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Privatization and Labor Cost Savings: Evidence from Health Care Services

Abstract

This study examines whether privatization is associated with low public sector health care wages and with low probability of public sector employment for health care providers. Findings suggest that privatization contributes significantly to low wages of union health care providers in the public sector. Privatization also contributes to a low probability of public sector employment in this industry, especially to unionized workers. These results indicate that competition enhancing policy can promote lower labor costs even in a service sector that employs a highly skilled work force.

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Notes

  1. Erickcek, Houseman, and Kalleberg (2002) observe that health care providers also contract-out food services and security.

  2. Hart, Shleifer, and Vishny (1997) report the difficulty predicting the effectiveness of privatization (contracting-out) in the health care sector. Their analysis further supports the need for empirical testing of labor cost-savings arising from privatization.

  3. Goddeeris (2004) reports that health care spending was 13.1% the size of U.S. GDP in 2000 compared to only 8.0% for OECD countries. Higher U.S. costs are not necessarily associated with high quality care as U.S. infant mortality rates are above the median rate for OECD countries and female life expectancy closely resembles rates for OECD countries.

  4. Bender et al. (2006) find that risk compensation increases wage rates by 13.4% for union hospital janitors and is a major source of their wage advantage over nonunion janitors in other industries. Shumacher and Hirsch (1997) report unmeasured worker characteristics explain 33 to 50% of the earnings premium for hospital nurses over nurses in other industries.

  5. Township population sizes are used as weights when computing this measure of privatization.

  6. Information is pooled for these annual files to provide a sample population that is large enough to examine wage and employment patterns of public sector health care providers.

  7. The descriptions of these variables are presented in the Appendix.

  8. Hourly wage rates are calculated by taking the ratio of individual workers’ weekly earnings and weekly hours worked.

  9. Metropolitan areas where all townships contract-out health care services do not rely completely on private contractors, since privatization of any of several operations constitutes privatization. It is also important to note the estimated coefficient on the private variable can be used to compare wage differentials among metropolitan areas where a fraction of the townships contract-out health care services. This study compares wages of non-privatized and fully privatized metropolitan areas for ease of presentation.

  10. Estimated coefficient are converted to percentage earnings differentials by using the formula \( {\left( {e^{\beta } - 1} \right)} \times 100. \)

  11. A joint significance test for the east-midwest residency wage differential yields a t value of 1.77.

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Acknowledgment

The authors are grateful for the suggestions and comments of Richard Perlman.

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Correspondence to James Peoples.

Appendix: Description of Non-Key Explanatory Variables

Appendix: Description of Non-Key Explanatory Variables

Variable:

Description

Full-time:

Dummy variable indicates worker’s full-time or part-time status, value equal to 1 for full-time

Male:

Dummy variable indicates worker’s sex, value equal to 1 for male

Age:

Worker’s age

age-squared:

Worker’s age squared

time2000:

Dummy variable indicates the year of the observation, value equal to 1 for year 2000, value equal to 0 for year 1999

BA degree:

Dummy variable indicates worker’s education attainment, value equal to 1 if the highest degree is bachelors

graduate degree:

Dummy variable indicates worker’s education attainment, value equal to 1 if the highest degree is graduate degree

City:

Dummy variable indicates worker’s residence in the city or not, value equal to 1 if a worker lives in a city

East:

Dummy variable indicates worker’s geographical regional residence status, value equal to 1 if a worker resides in the east

Midwest:

Dummy variable indicates worker’s geographical regional residence status, value equal to 1 if a worker resides in the midwest

South:

Dummy variable indicates worker’s geographical regional residence status, value equal to 1 if a worker resides in the south

Black:

Dummy variable indicates worker’s race, value equal to 1 if a worker is black

White:

Dummy variable indicates worker’s race, value equal to 1 if a worker is white

Married:

Dummy variable indicates worker’s marital status, value equal to 1 for married workers

war veteran:

Dummy variable indicates worker’s veteran status, value equal to 1 for war veterans

Manager:

Dummy variable indicates worker’s occupation, value equal to 1 for managers

Professional:

Dummy variable indicates worker’s occupation, value equal to 1 if a worker is a professional

Technician:

Dummy variable indicates worker’s occupation, value equal to 1 if a worker is a technician

Service:

Dummy variable indicates worker’s occupation, value equal to 1 if a worker is a service person

Craft:

Dummy variable indicates worker’s occupation, value equal to 1 if a worker is a craftsman

For education attainment, the base case is workers without a bachelor’s degree; for geographic regional residence, the base case is the west; for worker’s race, the base case is American Indian, Asian, and other; for occupation, the base case is laborer.

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Peoples, J., Wang, B. Privatization and Labor Cost Savings: Evidence from Health Care Services. Atl Econ J 35, 145–157 (2007). https://doi.org/10.1007/s11293-006-9049-3

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Keywords

  • labor cost
  • health care services
  • service sector

JEL Classifications

  • I11
  • J31