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Analysis of Poverty Data by Small Area Estimation (Hardcover)
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Analysis of Poverty Data by Small Area Estimation (Hardcover)
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A comprehensive guide to implementing SAE methods for poverty
studies and poverty mapping There is an increasingly urgent demand
for poverty and living conditions data, in relation to local areas
and/or subpopulations. Policy makers and stakeholders need
indicators and maps of poverty and living conditions in order to
formulate and implement policies, (re)distribute resources, and
measure the effect of local policy actions. Small Area Estimation
(SAE) plays a crucial role in producing statistically sound
estimates for poverty mapping. This book offers a comprehensive
source of information regarding the use of SAE methods adapted to
these distinctive features of poverty data derived from surveys and
administrative archives. The book covers the definition of poverty
indicators, data collection and integration methods, the impact of
sampling design, weighting and variance estimation, the issue of
SAE modelling and robustness, the spatio-temporal modelling of
poverty, and the SAE of the distribution function of income and
inequalities. Examples of data analyses and applications are
provided, and the book is supported by a website describing scripts
written in SAS or R software, which accompany the majority of the
presented methods. Key features: * Presents a comprehensive review
of SAE methods for poverty mapping * Demonstrates the applications
of SAE methods using real-life case studies * Offers guidance on
the use of routines and choice of websites from which to download
them Analysis of Poverty Data by Small Area Estimation offers an
introduction to advanced techniques from both a practical and a
methodological perspective, and will prove an invaluable resource
for researchers actively engaged in organizing, managing and
conducting studies on poverty.
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