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Health care expenditure and environmental pollution: a cross-country comparison across different income groups

Environmental Science and Pollution Research volume 27, pages 8142–8156 (2020)Cite this article

Abstract

This paper investigates the long-run dynamics between health care expenditure and environmental pollution across four global income groups. The analysis uses data from 178 countries, spanning the period 1995–2017. Panel estimations are employed with unobserved heterogeneity, temporal persistence, and cross-sectional dependence using a model with common correlated effects. The findings document that the health care expenditure is a necessity for all sub-groups. We established that a 1% increase in national income increased health expenditure by 7.2% in the full sample, and 9.3%, 8.6%, 6.8% and 2.9% for low, low-middle, upper-middle and high-income groups, respectively, while a 1% increase in CO2 emissions increased health expenditure by 2.5% in the full sample, and 2.9%, 1.2%, 2.3% and 2.6% across these four income groups. We recommend that coordinated approach is needed in setting policy goals both in energy and health sectors in mitigating the negative effects of pollution. Our findings indicate that low-carbon emissions and energy efficient health care services will significantly reduce future health care expenses.

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Notes

  1. http://www.cop21paris.org/

  2. Fantom and Serajuddin (2016)

  3. Improvements in energy efficiency from consumption alone could achieve 31% reduction necessary to halve emissions by 2050, compared to 2009 levels (IEA 2012).

  4. We ignore here other sectors in an economy as our emphasis is on health care sector.

  5. Changes in the energy intensity may occur due to a greater number of other factors which may or may not be carbon related.

  6. Bhattacharya et al. (2017) has emphasised the role of institution in reducing CO2 emissions.

  7. In addition, the universal health care system was initiated for most of the developing countries around this period.

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Affiliations

  1. University of Derby, Kedleston Rd, Derby, DE22 1GB, UK

    Nicholas Apergis

  2. Department of Economics, Monash University, Caulfield, , Melbourne, 3145, Australia

    Mita Bhattacharya

  3. UAQUAP, Higher Institute of Management, University of Tunis, Boulevard du 9 Avril, 1938, Tunis, Tunisia

    Walid Hadhri

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  1. Nicholas Apergis
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Correspondence to Mita Bhattacharya.

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Appendices

Appendix

Country Coverage

Full Sample: 178 countries

Low income countries: 26 countries

Benin, Burkina Faso, Burundi, Cambodia, Central African Republic, Chad, Comoros, Congo Democratic, Congo Republic, Ethiopia, Gambia, Guinea, Haiti, Liberia, Madagascar, Malawi, Mali, Mozambique, Nepal, Niger, Rwanda, Sierra Leone, Somalia, Tanzania, Togo, Uganda.

Lower middle-income countries: 45 countries

Armenia, Bangladesh, Bhutan, Bolivia, Cameroon, Cape Verde, Cote d’Ivoire, Djibouti, Egypt, El Salvador, Georgia, Ghana, Guatemala, Guyana, Honduras, India, Indonesia, Kenya, Kiribati, Kyrgyz Republic, Laos, Mauritania, Moldova, Morocco, Myanmar, Nicaragua, Nigeria, Pakistan, Papua New Guinea, Philippines, Samoa, Sao Tome & Principe, Senegal, Solomon Islands, Sri Lanka, Sudan, Swaziland, Syrian Arab Republic, Tajikistan, Ukraine, Uzbekistan, Vanuatu, Vietnam, Yemen, Zambia.

Upper middle-income countries: 49 countries

Albania, Algeria, Angola, Azerbaijan, Belarus, Belize, Bosnia-Herzegovina, Botswana, Brazil, Bulgaria, China, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, Fiji, FYROM, Gabon, Grenada, Iran, Iraq, Jamaica, Jordan, Kazakhstan, Lebanon, Libya, Malaysia, Maldives, Marshall Islands, Mauritius, Mexico, Mongolia, Montenegro, Namibia, Panama, Paraguay, Peru, Romania, Serbia, South Africa, St. Lucia, St. Vincent & Grenadines, Suriname, Thailand, Tonga, Tunisia, Turkey, Turkmenistan.

High-income countries: 58 countries

Andorra, Argentina, Australia, Austria, Bahamas, Bahrain, Barbados, Belgium, Brunei, Canada, Chile, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Kuwait, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Netherlands, New Zealand, Norway, Oman, Poland, Portugal, Qatar, Russia, San Marino, Saudi Arabia, Seychelles, Singapore, Slovakia, Slovenia, South Korea, Spain, St. Kitts & Nevis, Sweden, Switzerland, Taiwan, Trinidad & Tobago, United Arab Emirates, United Kingdom, United States, Uruguay, Venezuela.

Appendix

Table 5 Descriptive statistics of variables: 1960–2017
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Table 6 Correlations
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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, 8142–8156 (2020). https://doi.org/10.1007/s11356-019-07457-0

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Keywords

  • Health care expenditure
  • Environmental pollution
  • CO2 emissions
  • Income groups
  • Panel estimation

JEL classification

  • C310
  • C330
  • H510