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Income inequality, educational attainment and environmental degradation: evidence from global panel

  • Applied Economics of Energy and Environment in Sustainability
  • Published:
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Abstract

The Sustainable Development Goal (SDG) 10 focuses on combating the climate change and its effects. The inclusion of this agenda in the Sustainable Development Goals by the United Nations has shown that worsened environmental degradation is currently a major threat facing humankind. The World Commission on Environment and Development 2015 has highlighted that income inequality is one of the major causes for environmental deterioration. Hence, reducing environmental degradation requires a look at the problem of unequal income distribution. Moreover, educational attainment plays a vital role in providing relevant knowledge and skills to people in handling environmental problems. Thus, the objective of the study is to investigate the relationship between income inequality, educational attainment, and CO2 emissions by employing a panel data analysis for a group of 64 countries from 1990 to 2016.The study uses mainly dynamic common correlated effects (DCCE) estimator to take into account the issue of cross-section dependence which has been ignored by most of the previous studies. By tackling the problem of cross-section dependence, unbiased and reliable results could be produced in estimations. Our results portray that an inverted U-shaped environmental Kuznets curve (EKC) is found to be valid. Additionally, income inequality has a negative impact on environmental degradation. Likewise, educational attainment and CO2 emissions are revealed to be negatively correlated. The findings of the study could provide a better understanding on the root causes of environmental degradation, and further suggest remedial actions to overcome the problem.

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Data availability

Data were sourced from the World Bank and Standardized World Income Inequality Database. It is available upon request.

Notes

  1. The period between 2008 and 2012 can be referred as the protocol’s first commitment period.

  2. The importance of education is highlighted by United Nations as one of the 17 SDGs—SDG 4 (Quality Education) (United Nations 2015).

  3. EKC model is a model linking economic growth and other explanatory variables to environmental degradation.

  4. Austria, Belgium, Bulgaria, Canada, Chile, China, Colombia, Costa Rica, Croatia, Cyprus, Czech Republic, Denmark, Egypt-Arab Rep., Estonia, Finland, France, Georgia, Germany, Greece, Hungary, India, Indonesia, Iran-Islamic Rep., Ireland, Israel, Italy, Japan, Korea-Rep., Kyrgyz Republic, Latvia, Lithuania, Luxembourg, Malawi, Malaysia, Mauritania, Mauritius, Mexico, Moldova, Morocco, the Netherlands, New Zealand, Norway, Panama, Paraguay, Peru, the Philippines, Poland, Portugal, Romania, Russian Federation, Rwanda, Slovak Republic, Slovenia, South Africa, Spain, Sweden, Switzerland, Thailand, Tunisia, Turkey, Ukraine, the UK, Uruguay, Venezuela-RB.

  5. These studies include Dijkgraaf and Vollebergh (1998), Hanif and Gago-de-Santos (2017), Jalil and Mahmud (2009), Khan and Ullah (2019) and etc.

  6. Of which 65% come from the fossil fuel use and industrial processes while the remaining is caused by deforestation and other land use.

  7. Examples of past studies include Ahmad and Satrovic (2021); Baek (2015); Iwata et al. (2010); Rojas-Vallejos and Lastuka (2020); Zhang et al. (2019).

  8. For example, Gini coefficient, income shares ratio, generalized entropy index, the Robin Hood index, and the Atkinson index.

  9. The Gini coefficient or Gini index was first introduced by the Italian Scholar named Corrado Gini (Liu et al. 2019).

  10. World Development Indicators provide the data for CO2 emissions up to 2016 only. Even though other data sources such as British Petroleum do have more recent data for CO2 emissions but the coverage is limited to only certain countries.

  11. The term “marginal propensity to emit” states that at different income levels, people have different marginal propensity to consume carbon intensive goods as they alter their consumption pattern. As individuals get richer, they tend to spend more on high-carbon products that they could not afford earlier (Jorgenson et al. 2017).

  12. Most of the 64 countries examined in this study have relatively lower Gini Coefficient that indicates lower inequality.

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  1. Universiti Tunku Abdul Rahman, Kampar Campus, Malaysia

    Suet-Ling Ching, Lin-Sea Lau & Chee-Keong Choong

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  1. Suet-Ling Ching
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Lin-Sea Lau: introduction; Chee-Keong, Choong: literature review; Suet-Ling, Ching: data collection, econometric analysis, and result interpretation; and Lin-Sea Lau: conclusion. All authors read and approved the final manuscript.

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Ching, SL., Lau, LS. & Choong, CK. Income inequality, educational attainment and environmental degradation: evidence from global panel. Environ Sci Pollut Res 30, 43056–43067 (2023). https://doi.org/10.1007/s11356-022-19256-1

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