Abstract
The priority aim of this study is to investigate the effect of carbon footprint, which is an indicator of environmental degradation, on health expenditures for the USA. In the study, cointegration analysis was performed for the period 1970–2016 by using health expenditures, carbon footprint, gross domestic product per capita and life expectancy at birth variables. According to the results of standard cointegration analysis, only cointegration relationship between health expenditures and income was found. In the models with carbon footprint, no cointegration relationship was discovered between the original values of the variables. This result was approached with suspicion, and it was thought that there might be a hidden cointegration between healthcare expenditures and carbon footprint. For this purpose, the hidden cointegration analysis and crouching error correction model proposed by Granger and Yoon [18] were employed among the positive and negative components of the variables of healthcare expenditures and carbon footprint. The results of the hidden cointegration analysis revealed that there was a hidden cointegration relationship between the positive components of healthcare expenditures and the positive components of carbon footprint. Analysis results show that a 1% increase in carbon footprint will cause a 2.04% increase in healthcare expenditures in the long term in the USA. When the positive components of the variables were considered, it was concluded that there was a one-way long-term asymmetric causality relationship between carbon footprint and healthcare expenditures. As a result of the study, it was proposed that the carbon footprint should be diminished to prevent the increasing burden of the healthcare expenditures on the budget.
Similar content being viewed by others
Change history
21 October 2020
The author would like to correct the errors in the publication of the original article.
References
Ahmad, M., Ur Rahman, Z., Hong, L., Khan, S., Khan, Z., Naeem Khan, M.: Impact of environmental quality variables and socio-economic factors on human health: empirical evidence from China. Pollution 4(4), 571–579 (2018)
Apergis, N., Gupta, R., Lau, C.K.M., Mukherjee, Z.: US state-level carbon dioxide emissions: Does it affect health care expenditure? Renew. Sustain. Energy Rev. 91, 521–530 (2018)
Apergis, N., Bhattacharya, M., Hadhri, W.: Health care expenditure and environmental pollution: a cross-country comparison across different income groups. Environ. Sci. Pollut. Res. 27(12), 1–15 (2020)
Azad, A.K., Abdullah, S.M., Fariha, T.R.: Does carbon emission matter for health care expenditure? Evidence from SAARC region using panel cointegration. J. Polit. Econ. Polit. 34(1), 611–634 (2018)
Beveridge, S., Nelson, C.R.: A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the “business cycle”. J. Monet. Econ. 7, 151–174 (1981)
Blázquez-Fernández, C., Cantarero-Prieto, D., Pascual-Sáez, M.: On the nexus of air pollution and health expenditures: new empirical evidence. Gac. Sanit. 33, 389–394 (2019)
Chaabouni, S., Saidi, K.: The dynamic links between carbon dioxide (CO2) emissions, health spending and GDP growth: a case study for 51 countries. Environ. Res. 158, 137–144 (2017)
Chen, L., Zhuo, Y., Xu, Z., Xu, X., Gao, X.: Is carbon dioxide (CO2) emission an important factor affecting healthcare expenditure? Evidence from China, 2005–2016. Int. J. Environ. Res. Public Health 16(20), 3995 (2019)
Corvalán, C., Kjellström, T., Smith, K.: Health, environment and sustainable development: identifying links and indicators to promote action. Epidemiology 10(5), 656–660 (1999)
Crémieux, P.Y., Ouellette, P., Pilon, C.: Health care spending as determinants of health outcomes. Health Econ. 8(7), 627–639 (1999)
Di Matteo, L.: The determinants of the public–private mix in Canadian health care expenditures: 1975–1996. Health Policy 52(2), 87–112 (2000)
Di Matteo, L., Di Matteo, R.: Evidence on the determinants of Canadian provincial government health expenditures: 1965–1991. J. Health Econ. 17(2), 211–228 (1998)
Dickey, D.A., Fuller, W.A.: Distribution of the estimators for autoregressive time series with a unit root. J. Am. Stat. Assoc. 74(366a), 427–431 (1979)
Engle, R.F., Granger, C.W.J.: Cointegration and error correction: representation, estimation, and testing. Econometrica 55, 251–276 (1987)
Epstein, P.R., Mills, E.: Climate change futures: health, ecological and economic dimensions. The Center for Health and the Global Environment, Harvard Medical School (2005)
