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)
Google Scholar
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)
Google Scholar
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)
Google Scholar
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)
Google Scholar
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)
Google Scholar
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)
PubMed
Google Scholar
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)
CAS
PubMed
Google Scholar
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)
PubMed Central
Google Scholar
Corvalán, C., Kjellström, T., Smith, K.: Health, environment and sustainable development: identifying links and indicators to promote action. Epidemiology 10(5), 656–660 (1999)
PubMed
Google Scholar
Crémieux, P.Y., Ouellette, P., Pilon, C.: Health care spending as determinants of health outcomes. Health Econ. 8(7), 627–639 (1999)
PubMed
Google Scholar
Di Matteo, L.: The determinants of the public–private mix in Canadian health care expenditures: 1975–1996. Health Policy 52(2), 87–112 (2000)
PubMed
Google Scholar
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)
PubMed
Google Scholar
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)
Google Scholar
Engle, R.F., Granger, C.W.J.: Cointegration and error correction: representation, estimation, and testing. Econometrica 55, 251–276 (1987)
Google Scholar
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)
Google Scholar
Gbesemete, K.P., Gerdtham, U.G.: Determinants of health care expenditure in Africa: a cross-sectional study. World Dev. 20(2), 303–308 (1992)
Google Scholar
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)
CAS
PubMed
Google Scholar
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)
Google Scholar
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)
PubMed
Google Scholar
Hitiris, T., Posnett, J.: The determinants and effects of health expenditure in developed countries. J. Health Econ. 11(2), 173–181 (1992)
CAS
PubMed
Google Scholar
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)
Google Scholar
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)
Google Scholar
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)
CAS
Google Scholar
Johansen, S., Nielsen, M.O.: Likelihood inference for a nonstationary fractional autoregressive model. J. Econ. 158, 51–66 (2010)
Google Scholar
Johansen, S., Nielsen, M.O.: Likelihood inference for a fractionally cointegrated vector autoregressive model. Econometrica 80, 2667–2732 (2012)
Google Scholar
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)
Google Scholar
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)
Google Scholar
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)
Google Scholar
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)
Google Scholar
Matthews, H.S., Hendrickson, C.T., Weber, C.L.: The importance of carbon footprint estimation boundaries. Environ Sci Technol. 42(16), 5839–5842 (2008)
CAS
PubMed
Google Scholar
Mehrara, M., Sharzei, G., Mohaghegh, M.: The relationship between health expenditure and environmental quality in developing countries. J. Health Admin. 14, 46 (2011)
Google Scholar
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)
Google Scholar
Murthy, N.V., Ukpolo, V.: Aggregate health care expenditure in the United States: evidence from cointegration tests. Appl. Econ. 26(8), 797–802 (1994)
Google Scholar
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)
Google Scholar
Newhouse, J.P.: Medical-care expenditure: a cross-national survey. J. Hum. Resour. 12(1), 115–125 (1977)
CAS
PubMed
Google Scholar
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)
Google Scholar
Remoundou, K., Koundouri, P.: Environmental effects on public health: An economic perspective. Int J Environ Res Public Health 6(8), 2160–2178 (2009)
PubMed
PubMed Central
Google Scholar
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)
Google Scholar
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)
Google Scholar
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)
Google Scholar
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)
Google Scholar
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)
CAS
Google Scholar
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)
PubMed
Google Scholar
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)
Google Scholar