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Environmental impacts of income inequality: evidence from G7 economies

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Abstract

This study probes the environmental consequences of income inequality (INQ) in G7 economies from 1971 to 2015. INQ is captured by four indicators comprising GINI coefficients, Palma ratio, Theil index, and Atkinson index on per capita carbon emission as a proxy for environmental degradation using both fully modified OLS (FM-OLS) and dynamic OLS (D-OLS). The empirical data are subjected to pre-test using cross-sectional dependence (CSD) test and panel unit root and panel cointegration tests. The following results are established. First, the absence of CSD and presence of cointegration is confirmed. Second, positive effects of INQ indices are reported for the panel analyses. Third, the results of country-specific analyses are divergent and mixed among the G7 economies. For instance, positive impacts are reported for Canada, Japan, and the USA and negative for France and Germany; and insignificant impacts are evident in the case of Italy and the UK. Fourth, the effects of other covariates emerge from two directions entailing both positive and negative. While per capita GDP (LGDPPC) and trade openness (OPN) are aligned with the former a prior, per energy use (PEU) and inflation (INF) satisfied the latter. Consequently, embarking on pro-poor programs such as social welfare funds, private initiative support fund, and state intervention aimed at checkmating the excesses of the capitalists is seen as sacrosanct to solving the INQ-pco2 nexus disharmony.

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Data Availability

The datasets generated during and/or analyzed during the current study are available in World Bank Development Indicators (WDI): https://databank.worldbank.org/source/world-development-indicators.

Notes

  1. Goal 10 of SDGs focuses on how to reduce inequality within and among countries, while goals 8, 11, 12, 13, 14, and 15 respectively are devoted to environment and other environmental related issues.

  2. These countries are Canada, France, Germany, Italy, Japan, the UK, and the USA.

  3. Is an acronym for Oxford Committee for Famine Relief

  4. This is the not the focus of the study.

  5. With the exception of the USA that has decided to withdraw from the Paris Agreement 2020. That said, the USA is still the largest economy and producer as well as consumer of fossil fuel.

  6. This activity alone is the third largest source of greenhouse gas emissions, generating between 15 and 20% of overall carbon emissions (Wolde-Rufael and Idowu, 2016).

  7. DOSL is a modification of the FMOLS model by supplementing the cointegrating regression with lead and lagged differences of the regressors. This enables correction for endogeneity and serial correlation parametrically (see Pedroni 2000) for mathematical details).

  8. It should be noted that the model allows for deviation in the patterns of the deterministic term and also variation in the lag lengths for individual series. The conditions for each pi can be computed by adopting a general-to-specific approach based on current information with respect to either AIC or the SIC criterion or on successively evaluating the last coefficient of the Δgi, t − j.

  9. For the purpose of precision, this study is limited by the mathematical equation to LLC and IPS panel unit roots (for details on the other types of panel unit roots, see Levin et al. (2002), Im et al. (2003), Breitung (2000), and Maddala and Wu (1999)).

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Authors and Affiliations

  1. Department of Economies, University of Lagos, Lagos, Nigeria

    Kazeem Bello Ajide &  Ridwan Lanre Ibrahim

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  1. Kazeem Bello Ajide
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  2. Ridwan Lanre Ibrahim
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KBA writes the manuscript.

RLI writes the manuscript.

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Correspondence to Kazeem Bello Ajide.

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Appendix

Appendix

Table 8 Country-specific descriptive statistics
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Table 9 Country-specific fully modified ordinary least squares (FOLS) estimates
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Table 10 Country-specific fully modified ordinary least squares (FOLS) estimates
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Table 11 Country-specific fully modified ordinary least squares (FOLS) estimates
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Table 12 Country-specific dynamic ordinary least squares (D-OLS) estimates
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Table 13 Country-specific dynamic ordinary least squares (D-OLS) estimates
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Table 14 Country-specific fully modified ordinary least squares (D-OLS) estimates
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Ajide, .B., Ibrahim, .L. Environmental impacts of income inequality: evidence from G7 economies. Environ Sci Pollut Res 29, 1887–1908 (2022). https://doi.org/10.1007/s11356-021-15720-6

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