Gbesemete, K.P., Gerdtham, U.G.: Determinants of health care expenditure in Africa: a cross-sectional study. World Dev. 20(2), 303–308 (1992)
Global Footprint Network: Carbon footprint https://www.footprintnetwork.org/resources/glossary/, Accessed 12 November 2019 (2019)
Granger, C.W., Yoon, G.: Hidden cointegration. U of California, Economics Working Paper, (2002–02) (2002)
Hammond, G.: Time to give due weight to the “carbon footprint” issue. Nature 445(7125), 256 (2007)
Hatemi‐J, A.: Hidden panel cointegration. Munich Personal RePEc Archive Paper No. 31604 (2011)
Hatemi-J, A., Irandoust, M.: Asymmetric interaction between government spending and terms of trade volatility: New evidence from hidden cointegration technique. J. Econ. Stud. 39(3), 368–378 (2012)
Hazra, N.C., Rudisill, C., Gulliford, M.C.: Determinants of health care costs in the senior elderly: age, comorbidity, impairment, or proximity to death? Eur. J. Health Econ. 19(6), 831–842 (2018)
Hitiris, T., Posnett, J.: The determinants and effects of health expenditure in developed countries. J. Health Econ. 11(2), 173–181 (1992)
Hua, H., Pan, Y., Yang, X., Wang, S., Shi, Y.: Dynamic relations between Energy carbon footprint and economic growth in ethnic minority autonomous regions China. Energy Proc. 17, 273–278 (2012)
Huddart, K.E., Krahn, H., Krogman, N.T.: Are we counting what counts? A closer look at environmental concern, pro-environmental behaviour, and carbon footprint. Local Environ. 20(2), 220–236 (2015)
Jerrett, M., Eyles, J., Dufournaud, C., Birch, S.: Environmental influences on healthcare expenditures: an exploratory analysis from Ontario, Canada. J. Epidemiol. Commun. Health 57(5), 334–338 (2003)
Johansen, S., Nielsen, M.O.: Likelihood inference for a nonstationary fractional autoregressive model. J. Econ. 158, 51–66 (2010)
Johansen, S., Nielsen, M.O.: Likelihood inference for a fractionally cointegrated vector autoregressive model. Econometrica 80, 2667–2732 (2012)
Knowlton, K., Rotkin-Ellman, M., Geballe, L., Max, W., Solomon, G.M.: Six climate change–related events in the United States accounted for about $14 billion in lost lives and health costs. Health Aff. 30(11), 2167–2176 (2011)
Kumara, A.S., Samaratunge, R.: Patterns and determinants of out-of-pocket health care expenditure in Sri Lanka: evidence from household surveys. Health Policy Plann. 31(8), 970–983 (2016)
Laurent, A., Olsen, S.I., Hauschild, M.Z.: Carbon footprint as environmental performance indicator for the manufacturing industry. CIRP Ann. 59(1), 37–40 (2010)
Lee, K., Cheong, I.: Measuring a carbon footprint and environmental practice: the case of Hyundai Motors Co. (HMC). Ind. Manag. Data Syst. 111(6), 961–978 (2011)
Matthews, H.S., Hendrickson, C.T., Weber, C.L.: The importance of carbon footprint estimation boundaries. Environ Sci Technol. 42(16), 5839–5842 (2008)
Mehrara, M., Sharzei, G., Mohaghegh, M.: The relationship between health expenditure and environmental quality in developing countries. J. Health Admin. 14, 46 (2011)
Mert, M., Çağlar, A.E.: Eviews ve Gauss Uygulamalı Zaman Serileri Analizi [Eviews and Gauss Applied Time Series Analysis], Detay Yayıncılık, Ankara, ISBN: 978-605-254-126-5 (2019)
Murthy, V.N., Okunade, A.A.: Determinants of US health expenditure: evidence from autoregressive distributed lag (ARDL) approach to cointegration. Econ. Model. 59, 67–73 (2016)
Murthy, N.V., Ukpolo, V.: Aggregate health care expenditure in the United States: evidence from cointegration tests. Appl. Econ. 26(8), 797–802 (1994)
Narayan, P.K., Narayan, S.: Does environmental quality influence health expenditures? Empirical evidence from a panel of selected OECD countries. Ecol. Econ. 65(2), 367–374 (2008)
Newhouse, J.P.: Medical-care expenditure: a cross-national survey. J. Hum. Resour. 12(1), 115–125 (1977)
OECD: Health spending (indicator), OECD Health Statistics (database), https://doi.org/10.1787/8643de7e-en. Accessed 30 Nov 2019 (2019)
Phillips, P.C., Perron, P.: Testing for a unit root in time series regression. Biometrika 75(2), 335–346 (1988)
Remoundou, K., Koundouri, P.: Environmental effects on public health: An economic perspective. Int J Environ Res Public Health 6(8), 2160–2178 (2009)
Roberts, J.: Spurious regression problems in the determinants of health care expenditure: A comment on Hitiris (1997). Appl. Econ. Lett. 7(5), 279–283 (2000)
Ruth, M., Coelho, D., Karetnikov, D.: The US economic impacts of climate change and the costs of inaction: A review and assessment by the Center for Integrative Environmental Research (CIER) at the University of Maryland (2007).
