This Selected Issues paper on United States 2012 Article IV Consultation discusses rebound of manufacturing production. The U.S. share in global manufacturing production declined through most of the past three decades, but it has stabilized since the Great Recession. It currently represents about 20 percent of global manufacturing value added. Interestingly, after a sharp increase during most of the previous decade, China’s share in global manufacturing has also stabilized since the Great Recession, at a level similar to that of the United States. The notion of a manufacturing renaissance has been fuelled partly by the rebound in production since the end of the Great Recession.

Abstract

This Selected Issues paper on United States 2012 Article IV Consultation discusses rebound of manufacturing production. The U.S. share in global manufacturing production declined through most of the past three decades, but it has stabilized since the Great Recession. It currently represents about 20 percent of global manufacturing value added. Interestingly, after a sharp increase during most of the previous decade, China’s share in global manufacturing has also stabilized since the Great Recession, at a level similar to that of the United States. The notion of a manufacturing renaissance has been fuelled partly by the rebound in production since the end of the Great Recession.

Risky Business: The Uncertainty in U.S. Health Care Spending1

A. Introduction

1. Health care spending in the United States has risen considerably during the past 50 years and is a major threat to the sustainability of U.S. public finances. In 2011, national health care spending accounted for 18 percent of GDP, up from 5 percent in 1960 (Chart). The share of public expenditures increased from 22 percent to 47 percent over the same period. Today public health care expenditure (federal and state and local governments combined) stands at about 8 percent of GDP but is projected to increase to almost 15 percent in 2037 (CBO, 2012; GAO, 2013). Calls for containing the risks posed by this large increase have gained momentum as the higher public debt levels—a legacy of the 2007–08 crisis—brought fiscal consolidation to the forefront of policy discussions (e.g., Emanuel et al., 2012; Orszag, 2013).

uA03fig01

United States: Evolution of Health Care Spending

(percent of GDP)

Citation: IMF Staff Country Reports 2013, 237; 10.5089/9781484376553.002.A003

Sources: Centers for Medicare and Medicaid Services; IMF staff calculations.

2. More recently however, health care expenditure growth has slowed (Chart).2 Private health care spending growth closely mimicked GDP growth during the 2003–11 period, declining sharply in 2008 and then slightly increasing in 2010 and 2011. Growth of public health care spending started declining in the early 2000s, increased in 2009 when GDP plunged, and has been declining since then.3

uA03fig02

Health Care Spending and GDP Growth

(real, percent)

Citation: IMF Staff Country Reports 2013, 237; 10.5089/9781484376553.002.A003

Sources: Centers for Medicare and Medicaid Services; Bureau of Economic Analysis; World Economic Outlook; IMF staff calculations.Note: GDP is deflated by CPI; health care spending is deflated by medical CPI.

3. The objective of this chapter is three-fold:

  • First, we assess whether the recent slowdown is permanent or temporary. Understanding the nature of the decline in health care spending growth has key implications for the forecasts. To the extent that the recent slowdown is reflecting fundamental changes in health care delivery and payment practices, one can be confident that the more moderate growth in expenditure can be sustained going forward. If the slowdown is primarily driven by the economic cycle, it must be treated as temporary and appropriately discounted in the projections.

  • Second, based on this assessment, economic and demographic trends, and the anticipated impact of the Patient Protection and Affordable Care Act of 2010 (ACA) and other current policy initiatives, we draw inferences for future health care spending.

  • Third, we discuss the policy options going forward.

4. The chapter concludes that, even under optimistic assumptions about the growth health care costs, spending will rise due to population aging, requiring measures that lower per capita spending or raise additional revenues. We find that cyclical factors explain some but not all of the slowdown, in line with recent studies, with the unexplained portion of the slowdown likely to be related to recently implemented policies. Even if these savings were to persist going forward, pressure from population aging will increase health care spending as a share of GDP. Hence, new, revenue-raising measures that increase the degree to which beneficiaries share the costs related to the provision of health care should also be considered, in addition to the cost-bending initiatives already in the pipeline.

