WP/21/180 U.S. Healthcare: A Story of Rising Market Power, Barriers to Entry, and Supply Constraints by Li Lin, Mico Mrkaic and Anke Weber © 2021 International Monetary Fund WP/21/180 IMF Working Paper Western Hemisphere Department U.S. Healthcare: A Story of Rising Market Power, Barriers to Entry, and Supply Constraints Prepared by Li Lin, Mico Mrkaic and Anke Weber1 Authorized for distribution by Nigel Chalk July 2021 IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management. Abstract Healthcare in the United States is the most expensive in the world, with real per capita spending growth averaging 4 percent since 1980. This paper examines the role of market power of U.S. healthcare providers and pharmaceutical companies. It finds that markups (the ability to charge prices above marginal costs) for publicly listed firms in the U.S. healthcare sector have almost doubled since the early 1980s and that they explain up to a quarter of average annual real per capita healthcare spending growth. The paper also finds evidence that the Affordable Care Act and Medicaid expansion were successful in raising coverage and expanding care, but may have had the undesirable side-effect of leading to labor cost increases: Hourly wages for healthcare practitioners are estimated to have increased by 2 to 3 percent more in Medicaid expansion states over a five-year period, which could be an indication that the supply of medical services is relatively inelastic, even over a long time horizon, to the boost to demand created by the Medicaid expansion. These findings suggest that promoting more competition in healthcare markets and reducing barriers to entry can help contain healthcare costs. JEL Classification Numbers: I11, I13, I18, D43 Keywords: Healthcare, Market Power, Affordable Care Act. Author’s E-Mail Address: aweber@imf.org, llin@imf.org, mmrkaic@imf.org 1 We thank Keith Branham, Piergiorgio Carapella, Nigel Chalk, Federico Diez, Kenneth Finegold, Daniel Leigh, Rui Mano, Nguyen, Steven Sheingold, Joel Ruhter, Benjamin Sommers, Suchanan Tambunlertchai, Yannick Timmer, Jeromin Zettelmeyer and IMF seminar participants for helpful comments and discussion. Peter Williams provided excellent research assistance. We are grateful to Federico Diez, Daniel Leigh and Suchanan Tambunlertchai for sharing their codes on computing markups. All remaining errors are our own. 3 Contents Abstract ..................................................................................................................................... 2 I. Introduction ........................................................................................................................... 4 II. Key Institutional Arrangements of the U.S. Healthcare System.......................................... 6 III. A Few Observations on U.S. Healthcare and Comparison To Other Countries................. 9 IV. Market Power.................................................................................................................... 13 A. Overall Healthcare Sector Markups ............................................................................... 14 B. Hospitals......................................................................................................................... 16 C. Healthcare Practitioners ................................................................................................. 16 D. Insurers........................................................................................................................... 17 E. Correlations .................................................................................................................... 19 V. Market Power and Healthcare Cost Determinants ............................................................. 19 A. Data and Methodology................................................................................................... 20 B. Results ............................................................................................................................ 22 VI. The Impact of the Patient Protection and Affordable Care Act on Healthcare Sector Wages...................................................................................................................................... 24 A. Empirical Strategy.......................................................................................................... 26 B. Data ................................................................................................................................ 29 C. Results ............................................................................................................................ 29 VII. Conclusion....................................................................................................................... 33 References............................................................................................................................... 47 4 I. INTRODUCTION 1. Healthcare in the U.S. is the most expensive in the world, both in absolute dollar terms and as a share of GDP. In 2019, the United States spent about $3.8 trillion on healthcare or about $11,000 per person. Furthermore, the share of healthcare costs in GDP has increased from 5 percent in 1960 to about 18 percent in 2019.2 2. Effective provision of healthcare has become a macro-critical issue for three reasons. First, as argued by Case and Deaton (2020), the U.S. healthcare system has long underperformed in ensuring the effective delivery of services, particularly to the poor and vulnerable, producing results (for example, measured by lifespan, infant mortality, burden of chronic diseases and other health indicators) that are significantly below countries that spend less per capita. This underperformance increases inequality and consequently weighs on economic growth.3 Second, the large and increasing cost of healthcare has important fiscal consequences. Curbing the excessive growth of healthcare cost is a necessary condition to rein in the unsustainable growth of U.S. fiscal entitlement spending. Finally, given the predominance of employer funded health insurance in the U.S., increasing healthcare costs could crowd out wage growth and shift more and more compensation to non-cash benefits. 