it is important to control for the seasonality of LFP for young, single males given the influx of university-bound males during the summer months. Thus, the graph is seasonally adjusted.

  15. 15.

    I also analyzed a number of other characteristics of welfare reform, but did not include them in the final first-stage regression models because of their weak predicative power. Including them violates the relevance criterion of an instrumental variable. Examined in this analysis but not included in the final modeling were TANF attributes regarding the strictness of sanctions and time limits (Pavetti and Bloom 2001), state diversion policies under TANF (Urban Institute, Welfare Rules Database; anfdata.urban.org/wrd/wrdwelcome.cfm), and states with childcare fee waivers available through the Child Care Development Fund (Blau 2003).

  16. 16.

    The first three are rather self-explanatory. The personal responsibility clauses include restrictions on benefits for increasing the family size (i.e., family caps), as well as the children’s regular school attendance and health check-ups.

  17. 17.

    Wolfers et al. (2015) reported the number of 25- to 54-year-old black males who are “missing” based on deviations from the biological sex ratio at birth. Using Census Bureau data and a ratio of 1 male to every female, they found almost 20 % (or 1.5 million) fewer black men living in the U.S. general population. As the authors noted, the primary factors contributing to this gap are differential incarceration and mortality rates—issues that disproportionately impact low-skilled males. The authors also found that this gap exists among whites, although the impact is not as pronounced.

  18. 18.

    This ratio is derived from the same underlying CPS data. To obtain a more precise estimate, I construct this ratio at the annual level. In addition, I estimate it for all less-educated males and females within the group examined. This latter decision further increases the precision of the estimate and reduces bias from contemporaneous family structure decisions based on sex ratios.

  19. 19.

    This test reveals that the instruments in this analysis do not directly influence male labor supply but that the impact is moderated through the instrument’s influence on female LFP. In other words, they meet the exclusion restriction of a valid IV. This finding is critical to establish a valid IV research design and, as will be shown, is not typically found in the modeling for other groups.

  20. 20.

    Holzer et al. (2005) examined the 1979–2000 period as well as a different set of age categories.

  21. 21.

    Recall that DI and SSI beneficiaries, by definition, are not part of the labor market. This is also the rationale behind not including variables such as the unemployment rate in the models. Other modeling (not shown but available upon request) includes state and federal SSI generosity in both the first and second stages, but results remain substantively unaffected.


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

    Google Scholar 

  2. Bagley, B. (2012). Drug trafficking and organized crime in the Americas: Major trends in the twenty-first century (Woodrow Wilson Center Update on the Americas). Washington, DC: Woodrow Wilson International Center for Scholars. Retrieved from http://www.wilsoncenter.org/sites/default/files/BB%20Final.pdf

  3. Bartik, T. J. (2002). Instrumental variable estimates of the labor market spillover effects of welfare reform (Upjohn Institute Working Paper No. 02-78). Kalamazoo, MI: W.E. Upjohn Institute for Employment Research. Retrieved from http://research.upjohn.org/up_workingpapers/78

  4. Blanchflower, D. G., & Freeman, R. B. (2000). Youth employment and joblessness in advanced countries. Chicago, IL: University of Chicago Press.

    Book  Google Scholar 

  5. Blank, R. M. (2002). Evaluating welfare reform in the United States. Journal of Economic Literature, 40, 1105–1166.

    Article  Google Scholar 

  6. Blank, R. M. (2009). Economic change and the structure of opportunity for less-skilled workers. Focus, 26(2), 14–20. Retrieved from http://www.irp.wisc.edu/publications/focus/pdfs/foc262c.pdf

  7. Blank, R. M., & Gelbach, J. (2006). Are less-educated women crowding less-educated men out of the labor market? In R. B. Mincy (Ed.), Black males left behind (pp. 87–119). Washington, DC: The Urban Institute Press.

    Google Scholar 

  8. Blau, D. M. (2003). Child care subsidy programs. In R. Moffitt (Ed.), Means-tested transfer programs in the United States (pp. 443–516). Chicago, IL: University of Chicago Press.

    Google Scholar 

  9. Bloom, D., & Haskins, R. (2010). Helping high school dropouts improve their prospects (Future of Children Policy Brief, Social Genome Project Research Series No. 4). Princeton, NJ: Princeton-Brookings. Retrieved from http://www.brookings.edu/research/papers/2010/04/27-helping-dropouts-haskins.

