Integrating Surveys With Geospatial Data Through Small Area Estimation To Disaggregate Sdg Indicators At Subnational Level
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Author | : Food and Agriculture Organization of the United Nations |
Publisher | : Food and Agriculture Organization of the United Nations |
Total Pages | : 46 |
Release | : 2023-01-20 |
Genre | : Social Science |
ISBN | : 9251375453 |
The present technical report illustrates a case study on the adoption of small area estimation techniques to produce granular sub-national estimates of SDG Indicators 2.3.1 and 2.3.2, by integrating survey microdata with auxiliary information retrieved from various trustworthy geospatial information systems. The technical report provides practical guidance to national statistical offices and other institutions wanting to implement small area estimation techniques on SDG Indicators 2.3.1 and 2.3.2 or similar indicators based on surveys microdata.
Author | : Food and Agriculture Organization of the United Nations |
Publisher | : Food & Agriculture Org. |
Total Pages | : 51 |
Release | : 2022-03-14 |
Genre | : Business & Economics |
ISBN | : 9251358931 |
This technical report presents a case study based on the use of a small area estimation (SAE) approach to produce disaggregated estimates of SDG Indicator 5.a.1 by sex and at granular sub-national level. In particular, after introducing the framework for using SAE techniques, the report discusses a possible model-based technique to integrate a household or agricultural survey measuring the indicator of interest with census microdata, in order to borrow strength from a more comprehensive data source and produce estimates of higher quality. The discussed estimation approach could also be extended or customized for the integration of survey data with alternative data sources, such as administrative records, and/or geospatial information, and for the disaggregation of other (SDG) indicators based on survey microdata.
Author | : Food and Agriculture Organization of the United Nations |
Publisher | : Food & Agriculture Org. |
Total Pages | : 148 |
Release | : 2023-10-10 |
Genre | : Technology & Engineering |
ISBN | : 9251380570 |
This catalogue aims to improve the dissemination and outreach of FAO’s knowledge products and overall publishing programme. By providing information on its key publications in every area of FAO’s work, and catering to a range of audiences, it thereby contributes to all organizational outcomes. From statistical analysis to specialized manuals to children’s books, FAO publications cater to a diverse range of audiences. This catalogue presents a selection of FAO’s main publications, produced in 2023 or earlier, ranging from its global reports and general interest publications to numerous specialized titles. In addition to the major themes of agriculture, forestry and fisheries, it also includes thematic sections on climate change, economic and social development, and food safety and nutrition.
Author | : Asian Development Bank |
Publisher | : Asian Development Bank |
Total Pages | : 137 |
Release | : 2021-05-01 |
Genre | : Business & Economics |
ISBN | : 9292627759 |
The "leave no one behind" principle espoused by the 2030 Agenda for Sustainable Development requires measures of progress for different segments of the population. This entails detailed disaggregated data to identify subgroups that might be falling behind, to ensure progress toward achieving the Sustainable Development Goals (SDGs). The Asian Development Bank and the Statistics Division of the United Nations Department of Economic and Social Affairs developed this practical guidebook with tools to collect, compile, analyze, and disseminate disaggregated data. It also provides materials on issues and experiences of countries regarding data disaggregation for the SDGs. This guidebook is for statisticians and analysts from planning and sector ministries involved in the production, analysis, and communication of disaggregated data.
Author | : Asian Development Bank |
Publisher | : Asian Development Bank |
Total Pages | : 152 |
Release | : 2020-05-01 |
Genre | : Business & Economics |
ISBN | : 9292622234 |
This guide to small area estimation aims to help users compile more reliable granular or disaggregated data in cost-effective ways. It explains small area estimation techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes. The guide is intended for staff of national statistics offices and for other development practitioners. It aims to help them to develop and implement targeted socioeconomic policies to ensure that the vulnerable segments of societies are not left behind, and to monitor progress toward the Sustainable Development Goals.