3. The literature has proposed several reasons for the high cost of U.S. healthcare, which include both market failures and bad policies. The typical candidates are: • Luxury good hypothesis: consumption of healthcare will increase more than proportionally as income rises. • Supplier driven demand: doctors suggest or prescribe tests and procedures with unproven medical benefits; consumers/patients comply with the suggestions due to asymmetric information, combined with lack of a user pay incentive for those with coverage and low pricing transparency. • Baumol’s cost disease: due to the equalization of wages across industries and sectors, the sectors with slower productivity growth see their unit costs increase. Healthcare is typically considered a non-progressive (less productive) sector. • Market power of the main players, that is providers and insurers. For example, U.S. medical doctors limit the entry into the profession, thereby increasing the cost of labor. In addition, mergers of hospitals have increased their market power and prices (and also reduced the quality of care). 2 Source: Center for Medicare and Medicaid Services (CMS), National Health Expenditure Accounts. 3 A large and growing literature documents the central role of health status in shaping economic outcomes both within and between generations (Haas, Glymour, and Berkman, 2011; Kane, 2015; O’Brien and Robertson, 2018). 5 4. This paper focuses on market power and competition in the healthcare sector, taking a three-pronged approach: • Estimating market power. We explain how we measure market power in the form of markups (the ability to charge prices above marginal costs) and provide estimates for the overall healthcare sector (including providers, pharmaceuticals, and healthcare equipment). We also use micro-data on U.S. hospitals and calculate markups across states. Hospitals are of particular interest since about one-third of healthcare spending is associated with hospitals.4 In addition, we explore whether healthcare practitioners enjoy wage premia over employees in other sectors with similar profiles and qualifications and shed some light on marginal loss ratios (the ratio of claims over premia, the inverse markup) of insurers. We also assess whether higher hospital markups are associated with lower wage premia and markups of insurers. • The impact of market power on healthcare spending. We analyze the connection between market power and other determinants of healthcare spending, notably income and Baumol’s cost disease and their impact on costs. We do so in a cross-country setting and also exploit the variation in costs across U.S. states. • Event study on the impact of the Affordable Care Act (ACA) on healthcare sector wages. We study if the ACA contributed to the faster pace of healthcare wage increases in recent years by using an event study that exploits the heterogeneity in states’ choices and timing in expanding Medicaid. 5. We find evidence that market power in the U.S. healthcare sector has increased significantly since the 1980s and has contributed to rising healthcare costs. Markups for publicly listed firms in the U.S. healthcare sector have almost doubled since the early 1980s. Hospital markups have also increased significantly (by more than 6 percent on average) since the late 1990s across U.S. states. Incorporating markups into OECD cross-country regressions shows that, on average, they have contributed to up to a quarter of annual per capita U.S. healthcare cost growth. Similarly, results from U.S. state level regressions show that hospital markups are a significant driver of healthcare spending, explaining about 15 percent of variation across states. Rising hospital markups are not, however, associated with lower labor costs or insurance markups (suggesting that providers use their market power to raise prices to consumers rather than taking advantage of their monopsony power to lower costs of providers further down the supply chain). In fact, physicians’ salaries have increasingly risen above the salaries of non-physicians with similar years of education and experience. 6. Following the ACA, wages for healthcare practitioners have increased by more in Medicaid expansion states, compared with non-expansion states. The Affordable Care Act and Medicaid expansion were successful in raising coverage and expanding care, including for low-income individuals. But they may have had the undesirable side-effect of 4Also, publicly traded companies represent only a minority of inpatient and physician care in the U.S., and hence it is important to go more granular, with quality data available for a large number of hospitals. 