B. What Explains the Recent Slowdown in Health Care Spending Growth?

5. There are five major drivers of health care spending growth (BPC, 2012).

  • Income growth: rising income leads to higher spending on health care while falling income and job losses may lead to less demand for health care as dispensable needs are deferred4;

  • Relative inflation: in sectors where productivity gains are more difficult to achieve, such as health care and education, unit costs rise faster (the “Baumol effect”) and thus may drive a gap between health care inflation and general inflation;

  • Institutional framework and policies determining the way health care is provided and financed;

  • Advances in medical technology5;

  • Demographic factors affecting the health profile of the population, in particular, longer life expectancy and the rising prevalence of chronic conditions due to aging and lifestyles.

6. A few studies have focused on the relationship between health care spending and income growth to assess whether the recent slowdown can be explained by cyclical factors. Estimates of the portion attributable to cyclical factors range from about one third (Cutler and Sahni, 2013) to three-quarters (KFF, 2013). Others argue that falling real incomes had a role but so did changes in insurance coverage (Holahan and McMorrow, 2013). All agree that there is at least the potential that secular trends—greater provider efficiency, slower diffusion of technology, increased cost sharing—have also contributed and that these trends may continue to generate savings. Indeed, studies using disaggregated data show that changing practices by providers (e.g., a shift away from treating terminal-stage diseases to preventive care) and insurers (e.g., less generous benefits) helped reduce health care spending growth over the last decade (Shapiro, 2013; Ryu et al., 2013).

uA03fig03

Decomposing Health Care Spending Growth

(percent)

Citation: IMF Staff Country Reports 2013, 237; 10.5089/9781484376553.002.A003

Sources: Centers for Medicare and Medicaid Services, Bureau of Labor Statistics; IMF staff calculations.

7. Decomposing health care spending growth into price and volume components shows that both have played a role in the moderation observed since the early 2000s (Chart).6

  • The relative price of health care (estimated as medical care CPI adjusted for overall CPI) has grown at a generally slower pace.7 The slower pace was not in a single category but was observed in prices for inpatient services, outpatient services, and medical products.

  • The volume component shows a stronger co-movement with real GDP growth, and reveals a steady decline over the last decade, which has accelerated during the Great Recession.8 Part of the continued drop can be explained by the fact that recessions tend to affect health care spending with a lag, as insurance contracts are often negotiated a year or more in advance and individuals may become eligible for insurance coverage under Medicaid.9

8. Breaking down the aggregate spending also reveals that the slowdown has been widespread across different financing programs and spending categories (Table). An interesting observation is that the slowdown occurred even in Medicare, a program that is relatively insensitive to cyclical changes in the economy as it covers older (mostly retired) beneficiaries. This suggests that the slowdown cannot be entirely due to cyclical factors (Orszag, 2013).

Health Care Expenditures by Source and Category

(real annual change, percent)

article image
Sources: Centers for Medicare and Medicaid Services; IMF International Financial Statistics; IMF staff calculations.

9. Interestingly, slower growth in health care spending was not limited to the United States and occurred broadly across OECD countries. This may be interpreted as an indication that macroeconomic developments may have driven the slowdown at a global level. Indeed, health care expenditure as a share of GDP is positively related to the rate of GDP growth in the post-crisis period. However, the common factor at work may also be related to changes in policies. Many countries have recently adopted policies intended to reduce health care spending growth, including by cutting national health budgets, increasing user charges, introducing non-price rationing, and controlling medical prices (Mladovsky et al., 2012; Morgan and Astolfi, 2013).