Author | : Asian Development Bank |
Publisher | : Asian Development Bank |
Total Pages | : 159 |
Release | : 2021-03-01 |
Genre | : Business & Economics |
ISBN | : 9292621327 |
The “leave no one behind” principle of the 2030 Agenda for Sustainable Development requires appropriate indicators for different segments of a country’s population. This entails detailed, granular data on population groups that extend beyond national trends and averages. The Asian Development Bank, in collaboration with the Philippine Statistics Authority and the World Data Lab, conducted a feasibility study to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics in the Philippines. This report documents the results of the study, which capitalized on satellite imagery, geospatial data, and powerful machine learning algorithms to augment conventional data collection and sample survey techniques.
Author | : Asian Development Bank |
Publisher | : |
Total Pages | : 54 |
Release | : 2020-09 |
Genre | : |
ISBN | : 9789292623135 |
This special supplement to the Key Indicators for Asia and the Pacific 2020 discusses how poverty estimates can be enhanced by integrating household surveys and censuses with data extracted from satellite imagery. As part of a special ADB knowledge initiative, computer vision techniques and machine-learning algorithms were applied on datasets from the Philippines and Thailand to demonstrate increased granularity of poverty estimation using artificial intelligence. The report identifies practical considerations and technical requirements for this novel approach to mapping the spatial distribution of poverty. It also outlines the investments required by national statistics offices to fully capitalize on the benefits of incorporating innovative data sources into conventional work programs.
Author | : Asian Development Bank |
Publisher | : Asian Development Bank |
Total Pages | : 141 |
Release | : 2021-04-01 |
Genre | : Business & Economics |
ISBN | : 9292627694 |
The “leave no one behind” principle of the 2030 Agenda for Sustainable Development requires appropriate indicators for different segments of a country’s population. This entails detailed, granular data on population groups that extend beyond national trends and averages. The Asian Development Bank (ADB), in collaboration with the National Statistical Office of Thailand and the Word Data Lab, conducted a feasibility study to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics in Thailand. This report documents the results of the study, providing insights on data collection requirements, advanced algorithmic techniques, and validation of poverty estimates using artificial intelligence to complement traditional data sources and conventional survey methods.
Author | : Sachin Chaturvedi |
Publisher | : Springer Nature |
Total Pages | : 733 |
Release | : 2021 |
Genre | : Africa--Politics and government |
ISBN | : 3030579387 |
This open access handbook analyses the role of development cooperation in achieving the 2030 Agenda in a global context of 'contested cooperation'. Development actors, including governments providing aid or South-South Cooperation, developing countries, and non-governmental actors (civil society, philanthropy, and businesses) constantly challenge underlying narratives and norms of development. The book explores how reconciling these differences fosters achievement of the Sustainable Development Goals. Sachin Chaturvedi is Director General at the Research and Information System for Developing Countries (RIS), a New Delhi, India-based think tank. Heiner Janus is a researcher in the Inter- and Transnational Cooperation programme at the German Development Institute. Stephan Klingebiel is Chair of the Inter- and Transnational Cooperation programme at the German Development Institute and Senior Lecturer at the University of Marburg, Germany. Xiaoyun Li is Chair Professor at China Agricultural University and Honorary Dean of the China Institute for South-South Cooperation in Agriculture. Prof. Li is the Chair of the Network of Southern Think Tanks and Chair of the China International Development Research Network. André de Mello e Souza is a researcher at the Institute for Applied Economic Research (IPEA), a Brazilian governmental think tank. Elizabeth Sidiropoulos is Chief Executive of the South African Institute of International Affairs. She has co-edited Development Cooperation and Emerging Powers: New Partners or Old Patterns (2012) and Institutional Architecture and Development: Responses from Emerging Powers (2015). Dorothea Wehrmann is a researcher in the Inter- and Transnational Cooperation programme at the German Development Institute.
Author | : Jeffrey Sachs |
Publisher | : Cambridge University Press |
Total Pages | : 517 |
Release | : 2021-10-14 |
Genre | : Business & Economics |
ISBN | : 1009098918 |
Contains insights on current issues in research on sustainable development, featuring the SDG Index and Dashboards.