6 leading to labor cost increases. Hourly wages for healthcare practitioners and technical occupations are estimated to have increased by 2 to 3 percent more in expansion states over a five-year period. We test the results using both state-level wages for healthcare practitioners and technical occupations from the Occupational Employment and Wage Statistics and the metropolitan-level wage index used by Medicare to adjust for labor costs for hospital in different areas. The result is confirmed by an analysis using individual-level data from the Current Population Survey (CPS). We find no significant evidence that wages for other professions increased more in expansion than non-expansion states. 7. The contribution of this paper is thus threefold. First, it presents evidence on the evolution of market power for the healthcare sector overall (and vis-à-vis other OECD countries) and on a more granular basis for the U.S., including by looking at microdata for hospitals. Second, it investigates how this evolution relates to healthcare costs in advanced countries and across U.S. states. Third, it sheds light on a related but less discussed issue, namely that the supply of medical services may be relatively inelastic, even over a longer period, to the boost to demand created by the Medicaid expansion. This could be due to barriers to entry (and even barriers to mobility of existing providers across states), a preference by oligopolistic providers to respond to higher demand with higher prices (and less with an increase in supply) and/or a feature of medical services in general given the high set up costs and time it takes to build capacity. 8. The remainder of the paper is structured as follows. Section II describes some key institutional features of the U.S. healthcare system. Section III benchmarks U.S. healthcare costs and compares prices and outcomes to other countries. Section IV analyzes the evolution of market power in the U.S. healthcare sector, by computing markups for the overall sector, and then goes more granular by looking into hospitals, insurers and medical providers. Section V examines the connection between market power and other determinants of healthcare costs including Baumol’s cost disease and quantifies their effect. Section VI studies the impact of the ACA on healthcare sector wages. Section VII concludes. II. KEY INSTITUTIONAL ARRANGEMENTS OF THE U.S. HEALTHCARE SYSTEM 9. The provision of healthcare in the U.S. is considerably more complex than in other advanced economies. In the U.S., healthcare services are provided by government owned, non-profit institutions and for-profit institutions, with for-profit hospitals accounting for about one fifth of the total number of hospitals.5 Most advanced economies other than the U.S. have universal public healthcare coverage, which covers (at least) primary healthcare services.6 5 Source: https://www.aha.org/statistics/fast-facts-us-hospitals 6 Source: https://www.oecd-ilibrary.org/social-issues-migration-health/data/oecd-health-statistics/oecd-healthdata-social-protection_data-00544-en 7 10. Payment in the U.S. is mostly indirect and a mixture of public and private programs, with private insurance mostly purchased by employers.7 More than half of the population is covered by private insurance, and another 40 percent by the two main public insurance programs, Medicare and Medicaid that date back to 1965 and were enacted through the Social Security Act (Box 1). Medicare ensures access to healthcare for persons age 65 and older. All beneficiaries are entitled to traditional Medicare, a fee-for-service program that provides hospital insurance (Part A) and medical insurance (Part B). Since 1973, beneficiaries have had the option of receiving their coverage through either traditional Medicare or Medicare Advantage (Part C), under which people enroll in a private health maintenance organization (HMO) or managed care organization. In 2003, Part D, a voluntary outpatient prescription drug coverage option provided through private carriers, was added to Medicare coverage. The Medicaid program provides health coverage to eligible low-income adults, children, pregnant women, elderly and people with disabilities. As it is a stateadministered, means-tested program, eligibility criteria vary by state.8 11. The 2010 Affordable Care Act (ACA), popularly known as Obamacare, represented a major overhaul of the system. The act largely retained the existing structure of Medicare, Medicaid and the employer-sponsored market. Effective in 2014, it prohibited most insurance plans from excluding people for preexisting conditions, discriminating based on health status, and imposing annual monetary caps on coverage; and included reforms to require guaranteed issue and renewal of policies, premium rating rules, nondiscrimination in benefits, and mental health and substance abuse parity. The ACA also contained two major components that increased healthcare coverage. The Act expanded the eligibility for the Medicaid program, starting in 2014 with the help of federal subsidies. In states that chose this option, the eligibility threshold for Medicaid increased from 100 percent of the federal poverty line to 138 percent. The ACA also introduced the individual mandate and penalty for not having insurance coverage (although legislation enacted in December 2017 effectively repealed that requirement, starting in 2019) and created the Marketplace, effective in 2014, that offers insurance plans to individuals, families, and small businesses at a subsidized premium. As a result, the share of uninsured approximately halved, from 16 percent before the passage of the Act to about 9 ½ percent in 2019.9 7 The origin of this arrangement goes back to WWII when employers started offering health insurance to compete for scarce workers. 8 Source: https://www.commonwealthfund.org/international-health-policy-center/countries/united-states 9 Source: Center for Medicare and Medicaid Services (CMS), National Health Expenditure Accounts. 