10. Econometric analysis suggests that the slowdown can be only partially explained by cyclical factors (Appendix). A regression specification with only country-specific trends and aging indicator does not predict the low rates of health care spending growth in 2008–11. When macroeconomic indicators (such as real GDP growth) are added to the specification, the model predicts significantly lower growth rates. To see what the counterfactual would have been if the Great Recession had not happened, we replace the actual values of the economic indicators in 2008–11 with their average values observed in 2005–07. Growth rates of health care spending simulated in this way are in line with the pre-recession levels. Similarly, the decline in 2002–04 could also be partly explained by the economic slowdown in 2001–02. The results hold for both total and public health care expenditures. Yet, the model fails to explain a considerable portion of the slowdown, indicating a role for factors other than macroeconomic developments.

11. Structural changes (including policies) also have played a role. Excess cost growth (ECG), a catch-all term for all drivers of health care spending other than income growth and population aging, has decreased sharply over the last few years (CBO, 2013). This may be a consequence of a series of recent developments, such as:

  • Increased user charges in the private sector between 2009 and 2011 and high-deductible plans being more widely adopted (Ryu et al., 2013);

  • Greater provider efficiency as a result of quality improvement and cost-cutting initiatives focusing on patient safety, which may have been incentivized by recent and scheduled changes to Medicare policies under the ACA, such as elimination of payments for hospital-acquired conditions in 2009, financial penalties for high readmission rates in 2013 and for hospital-acquired conditions in 2015 (Cutler and Sahni, 2013);

  • Changes in payment policies under the Deficit Reduction Act of 2005 (DRA), which reduced payment rates for imaging, home health services, and durable medical equipment, and the Medicare Improvements for Patients and Providers Act of 2008 (MIPPA), which made substantial cuts to Medicare Advantage plans (White and Ginsburg, 2012);

  • Patent expiration on popular brand-name drugs, and greater availability of lower-cost generics (IMS, 2013);

  • More moderate use of high-cost medical technologies such as magnetic resonance imaging (Cutler and Sahni, 2013).

C. Projecting Health Care Spending: Population Aging is the Key Driver

12. Based on these results, some caution should be used in extrapolating recent health care spending trends into the future. The findings from our analysis are consistent with the general view that the slowdown may have been partly driven by cyclical developments. But even if changes in policies had an impact, some of these changes were a reaction to the recession, and high growth rates could return once the economy fully recovers, or if these policies were reversed or proved to have diminishing returns.

13. In particular, there is some uncertainty on the extent to which ACA will affect health care spending going forward. Expected savings from cost containment provisions and increasing receipts from new taxes within the ACA will have to counter the costs of coverage expansion, as well the costs associated with faster growth in Medicare enrollment due to population aging. Of course, savings from the ACA may prove to be larger than anticipated, but this remains to be seen. Further uncertainty on future dynamics of health care stems from a series of issues related to the ACA implementation (see Box).

14. In light of the recent slowdown, the Congressional Budget Office (CBO) has revised downward its projections of Medicare and Medicaid spending over the next decade.10 For example, in February 2013, the estimates of federal spending for the two programs in 2020 were reduced by about $200 billion—by $126 billion for Medicare and by $78 billion for Medicaid, or by roughly 15 percent for each program—relative to the March 2010 baseline. About two-thirds of the reduction can be attributed to the extrapolation in the future of the slower growth rates observed in the past few years (CBO, 2013). This revision roughly translates to an implicit assumption that expenditures per beneficiary will grow at approximately the rate of growth of per capita GDP over the next decade (that is, ECG is assumed to be close to zero) (Kronick and Po, 2013). In comparison, the weighted average ECG over the 1985–2010 period was 1.5 percent for Medicare and 0.9 percent for Medicaid.11

15. While staff’s health care projections over the next 10 years use CBO assumptions on ECG and factor in additional cost saving measures, health care spending is still expected to increase rapidly. Staff’s forecasts are based on CBO projections, which already incorporate the estimated savings from ACA implementation, and also assume that additional cost saving measures from the administration’s current budget proposal will be implemented, such as drug rebates. Still, public health spending growth is projected to accelerate from historically slow rates starting in 2014, owing to the expansion of coverage under ACA and an increase in the number of baby-boomers becoming eligible for Medicare starting from 2019. As a result, federal health care spending is projected to continue to rise rapidly after 2018, reaching 7 percent of GDP by early in the next decade up from about the current level of 5 percent of GDP.