  10. Card, D., & Krueger, A. B. (1994). Minimum wages and employment: A case study of the fast-food industry in New Jersey and Pennsylvania. American Economic Review, 84, 772–793.

    Google Scholar 

  11. Carlson, M., McLanahan, S., & England, P. (2004). Union formation in fragile families. Demography, 41, 237–261.

    Article  Google Scholar 

  12. Carlson, M. J., VanOrman, A. G., & Pilkauskas, N. V. (2013). Examining the antecedents of U.S. nonmarital fatherhood. Demography, 50, 1421–1447.

    Article  Google Scholar 

  13. Cherlin, A. J. (2009). The marriage-go-round: The state of marriage and the family in America today. New York, NY: Knopf Doubleday Publishing Group.

    Google Scholar 

  14. Cherlin, A. J. (2010). Demographic trends in the United States: A review of research in the 2000s. Journal of Marriage and Family, 72, 403–419.

    Article  Google Scholar 

  15. Danziger, S., Heflin, C. M., Corcoran, M. E., Oltmans, E., & Wang, H.-C. (2002). Does it pay to move from welfare to work? Journal of Policy Analysis and Management, 21, 671–692.

    Article  Google Scholar 

  16. DeParle, J. (2004). American dream: Three women, ten kids, and a nation’s drive to end welfare. New York, NY: Viking Adult.

    Google Scholar 

  17. Edin, K., & Kefalas, M. J. (2005). Promises I can keep: Why poor women put motherhood before marriage. Berkeley: University of California Press.

    Google Scholar 

  18. Edin, K., & Lein, L. (1997). Work, welfare, and single mothers’ economic survival strategies. American Sociological Review, 62, 253–266.

    Article  Google Scholar 

  19. Ellwood, D. T. (1988). Poor support: Poverty in the American family. New York, NY: Basic Books.

    Google Scholar 

  20. Flood, S., King, M., Ruggles, S., & Warren, J. R. (2015). Integrated Public Use Microdata Series, Current Population Survey: Version 4.0 [Machine-readable database]. Minneapolis: University of Minnesota.

  21. Freeman, R. B. (2000). Disadvantaged young men and crime. In D. G. Blanchflower & R. B. Freeman (Eds.), Youth employment and joblessness in advanced countries (pp. 215–246). Chicago, IL: University of Chicago Press. Retrieved from http://www.nber.org/chapters/c6806

  22. Grogger, J., & Karoly, L. (2005). Welfare reform: Effects of a decade of change. Cambridge, MA: Harvard University Press.

    Book  Google Scholar 

  23. Harlow, C. W. (2003). Education and correctional populations (Bureau of Justice Statistics special report). Washington, DC: Bureau of Justice Statistics, U.S. Department of Justice. Retrieved from http://www.eric.ed.gov/ERICWebPortal/detail?accno=ED477377

  24. Holzer, H. J., & Offner, P. (2006). Trends in the employment outcomes of young black men, 1979–2000. In R. B. Mincy (Ed.), Black males left behind (pp. 11–37). Washington, DC: The Urban Institute Press.

    Google Scholar 

  25. Holzer, H. J., Offner, P., & Sorensen, E. (2005). Declining employment among young black less-educated men: The role of incarceration and child support. Journal of Policy Analysis and Management, 24, 329–350.

    Article  Google Scholar 

  26. Huang, C.-C., Kunz, J., & Garfinkel, I. (2002). The effect of child support on welfare exits and re-entries. Journal of Policy Analysis and Management, 21, 557–576.

    Article  Google Scholar 

  27. Levitt, S. D. (2001). Alternative strategies for identifying the link between unemployment and crime. Journal of Quantitative Criminology, 17, 377–390.

    Article  Google Scholar 

  28. McLaughlin, D. K., & Lichter, D. T. (1997). Poverty and the marital behavior of young women. Journal of Marriage and Family, 59, 582–594.

    Article  Google Scholar 

  29. Men adrift: Badly educated men in rich countries have not adapted well to trade, technology, or feminism. (2015, May 30). The Economist. Retrieved from http://www.economist.com/news/essays/21649050-badly-educated-men-rich-countries-have-not-adapted-well-trade-technology-or-feminism

  30. Meyer, D. R., Cancian, M., & Cook, S. T. (2005). Multiple‐partner fertility: Incidence and implications for child support policy. Social Service Review, 79, 577–601.