8 PRIVATE HOUSEHOLDS PROVIDERS OF HEALTHCARE Box 1. The Flow of Funds in U.S. Healthcare Most of healthcare financing deals with the flow of funds from U.S. households into health insurance funds (both governmental and private), which in turn disburse those funds to various providers. State and Local Taxes Premiums paid to private insurers for state employees STATE GOVT. Medicaid Other programs Federal Medicaid Match Federal Taxes Cuts in paycheck PRIVATE EMPLOYERS FEDERAL GOVT. Medicare Medicaid, etc Premium contributions for federal employees, Marketplace (subsidies), Medicare Advantage PRIVATE HEALTH INSURERS Individual insurance, top off employment-based insurance, or Medigap, or Medicare Advantage Plans Out of pocket at point of service Other private spending Sources: Reinhardt, 2011 and IMF staff. About 40 percent of funds come from public sources (Medicare/Medicaid), while another third come from private health insurance. Out of pocket expenses account for about 10 percent of total expenditures. More than half of the population is covered by employer-sponsored health insurance, about forty percent by Medicare and Medicaid. A relatively small proportion (3 percent) is part of the Marketplace. About 10 percent remains uninsured. National Health Expenditures (2019=US$3.8 trillion) Type of Insurance (2019, percent of population) Out of pocket 60 5% 11% 11% Private Health 50 Insurance 40 Medicare 4% 30 Medicaid 16% 32% 20 Other Health Insurance Programs 10 21% Other Third Party Payers 0 Investment Sources: CMS. Notes: Right chart does not add up to 100 percent, as various insurance types can overlap. Other Third Party Payers include worksite health care, other private revenues, Indian Health Service, workers' compensation, general assistance, maternal and child health, vocational rehabilitation, other federal programs, Substance Abuse and Mental Health Services Administration, other state and local programs, and school health. 9 III. A FEW OBSERVATIONS ON U.S. HEALTHCARE AND COMPARISON TO OTHER COUNTRIES Income and healthcare spending are correlated but the U.S. is a total outlier. 12. The share of healthcare in GDP grew in all OECD countries, but Figure 1. Health Care Spending Per Capita, 2019 12000 Health Care Spending (USD PPP) the growth in the U.S. was much 10000 faster. While in 1970 the share of United States healthcare expenditures in the U.S. was 8000 high at around the 90th percentile of 6000 OECD countries, its fast growth pushed 4000 the U.S. above all other OECD countries Ireland Luxembourg by 2019 (Figure 2).10 The same is true in 2000 per capita terms, with U.S. per capita 0 health expenditures (based on purchasing power parity) rising to about four times the median of the OECD by 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 GDP per capita (USD PPP) Sources: OECD, IMF Staff Calculations. 2019. Taking into account that the per capita income in the U.S. is higher than in most OECD countries fails to explain the phenomenon (Figure 1). 20 Figure 2. Healthcare Spending in OECD Countries OECD Countries: Total Health Expenditures 10th percentile Median 90th percentile USA 10000 OECD Countries: Total Health Expenditures 10th percentile Median 90th percentile USA 15 5000 USD per capita 10 Percent of GDP 5 0 0 1970 1980 1990 2000 2010 2020 1970 1980 1990 2000 2010 2020 Sources: OECD and IMF staff calculations. Per capita health care spending is measured as USD PPP. Key health-related indicators do not reflect the high expense. 13. The high healthcare expenditures in the U.S. do not lead to better outcomes. Life expectancy, arguably the most important indicator of health, is significantly lower in the U.S. than in comparator countries and has declined after 2012. Several potential explanations are 10 The aging of baby boomers likely has contributed to increasing spending, e.g., Alemayehu and Warner (2004) estimated that per capita health care costs from 2000 to 2030 would increase 20 percent due to aging, or 0.6 percent/year. 10 on hand for this phenomenon, including inefficient utilization of healthcare resources and a high prevalence of chronic diseases and obesity of the U.S. population (both are about twice as high as in other advanced countries). The opioid crisis and gun violence may also play a role. However, for some determinants of health such as smoking, the U.S. ranks among the lowest in advanced countries (Papanicolas and others, 2018). Life expectancy at birth Figure 3. Life Expectancy and Health Care 90 85 80 United States 75 70 65 60 0 2000 4000 6000 8000 Health Care Spending (USD PPP) Sources: OECD, IMF Staff Calculations. 10000 12000 The largest percentage of spending goes to in-patient and outpatient care. 14. U.S. spending on inpatient and outpatient care per capita is about twice that of comparable countries11 and accounts for about 60 percent of total spending. Inpatient care is provided in a hospital or other type of inpatient facility, where the patient spends at least one night. Outpatient care refers to almost any other kind of care (and can be provided by hospitals, walk-in clinics, outpatient surgery centers or doctors’ offices). Out of the $3.8 trillion spent on healthcare in 2019, about $1.2 trillion was spent on hospitals and $1 trillion on professional services (physicians/dental).12 Another category where the U.S. stands out is on administrative spending, which is more than four times higher per capita than in other comparable countries. Part of this difference is likely driven by the complexity of the U.S. healthcare system, as described in Section II. In most advanced economies, governments are heavily involved in healthcare and provide insurance to their citizens, which reduces the direct costs of insurance and other administrative costs. But administrative costs fail to account for the bulk of the cost differences between the U.S. and other advanced economies. Table 1. Healthcare Spending Per Capita, by Category (2018) Inpatient and outpatient USA Comparable Countries $6,624 $2,718 Prescription drugs and medical goods $1,397 $884 Administrative $937 $201 Long-term $516 $1,111 Preventive $309 $175 Other $854 $439 Total $10,637 $5,528 Source: https://www.healthsystemtracker.org/archive/?