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Estimating the Relationship between Employer-Provided Health Insurance, Worker Mobility, and Wages

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  • Martha Harrison Stinson

    (U.S. Census Bureau)

Abstract

Two separate literatures have sought to quantify the relationship between wages and job tenure and quit decisions and employer-provided health insurance. The fundamental difficulty in both cases is the presence of unobservable person and job characteristics that are correlated with both compensation outcomes and personal mobility. This paper seeks to bring these two strands of research together by estimating a joint model of wages, hazard of a job ending, and probability of holding employer-provided health insurance and allowing for correlated person and job heterogeneity across the three equations. Using data from the 1990 and 1996 Survey of Income and Program Participation (SIPP) Panels linked to SSA administrative job histories, the model is estimable due to the presence of monthly wage, job tenure, and health insurance observations for a relatively large, nationally representative sample of people over the course of 2 1/2 and 4 years respectively. Multiple jobs per person and multiple observations per job allow the identification of the part of the variation in wages, tenure, and health insurance status due to unobservable person and job characteristics and the correlation between individual and job propensities for high wages, low mobility, and high probability of benefits. The explicit modeling of this correlation not only produces unbiased estimates of the tenure and health insurance effects, but also allows the comparison of hazard rates for high-wage jobs versus jobs with a high probability of providing health insurance. I find substantial levels of job-lock of 30%-60% and annual returns to seniority of 1.5%-2% after the first four years of a job. In addition, I find that increasing the job-specific probability of obtaining employer-provided health insurance from 60% to 73%, or increasing the job-specific hourly wage rate by $.80, are both associated with an equivalent 6% decrease in the hazard of the employer-worker match ending, although, on average, the dollar value of the wage benefit is higher.

Suggested Citation

  • Martha Harrison Stinson, 2002. "Estimating the Relationship between Employer-Provided Health Insurance, Worker Mobility, and Wages," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B1-2, International Conferences on Panel Data.
  • Handle: RePEc:cpd:pd2002:b1-2
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    References listed on IDEAS

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    1. John M. Abowd & Francis Kramarz & David N. Margolis, 1999. "High Wage Workers and High Wage Firms," Econometrica, Econometric Society, vol. 67(2), pages 251-334, March.
    2. Thomas C. Buchmueller & Robert G. Valletta, 1996. "The Effects of Employer-Provided Health Insurance on Worker Mobility," ILR Review, Cornell University, ILR School, vol. 49(3), pages 439-455, April.
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    6. Robert H. Topel & Michael P. Ward, 1992. "Job Mobility and the Careers of Young Men," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(2), pages 439-479.
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    Cited by:

    1. Melissa Bjelland, 2005. "Are the Lasting Effects of Employee-Employer Separations induced by Layoff and Disability Similar? Exploring Job Displacement using Survey and Administrative Data," Longitudinal Employer-Household Dynamics Technical Papers 2005-03, Center for Economic Studies, U.S. Census Bureau.
    2. Anna Sanz De Galdeano, 2004. "Health Insurance and Job Mobility: Evidence from Clinton's Second Mandate," CSEF Working Papers 122, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    3. John M. Abowd & Paul A. Lengermann & Kevin L. McKinney, 2002. "The Measurement of Human Capital in the U.S. Economy," Longitudinal Employer-Household Dynamics Technical Papers 2002-09, Center for Economic Studies, U.S. Census Bureau, revised Mar 2003.
    4. Simon D Woodcock, 2002. "Agent Heterogeneity and Learning: An Application to Labor Markets," Longitudinal Employer-Household Dynamics Technical Papers 2002-20, Center for Economic Studies, U.S. Census Bureau.

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