Comparing the Income Elasticity of Health Spending in Middle-Income and High-Income Countries: The Role of Financial Protection

Document Type : Original Article

Authors

1 Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, CA, USA

2 Department of Health Care Administration, California State University, Long Beach, CA, USA

Abstract

Background
As middle-income countries become more affluent, economically sophisticated and productive, health expenditure patterns are likely to change. Other socio-demographic and political changes that accompany rapid economic growth are also likely to influence health spending and financial protection.
 
Methods
This study investigates the relationship between growth on per-capita healthcare expenditure and gross domestic product (GDP) in a group of 27 large middle-income economies and compares findings with those of 24 high-income economies from the Organization for Economic Cooperation and Development (OECD) group. This comparison uses national accounts data from 1995-2014. We hypothesize that the aggregated income elasticity of health expenditure in middle-income countries would be less than one (meaning healthcare is a normal good). An initial exploratory analysis tests between fixed-effects and random-effects model specifications. A fixed-effects model with time-fixed effects is implemented to assess the relationship between the two measures. Unit root, Hausman and serial correlation tests are conducted to determine model fit. Additional explanatory variables are introduced in different model specifications to test the robustness of our regression results. We include the out-of-pocket (OOP) share of health spending in each model to study the potential role of financial protection in our sample of high- and middle-income countries. The first-difference of study variables is implemented to address non-stationarity and cointegration properties.
 
Results
The elasticity of per-capita health expenditure and GDP growth is positive and statistically significant among sampled middle-income countries (51 per unit-growth in GDP) and high-income countries (50 per unit-growth in GDP). In contrast with previous research that has found that income elasticity of health spending in middle-income countries is larger than in high-income countries, our findings show that elasticity estimates can change if different criteria are used to assemble a more homogenous group of middle-income countries. Financial protection differences between middle- and high-income countries, however, are not associated with their respective income elasticity of health spending. `
 
Conclusion
The study findings show that in spite of the rapid economic growth experienced by the sampled middleincome countries, the aggregated income elasticity of health expenditure in them is less than one, and equals that of high-income countries.