_sft_category=spending. Data consist of current expenditures on health expressed as per capita, current prices, current purchasing power parity (PPP), in U.S. dollars. 11 Comparable countries include Austria, Belgium, Canada, France, Germany, Netherlands, Sweden, Switzerland, and the United Kingdom. 12 Some have argued that doctors’ liability (malpractice) insurance is one of the main causes of high healthcare cost. However, the data do not support this explanation. The average annual payouts from malpractice insurance are about $5 billion per year, which is a small fraction of total healthcare cost. Furthermore, data show that the utilization of healthcare resources in the U.S. is not higher than in comparable countries (which does not support the argument that fear of litigation creates strong incentives to undertake unnecessary procedures). 11 “It’s the prices.” 15. Price differences are broad based and not limited to a few procedures. Looking at the largest category of spending, Figure 4 shows that with a solitary exception, prices of both inpatient and outpatient procedures are significantly higher in the U.S. than in other countries. A comparison of prices of other categories of spending leads to similar conclusions.13 Figure 4. Prices of Hospital and Outpatient Procedures (2017) Source: Healthcare Cost Institute. Notes: Figure shows median prices in USD paid by a sample of private health insurance companies for specific health care services in nine countries. Comparisons across different countries are complicated by differences in sectors, fee schedules, and prices may not be representative of prices paid by other plans in that market. The HCCI attempted to minimize these limitations by selecting services with very specific definitions and wording survey questions to match the procedures that are the basis of the US payment system. 16. Increased utilization contributes less to total costs than price growth. It is instructive to decompose changes in total U.S. healthcare expenditures into price growth and changes in quantities (i.e. utilization).14 Figure 5 shows the decomposition for the period 2014–18. During this period, price growth contributed approximately three times as much as changes in utilization to the growth in total expenditures. 13 See also https://www.brookings.edu/research/a-dozen-facts-about-the-economics-of-the-u-s-health-caresystem/ 14 Metrics like average length of stay in hospital are below the OECD average, suggesting that the U.S. is not an outlier in utilization. https://data.oecd.org/healthcare/length-of-hospital-stay.htm 12 Figure 5. Cumulative Change in Spending per Person, Utilization, and Average Price by Service Category 30% 25% 20% Total Inpatient Outpatient Professional Services Prescription Drugs 30% 25% 20% Average Price 15% 15% Spending 10% 10% 5% 5% Utilization 0% 2014 2015 2016 2017 2018 0% 2014 2015 2016 2017 2018 -5% -5% Sources: Healthcare Cost Institute, Annual Report. Notes: Utilization and average prices (adjusted for inflation) on left chart account for changes in the type or intensity of services used, except for prescription drugs. Prescription drug spending is the amount paid on the pharmacy claim, which reflects discounts from the wholesale price, but not manufacturers’ rebates. Density of healthcare providers is well below comparable countries. 17. The density of physicians in the U.S. is below other advanced economies and this is not compensated by a larger number of nurses. In 2018, the U.S. had 2.5 physicians per 1000, well below other countries and the difference to other countries has been increasing over time.15 While in the U.S. nurses perform some services that in other countries only physicians are allowed to perform, there is no evidence that the U.S. has a higher density of practicing nurses than other countries today. This was different some years ago, but growth in the U.S. has not kept pace with other countries.16 15 Nunn and others (2020) find that the flat rate of per-capita medical residency positions since 1960— contrasted with rising expenditures and healthcare needs for an aging and richer population—suggests that limited supply of physicians has been a problem. 16 Zhang and others (2020) predict a shortage of 139,160 physician jobs by 2030. Domestic barriers to entry include the limited numbers of residency positions, which are capped by Medicare. Efforts are underway to increase positions through the Resident Physician Shortage Reduction Act of 2021, which would gradually raise the number of Medicare supported graduate medical education positions by 2,000 per year for seven years, for a total of 14,000 new slots. Barriers to entry for immigrating healthcare sector professionals are also high, with strict licensing requirements. In addition to passing a medical exam, immigrating physicians are required to undertake a medical residency program, with some studies showing that the number of years of U.S. medical residencies required for foreign-trained doctors to get licensed in the United States—regardless of how many years of experience they have in other countries—is often higher than it is for a graduate from a U.S. medical school (Center for American Progress, 2020). 