Publication: Environmental Reliance, Climate Exposure, and Vulnerability: A Cross-Section Analysis of Structural and Stochastic Poverty
Date
2015-11
ISSN
Published
2015-11
Author(s)
Angelsen, Arild
Dokken, Therese
Abstract
This paper analyzes environmental
reliance, poverty, and climate vulnerability among more than
7,300 households in forest adjacent communities in 24
developing countries. The data are from the detailed,
quarterly income recording done by the Poverty Environment
Network project. Observed income is combined with predicted
income (based on households’ assets and other
characteristics) to create four categories of households:
income and asset poor (structurally poor), income rich and
asset poor (stochastically non-poor), income poor and asset
rich (stochastically poor), and income and asset rich
(structurally non-poor). The income and asset poor generate
29 percent of their income from environmental resources,
more than the other three categories. The income poor are
more exposed to extreme and variable climate conditions.
They tend to live in dryer (and hotter) villages in the dry
forest zones, in wetter villages in the wet zones, and
experience larger rainfall fluctuations. Among the
self-reported income-generating responses to income shocks,
extracting more environmental resources ranks second to
seeking wage labor. Given high reliance on forest and other
environmental resources, a concerning finding is that, in
the Africa subsample (dominated by dry forests), the rate of
forest loss is more than four times higher for the income
asset poor compared with the income asset rich. Special
attention should be given to the poorest households in dry
areas, predominantly in Africa. They are (already) exposed
to more extreme climate conditions, they suffer the highest
forest loss, and the forest benefits are at risk in global
warming scenarios.
Link to Data Set
Citation
“Angelsen, Arild; Dokken, Therese. 2015. Environmental Reliance, Climate Exposure, and Vulnerability: A Cross-Section Analysis of Structural and Stochastic Poverty. Policy Research Working Paper;No. 7474. © World Bank, Washington, DC. http://hdl.handle.net/10986/23444 License: CC BY 3.0 IGO.”
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