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Atlantic Economic Journal

, Volume 46, Issue 4, pp 389–403 | Cite as

Income Elasticity Decomposition Models and Determinants of U.S. Pharmaceutical Expenditures

  • Gregory G. LubianiEmail author
  • Albert A. Okunade
  • Weiwei Chen
Article
  • 26 Downloads

Abstract

Prescription drugs are the third largest component of U.S. healthcare spending, and quickly growing. This novel study provides greater information on consumer behavior in the market for prescription drugs, and how that behavior may vary due to fluctuating economic conditions, using an annual panel dataset. Specifically, the research presented applied the income elasticity decomposition methodology to prescription drug expenditures, deriving both its quality and quantity components. Per capita gross domestic product and median home values were used interchangeably to test whether alternative income concepts affect income elasticity estimates. The system generalized method of moments three-stage least squares estimation results revealed that the: (a) 0.647 short-run income elasticity comprises 0.453 and 0.194 in quantity and quality components; (b) long-run income elasticity estimate of 0.167 has 0.027 and 0.140 quantity and quality components. Pharmaceuticals were found to behave as a necessity and normal good with significant tendencies for long-run consumption shifts towards quality. Further illustrated are supply and demand-side impacts, with policy implications for Medicare and Medicaid programs, among others.

Keywords

Prescription drugs Income elasticity Quantity-quality decomposition Medicare Part D 