13 Figure 6. Density of Physicians and Nurses Sources: OECD and IMF staff calculations. Notes: Practicing nurses refers to the total number of nurses certified/registered and actively practicing in public and private hospitals, clinics, and other health facilities, including self-employed. Nursing assistants and midwives should be included. IV. MARKET POWER 18. Market concentration in the U.S. healthcare sector is high. One indicator is the Herfindahl-Hirschman Index (HHI), shown in Figure 7, which takes the market shares of the respective market competitors (in percent), squares and adds them together, with specific cutoff values indicating levels of concentration. Under the Department of Justice/Federal Trade Commission Merger Guidelines, an HHI of 1,500 indicates a moderately concerning concentration level, and a HHI of 2,500 indicates high concentration. As shown in the figure, insurers, specialist physicians, and hospitals markets are all highly concentrated, with hospital market concentration especially high (with a HHI of 5,790 in 2016). Primary care physicians are between the moderate and high concentration levels, but they have experienced a rapid increase in the HHI. One explanation for this is that many private practices have been acquired by larger groups. 14 Figure 7. Market Concentration in U.S. Healthcare Source: Fulton, 2017. Notes: The geographic market for hospitals, specialist physician organizations, and insurers in this study was the Metropolitan Statistical Areas (MSAs). The figure shows the mean MSA Herfindahl-Hirschman Index (HHI) using data from the American Hospital Association (AHA) Annual Survey database; the SK&A Office Based Physicians Database provided by IMS Health (now Quintiles); and for insurers, the Managed Market Surveyor File from Health Leaders InterStudy (now Decision Resources Group). 19. Many studies have linked the high market concentration to prices and outcomes. Although higher concentration could result in greater economies of scale and produce efficiencies, the evidence does not point in that direction (Gaynor, 2020). Concentrated markets are associated with higher hospital prices, with price increases often exceeding 20 percent when mergers occur in such markets (e.g., Dafny and others 2019, Thompson 2011, Gowrisankaran and others, 2015). Cooper and others (2019) examine the 366 mergers and acquisitions that occurred between 2007 and 2011, and find that prices increased by over 6 percent when the merging hospitals were geographically close (e.g., 5 miles or less apart), but not when the hospitals were geographically distant (e.g., over 25 miles apart). These price increases did not appear to improve quality (Dafny and others, 2020). A relatively small number of studies has examined the impact of physician organization concentration. Overall, these studies found that higher concentration was associated with higher physician prices across a range of services (e.g., Baker and others, 2014). 20. This section will explore alternative measures of market power, with a focus on firm-level markups—the ratio of prices to (marginal) production costs. Thereby we provide a more granular measure of market power than concentration. We also compute measures of market power of healthcare practitioners (wage premia) and insurers (marginal loss ratios) to examine if increased market power by hospitals is associated with lower labor costs and insurers profits. A. Overall Healthcare Sector Markups 21. Estimation of markups from income statements and balance sheets is based on the methodology of Diez and others (2018). Diez and others (2018) extend the U.S. based 15 work of De Loecker and Eeckhout (2017) to a multi-country setup. The idea is to estimate a production function to recover the input elasticity, and combine it with data on input and output to obtain the markup estimates.17 The approach uses the first order conditions of firm’s profit maximization to derive an expression for the markup based on the elasticity of output to the capital stock and the ratio of sales to expenditures. Elasticities are then estimated using GMM. 22. The analysis uses Worldscope data, obtained through Datastream provided by Thomson Reuters. It contains information on financial fundamentals and ratios from over 81,000 publicly listed companies, accounting for over 99 percent of world market capitalization in 74 economies. Firms in the healthcare sector encompass healthcare equipment, healthcare providers and services, pharmaceuticals, and medical research. For advanced economies, the data date back to the 1980s. After selecting countries with enough observations and some data cleaning, markups were computed for 9 advanced countries (Australia, Canada, Germany, France, UK, Japan, Korea, Sweden, United States). 23. U.S. healthcare firms have been able to run persistently higher markups than firms in other countries. In line with rising market concentration, U.S. healthcare median markups have increased by more than 70 percent since 1980. In contrast, the median markup of other advanced economies has risen by about 40 percent (Figure 8). Zooming in on the U.S., healthcare sector markups have been increasing rapidly compared to industrials, with less of an increase compared to all other industries, meaning that rising market power is not unique to the healthcare sector.18 Figure 8. Comparing Markups in the U.S. and Select Advanced Economies Median Markups in Healthcare: U.S. vs Select AEs 2.3 2.1 USA Other 1.9 1.7 1.5 1.3 1.1 0.9 0.7 0.5 U.S. Healthcare Markup Relative to... 1.50 …All Sectors …Industrials 1.40 1.30 1.20 1.10 1.00 0.90 0.80 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 Sources: Thomson Reuters, OECD, IMF staff calculations. 