Download Free Disaggregation Book in PDF and EPUB Free Download. You can read online Disaggregation and write the review.

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.
This volume is intended to expand the dialogue and interest among both practitioners and academicians in a problem area worthy of attention by all. The concept of disaggregation admits to our current inability to solve many types of interrelated hierarchical problems simultaneously. It offers instead a sequential, iterative process as a workable and necessary procedure. The papers in this volume are selected from those presented at a Disaggregation Conference held in March, 1977 at The Ohio State University. We heartily applaud all those who participated in the conference and particularly appreci ate the cooperation of those authors whose work is published in this collection. Part A contains four papers which define the various dimensions of disaggregation. The paper by Martin Starr, which was the text of his luncheon address at the conference, provides several interesting perspectives to the problem. Although disaggregation suggests tear ing apart, as Professor Starr illustrates with his butterfly example, it also suggests a putting together or a synthesis which recognizes interrelationships and dependencies. The next paper by Lee Kra jewski and Larry Ritzman offers a general model of disaggregation for both the manufacturing and service sectors. After reading the papers in this section, as well as the papers in subsequent sections, you will identify other dimensions to hierarchical decision making which go beyond this generalized model.
In this book, first published in 1990, leading theorists and applied economists address themselves to the key questions of aggregation. The issues are covered both theoretically and in wide-ranging applications. Of particular intrest is the optimal aggregation of trade data, the need for micro-modelling when imoprtant non-linearities are present (for example, tax exhaustion in modelling company behaviour) and the use of a micro-model to stimulate labour supply behaviour in a macro-model of the Netherlands.
This book presents the main principles of preference disaggregation analysis and covers theoretical advances in preference modelling, group decision making, classification methods, robustness analysis, process mining, and decision support systems. In addition, it highlights several applications of the preference disaggregation analysis in a wide range of areas, such as customer satisfaction analysis, consumer behavior, energy and environmental policy, strategy development, and agricultural marketing. This book was published in honor of Yannis Siskos on the occasion of his retirement from the University of Piraeus, Greece. It offers a unique snapshot of the preference disaggregation philosophy in multiple criteria decision analysis and presents a range of research ideas, many of which were significantly influenced by Professor Siskos work.
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.
As a member of the working group on data disaggregation, the Food and Agriculture Organization of the United Nations (FAO) has taken numerous steps towards supporting Member Countries in the production of disaggregated estimates. Within this framework, these Guidelines offer methodological and practical guidance for the production of direct and indirect disaggregated estimates of SDG indicators having surveys as their main or preferred data source. Furthermore, the publication provides tools to assess the accuracy of these estimates and presents strategies for the improvement of output quality, including Small Area Estimation methods.
This report is the presentation of the methodology applied in Italy to spatially disaggregate the computation of the level of water stress from the national to the subnational scale (SDG indicator 6.4.2). Compared to the national assessment, which results in a low level of water stress in the country, the spatial disaggregation of the indicator by the hydrological unit highlighted the presence of basins affected by water stress exceeding 60 per cent (district of the Po river basin). The analysis was performed considering the long-term average of the available fresh water resources calculated on different reference periods (1951-2020, 1961-90, 1991-2020), and this put in evidence the impact of climate change on the level of water stress. This report is part of the series SDG 6.4 MONITORING SUSTAINABLE USE OF WATER RESOURCES PAPERS that collects all the achievements on SDG 6.4. The study was implemented by the Italian Institute for Environmental Protection and Research (ISPRA), responsible for the model and data used to assess the total renewable freshwater resources, and the Italian National Institute of Statistics (ISTAT), which has provided the methodology and the official statistics related to water withdrawals by economic sector (Agriculture, Services, and Industry). The study is the outcome of an agreement between FAO and ISPRA under the Integrated Monitoring Initiative for SDG 6 (IMI-SDG6), designed to produce a map of Italy showing the SDG indicator 6.4.2 “Level of water stress: freshwater withdrawal as a proportion of available freshwater resources” disaggregated at river basin district level. To learn more about the Integrated Monitoring Initiative for SDG 6, visit www.sdg6monitoring.org.
This volume is intended to expand the dialogue and interest among both practitioners and academicians in a problem area worthy of attention by all. The concept of disaggregation admits to our current inability to solve many types of interrelated hierarchical problems simultaneously. It offers instead a sequential, iterative process as a workable and necessary procedure. The papers in this volume are selected from those presented at a Disaggregation Conference held in March, 1977 at The Ohio State University. We heartily applaud all those who participated in the conference and particularly appreci ate the cooperation of those authors whose work is published in this collection. Part A contains four papers which define the various dimensions of disaggregation. The paper by Martin Starr, which was the text of his luncheon address at the conference, provides several interesting perspectives to the problem. Although disaggregation suggests tear ing apart, as Professor Starr illustrates with his butterfly example, it also suggests a putting together or a synthesis which recognizes interrelationships and dependencies. The next paper by Lee Kra jewski and Larry Ritzman offers a general model of disaggregation for both the manufacturing and service sectors. After reading the papers in this section, as well as the papers in subsequent sections, you will identify other dimensions to hierarchical decision making which go beyond this generalized model.
Stochastic hydrology is an essential base of water resources systems analysis, due to the inherent randomness of the input, and consequently of the results. These results have to be incorporated in a decision-making process regarding the planning and management of water systems. It is through this application that stochastic hydrology finds its true meaning, otherwise it becomes merely an academic exercise. A set of well known specialists from both stochastic hydrology and water resources systems present a synthesis of the actual knowledge currently used in real-world planning and management. The book is intended for both practitioners and researchers who are willing to apply advanced approaches for incorporating hydrological randomness and uncertainty into the simulation and optimization of water resources systems. (abstract) Stochastic hydrology is a basic tool for water resources systems analysis, due to inherent randomness of the hydrologic cycle. This book contains actual techniques in use for water resources planning and management, incorporating randomness into the decision making process. Optimization and simulation, the classical systems-analysis technologies, are revisited under up-to-date statistical hydrology findings backed by real world applications.
This implementation guide has been prepared for users of the WHO Functioning and Disability Disaggregation (FDD11) Tool. It introduces the tool and its goals and provides a straightforward question-byquestion guide for the implementation of the questionnaire.