JEL

I00 

Notes

References

  1. Acemoglu, D., Finkelstein, A., & Notowidigdo, M. J. (2013). Income and health spending: Evidence from oil price shocks. Review of Economics and Statistics, 95(4), 1079–1095.CrossRefGoogle Scholar
  2. Aitken, M., Berndt, E., & Cutler, D. (2009). Prescription drug spending trends in the United States: Looking beyond the turning point. Health Affairs, 28(1), 151–160.CrossRefGoogle Scholar
  3. Alfonso, Y. N., Ding, G., & Bishai, D. (2015). Income elasticity of vaccines spending versus general healthcare spending. Health Economics. Google Scholar
  4. Baltagi, B., & Moscone, F. (2010). Health care expenditure and income in the OECD reconsidered: Evidence from panel data. Economic Modelling, 27, 804–811.CrossRefGoogle Scholar
  5. Blewett, L. A., & Hempstead, K. (2014). The need for state health services and policy research. Health Services Research, 49(S2), 2035–2040.CrossRefGoogle Scholar
  6. Centers for Disease Control and Prevention (2015). Behavioral Risk Factors Data Portal. Retreived from https://chronicdata.cdc.gov/browse?category=Behavioral+Risk+Factors. Last accessed August, 2015.
  7. Chen, W., Okunade, A., & Lubiani, G. G. (2014). Quality-quantity decomposition of income elasticity of U.S. hospital care expenditure using state-level panel data. Health Economics, 23, 1340–1352.CrossRefGoogle Scholar
  8. Clemente, J., Marcuello, C., & Montanes, A. (2008). Pharmaceutical expenditure, Total health-care expenditure and GDP. Health Economics, 17, 1187–1206.CrossRefGoogle Scholar
  9. Conroy, S., Alsenani, A., & Sammons, H. (2015). The role of the PAEDIATRIC clinical pharmacist in reducing medication errors: A systematic literature review. Archives of Disease in Childhood, 100(6), e1–e1.Google Scholar
  10. Dave, D., & Saffer, H. (2012). Impact of direct-to-consumer advertising on pharmaceutical prices and demand. Southern Economic Journal, 79(1), 97–126.CrossRefGoogle Scholar
  11. Davit, B. M., Nwakama, P. E., Buehler, G. J., Conner, D. P., Haidar, S. H., Patel, D. T., Yang, Y., Yu, L. X., & Woodcock, J. (2009). Comparing generic and innovator drugs: A review of 12 years of bioequivalence data from the United States Food and Drug Administration. Annals of Pharmacotherapy, 43(10), 1583–1597.CrossRefGoogle Scholar
  12. Goldsmith, J., Aikin, K. J., Encinosa, W. E., & Nardinelli, C. (2012). Despite 2007 law requiring FDA hotline to be included in print drug ads, reporting of adverse events by consumers still low. Health Affairs, 31(5), 1022–1029.CrossRefGoogle Scholar
  13. Guignard, B., Bonnabry, P., Perrier, A., Dayer, P., Desmeules, J., & Samer, C. F. (2015). Drug-related problems identification in general internal medicine: The impact and role of the clinical pharmacist and pharmacologist. European Journal of Internal Medicine, 26(6), 399–406.CrossRefGoogle Scholar
  14. Huttin, C. (2000). A cluster analysis on income elasticity variations and US pharmaceutical expenditures. Applied Economics, 32, 1241–1247.CrossRefGoogle Scholar
  15. Kaiser Family Foundation. (2015a) Retail Sales for Prescription Drugs Filled at Pharmacies. Retreived from https://www.kff.org/health-costs/state-indicator/total-sales-for-retail-rx-drugs/. Last Accessed August, 2015.
  16. Kaiser Family Foundation. (2015b) Retail Prescription Drugs Filled at Pharmacies. Retreived from https://www.kff.org/health-costs/state-indicator/retail-rx-drugs-per-capita/. Last Accessed August, 2015.
  17. Kaiser Family Foundation. (2015c) State HMO Penetration Rate. Retreived from https://www.kff.org/other/state-indicator/hmo-penetration-rate/. Last accessed August, 2015.
  18. LaGanga, L. R., & Lawrence, S. R. (2012). Appointment overbooking in health care clinics to improve patient service and clinic performance. Production and Operations Management, 21(5), 874–888.CrossRefGoogle Scholar
  19. Manz, C., Ross, J. S., & Grande, D. (2014). Marketing to physicians in a digital world. New England Journal of Medicine, 371(20), 1857–1859.CrossRefGoogle Scholar
  20. Medicare Prescription Drug, Improvement and Modernization (2003) Act of 2003, Pub. L. No. 108–173, § 1101, 117 Stat 2069, 2448–54. Available at: https://www.congress.gov/108/plaws/publ173/PLAW-108publ173.pdf.
  21. Mestre-Ferrandiz, J., Sussex, J., & Towse, A. (2012). The R&D cost of a new medicine. Office of Health Economics Monograph. Available at: https://www.ohe.org/publications/rd-cost-new-medicine.
  22. National Conference of State Legislatures. (2017). Statewide Prescription Drug Database. Retreived from http://www.ncsl.org/research/health/prescription-drug-statenet-database.aspx. Last Accessed May, 2017.
  23. Nakayama, C., Kimata, S., Oshima, T., Kato, A., & Nitta, A. (2016). Analysis of pharmacist–patient communication using the roter method of interaction process analysis system. Research in Social and Administrative Pharmacy, 12(2), 319–326.CrossRefGoogle Scholar
  24. Okunade, A., Suraratdecha, C., & Benson, D. (2010). Determinants of Thailand household healthcare expenditure: The relevance of permanent resources and other correlates. Health Economics, 19, 365–376.CrossRefGoogle Scholar
  25. Patient Protection and Affordable Care Act (2010) 42 U.S.C. § 18001. 18001. Available at: https://www.govinfo.gov/app/details/USCODE-2010-title42/USCODE-2010-title42-chap157-subchapI-sec18001.
  26. Ray, W. A., & Stein, C. M. (2006). Reform of drug regulation-beyond an independent drug-safety board. New England Journal of Medicine, 354(2), 194–201.CrossRefGoogle Scholar
  27. U.S. Bureau of Economic Analysis. (2015). GDP by State. Retreived from https://www.bea.gov/data/gdp/gdp-state. Last Accessed August, 2015.
  28. U.S. Bureau of Labor Statistics (2015a). Consumer Price Index. Retreived from https://www.bls.gov/cpi/. Last Accessed August, 2015.
  29. U.S. Bureau of Labor Statistics. (2015b). State and Metro Area Employment, Hours, & Earnings. Retreived from https://www.bls.gov/sae/. Last Accessed August, 2015.
  30. U.S. Census Bureau. (2015). American Community Survey. Retreived from https://www.census.gov/programs-surveys/acs/. Last Accessed August, 2015.
  31. Windmeijer, F., Laat, E., Douven, R., & Mot, E. (2006). Pharmaceutical promotion and GP prescription behaviour. Health Economics, 15, 5–18.CrossRefGoogle Scholar
  32. Wolff, E. N. (2014). Household wealth trends in the United States, 1983–2010. Oxford Review of Economic Policy, 30(1), 21–43.CrossRefGoogle Scholar

Copyright information

© International Atlantic Economic Society 2019

Authors and Affiliations

  1. 1.Department of Economics & Finance, Office 102CTexas A&M University – CommerceCommerceUSA
  2. 2.Department of Economics, Office 450BB (The FCBE)University of MemphisMemphisUSA
  3. 3.School of Public Health, Office AHC5 448Florida International UniversityMiamiUSA

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