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Estimating the absolute wealth of households.

Hruschka DJ, Gerkey D, Hadley C - Bull. World Health Organ. (2015)

Bottom Line: We also compared the accuracy of absolute versus relative wealth estimates for the prediction of anthropometric measures.Absolute wealth estimates provide new opportunities for comparative research to assess the effects of economic resources on health and human capital, as well as the long-term health consequences of economic change and inequality.Abstract available from the publisher.

View Article: PubMed Central - PubMed

Affiliation: School of Human Evolution and Social Change, Arizona State University, PO Box 872402, Tempe, Arizona, 85287-2402, United States of America (USA).

ABSTRACT

Objective: To estimate the absolute wealth of households using data from demographic and health surveys.

Methods: We developed a new metric, the absolute wealth estimate, based on the rank of each surveyed household according to its material assets and the assumed shape of the distribution of wealth among surveyed households. Using data from 156 demographic and health surveys in 66 countries, we calculated absolute wealth estimates for households. We validated the method by comparing the proportion of households defined as poor using our estimates with published World Bank poverty headcounts. We also compared the accuracy of absolute versus relative wealth estimates for the prediction of anthropometric measures.

Findings: The median absolute wealth estimates of 1,403,186 households were 2056 international dollars per capita (interquartile range: 723-6103). The proportion of poor households based on absolute wealth estimates were strongly correlated with World Bank estimates of populations living on less than 2.00 United States dollars per capita per day (R(2)  = 0.84). Absolute wealth estimates were better predictors of anthropometric measures than relative wealth indexes.

Conclusion: Absolute wealth estimates provide new opportunities for comparative research to assess the effects of economic resources on health and human capital, as well as the long-term health consequences of economic change and inequality.

No MeSH data available.


Correlation between two sets of estimates of the proportions of surveyed households in poverty, 66 countries, 1994–2011
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Figure 5: Correlation between two sets of estimates of the proportions of surveyed households in poverty, 66 countries, 1994–2011

Mentions: The value of γ that gave the best fit between the poverty headcounts based on the absolute wealth estimates and the World Bank poverty headcounts was 0.32. We therefore used Wealth0.32 in subsequent analyses (Fig. 1). The thresholds for Wealth0.32 that gave the best approximations of the World Bank poverty headcounts based on thresholds for consumption expenditure of US$ 1.25 and US$ 2.00 per capita per day were about 1000 and 2200 international dollars per capita, respectively. When these thresholds for Wealth0.32 were used, there were strong correlations between the poverty headcounts based on the absolute wealth estimates and the corresponding World Bank poverty headcounts: R2 = 0.80 for a threshold of US$ 1.25 per capita per day and R2 = 0.84 for a threshold of US$ 2.00 per capita per day (Fig. 5).


Estimating the absolute wealth of households.

Hruschka DJ, Gerkey D, Hadley C - Bull. World Health Organ. (2015)

Correlation between two sets of estimates of the proportions of surveyed households in poverty, 66 countries, 1994–2011
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4490812&req=5

Figure 5: Correlation between two sets of estimates of the proportions of surveyed households in poverty, 66 countries, 1994–2011
Mentions: The value of γ that gave the best fit between the poverty headcounts based on the absolute wealth estimates and the World Bank poverty headcounts was 0.32. We therefore used Wealth0.32 in subsequent analyses (Fig. 1). The thresholds for Wealth0.32 that gave the best approximations of the World Bank poverty headcounts based on thresholds for consumption expenditure of US$ 1.25 and US$ 2.00 per capita per day were about 1000 and 2200 international dollars per capita, respectively. When these thresholds for Wealth0.32 were used, there were strong correlations between the poverty headcounts based on the absolute wealth estimates and the corresponding World Bank poverty headcounts: R2 = 0.80 for a threshold of US$ 1.25 per capita per day and R2 = 0.84 for a threshold of US$ 2.00 per capita per day (Fig. 5).

Bottom Line: We also compared the accuracy of absolute versus relative wealth estimates for the prediction of anthropometric measures.Absolute wealth estimates provide new opportunities for comparative research to assess the effects of economic resources on health and human capital, as well as the long-term health consequences of economic change and inequality.Abstract available from the publisher.

View Article: PubMed Central - PubMed

Affiliation: School of Human Evolution and Social Change, Arizona State University, PO Box 872402, Tempe, Arizona, 85287-2402, United States of America (USA).

ABSTRACT

Objective: To estimate the absolute wealth of households using data from demographic and health surveys.

Methods: We developed a new metric, the absolute wealth estimate, based on the rank of each surveyed household according to its material assets and the assumed shape of the distribution of wealth among surveyed households. Using data from 156 demographic and health surveys in 66 countries, we calculated absolute wealth estimates for households. We validated the method by comparing the proportion of households defined as poor using our estimates with published World Bank poverty headcounts. We also compared the accuracy of absolute versus relative wealth estimates for the prediction of anthropometric measures.

Findings: The median absolute wealth estimates of 1,403,186 households were 2056 international dollars per capita (interquartile range: 723-6103). The proportion of poor households based on absolute wealth estimates were strongly correlated with World Bank estimates of populations living on less than 2.00 United States dollars per capita per day (R(2)  = 0.84). Absolute wealth estimates were better predictors of anthropometric measures than relative wealth indexes.

Conclusion: Absolute wealth estimates provide new opportunities for comparative research to assess the effects of economic resources on health and human capital, as well as the long-term health consequences of economic change and inequality.

No MeSH data available.