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Innovations in Small Area Estimation Methodologies

Innovations in Small Area Estimation Methodologies
小区域估算方法的创新
批准号:
ES/N011619/1
负责人:
Nikolaos Tzavidis
金额:
$82.6万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --

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中文摘要
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英文摘要
Reliable statistics are crucial for policy relevant research. Small Area Estimation (SAE) methods generate robust reliable and consistent statistics at geographical scales for which survey data are either non-existent or too sparse to provide direct estimates of acceptable accuracy. The last decade has seen a rapid increase in the use of SAE. Statistical agencies and Governmental organisations are actively developing their own suites of estimates. In the UK the Office for National Statistics (ONS) has responded to user demands by producing estimates of average household income for wards and using SAE to answer queries from local authorities, policy advisers and government departments. The Welsh Assembly Government (WAG) is actively seeking to develop capacity for SAE. Public Health England produces SAEs of adolescent smoking and chronic kidney disease.Initial demands for small area statistics are now shifting to requirements for more complex statistics that extend beyond averages and proportions to encompass estimates of statistical distributions, multidimensional indicators (e.g. inequality and deprivation indicators) and methods for replacing the Census and adjusting Census results for undercount. These developing requirements pose significant methodological and applied real-world challenges. These challenges are deepened by different methodological approaches to SAE remaining largely unconnected, locked in disciplinary silos. The technical presentation of SAE also impedes more widespread uptake by social scientists and understanding by users.The proposed programme of work aims to (a) develop novel SAE methodologies to better serve the needs of users and producers of SAE (b) bridge different methodological approaches to SAE, (c) apply SAE for answering substantive questions in the social sciences and (d) 'Mainstream' SAE within the quantitative social sciences through the creation of methodologically comprehensive and accessible resources. The project comprises three work packages of methodological innovative research designed to deepen the understanding of SAE and achieve the aforementioned aims. The project will capitalise on a cross-disciplinary research team drawn together through an NCRM methodological network and reflecting a large part of the SAE expertise in the UK. Through long-standing collaborations with national and international agencies in the UK, Mexico and Brazil, which are placed at the centre of the project, we enjoy access to individual level secondary survey and Census data. Collaboration with key SAE users will ensure that the project remains relevant to user needs and that methodologies are used for expanding the set of small area statistics currently available. The involvement of international experts ensures the quality and relevance of the research.Substantive outputs will include SAEs of attributes of interest to users, including income, inequality, deprivation, health, ethnicity and a realistic pseudo-Census dataset for use by other researchers. The project will advance knowledge across disciplines in the social sciences including social statistics, applied economics, human geography and sociology. It will additionally impact on the production of official and Census statistics. The project is committed to adding value to NCRM's training and capacity building activities by developing new resources.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
A global optimisation approach to range-restricted survey calibration.
范围限制测量校准的全局优化方法。
DOI: 10.1007/s11222-017-9739-5
发表时间: 2018
期刊: Statistics and computing
影响因子: 2.2
作者: [Espuny-Pujol F]
通讯作者: Espuny-Pujol F
Switching Between Different Non-Hierachical Administrative Areas via Simulated Geo-Coordinates: A Case Study for Student Residents in Berlin
通过模拟地理坐标在不同的非等级行政区域之间切换:柏林学生居民的案例研究
DOI: 10.2478/jos-2020-0016
发表时间: 2020
期刊: Journal of Official Statistics
影响因子: 1.1
作者: [Groß M]
通讯作者: Groß M
The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators
用于估计和绘制区域分类指标的 R 包 emdi
DOI: 10.18637/jss.v091.i07
发表时间: 2019
期刊: Journal of Statistical Software
影响因子: 5.8
作者: [Kreutzmann A]
通讯作者: Kreutzmann A
Empirical likelihood approach for aligning information from multiple surveys
用于调整多项调查信息的经验似然法
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者: [Berger, Y.]
通讯作者: Berger, Y.
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