Impact of climate vulnerability and climate readiness on income inequality: Evidence from developing countries
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DOIhttp://dx.doi.org/10.21511/ee.16(3).2025.06
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Article InfoVolume 16 2025, Issue #3, pp. 82-99
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Type of the article: Research Article
Abstract
Recognizing the link between climate vulnerability, climate readiness, and income inequality is crucial, as economic disparities can exacerbate climate risks and hinder adaptation, particularly in developing countries. This study analyzes the impact of climate vulnerability and climate readiness on income inequality across 61 developing countries from 1995 to 2022. The Quasi-likelihood under the Independence Model Criterion (QIC) was applied to determine the optimal correlation structure and identify the most relevant covariates. Additionally, Generalized Estimating Equations (GEE), Panel-Corrected Standard Errors (PCSE), and Feasible Generalized Least Squares (FGLS) were employed to ensure robust estimation. To account for measurement uncertainty, 100 multiple imputations of the Gini index from the latest Standardized World Income Inequality Database (SWIID) were used instead of a single point estimate. Empirical results indicate that climate vulnerability significantly (p < 0.01) exacerbates income inequality, with estimates ranging from 10.426 to 48.997, whereas climate readiness significantly (p < 0.01) mitigates inequality, with elasticity values between –47.259 and –25.764. Control variables, including trade balance, unemployment, and urban population growth, exhibit a strong positive correlation with income inequality, while democracy and natural resource rents are associated with a more equitable income distribution. Economic growth demonstrates a positive and significant effect on inequality, whereas its squared term is negative but generally insignificant, providing only weak support for the Kuznets hypothesis. The findings highlight the pivotal role of climate readiness in mitigating the socio-economic impacts of environmental risks, emphasizing the importance of implementing targeted adaptation policies in highly vulnerable countries.
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JEL Classification (Paper profile tab)D31, Q54, O15, C01
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References47
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Tables9
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Figures2
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- Figure 1. Scatterplot matrix of climate vulnerability, climate readiness, GDP, and Gini index across countries
- Figure A1. Plots SWIID gini_disp estimates with Confidence Intervals for the 61 countries of our sample
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- Table 1. Summary statistics
- Table 2. Correlation statistics
- Table 3. CD, panel unit root, and cointegration test
- Table 4. QIC for model selection under normal distribution
- Table 5. GEE results (Dep Var: Gini)
- Table 6. PCSE results (Dep Var: Gini)
- Table 7. FGLS results (Dep Var: Gini)
- Table 8. Multiple-imputation estimates, GEE results (Dep Var: Gini)
- Table A1. Variables description with measurements and source
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