Analysis Of Poverty Data By Small Area Estimation


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Analysis of Poverty Data by Small Area Estimation


Analysis of Poverty Data by Small Area Estimation

Author: Monica Pratesi

language: en

Publisher: John Wiley & Sons

Release Date: 2016-02-23


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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.

A Course on Small Area Estimation and Mixed Models


A Course on Small Area Estimation and Mixed Models

Author: Domingo Morales

language: en

Publisher: Springer Nature

Release Date: 2021-03-12


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This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation. It presents the theory in a rigorous way and compares and contrasts various statistical methodologies, helping readers understand how to develop new methodologies for small area estimation. It also includes numerous sample applications of small area estimation techniques. The underlying R code is provided in the text and applied to four datasets that mimic data from labor markets and living conditions surveys, where the socioeconomic indicators include the small area estimation of total unemployment, unemployment rates, average annual household incomes and poverty indicators. Given its scope, the book will be useful for master and PhD students, and for official and other applied statisticians.

Research Handbook on Measuring Poverty and Deprivation


Research Handbook on Measuring Poverty and Deprivation

Author: Jacques Silber

language: en

Publisher: Edward Elgar Publishing

Release Date: 2023-03-02


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Encompassing chapters that address both unidimensional and multidimensional poverty, this timely Research Handbook explores all aspects of poverty and deprivation measurement, not only detailing broad issues but also scrutinising specific domains and aspects of poverty, such as health, energy and housing. Its succinct and highly focussed chapters, written by a diverse range of authors, employ a combination of theoretical and empirical methodologies to offer well-rounded explorations of complex topics.