A monopoly in professional labor markets: concentration of the hospital system and the growth of nurse wages

ive here. If you suspect monopoly purchase, as in concentrated buyers driving prices down, look no further than the Department of Justice’s successful lawsuit against tech giants like Apple, Google and Intel who colluded to suppress tech workers’ wages. The victims here are the nurse’s wages, which have been stagnant for more than 20 years.

And yes, the collective oil price ceiling of the West is an attempt to play monopoly, but the participants do not have enough purchasing power. Plus they need the product to cheat a bit.

By Silvia Allegretto, Senior Economist, Center for Economics and Policy Research, Washington, D.C., and Dave Graham Squire, Senior Statistician, University of California, San Francisco, Benioff Homelessness and Housing Initiative. Originally published on the Institute for New Economic Thinking website

Continuous waves of consolidation have greatly reduced the number of hospital systems in the United States, leading to a dominance of regional systems. Increased focus may affect industry quality, prices, efficiency, wages, etc. Much consolidation research focuses on merger events and estimating the effects on the merging entities. In contrast, our new worksheet not only relies on merger data, but takes into account the overall increase in mergers across the country without considering cause.

Specifically, we use the severity of changes in hospital system integration in metropolitan statistical areas (MSAs) over two periods to estimate their impact on wage growth for high-income professional workers – in this case registered nurses. We focus on Registered Nurses as a homogeneous group of workers with some degree of education and industry-specific skills. Registered nurses represent the single largest occupational designation in hospitals and urgent care centers, accounting for one in four workers.

Understanding the dynamics of local labor markets for healthcare is critical given the importance of this sector to the US economy; Even more so in the aftermath of the pandemic amid ongoing uncertainty about the long-term effects (such as early retirement, career changes, and delays in education). Moreover, understaffing among hospital nurses, which may be a symptom of monopoly, has been endemic to the industry for many years. Nurses’ wages remained stagnant between 1995 and 2015 despite healthcare demand increasing during the same time frame even though it was the only sector adding jobs during the Great Recession. The explanations for the slump in wages for nurses–in one of the most unionized professional professions in the country–are not readily apparent.

Like many studies, we use a geographically site-specific (ie, MSA-specific) Herfindahl-Hirschman Index (HHI) to measure the severity of change in hospital focus. We use American Community Survey data to compile our sample of nurses for two periods: 2007-11 and 2015-19. It was necessary to accumulate several years of ACS data to obtain a sufficient number of MSA – each MSA required a sufficient sample of pathogens to be included.

We ended up with 214 MSAs being studied. Most have fewer than 20 hospitalizations with an average of five, and period HHI scores range from 0.035 to 1.00. The smallest MSAs had to be excluded from the sample due to insufficient data. Large MSA tend to have many hospitalizations and have the lowest levels and concentration growth. The majority (77 percent) of MSAs have an HHI higher than 0.25, which is considered highly concentrated by the Federal Trade Commission. The largest increases in HHI scores occurred in the smallest MSA, therefore calculating the magnitude of MSA in our model is critical.

We design an MSA quasi-experiment to estimate a simple linear equation describing nurse wage growth as a function of national wage trends, MSA baseline wage trends, and changes in hospital consolidation while accounting for economic trends and hospital effects. One of the challenges in this research is how to account for the heterogeneous underlying wage growth at the MSA level which may confound the effect of consolidation. We choose to incorporate a non-parametric flexible step to the preprocessing data that allows us to detect trends for MSA. We use GenMatch, a statistical matching package, to apply a complex algorithm to match four ‘similar’ workers to each nurse by the MSA, public cohort. Matches are based on worker and demographic characteristics from American Community Survey data. Workers’ wage growth similar to the baseline net growth of the MSA is used, leaving a standardized measure of nurses’ wage growth used in subsequent parametric linear regression analyses.

Results from our preferred specification that takes market size into account strongly suggest that increased hospital system consolidation in smaller MSAs (i.e., MSAs with fewer than 5 hospitals, except for the smallest not in the study) is negatively associated with nurse wage growth. The coefficients from our set of regressions interacting with HHI growth with a small dummy variable MSA give consistent results across the three specifications: 8.95, 8.53 and 7.03 (the coefficients are significant at the 5% level, and are not statistically distinguishable). Reduces impact without controlling the amount of MSA.

These estimates translate to a pay fine for nurses of between $0.70 and $0.90 per hour for every 0.1 increase in the HHI standardization measure. However, the standard errors are quite large—a 95 percent confidence interval around our preferred estimate runs from a large negative effect to a slight negative effect (-13.64 to -0.42 from a point estimate of -7.03). The average hourly wage for nurses at small MSA is $35.22 in the second shift. Applying a 0.1 increase in consolidation—a typical increase for smaller MSAs as consolidation increases—means that hourly wages would have been $0.70 higher, indicating a 2% pay cut. This is an outcome that could add up to very large losses in wages given the high degrees of hospital consolidation. This plus our secondary finding that real hourly wages for nurses grew less than wages for similar workers by $4.08 an hour determines the relative gap in nurse wage growth.

The results presented here strongly suggest that increased integration into local hospital markets limits nurse wage growth. This research has policy implications for antitrust regulation and healthcare policy given that the authorities focus their attention primarily on merger activity. Our results suggest that they may have to widen their surveillance and enforcement lens and pay attention to other ways in which consolidation occurs, for example through hospital closures, which lead to higher levels of concentration that alter degrees of monopoly and/or monopoly power.

One caveat to this study is that smaller rural and rural areas were not included due to data limitations. Further exploration, perhaps using administrative data on nurses, may provide further insight into the dynamics of smaller market concentration.
Silvia

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