16. Over the longer term, federal health care spending is projected to increase to about 10 percent of GDP by 2037. Beyond 2023, population aging will add about 3 percent annually to the number of Medicare beneficiaries. The dynamics of ECG are subject to significant uncertainty. In the absence of any anchors to pin down these dynamics, the past is taken as the guide and ECG is assumed to gradually revert back to its historical norm. Overall, ECG is estimated to account for 40 percent of the projected increase of health care spending over the next 25 years, while population aging accounts for the remaining 60 percent (CBO, 2012).

D. Policy Options to Bend the Cost Curve

17. Compared to most other advanced economies, pressures from escalating health care spending is relatively stronger in the United States. Many advanced countries, with very different health care systems, face similar pressures (Clements et al., 2012). Yet, the United States spends much more per capita on health care—18 percent of GDP in 2011 compared to the OECD average of 9½ percent. The discrepancy between the level of health care spending the United States and that in other OECD countries was smaller in the 1970s but widened in the 1980s and persisted in the 1990s and 2000s. Comparison of the long-term (1970–2002) rates of growth in health spending per capita in the United States and a other high-income OECD countries reveals that, although rates of population aging and overall economic growth were similar, ECG was much higher in the United States: 2 percent versus the 1.1 percent OECD average (White, 2007).

18. This mainly reflects the specific U.S. institutional and policy framework. Given that technological advances and health care inflation are likely to be relevant in other countries too, the discrepancy in ECG between the United States and other advanced countries might reflect specific features of the U.S. health care delivery and payment system. These could include:

  • Generous insurance benefit designs that encompass tax deductibility of health insurance costs and low cost-sharing, as measured by out-of-pocket expenses (Furman, 2007);

  • High administrative burden and waste due to fragmentation of care delivery, and distorted incentives because of the reimbursement structure which often is fee-for-service rather than bundled or value-based (Cutler and Ly, 2011);

  • Lack of transparency about the cost and quality of health care and about clinical “best practice” guidelines, which might prevent patients from comparing different hospitals or providers and thus making informed decisions (Kane, 2012).

19. ACA is an important, multipronged step forward towards targeting inefficiencies in the U.S. health care delivery and payment systems and controlling both the level and the growth rate of health care spending. Overall, ACA aims to reform the health care system by improving the infrastructure, information flow, and incentives. The law encompasses a range of potential cost containment measures, targeting some of the institutional features that have been identified as sources of inefficiencies (see Table and Box for a more detailed description of some of these measures). For example, while administrative simplification (through coordination of care and more widespread use of uniform, standard electronic records) and elimination of unnecessary costs (including fraud and abuse) aim to reduce the level of spending, an excise tax on “Cadillac” insurance plans seeks to bend the cost curve by creating incentives for employers and health insurers to devise more cost-effective plans with lower premiums.12 Additionally, the prices that hospitals charge to Medicare for common inpatient procedures have been released for the first time, in an effort to improve transparency and facilitate informed decision making starting in May 2013.

Major Cost-Saving Measures under the ACA

article image
Sources: Centers for Medicare & Medicaid Services; IMF staff estimates.

20. But more can be done. In particular, additional efforts could target prevention as well as better management of chronic conditions and discourage overuse of medical technology.