    Article  Google Scholar 

  31. Moffitt, R. (1992). Incentive effects of the U.S. welfare system: A review. Journal of Economic Literature, 30, 1–61.

    Google Scholar 

  32. Moffitt, R. A. (2002). Welfare programs and labor supply. In A. J. Auerbach & M. Feldstein (Eds.), Handbook of public economics (Vol. 4, pp. 2393–2430). Amsterdam, The Netherlands: Elsevier.

    Google Scholar 

  33. Moffitt, R. A. (2007). Four decades of antipoverty policy: Past developments and future directions. Focus, 25(1), 39–44.

    Google Scholar 

  34. Moffitt, R. A. (2015). The deserving poor, the family, and the U.S. welfare system. Demography, 52, 729–749.

    Article  Google Scholar 

  35. Pavetti, L., & Bloom, D. (2001). State sanctions and time limits. In R. Blank & R. Haskins (Eds.), The new world of welfare (pp. 245–269). Washington, DC: The Brookings Institution.

    Google Scholar 

  36. The Pew Charitable Trusts. (2010). Collateral costs: Incarceration’s effect on economic mobility (Joint report of the Economic Mobility Project and the Public Safety Performance Project). Washington, DC: The Pew Charitable Trusts. Retrieved from http://www.pewstates.org/research/reports/collateral-costs-85899373309

  37. Rangarajan, A., & Gleason, P. (1998). Young unwed fathers of AFDC children: Do they provide support? Demography, 35, 175–186.

    Article  Google Scholar 

  38. Smeeding, T. M., Garfinkel, I., & Mincy, R. B. (2011). Young disadvantaged men: Fathers, families, poverty, and policy. ANNALS of the American Academy of Political and Social Science, 635, 6–21.

    Article  Google Scholar 

  39. United Nations Office on Drugs and Crime (UNODC). (2012). World drug report: 2012. Vienna, Austria: UNODC. Retrieved from https://www.unodc.org/documents/data-and-analysis/WDR2012/WDR_2012_web_small.pdf

  40. University of Kentucky Center for Poverty Research. (2015). UKCPR National Welfare Data, 1980–2014 [Data set]. Lexington, KY: Gatton College of Business & Economics, University of Kentucky. Retrieved from http://www.ukcpr.org/data

  41. U.S. Department of Health and Human Services. (1999). Table A: State implementation of major changes in welfare policies, 1992–1998. Retrieved from http://aspe.hhs.gov/hsp/waiver-policies99/Table_A.PDF

  42. The weaker sex: Boys are being outclassed by girls at both school and university, and the gap is widening. (2015, March 7). The Economist. Retrieved from http://www.economist.com/news/leaders/21652323-blue-collar-men-rich-countries-are-trouble-they-must-learn-adapt-weaker-sex

  43. Wilson, W. J. (1987). The truly disadvantaged: The inner city, the underclass, and public policy. Chicago, IL: University of Chicago Press.

    Google Scholar 

  44. Wolfers, J., Leonhardt, D., & Quealy, K. (2015, April 20). 1.5 million missing black men. New York Times. Retrieved from http://www.nytimes.com/interactive/2015/04/20/upshot/missing-black-men.html

  45. Ziliak, J. P., Figlio, D. N., Davis, E. E., & Connolly, L. S. (2000). Accounting for the decline in AFDC caseloads: Welfare reform or the economy? Journal of Human Resources, 35, 570–586.

    Article  Google Scholar 

Download references


PhD program funding from Syracuse University greatly supported this research. The author gratefully acknowledges Leonard M. Lopoo for his patience, helpful comments and suggestions, and encouragement throughout the various iterations of this work. Invaluable input was received from a number of other faculty at the Maxwell School, including Sarah Hamersma, Jeffery D. Kubik, Douglas Wolf, Robert Bifulco, David Popp, and Leonard Burman. Finally, the author would like to thank the editorial staff at Demography, as well as a number of anonymous referees, for their valuable feedback during the review process.

Author information



Corresponding author

Correspondence to Lincoln H. Groves.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Online Resource 1

(PDF 221 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Groves, L.H. Welfare Reform and Labor Force Exit by Young, Low-Skilled Single Males. Demography 53, 393–418 (2016). https://doi.org/10.1007/s13524-016-0460-3

Download citation


  • Labor supply
  • Instrumental variables
  • Welfare reform
  • Young, low-skilled males
  • Disconnected men