Keywords

Main Subjects

References

  1. Cook BL, Manning WG. Measuring racial/ethnic disparities across the distribution of health care expenditures. Health Serv Res. 2009;44(5 Pt 1):1603-1621. doi:10.1111/j.1475-6773.2009.01004.x
  2. World Health Organization (WHO). The World Health Report 2000: Health Systems - Improving Performance. Geneva: WHO; 2001.
  3. Vazquez ST, Sumner A. Revisiting the Meaning of Development: A Multidimensional Taxonomy of Developing Countries. J Devt Stud. 2013;49(12):1728-1745. doi:10.1080/00220388.2013.822071
  4. Alonso J, Luiza Cortez A, Klasen S. LDC and other country groupings: how useful are current approaches to classify countries in a more heterogeneous developing world? New York: CDP Background Paper No. 21; 2014.
  5. World Bank. The Day After Tomorrow: A Handbook on the Future of Economic Policy in the Developing World. Washington DC: The World Bank Group; 2010. 
  6. Farag M, NandaKumar AK, Wallack S, Hodgkin D, Gaumer G, Erbil C. The income elasticity of health care spending in developing and developed countries. Int J Health Care Finance Econ. 2012;12(2):145-162. doi:10.1007/s10754-012-9108-z
  7. Alfonso YN, Ding G, Bishai D. Income Elasticity of Vaccines Spending versus General Healthcare Spending. Health Econ. 2016;25(7):860-872. doi:10.1002/hec.3190
  8. Lutz W, Sanderson WC, Scherbov S, eds. The End of World Population Growth in the 21st Century: New Challenges for Human Capital Formation & Sustainable Development. New York: Earthscan; 2004. 
  9. Frenk J. Bridging the divide: global lessons from evidence-based health policy in Mexico. Lancet. 2006;368(9539):954-961. doi:10.1016/S0140-6736(06)69376-8
  10. Rawlings LB, Rubio GM. Evaluating the impact of conditional cash transfer programs. World Bank Research Observer. 2005;20(1):29-55. doi:10.1093/Wbro/Lki001
  11. Lago-Peñas S, Cantarero-Prieto D, Blázquez-Fernández C. On the relationship between GDP and health care expenditure: a new look. Econ Model. 2013;32:124-129. 
  12. Gerdtham U, B Jonsson. International Comparisons of Health Expenditure: Theory, Data and Econometric Analysis. In: Culyer A, Newhouse J, eds. Handbook of Health Economics. Netherlands: Eisevier; 2000.
  13. Newhouse JP. Medical-care expenditure: a cross-national survey. J Hum Resour. 1977;12(1):115-125. 
  14. Roberts J. Spurious regression problems in the determinants of health care expenditure: a comment on Hitiris (1997). Appl Econ Lett. 2000;7(5):279-283. 
  15. Baltagi BH, Moscone F. Health care expenditure and income in the OECD reconsidered: Evidence from panel data. Econ Model. 2010;27(4):804-811. doi: 10.1016/J.Econmod.2009.12.001
  16. Barros PP. The black box of health care expenditure growth determinants. Health Econ. 1998;7(6):533-544. doi:10.1002/(SICI)1099-1050(199809)7:63.0.CO;2-B 
  17. Wagstaff A. Measuring Financial Protecton in Health. Washington DC: The World Bank; 2008.
  18. Chakroun M. Health care expenditure and GDP: an international panel smooth transition approach. Int J Econ. 2010;4:189-200. 
  19. Liu DD, Li R, Wang ZJ. Testing for structural breaks in panel varying coefficient models: with an application to OECD health expenditure. Empir Econ. 2011;40(1):95-118. doi:10.1007/s00181-010-0375-6
  20. Okunade AA, Murthy VNR. Technology as a 'major driver' of health care costs: a cointegration analysis of the Newhouse conjecture. J Health Econ. 2002;21(1):147-159. doi:10.1016/S0167-6296(01)00122-9
  21. Xu K, Evans DB, Kawabata K, Zeramdini R, Klavus J, Murray CJ. Household catastrophic health expenditure: a multicountry analysis. Lancet. 2003;362(9378):111-117. doi:10.1016/S0140-6736(03)13861-5
  22. Musgrove P, Zeramdini R, Carrin G. Basic patterns in national health expenditure. Bull World Health Organ. 2002;80(2):134-142. 
  23. Xu K, Evans DB, Carrin G, Aguilar-Rivera AM, Musgrove P, Evans T. Protecting households from catastrophic health spending. Health Aff (Millwood). 2007;26(4):972-983. doi:10.1377/hlthaff.26.4.972
  24. O'Neill JAS. The Long-Term Outlook for the BRICs and N-11 Post Crisis. New York, NY: Goldman Sachs; 2009.
  25. DowJonesIndexes. Dow Jones Total Stock Market Indexes. New York: FTSE International Limited and Dow Jones Indexex; 2010.
  26. World Economic Outlook. http://www.imf.org/external/pubs/ft/weo/2008/02/weodata/groups.htm. Accessed October 1, 2010. Published 2008.
  27. Data and Statistics. International Monetary Fund website. http://www.imf.org/external/data.htm. Accessed October 1, 2010. Published 2010.
  28. World Health Organization. WHO Statistical Information System. http://apps.who.int/whosis/data/Search.jsp. Accessed October 7, 2010. Published 2010.
  29. U.S. Census Bureau. An Aging World: 2015, International Populations Reports. https://census.gov/content/dam/Census/library/publications/2016/demo/p95-16-1.pdf.
  30. Wooldridge J. Econometric Analysis of Cross-Section and Panel Data. Cambridge: Massachusetts Institute of Technology; 2002. 
  31. Health Data 2010. Organization for Economic Cooperation and Development (OECD) website. http://stats.oecd.org/index.aspx?r=276373. Accessed October 1, 2010. Published 2010
  32. Baicker K, Skinner J. Health care spending growth and the future of U.S. Tax Rates. NBER Working Paper No. 16772. Published February 2011.
International Journal of Health Policy and Management
Volume 7, Issue 3
March 2018
Pages 255-263

Files

History

  • Receive Date: 31 August 2016
  • Revise Date: 09 July 2017
  • Accept Date: 09 July 2017

Share

How to cite

Statistics