Abstract
After a brief reprieve, healthcare spending in the United States is expected to once again rise rapidly, continuing the trend of the past half-century. To inform the debate about whether policymakers should take action to contain high and rising medical care costs, we use panel data on all 50 states for the period 1993 to 2009 to estimate a healthcare spending model. Our framework, which includes a structural spending equation and a health production function, identifies the pathways through which medical technology and income affect healthcare costs and the potential health benefits they produce. We find evidence that medical technology and income are important factors fueling rising healthcare costs in the United States. However, our results also indicate they generate large health benefits in the form of lower mortality that may outweigh the costs and increase social economic welfare.
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Notes
For a detailed description of the theoretical framework, see Thornton and Rice (2008), Appendix.
Population health comprises both duration and quality of life. Like prior aggregate health production function studies, we adopt a length-of-life measure.
Past studies estimate the parameters of a reduced-form aggregate healthcare spending equation obtained by substituting the health production function (2) into the structural spending equation (1), and therefore cannot identify the pathways through which variables affect spending.
Baltagi and Griffin (1988) discuss in detail the history of using time trends and time dummy variables to describe technical change in econometric literature.
The direction of the effect will largely depend on the impact of more or fewer providers on supply conditions in the market for medical care and their willingness and ability to influence consumer demand for medical services.
BMI is defined as weight in kilograms divided by height in meters squared. BMI ≥ 30.0 indicates obesity.
The Hansen J statistics of 5.00 (p-value =0.17) and 4.25 (p-value =0.51) for the spending and health equations respectively provide evidence that the instruments used to identify both equations are exogenous. Additionally, the F-statistic of 39.41 (p-value <0.001) of the joint effect of identifying variables in the first-stage regression for the spending equation indicates that the instruments are strong. Similarly, the instruments used to identify the health production function are also jointly significant, with an F-statistic of 9.56 (p-value <0.001).
The objective of Freeman (2012) is to obtain an estimate of the income elasticity of healthcare spending, and therefore he includes few non-income factors.
Because the measure of technology provides an upper bound, the calculated monetary benefit of technological advancement may be too high, while the monetary cost too low.
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We are grateful to James W. Saunoris for helpful comments and suggestions.
APPENDIX
APPENDIX
Variable Definitions and Data Sources [Mean, Standard Deviation]
Healthcare spending - real personal healthcare spending per capita, constant 2009 dollars. The data on nominal personal health care spending per capita by state of recipient are obtained from the Centers for Medicare and Medicaid Services (CMS) web-site http://cms.hhs.gov, and are estimates produced by the Office of the Actuary. National Consumer Price Index is obtained from the Bureau of Labor Statistics, Economic Report of the President 2013 [5525.11, 1123.47].
Health/Mortality - crude death rate measured by number of deaths per 100,000 population. The data are taken from Centers for Disease Control website, http://wonder.cdc.gov [852.60, 128.05].
Income - real personal income per capita, constant 2009 dollars. Data on nominal personal income per capita are obtained from the Bureau of Economic Analysis, U.S. Department of Commerce website, http://www.bea.gov. National Consumer Price Index is obtained from the Bureau of Labor Statistics, Economic Report of the President 2013 [35,398.78, 5763.43].
Education - percent of the state population 25 years of age or older with a high school degree or more. Data are taken from U.S. Census website, http://www.census.gov, annual March Current Population Report and American Community Survey [84.86, 4.49].
Unemployment - percent of the labor force unemployed. Bureau of Labor Statistics website, www.bls.gov [5.10, 1.54].
Insurance coverage - percent of the population with private or public health insurance. U.S. Census Bureau website, http://www.census.gov/hhes/www/hlthins [86.39, 3.98].
Medicare coverage - percent of the population with Medicare insurance. U.S. Census Bureau website,
http://www.census.gov/hhes/www/hlthins [13.78, 2.36].
Medicaid coverage - percent of the population with Medicaid insurance. U.S. Census Bureau website,
http://www.census.gov/hhes/www/hlthins [11.54, 3.52].
Non-HMO coverage - percent of the population not covered by an HMO health plan. It is measured as 100 minus the percent of the population covered by an HMO health plan. HMO data for years 1993–2005 are taken from various issues of Health United States; 2006–2008 are taken from Statistical Abstract of the United States, 2012; 2009 are taken from the Kaiser Family Foundation website, http://kff.org. The original source of all data is Interstudy Publications, Competitive Edge reports [81.25, 12.31].
Physicians - number of physicians per 100,000 population. Excludes federal physicians and doctors of osteopathy (DOs). The data are taken from various issues of the Statistical Abstract of the United States. The original data source is the American Medical Association, Physician Characteristics and Distribution in the U.S. It reports non-federal physicians for years 1993–2002. Beginning in year 2003, it includes federal physicians. We adjust the data for 2003–2009 by an estimate of the number of federal physicians by state [236.47, 59.99].
Hospitals - number of beds in community hospitals per 1000 population. Data for years 1993 to 2000 are taken from various issues of the Statistical Abstract of the United States. Data for years 2001 to 2009 are taken from Kaiser Family Foundation website, http://kff.org. The original data source is the American Hospital Association Annual Survey [3.14, 0.99].
Alcohol consumption - alcohol consumption per capita age 16 years and older, gallons. National Institute on Alcohol Abuse and Alcoholism (NIAAA) website, http://www.niaaa.nih.gov, Surveillance Report #95 [2.29, 0.47].
Cigarette consumption - cigarette consumption per capita, packs. Data are taken from the Centers for Disease Control website, http://cdc.gov, State Tobacco Activities Tracking and Evaluation System. The original data source is the consulting firm Orzechowski and Walker [82.07, 29.34].
Obesity - percent of the population 18 years of age and older with a body mass index (BMI) of 30 or greater. Data for 1992–1994 are taken from the American Cancer Society website, www.cancer.org; 1995–2009 are taken from the Centers for Disease Control website, http://wonder.cdc.gov, Behavioral Risk Factor Surveillance System [20.75, 5.08].
Population density - population per square mile of land area. Data on land area are taken from U.S. Census Bureau, MAF/TIGER database. Population data are taken from Centers for Disease Control web-site, http://wonder.cdc.gov, and are U.S. Census Bureau and National Center for Health Statistics estimates of state populations [183.84, 250.17].
Elderly, Black, Hispanic, Female - percent of the population 65 years of age and older [12.66, 1.86], African-American [10.53, 9.54], Hispanic [8.10, 9.04], and Female [50.81, 0.78]. The data are taken from Centers for Disease Control web-site, http://wonder.cdc.gov, and are U.S. Census Bureau and National Center for Health Statistics estimates of state populations.
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Beilfuss, S.N., Thornton, J.A. Pathways and Hidden Benefits of Healthcare Spending Growth in the U.S.. Atl Econ J 44, 363–375 (2016). https://doi.org/10.1007/s11293-016-9506-6
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DOI: https://doi.org/10.1007/s11293-016-9506-6