  • Relative to other countries, the prevalence of chronic conditions is higher in the United States (Thorpe et al., 2007). Moreover, patients with chronic conditions face problems with access and care efficiency, compared to other countries (Schoen et al., 2009). Measures that help gradually reduce the prevalence of chronic conditions and enhance coordination of services to these patients can lead to reductions in future health care spending (RWJF, 2010; Thorpe et al., 2010; Wagner et al., 2001). Such measures can be designed based on international experience.13

  • Intense use of medical technology and rapid diffusion of new advances is one of the features that separate the U.S. health care system from those in other advanced countries (Kane, 2012). Payment frameworks that better align incentives (e.g., bundled payments rather than fee-per-service) and initiatives to encourage informed decisions by patients could reduce overuse of medical technology (e.g., publication by physicians’ associations of cost-benefit analyses and general recommendations on the utilization of imaging technology).14

21. It is important to expedite implementation of the cost-saving measures under the ACA and look for additional ways to contain the rapid rise in health care expenditures in case the current policies fail to provide durable savings. Critically, past reforms have had only temporary effects on health care costs (Altman and Levitt, 2002). Continuous monitoring and successive reforms may be necessary to preserve the savings achieved through the control of ECG.15 Moreover, even if ECG was fully eliminated, an aging population would imply that health care spending as a share of GDP continues to increase and put upward pressure on public debt (Chart). Facing the obligation to serve more beneficiaries (who potentially have higher per capita health care costs because of aging), the health care system will require more financing in order to be able to maintain the same level and quality of benefits. Further measures to bring the costs in line with the benefits (such as through the elimination of health-related tax preferences and enhanced cost-sharing with the beneficiaries) should be part of the discussion on how to tame fiscal pressures from health care spending.

uA03fig04

Federal Debt under Different Health Care Scenarios

(debt held by public, fiscal year basis, percent of GDP)

Citation: IMF Staff Country Reports 2013, 237; 10.5089/9781484376553.002.A003

Sources: CBO; IMF staff estimates.1/ Scenario in which health care spending as a share of GDP remains at its 2012 level throughout the projection period.2/ Scenario in which ECG is assumed to be zero but health care spending continues to grow because of population aging.

ACA Implementation: Uncertainties and Risks

The Patient Protection and Affordable Care Act (ACA) was signed into law by President Obama on March 23, 2010. The Act primarily focuses on three goals: expanding coverage, controlling health care costs, and improving health care delivery system.

The ACA is designed to reduce the uninsured population and improve access to care. All citizens and legal residents are required to have health coverage through one of three options, otherwise they would have to pay a penalty:

  • Employers, who must offer coverage if they have 50 or more full-time workers;

  • Health Insurance Marketplaces, which provide premium credits and cost-sharing subsidies to those whose income is between 133 and 400 percent of the federal poverty level (FPL);

  • Medicaid, a primary health insurance program run jointly by the federal government and states covering nearly 60 million low-income individuals today (eligibility criteria vary across states), will be expanded to offer coverage to those with income below 133 percent of FPL. This portion of the insurance coverage expansion (a.k.a. “the Medicaid expansion”) was originally mandatory for all states, but later became optional following the Supreme Court ruling in June 2012.

The cost of coverage expansion would be partially financed with savings generated from cost containment measures. Financing sources also involve an excise tax on high-premium health insurance plans and an increase in the Medicare Part A tax rate for those with high incomes. The cost-saving measures include:

  • Restructuring of payments to Medicare Advantage plans to bring them more in line with those under traditional Medicare,

  • Reduction of payments for hospital-acquired preventable conditions and Disproportionate Share Hospital payments to hospitals that serve a significantly disproportionate number of low-income patients,

  • Implementation of measures advocated by an Independent Payment Advisory Board (IPAB),

  • Increase in the Medicaid rebate percentage for brand name drugs,

  • Reduction of waste, fraud, and abuse in Medicare, Medicaid, and all other public programs.

ACA plans to improve the health care delivery system via a range of measures including:

  • Reductions in preventable inpatient hospitalizations among residents of nursing facilities,

  • A new payment system where hospitals are reimbursed based on performance and quality,

  • A new bundled payment system under Medicaid for episodes of care,

  • Increased Medicaid payments to primary care physicians to improve access to care,

  • Increased funding for community health centers as part of prevention programs.

