The Review of Black Political Economy

, Volume 18, Issue 2, pp 05–22 | Cite as

Job characteristics and the labor force participation behavior of black and white male youth

  • Donald R. Williams


Previous work regarding the labor force participation of black and white youth has ignored the fact that they may face jobs with different characteristics, such as socioeconomic status or degree of danger. This article examines the effects that such characteristics have on the probability of participation for a sample of black and white males from the National Longitudinal Survey Youth Cohort. The results suggest that some job characteristics have a significant impact on participation, particularly socioeconomic status. The estimates presented here suggest, however, that racial differences in socioeconomic status probably explain only a small portion of the black-white male youth participation rate differential.


Labor Supply Labor Force Participation Reservation Wage Black Youth White Youth 
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  1. 2.
    Calculated from data presented in U. S. Department of Labor, Bureau of Labor Statistics,Employment and Earnings (September, 1988).Google Scholar
  2. 3.
    Paul J. Andrisani, “Internal-External Attitudes, Personal Initiative, and the Labor Market Experience of White and Black Men,”Journal of Human Resources, Volume 12 (1977), pp. 308–28.CrossRefGoogle Scholar
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    Linda Datcher-Loury and Glen C. Loury, “The Effects of Attitudes and Aspirations on the Labor Supply of Young Black Men,” in Richard Freeman and Harry Holzer, editors,The Black Youth Employment Crisis (Chicago, Ill.: University of Chicago Press, 1986).Google Scholar
  4. 5.
    Ibid., and Harry J. Holzer, “Black Youth Nonemployment: Duration and Job Search,” in op. cit. ).Google Scholar
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    Regarding reservation wages, see Harry J. Holzer, “Reservation Wages and their Labor Market Effects for Black and White Male Youth,”Journal of Human Resources, Volume 21 (1986), pp. 157–77. An analysis of willingness to accept low wage employ-ment is in Michael E. Borus, “Willingness to Work among Youth,”Journal of Human Resources, Volume 17 (1982), pp.581-94.CrossRefGoogle Scholar
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    Donald R. Williams,Labor Force Participation of Black and White Youth (Ann Arbor, Mich.: UMI Research Press, 1987).Google Scholar
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    See Albert Rees, “An Essay on Youth Joblessness,”Journal of Economic Liter- ature, Volume 24 (1986), pp. 613–628; Richard Freeman and David Wise, editors,The Youth Labor Market Problem: Its Nature, Causes, and Consequences (Chicago I11.: University of Chicago Press, 1982); or Freeman and Holzer,op. cit., for reviews of this literature. It should be noted that although these hypotheses may explain differences in thelevel of employment, some of them do little to explain the changes in employment which have occurred over time.Google Scholar
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    I put forth this argument based upon the work of Edward Lazear, “Narrowing of Black-White Wage Differentials is Illsory,”American Economic Review, Volume 69 (1979), pp. 553–64.Google Scholar
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    Williams, op. cit,. page 25. There is considerable evidence that racial differences in nonpecuniary rewards exist, including Greg J. Duncan, “Labor Market Discrimination and Non-pecuniary Work Rewards,” in F. Thomas Juster, editor,The Distribution of Economic Well-being (New York: National Bureau of Economic Research, 1977); Ann P. Bartel, “Race Differences in Job Satisfaction: A Reappraisal,”Journal of Human Re- sources, Volume 16 (1981), pp.294-303; David E. Kaun, “Black-White Differentials in the Quality of Work,”Review of Black Political Economy, Vol.6 (1975), pp.41-58; and Sam Rosenberg, “Racial Differentials in Younger Male Occupational Mobility over the Business Cycle, 1966-1975,Proceedings of the Thirty-eighth Annual Meeting (Madison, Wis.: Industrial Relations Research Association, 1986). These studies are based on sam- ples which include older workers, however, so that they are not directly applicable here.Google Scholar
  10. 11.
