Can Earth's and Society's Systems Meet the Needs of 10 Billion People? Summary of a Workshop (2014) / Chapter Skim
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6 Resource Distribution and Global Inequality
6 Resource Distribution and Global Inequality
Pages 53-64
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From page 53... ...
To measure inequality, Milanović used data from the International Comparison Program, which is a large undertaking that assesses purchasing power in different nations.1 While details of this project's results are subject to debate, he said, the project provides a comparison of prices across nations that can be used as a baseline metric. The International Comparison Program developed a price index normalized to the United States, in which a score 1For more information about the International Comparison Program, see http:// go.worldbank.org/X3R0INNH80 [February 2014]
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From page 54... ...
In other words, China's increasing population and increasing average income contributed to lower global Gini coefficients under Concept 2. However, the Gini coefficient within China was 2The Gini coefficient is a statistical measure of inequality, represented as a measure be tween 0 (complete equality)
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From page 55... ...
Concept 3 is represented by a small set of discrete dots because survey results on individual income are not consistently available across time and nations. As poorer nations typically do not provide survey results as often as developed nations, the data for Concept 3 should be considered a lower bound estimate.
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From page 56... ...
Milanović noted that one could look at inequality of carbon emissions as well: Because consumption patterns vary by income level, it should be possible to assess overall emission concentrations by measuring income levels in different areas. A participant asked Milanović if the ideal situation would be one in which everyone in the world would have the same income, and therefore there would be no inequality.
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From page 57... ...
He characterized this as a politically sensitive issue, as IPAT can "blame" the poorer nations for unsustainable practices. Under the PIES model, population concerns extend to all nations, although the issues facing each one are different.
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From page 58... ...
Age structure proved to be the largest contributor to inequality. Within countries in high-fertility settings, he examined differential fertility, fosterage, and teen pregnancy.
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From page 59... ...
The IPAT model and Malthusian principles emphasize population size and growth, but he argued that demographic distribution matters more. Eloundou-Enyegue said inequality trends are likely to continue, and social capital, family trends, and the life chances of children born to diverse circumstances are profoundly different.
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From page 60... ...
Lutz presented South Korea's demographic and education data from 1985 through 2010, which clearly demonstrated demographic metabolism: As time progressed, the uneducated older people were replaced with the more educated next generation. In addition, as educational levels increased, fertility decreased, and fewer 3The Human Development Index is a single composite metric that combines indicators of life expectancy, educational attainment, and income to measure development (United Nations Development Reports, see http://hdr.undp.org/en/statistics/hdi [February 2014]
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From page 61... ...
that discusses maternal education and population, and cited evidence with respect to the causality between increased maternal education and slower population growth. He stressed that education is not merely a proxy for socioeconomic status; there is strong evidence that it has direct functional causality.
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From page 62... ...
According to Lutz, a frequent mistake is to match future climate conditions to today's society and health capabilities; in reality, one must project both into the future. Lutz then looked at the five SSP scenarios, including population and age- and education- pyramid information for each scenario.
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From page 63... ...
found a strong correlation between increasing inequality and other negative outcomes, such as increased health and mortality rates. The danger with the Gini coefficient approach, he suggested, is that it focuses entirely within national borders, and in so doing equates a rich American with a rich African and a poor American with a poor African, when in reality those populations are not at all the same.
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From page 64... ...
The participant asked if absolute inequality is the only metric or if another metric can measure social mobility. Milanović responded that data on intergenerational mobility show a correlation between current inequality and lack of mobility.
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