Whether the ACA will be able to improve the fiscal outlook is uncertain. Benefits from expanded coverage (such as prevention of catastrophic medical expenses and gains from improved health status) are hard to quantify and predict. How ECG will evolve under the new measures is difficult to tell while Medicaid projections carry additional uncertainty because of the provisions governing: (i) the size of eligible population and the take-up decisions, (ii) access to and utilization of primary care, and (iii) reimbursements to health care providers.

It remains to be seen which states will expand Medicaid, with implications for the size of eligible population and, hence, the fiscal burden. Currently, 26 states and the District of Columbia have “opted in” to expand while 13 states are “opting out”, although these decisions are not necessarily binding. The number of total new enrollments depends on individual take-up decisions because of the considerable variation across states in terms of income level and distribution. As a result, the number of potential new enrollments ranges from 2 percent of the state population (Vermont) to 12 percent (New Mexico). CBO makes several assumptions in its projections to capture “the middle of a range of possible outcomes” (CBO, 2012), but there is no guarantee that the estimates will not miss the mark with a high margin.

Another source of uncertainty is related to the payments to primary care physicians in the effort to enhance access to these services. To boost physician participation in Medicaid, ACA raises Medicaid reimbursement rates for primary care to at least 100 percent of Medicare rates. The federal government will fully fund the increase in 2013–14. But, there is ambiguity as to how the increased rates will be implemented and the complexities arising from differences in state policies, claims systems, and provider databases have already led to delays. It is also unclear what will happen beyond 2014. The increase is intended to be temporary but there will be tremendous political pressure to maintain the higher rates with the burden resting on both the federal government and the state government finances.

Last but not least, burden sharing arrangements between the federal government and states for reimbursement of health care providers may prove unsustainable. The cost of coverage for the newly eligible will be entirely covered by the federal government through 2016. Federal funding will be reduced gradually and reach 90 percent in 2020 and thereafter. This is still substantially higher than the Federal Medical Assistance Percentages (FMAP)—the matching rate for the currently eligible beneficiaries—which averages 59 percent. Hence, keeping the matching rate for newly eligible beneficiaries at the promised level may turn out to be more difficult than predicted. Given the states’ own fiscal woes, cutting back of the federal funds on Medicaid would have significant ramifications.

Appendix I. Health Spending Growth and Economic Conditions: A Cross-Country Analysis

This appendix presents the trends in the growth of health care spending among OECD countries and estimates the relationship between health care spending growth and macroeconomic conditions. In particular, it analyzes how much of the recent slowdown in health care spending in the United States could be explained in a cross-country model of macroeconomic factors.

Data sources

Health care spending data are drawn from OECD health database. The database provides comparable data for various types of health care spending for OECD countries between 1980 and 2011, including total health care spending as a share of GDP and public health care spending as a share of total health care spending. Total health care spending as a share of GDP is only available for seven countries in the OECD health database. For the United States, total health care spending as a share of GDP in 2011 is imputed based on National Health Expenditure Accounts data from the Centers for Medicare and Medicaid Services. The annual growth rate of per capita health care spending is constructed, by combining with data on GDP in constant prices and the total population estimates as described below. Macroeconomic indicators, including GDP growth, gross debt as a share of GDP, output gap, and unemployment rate, are derived from the World Economic Outlook (WEO) database. We construct total population estimates and share of population aged above 65 based on the World Population Prospects, the 2010 Revision, from the United Nations.