17 As explained in Diez and others (2018), we use a Cobb-Douglas production function and control function approach. 18 As shown by Diez and others (2018) and Akcigit and others (2021), the technology sector also experienced rapid increases in markups. 16 B. Hospitals 24. Using data from the Centers for Medicare & Medicaid Services (CMS), we estimate markups for U.S. hospitals. Medicare-certified institutional providers are required to submit annual cost reports to a Medicare Administrative Contractor (MAC). CMS maintains the cost report data in the Healthcare Provider Cost Reporting Information System (HCRIS). To compute markups using the methodology of Diez and others (2018), we extract data from income and balance sheets on total operating expenses, total patient revenues and total fixed assets. After some data cleaning, we are left with more than 5000 hospitals between 1997 and 2018. 25. Markups for hospitals have been rising and there is significant variation across U.S. states. Figure 9 reports the distribution of markups in 1998 and 2018 for hospitals. The distribution of markups has broadened and become more skewed over time. Computing median markups over time across states, we find that hospitals’ median markups have been increasing by about 6 percent since 1997. While the overall increase is moderate, the increase in dispersion is consistent with markup increases being driven by the largest hospital groups. Figure 9. Markups in U.S. Hospitals Distribution of Hospital Markups 10 Median Hospital Markups Over Time Density .98 1 1.02 1.04 1.06 1.08 8 6 1998 2018 4 2 0 .8 1 1.2 1.4 Markup 1.6 1995 2000 2005 2010 year 2015 2020 median_markup p25 p75 Sources: CMS, IMF Staff Calculations. C. Healthcare Practitioners 26. Using data from the Current Population Survey, we estimate the wage premia of healthcare sector professionals. Following Glied and others (2015), we compare the wages of healthcare practitioners and technical occupations with wages of workers in other occupations that have the same years of education and work experience and the same individual characteristics (measured by race, sex, marital status, full-time work status and metropolitan Figure 10. Wage Premia Source: Current Population Survey and IMF staff calculations. 17 location).19 For physicians, the time spent in residency is counted as work experience, not years of schooling. We run regressions of individual wages from all occupations on the above variables and an occupation dummy (equals one for individual in healthcare occupations and zero otherwise). We interpret the coefficient on the dummy variable as the wage premia for healthcare sector professionals. The data are from 1997 to 2019. 27. Wage premia of healthcare sector professionals are close to 30 percent on average.20 Wage premia for physicians and surgeons are even higher and estimated at about 50 percent on average over our estimation horizon. Wage premia for both general healthcare sector and physicians have been largely stable in the past two decades, with the latter on a small upward trend in the last decade. Wage premia of physicians and surgeons appear to be more cyclical than wage premia for general healthcare professionals, even though the dependent variables are real wages (instead of nominal wages) and the regressions have incorporated the cyclical stance of the economy. This suggests that some healthcare services could resemble a “luxury good” more than a “necessity good”, the latter would imply that wage premia should tend to be “counter-cyclical”. D. Insurers 28. We follow Cicala and others (2019) and define markups for the insurance sector as the inverse of the medical loss ratio (MLR). The MLR is the ratio of a firm’s expenditures on medical claims to its premium revenues. An insurer with more market power will be able to achieve lower MLRs. As part of the ACA, the U.S. Federal Government instituted minimum requirements on insurers’ MLRs. On a state-by-state and segment-bysegment basis, the regulation requires insurers to maintain an MLR of at least 80 percent in the individual and small group market segments and 80 percent in the large group market segment. If an insurer falls below the threshold, it has to send rebates to its policyholders.21 CMS administers the rule and its Center for Consumer Information and Insurance Oversight (CCIIO) set new data reporting requirements for health insurers, collecting these in a new regulatory database since 2011, containing detailed financial information. We use the database to extract MLRs for 2486 insurance companies (following some data cleaning). 19 Healthcare practitioners and technical occupations cover a wide range of occupations including general practitioners, nurses, specialists, therapists, and healthcare technicians. For a complete list of occupations under this category, see the definition of “29-0000 Healthcare Practitioners and Technical Occupations (Major Group)” in the Occupational Employment and Wage Statistics. 20 The regression does not capture the quality of education. Therefore, the wage premia could be compensating for the quality of education, to the extent that medical education is of higher quality. In addition, the definition of “wages and salaries” in CPS explicitly includes cash bonuses, but not stock incentives. Therefore, the wage premia could also be compensating for the lack of stock incentives for physicians. 