    Regarding wages see, for example, Charles Brown, “Equalizing Differences in the Labor Market,”Quarterly Journal of Economics, Volume 95 (1980), pp. 113–34; Robert S. Smith, “Compensating Wage Differentials and Public Policy: A Review,”Industrial and Labor Relations Review, Volume 32 (1979), pp.339-52; or Greg J. Duncan and Bertil Holmlund, “Was Adam Smith Right After All? Another Test of the Theory of Compensating Wage Differentials,”Journal of Labor Economics, Volume 1 (1983), pp.366-79. For analyses of occupational choice, see John T. Warner and Matthew S. Gold- berg, “The Influence of Non-pecuniary Factors on Labor Supply: The Case of Navy Personnel,”Review of Economics and Statistics, Volume 66 (1984), pp.26-35; Randall K. Filer, “Male-Female Wage Differences: The Importance of Compensating Differen- tials,”Industrial and Labor Relations Review, Volume 38 (1985), pp.426-37; or Julie Holleman and W. Robert Reed, “Do Women Prefer Women’s Work?”, mimeo, Texas A&M University, (1986). The relationship between job characteristics and labor supply is studied in Randall K. Filer, “The Effects of Nonpecuniary Compensation on Estimates of Labor Supply Functions,”Quarterly Review of Economics and Business, Volume 26 (1986), pp.17-30; and B. K. Atrostic, “The Demand for Leisure and Nonpecuniary Job Characteristics,”American Economic Review, Volume 72 (1982), pp.428-40.CrossRefGoogle Scholar
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    For a survey and classification of models of labor supply, see Mark R. Killing- sworth,Labor Supply, (Cambridge: Cambridge University Press, 1983).Google Scholar
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    This section draws from the presentation in Killingsworth, ibid..Google Scholar
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    James J. Heckman, “Shadow Prices, Market Wages, and Labor Supply,”Econo- metrica, Volume 42 (1974), pp. 679–94.Google Scholar
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    There is no theoretically “correct” functional form for M *. The linear form seems to be accepted in the labor economics literature (Killingsworth, op. cit.).Google Scholar
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    It could be argued that a selection parameter should be included in equation 10 to adjust for the effects of sample selection bias, as in James J. Heckman, “Sample Selec- tion Bias as a Specification Error.”Econometrica, Volume 47 (1979), pp. 53–62. In order to do so, however, a probability of employment function would have to be estimated, which is dependent on R. The sample selection problem is ignored here.CrossRefGoogle Scholar
  16. 18.
    For examples of dynamic participation models, see Kenneth Burdett, Nicholas Kiefer, Dale Mortensen, and George Neumann, “A Markov Model of Employment, Unemployment, and Labor Force Participation,” Northwestern University Discussion Paper No.483, (May, 1981), or Killingsworth,op. cit., Chapter 5.Google Scholar
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    The evidence regarding racial differentials in costs of search among youth is mixed (Williams, op. cit., pp. 22–24). Of course we should still desire to take account of any individual variations in costs of search that might exist.Google Scholar
  18. 20.
    The relationship between measures of aggregate demand, such as the unemploy- ment rate, and labor force participation has been studied extensively (e.g., William G. Bowen and T. Aldrich Finegan,The Economics of Labor Force Participation (Princeton, N. J.: Princeton University Press, 1969). Studies that provide evidence for black and white male youth in particular include Kim Clark and Lawrence Summers, “The Dynamics of Youth Unemployment,” in Freeman and Wise,op. cit.; Clark and Summers, “Demo- graphic Differences in Cyclical Employment Variation,”Journal of Human Resources, Volume 16 (1981), pp.61-79; and Donald R. Williams, “Evidence on the Racial Dif- ferential in the Discouraged Worker Effect among Male Teenagers,”Proceedings of the Thirty-sixth Annual Meeting, Industrial Relations Research Association, (Madison, Wis., 1984).Google Scholar
  19. 21.
    Bowen and Finegan, op. cit..Google Scholar
  20. 22.
    The rationales behind these variables are that individuals from homes with more or less educated parents may have different attitudes toward work, single youth will have different family responsibilities than married ones, as will youth not living at home compared to those at home, and that youth in school are much less likely to participate than youth not-in-school (Bowen and Finegan, op. cit..; Alan L. Gustman and Thomas L. Steinmeier, “The Impact of Wages and Unemployment on Youth Enrollment and Labor Supply,”Review of Economics and Statistics. Volume 63 (1981), pp.553-60. The race variable is included to allow for the possibility that racial differences exist in attitudes toward work, even though research already noted suggests that they do not.Google Scholar