Econometric model

Rising income contributes to health care spending growth. As a large share of health care spending is funded by public sources, fiscal conditions would also matter in determining heath care spending growth. Here we use a fixed effects model, in the following form, to assess the relationship between health care spending growth and macroeconomic conditions:

hi,t = β0 + β1 *gi,t + β2 *xi,t + β3 *t + β4,i *μi + β5,i *μi *t +εi,t

where hi,t, denotes real per capita health spending growth; gi,t, denotes macroeconomic indicators and their lags, including GDP growth, unemployment rate and gross public debt; xi,t, denotes the share of the population aged 65 or above; t denotes a time trend; and μi denotes country fixed effects.

Results

As expected, the estimates indicate that GDP growth is positively associated with health care spending growth while unemployment rate and gross public debt are negatively associated with health care spending growth (Appendix Table 1).

Appendix Table 1.

Cross-Country Regression Estimates

article image
Sources: IMF staff estimates.

The model predicts lower growth rate than actual for 2009 while the predicted growth rates in 2010 and 2011 are more in line with the actual rates (Appendix Chart 1). The simulation exercise assumes that the average GDP growth rates, unemployment rates, and general government gross debt between 2003 and 2011 are the same as the average between 1995 and 2000. The simulated rates are well above the actual growth rates, indicating the slowdown in health care spending growth can in part be explained by the macroeconomic developments. The “simulated without debt” scenario assumes the average GDP growth rates and unemployment rates, but keeps the general government debt at its actual level (note that one might actually argue that public debt is structural rather than cyclical). These exercises indicate that slower GDP growth, high unemployment rates, and high general government debt have all contributed to the observed slowdown. Yet, the predicted growth rates are slightly higher than the actual rate prior to the recession, suggesting that there is an unexplained portion of the slowdown that is perhaps attributable to structural changes in the health care system.

Appendix Figure 1.
Appendix Figure 1.

Actual, Predicted, and Simulated Total and Public Spending Growth

Citation: IMF Staff Country Reports 2013, 237; 10.5089/9781484376553.002.A003

Sources: IMF staff estimates.

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1

Prepared by Deniz Igan, Kenichiro Kashiwase, and Baoping Shang.

2

In the 1990s, national health spending grew largely in line with GDP thanks to the growing dominance of managed care plans (Cutler and Sheiner, 1998). This trend, however, did not last as the social and legal backlash against the cost-containment practices of managed care organizations (particularly, Health Maintenance Organizations—HMOs) led to restrictions on such practices (Pinkovskiy, 2013).

3

The increase in public health care spending growth in 2006 reflects the introduction of Medicare Part D under the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (MMA).

4

Estimates for income elasticity of demand vary considerably with studies using data at the individual level delivering much lower estimates compared to studies at the aggregate level (Getzen, 2000; Feldstein, 2011). Earlier studies have even found elasticity coefficients exceeding one while more recent studies report coefficients less than unity (Farag et al., 2012). One explanation for the estimated elasticity to be above unity is that spending on health to extend life allows individuals to escape diminishing marginal utility of consumption within a period by purchasing additional periods of utility (Hall and Jones, 2007). It is unlikely that income growth alone can explain the health care spending growing as a share of GDP but, in general equilibrium, health care spending growth may outpace economic growth through the effect economic growth has on technological change and institutional features such as insurance coverage (Smith, Newhouse, and Freeland, 2009).

5

Experts believe that technological change is the most important driver of health care spending over time (see CBO, 2008, and references therein). Of course medical innovations could actually reduce spending (e.g., vaccines) but most technological advances to date have increased health care spending because they create new therapies that make it possible to treat previously-untreatable conditions (e.g., renal replacement therapy for kidney failure) and improve capabilities to make treatments available to a wider population (e.g., joint replacements).

6

Of course this is not an orthogonal decomposition. It may well be the case that the relative price of health care has increased and, hence, there is less demand for it.

7

The medical care CPI may be a poor proxy for the price paid for health care, especially under public programs because both Medicaid and Medicare have controls on how much reimbursement rates increase. Note that the temporary spike in 2009 reflects the drop in energy prices.

