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Analysis of poverty data by small area estimation / edited by Monica Pratesi

データ種別	電子ブック
出版者	(Chichester, West Sussex, United Kingdom : Wiley)
出版年	2016
大きさ	1 online resource
著者標目	Pratesi, Monica editor

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0005175	Wiley Online Library: Complete oBooks				9781118815007

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一般注記	Includes bibliographical references and index Print version record and CIP data provided by publisher Cover -- Title Page -- Copyright -- Contents -- Foreword -- Preface -- Acknowledgements -- About the Editor -- List of Contributors -- Chapter 1 Introduction on Measuring Poverty at Local Level Using Small Area Estimation Methods -- 1.1 Introduction -- 1.2 Target Parameters -- 1.2.1 Definition of the Main Poverty Indicators -- 1.2.2 Direct and Indirect Estimate of Poverty Indicators at Small Area Level -- 1.3 Data-related and Estimation-related Problems for the Estimation of Poverty Indicators 1.4 Model-assisted and Model-based Methods Used for the Estimation of Poverty Indicators: a Short Review -- 1.4.1 Model-assisted Methods -- 1.4.2 Model-based Methods -- References -- Part I Definition of Indicators and Data Collection and Integration Methods -- Chapter 2 Regional and Local Poverty Measures -- 2.1 Introduction -- 2.2 Poverty -- Dilemmas of Definition -- 2.3 Appropriate Indicators of Poverty and Social Exclusion at Regional and Local Levels -- 2.3.1 Adaptation to the Regional Level -- 2.4 Multidimensional Measures of Poverty 2.4.1 Multidimensional Fuzzy Approach to Poverty Measurement -- 2.4.2 Fuzzy Monetary Depth Indicators -- 2.5 Co-incidence of Risks of Monetary Poverty and Material Deprivation -- 2.6 Comparative Analysis of Poverty in EU Regions in 2010 -- 2.6.1 Data Source -- 2.6.2 Object of Interest -- 2.6.3 Scope and Assumptions of the Empirical Analysis -- 2.6.4 Risk of Monetary Poverty -- 2.6.5 Risk of Material Deprivation -- 2.6.6 Risk of Manifest Poverty -- 2.7 Conclusions -- References -- Chapter 3 Administrative and Survey Data Collection and Integration -- 3.1 Introduction 3.2 Methods to Integrate Data from Different Data Sources: Objectives and Main Issues -- 3.2.1 Record Linkage -- 3.2.2 Statistical Matching -- 3.3 Administrative and Survey Data Integration: Some Examples of Application in Well-being and Poverty Studies -- 3.3.1 Data Integration for Measuring Disparities in Economic Well-being at the Macro Level -- 3.3.2 Collection and Integration of Data at the Local Level -- 3.4 Concluding Remarks -- References -- Chapter 4 Small Area Methods and Administrative Data Integration -- 4.1 Introduction -- 4.2 Register-based Small Area Estimation 4.2.1 Sampling Error: A Study of Local Area Life Expectancy -- 4.2.2 Measurement Error due to Progressive Administrative Data -- 4.3 Administrative and Survey Data Integration -- 4.3.1 Coverage Error and Finite-population Bias -- 4.3.2 Relevance Error and Benchmarked Synthetic Small Area Estimation -- 4.3.3 Probability Linkage Error -- 4.4 Concluding Remarks -- References -- Part II Impact of Sampling Design, Weighting and Variance Estimation -- Chapter 5 Impact of Sampling Designs in Small Area Estimation with Applications to Poverty Measurement -- 5.1 Introduction 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 John Wiley and Sons Wiley Online Library: Complete oBooks HTTP:URL=https://onlinelibrary.wiley.com/doi/book/10.1002/9781118814963
件　名	LCSH:Poverty -- Statistical methods 全ての件名で検索 LCSH:Poverty -- Econometric models 全ての件名で検索 LCSH:Poverty -- Measurement 全ての件名で検索 LCSH:Income distribution -- Econometric models 全ての件名で検索 CSHF:Pauvret�e -- M�ethodes statistiques 全ての件名で検索 CSHF:Pauvret�e -- Mod�eles �econom�etriques 全ての件名で検索 CSHF:Revenu -- R�epartition -- Mod�eles �econom�etriques 全ての件名で検索 FREE:BUSINESS & ECONOMICS -- Economics -- Macroeconomics 全ての件名で検索 FREE:POLITICAL SCIENCE -- Economic Conditions 全ての件名で検索 FREE:Income distribution -- Econometric models 全ての件名で検索 FREE:Poverty -- Econometric models 全ての件名で検索 FREE:Poverty -- Measurement 全ての件名で検索 FREE:Poverty -- Statistical methods 全ての件名で検索
分　類	LCC:HC79.P6 DC23:339.4/60727
書誌ID	EB00004465
ISBN	9781118815007