  21. 24.
    Rosemary S. Clooney, Alice S. Clague, and Joseph J. Salvo, “Status Attainment of Young White Men and Women: Two Socioeconomic Measures,” in Mary G. Powers, editor,Measures of Socioeconomic Status (Boulder, Colo.: Westview Press 1982). The socioeconomic status variable whichis available in the Youth Cohort data is the Duncan index, but it was collected only for those individuals who were employed in the 1979 survey year, and related only to the occupation for that year. The occupational classifi- cations used to assign the TSS variable are the same as those listed in Appendix Table A2.Google Scholar
  22. 25.
    Otis D. Duncan, “A Socioeconomic Index for All Occupations,” in Albert J. Reiss, editor,Occupations and Social Status, (New York: The Free Press, 1961). The MSEI3 and PRESTIGE variables presented in David L. Featherman and Gillian Stevens, “A Revised Socioeconomic Index of Occupational Status: Application in Analysis of Sex Differences in Attainment,” in Powers,op. cit., were also employed, yielding similar results. All of these measures use the 1970 Census definitions of occupations. For prestige and status measures using the post-1980 occupational classifications, see Gilliam Stevens and Elizabeth Hoisington, “Occupational Prestige and the 1980 U.S. Labor Force,”Social Science Research, Volume 16 (1987), pp.74-105.Google Scholar
  23. 26.
    It might seem desirable to include another variable to proxy for the degree of employment opportunities, the minimum wage. Although considerable evidence exists indicating that the minimum affects the employment rates of youth (for recent cross- sectional analyses, see Ronald G. Ehrenberg and Alan J. Marcus, “Minimum Wages and Teenagers’ Enrollment-Employment Outcomes,”Journal of Human Resources, Volume 17 (1982), pp. 39–58; or Robert H. Meyer and David A. Wise, “The Effects of the Minimum Wage on the Employment and Earnings of Youth,”Journal of Labor Eco- nomics, Volume 1 (1983), pp.66-100, it has no significant effect onparticipation once the unemployment rate is controlled. For example, see Williams, (1987),op. cit. CrossRefGoogle Scholar
  24. 27.
    The relationships between these variables and job characteristics or status have been explored elsewhere. For examples, see Jack K. Martin and George A. Miller, “Job Satisfaction and Absenteeism,”Work and Occupations, Volume 13 (1986), pp. 33–46; the references cited therein; and Bartel,op. cit. CrossRefGoogle Scholar
  25. 29.
    This is relatively high. The official (Labor Department) labor force participation rate for males in this age group was 66.2 percent in 1982. For explanations of the difference between the BLS and NLS estimates, see Richard B. Freeman and James L. Medoff, “Why Does the Rate of Youth Labor Force Activity Differ Across Surveys?” in Freeman and Wise,op. cit. Google Scholar
  26. 30.
    Black and white youths’ jobs also differed in the values for job characteristics which are not used in the logit analysis, for reasons outlined in note 10 above. In particular, blacks’ jobs were less varied and offered less autonomy or chance to complete one’s task.Google Scholar
  27. 34.
    See notes 3 and 4 above.Google Scholar
  28. 35.
    Richard B. Freeman, “Job Satisfaction as an Economic Variable,”American Economic Review, Volume 68 (1978), pp. 135–141; and George J. Borjas, “Job Satis- faction, Wages, and Unions,”Journal of Human Resources, Volume 14 (1979), pp.21-40. They focused on “job satisfaction” variables, however, which are probably much more subjective than the variables used in this article.Google Scholar
  29. 36.
    The joint determinancy of enrollment and labor force status has been studied extensively elsewhere. See, for example, Gustman and Steinmeierop. cit., Ehrenberg and Marcus,op. cit., and the references cited therein. The joint nature of the participation/ enrollment decisions is being ignored in this study.Google Scholar

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© Springer 1989

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  • Donald R. Williams

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