Skip to main content

Monopsony Power in Occupational Labor Markets

We’re sorry, something doesn't seem to be working properly.

Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.


We collect data from the 1979 National Longitudinal Survey of Youth and create comparable measures of monopsonistic power for up to 46 occupational labor markets in the USA, starting in 1979 and ending in 2000. Our results suggest most occupational labor markets during that period were characterized by substantial amounts of monopsonistic, wage-setting power. Furthermore, after controlling for individual, time, and industry fixed effects, our results show a negative and significant correlation between the extent of monopsony power that characterizes a market and both, the wages and fringe benefits received by workers.

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

Fig. 1
Fig. 2


  1. 1.

    Mendez (2019) uses a similar approach to the one used in this paper, but looks at the effects of monopsony on the training of workers instead.

  2. 2.

    In the limit, as \(\frac {\lambda }{\delta }\) approaches infinity, the distribution of wages F(w) collapses to the perfectly competitive case and all workers get paid their marginal product.

  3. 3.

    Some data sets do contain the necessary information to compute the λ and δ parameters, but are not available to the public free of charge. The US Census Longitudinal Employer-Household Dynamics, for example, collects detailed data from both the employer and the employee, simultaneously. This data set, however, lacks the worker occupation information that would be necessary to replicate this study.

  4. 4.

    We preferred to use the NLSY79 over the CPS because the CPS does not contain continuous records of employment which are key for generating our approximation.

  5. 5.

    Results available upon request


  1. Acemoglu D, Pischke J-S (1999) Training in imperfect labor markets. Econ J 109(453):112–42

    Article  Google Scholar 

  2. Abrams R (2017) Why aren’t paychecks growing? A burger-joint clause offers a clue. The New York times, September 27

  3. Ashenfelter OC, Farber H, Ransom MR (2010) Labor market monopsony. J Labor Econ 28(2):203–10

    Article  Google Scholar 

  4. Barth E, Dale-Olsen H (2009) Monopsonistic discrimination, worker turnover, and the gender wage gap. Labour Econ 16(5):589–597

    Article  Google Scholar 

  5. Burdett K, Mortensen DT (1998) Wage differentials, employer size, and unemployment. Int Econ Rev 39(2):257–273

    Article  Google Scholar 

  6. Council of Economic Advisers Issue Brief (2016) October 2016

  7. Falch T (2010) The elasticity of labor supply at the establishment level. J Labor Econ 28(2):237–66

    Article  Google Scholar 

  8. Falch T (2011) Teacher mobility responses to wage changes: Evidence from a quasi-natural experiment. Am Econ Rev 101(3):460–65

    Article  Google Scholar 

  9. Hirsch TB, Schumacher J (2005) Classic or new monopsony? Searching for evidence in nursing labor markets Journal of Health Economics 24(5):969–989

    Google Scholar 

  10. Hirsch B, Schank T, Schnabel C (2010) Differences in labor supply to monopsonistic firms and the gender pay gap: An empirical analysis using linked employer-employee data from germany. J Labor Econ 28(2):291–330

    Article  Google Scholar 

  11. Kambourov G, Manovskii I (2009) Occupational specificity of human capital. Int Econ Rev 50(1):63–115

    Article  Google Scholar 

  12. Lewbel A (1997) Constructing instruments for regressions with measurement error when no additional data are available, with an application to patents and R&D. Econometrica 65(5):1201–1213

    Article  Google Scholar 

  13. Manning A (2003) Monopsony in motion. Princeton University Press, Princeton

    Google Scholar 

  14. Manning A (2011) Imperfect competition in the labour market. Handbook of labor economics 4(part B):973–1041

    Google Scholar 

  15. Mendez F (2019) Training opportunities in monopsonistic labor markets. Applied Economics, forthcoming

  16. Muehlemann S, Ryan P, Wolter SC (2013) Monopsony power, pay structure and training. ILR Rev 66(5):1097–1114

    Article  Google Scholar 

  17. Ransom MR, Sims DP (2010) Estimating the firm’s labor supply curve in a new monopsony framework: Schoolteachers in missouri. J Labor Econ 28(2):331–355

    Article  Google Scholar 

  18. Sullivan D (1989) Monopsony power in market for nurses. J Law Econ 32 (2):135–178

    Article  Google Scholar 

  19. Staiger DO, Spetz J, Phibbs CS (2010) Is there monopsony in the labor market? Evidence from a natural experiment. J Labor Econ 28(2):211–236

    Article  Google Scholar 

  20. Webber DA (2015) Firm market power and the earnings distribution. Labour Econ 35:123–34

    Article  Google Scholar 

  21. Webber DA (2016) Firm-level monopsony and the gender pay gap. Industrial Relations a Journal of Economy and Society 55(2):323–45

    Article  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Fabio Méndez.

Ethics declarations

Conflict of interests

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Appendix A: Theoretical Appendix

We derive the expected value of the labor sypply elasticity faced by firms (Eq. 2 in the text). As usual, the labor supply elasticity can be expressed as the mark up on the wage \(\varepsilon _{N,w}=\frac {w}{p-w}\). Furthermore, as shown by Manning (2003), the equilbrium solution of the model yields a wage distribution \(F(w)=\frac {\delta +\lambda }{\lambda }\left [1-\sqrt {\frac {p-w}{p-b}} \right ]\); with wages ranging from wmin = b to \(w_{max}= p-\left (\frac {\delta }{\delta +\lambda }\right )^{2}(p-b)\). To obtain the value in the text, the expected of the elasticity faced by firms is obtained simply by calculating the corresponding integral: \({\int }_{{w}_{min}}^{{w}_{max}} {\varepsilon }_{N,w} f(w) dw \).

Taking the derivative of F(w) and substituting for εN,w, this expression can be written as \({\int }_{{w}_{min}}^{{w}_{max}} \frac {w}{p-w} \frac {\lambda +\delta }{2\lambda }\frac {(p-w)^{\frac {-1}{2}}}{(p-b)^{\frac {1}{2}}} dw\); and further simplifying it can be expressed as follows:

$$ \frac{\lambda+\delta}{2\lambda}\frac{1}{(p-b)^{\frac{1}{2}}} {\int}_{{w}_{min}}^{{w}_{max}} w (p-w)^{\frac{-3}{2}}. $$

The solution of this integral can be verified to be

$$ \frac{\lambda+\delta}{2\lambda}\frac{1}{(p-b)^{\frac{1}{2}}}\left[2(p-w)^{\frac{1}{2}}+ 2p(p-w)^{\frac{-1}{2}}\right] \left|{~}_{{w}_{min}}^{{w}_{max}}\right. $$

which leads to the result reported in the paper when evaluated.

Appendix B: Empirical Appendix

Table 12 present the results obtained when a logistic regression is used to estimate the effects of monopsony on the availability of life and health insurance availability and of interest. More specifically, Table 12 show the results obtained after logit regressions are conducted while controlling for time and individual fixed effects in all cases, and for industry fixed effects in some of the specifications, as before.

Table 12 Health and life insurance logit regressions

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Méndez, F., Sepúlveda, F. Monopsony Power in Occupational Labor Markets. J Labor Res 40, 387–411 (2019).

Download citation


  • Monopsony
  • Wages
  • Fringe benefits

JEL Classification

  • J42
  • J31
  • J51