8

One could further break down the volume component into the number of people receiving health care (extensive margin) and the intensity of care received (intensive margin). Unfortunately, the data to compute these subcomponents are not available. One option is to use population growth as a proxy for the extensive margin, which suggests a big drop on the intensive margin given the persistence in population growth rate (Martin et al., 2012).

9

Also, they may be able to maintain coverage after losing a job by means of a spouse’s policy or under the Consolidated Omnibus Budget Reconciliation Act of 1985 (COBRA).

10

Similar adjustments were made by the Centers for Medicare and Medicaid Services (CMS). CMS attributes the downward revisions to lower-than-expected expenditure growth in recent years, changes in the macroeconomic projections (including state budget pressures), legislative and regulatory changes that occurred since their previous projection in April 2010, and structural changes (such as health insurance plan offerings and health care delivery process improvement initiatives on the part of health care providers, including the associated behavioral changes on the consumers’ part) (CMS, 2012).

11

Projections over the next 10 years are based on a bottom-up program-based approach that includes forecasts of spending per beneficiary reflecting recent trends. In its longer-term projections, CBO assumes that health care spending will evolve so that the underlying ECG will decline to zero for Medicaid and to 1 percent for Medicare over the next 75 years. ECG at the start of the projection period is calculated as a weighted average of historical ECG rates over a 25-year window, placing twice as much weight on the latest years compared to the earliest years.

12

The “Cadillac” plans are those that, in 2018, will charge more than $27,500 for families and $10,200 for individuals, excluding vision and dental benefits. Beginning in 2018, a 40-percent tax will be imposed on the portion of health insurance that is over these thresholds. After 2020, the premium threshold will increase at the rate of overall inflation in the economy. This excise tax is expected to lower premiums and help bend the cost curve, as the premium threshold increases with overall inflation rather than with the growth of health care costs.

13

For instance, the redesign of primary care delivery may be necessary (Schoen et al., 2011). In Germany, some savings and improvement in the quality of care provided to people with diabetes were reached through the Disease Management Programs, implemented in 2002. These programs emphasized primary care as a vehicle to promote adherence to treatment goals and self-management of the patients’ conditions, through coordinated care tailored to patients’ specific conditions (Stock et al., 2010). In the United Kingdom, the government implemented a flagship Expert Patient Program which emphasizes self-management of chronic illnesses, as well as a new pay-for-performance contract with primary care physicians (Ham, 2009; Schoen et al., 2009). Current measures under the ACA provide some incentives (through state grants) to evidence-based programs encouraging healthy behavior (e.g., tobacco cessation, weight control) among Medicaid beneficiaries, but these measures do not directly involve primary care delivery.

14

The Patient-Centered Outcomes Research Institute (PCORI) that was created by the ACA is a step in this direction. PCORI aims to provide physicians and patients with new information on the effectiveness of various medical technologies and interventions and, hence, improve decisions on diagnostic tests and treatment methods.

15

In addition to the PCORI, another initiative to ensure continuity of savings is the establishment of the Independent Payment Advisory Board (IPAB), charged with the mandate under the ACA to develop a proposal to reduce Medicare spending if the projected per capita growth rate exceeds the target growth rate. In addition, the CMS Innovation Center will be developing and evaluating pilot programs to enhance the quality of care for Medicare beneficiaries and reduce the cost of their care (the Secretary of the Department of Health and Human Services is authorized to expand successful pilot programs without the need for additional legislation).

United States: Selected Issues
Author: International Monetary Fund. Western Hemisphere Dept.
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    United States: Evolution of Health Care Spending

    (percent of GDP)

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    Health Care Spending and GDP Growth

    (real, percent)

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    Decomposing Health Care Spending Growth

    (percent)

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    Federal Debt under Different Health Care Scenarios

    (debt held by public, fiscal year basis, percent of GDP)

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    Actual, Predicted, and Simulated Total and Public Spending Growth