21 These are calculated so that when the insurer has paid out the rebates and the rebates are counted as claims, the MLR is equal to the regulated threshold (Cicala and others, 2019). Due to this regulation, there is an incentive to cluster around thresholds, representing a potential caveat to our analysis. But, as our results will show, there is still significant variation among insurers though. 18 29. MLRs vary significantly among insurers in the individual market with much less variation for group insurance. Figure 11 shows the cumulative density functions (CDF) of MLRs in the individual and group markets for years 2011, 2014, and 2019.22 After an initial increase in MLRs between 2011 and 2014, the distribution subsequently shifted to the left again, with more movement among firms close to the 0.80 federal threshold. There is very little variation in MLRs across groups insurers. Share of Life-Years Share of Life-Years Figure 11. Distribution of MLRs Individual Market 1 Large Group Market 1 .8 .8 .6 .6 .4 .4 .2 .2 0 .4 .6 .8 1 MLR 2011 2019 2014 0 1.2 .6 .8 1 1.2 MLR 2011 2019 2014 Sources: CMS, IMF Staff Calculations. 30. In line with the broadly flat Herfindahl indices shown in Figure 7, markups (inverse MLRs) have not increased significantly since 2011, but between state differences are correlated with market concentration. We calculate an average MLR for U.S. states using enrollment weighted averages of per-life year values between 2011-2019. The median MLR across states first increased substantially in 2014 among the individual market and subsequently decreased. There is less movement for the large group insurers. This could reflect ACA changes that took effect in 2014, which expanded access to health insurance, and which could have led to increased demand for healthcare with premia not catching up with claims initially. There is significant cross-state variation and MLRs are negatively correlated with market concentration as measured by the Herfindahl index. Regressing annual changes in MLRs across states on Herfindahl indices shows a clear negative relationship, which is significant for the individual market and small group but not for the large group market (Figure 12 and Table 2). 22 Self-insured plans are not required to report the MLR and hence are not included in the analysis. 19 Figure 12. MLRs Over Time and Correlation with Market Concentration Indices Median MLR Across U.S. States Market Concentration and MLRs (Individual Insurance) dHerfindahl = -.00176 - .02703 dHHI R2 = 0.8% .95 .4 .9 .2 Change in MLR .85 0 .8 -.2 2010 2012 2014 2016 year 2018 2020 Individual Market Large Group Small Group -1 -.5 0 .5 1 n = 400 RMSE = .0633665 Change in Herfindahl Sources: CMS, IMF Staff Calculations. E. Correlations 31. Pairwise correlations of our estimated markups and wage premia indicate that states with higher hospital markups do not experience lower wage premia or insurance markups. The correlation between the hospital markups and wage premia is very small and positive, suggesting that more market power by hospitals is not associated with doctors and nurses earning a smaller wage premium. Similarly, the correlation with insurance MLRs is negative, so more market power by hospitals is not associated with lower markups by insurers.23 This suggests that hospitals use their market power to raise prices to consumers rather than taking advantage of their monopsony power to lower costs of providers further down the supply chain. But there is a positive correlation between wage premia of practitioners and insurance MLRs, so in states in which insurance companies have more market power, physicians and nurses earn less (Table 3). The latter is in line with Roberts and others (2017) that find that higher health insurer concentration is being associated with lower physician prices. V. MARKET POWER AND HEALTHCARE COST DETERMINANTS 32. Does market power increase healthcare costs and exacerbate Baumol’s cost disease? Having estimated both overall markups for OECD countries and hospital markups for U.S. states, we can integrate these estimates in standard cross-country and state level regressions of per capita healthcare expenditures on various potential determinants. These regressions typically use OECD data and include per capita income and population aging (e.g., Baltagi and others, 2016, Newhouse, 1992, Smith and others, 2009 and Moscone and Tosetti, 2010 (U.S. states)). Some studies have also investigated the role of Baumol’s costs disease for OECD countries (Hartwig, 2008, 2011 and Colombier, 2017) and U.S. states (Bates and Santerre, 2013). The existing literature has typically identified income as the most important factor explaining healthcare cost differences across countries, finding an income 23 The annual correlation between hospital markups and Herfindahl indices for insurers is also positive. 20 elasticity of between 0.4 and 0.9 (suggesting health care is not a luxury good) and a significant but smaller effect of Baumol’s cost disease. There is limited evidence that other variables (e.g., aging) are significant determinants (Baltagi and Moscone, 2010, Grossman, 1972). But none of these studies have so far included market power as an explanatory variable or its potential interactions with Baumol’s cost disease. A. Data and Methodology 33. We first estimate regressions at the OECD level. The basic regression takes the following form: log�
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