Schorderet, Y.: A nonlinear generalization of cointegration: A note on hidden cointegration. Université de Genève/Faculté des sciences économiques et sociales, No 2002.03 (2002)
Shin, Y., Yu, B., Greenwood-Nimmo, M.: Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In: Sickles, R., Horrace, W. (eds.) Festschrift in Honor of Peter Schmidt. Springer, New York (2014)
Siti Khalijah, Z.: The impact of environmental quality on public health expenditure in Malaysia (Doctoral dissertation, Universiti Utara Malaysia) (2015)
Tsong, C.C., Lee, C.F., Tsai, L.J., Hu, T.C.: The fourier approximation and testing for the null of cointegration. Empiric. Econ. 51(3), 1085–1113 (2016)
Uddin, G.A., Salahuddin, M., Alam, K., Gow, J.: Ecological footprint and real income: panel data evidence from the 27 highest emitting countries. Ecol. Ind. 77, 166–175 (2017)
Wang, Z., Asghar, M.M., Zaidi, S.A.H., Wang, B.: Dynamic linkages among CO2 emissions, health expenditures, and economic growth: empirical evidence from Pakistan. Environ. Sci. Pollut. Res. 26(15), 15285–15299 (2019)
Wiedmann, T., Minx, J.: A definition of 'carbon footprint'. In: C. C. Pertsova, Ecological Economics Research Trends: Chapter 1, pp. 1–11, Nova Science Publishers, Hauppauge NY, USA. https://www.novapublishers.com/catalog/product_info.php?products_id=5999 (2008)
World Health Organization (WHO): Ten threats to global health in 2019, https://www.who.int/vietnam/news/feature-stories/detail/ten-threats-to-global-health-in-2019. Accessed 26 Nov 2019 (2019)
Yahaya, A., Nor, N.M., Habibullah, M.S., Ghani, J.A., Noor, Z.M.: How relevant is environmental quality to per capita health expenditures? Empirical evidence from panel of developing countries. Springer Plus 5(1), 925 (2016)
Yazdi, S., Zahra, T., Nikos, M.: Public healthcare expenditure and environmental quality in Iran. In Recent Advances in Applied Economics. https://www.wseas.us/e-library/conferences/2014/Lisbon/AEBD/AEBD-17.pdf. Accessed 05 Oct 2019 (2014)
Zaidi, S., Saidi, K.: Environmental pollution, health expenditure and economic growth in the Sub-Saharan Africa countries: Panel ARDL approach. Sust. Cities Soc. 41, 833–840 (2018)
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Gündüz, M. Healthcare expenditure and carbon footprint in the USA: evidence from hidden cointegration approach. Eur J Health Econ 21, 801–811 (2020). https://doi.org/10.1007/s10198-020-01174-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10198-020-01174-z
Keywords
- Healthcare expenditure
- Carbon footprint
- Carbon emissions
- Environmental quality
- Hidden cointegration
- Crouching error correction