Data collected from sources other than surveys and censuses are used extensively by the statistical offices of developed countries. Such data can maximize the consistency of published cross-sector figures and help to align survey data with information from non-statistical sources.
This Technical Report on “Linking Area and List Frames in Agricultural Surveys” is the result of a comprehensive literature review on the subject and further methodological developments. The Report introduces and discusses the problem of improving the quality of agricultural statistics by exploring methods to maximize the use of available frames, focusing on how to combine information from area frames and list frames in agricultural surveys.
The aim of this technical report on “Spatial Disaggregation and Small-Area Estimation Methods for Agricultural Surveys: Solutions and Perspectives” is to enhance disaggregation methods for adaptation to various agricultural situations and datasets.
This present report is a review of relevant literature, which includes publications manuals, methodologies and guidelines on estimating post-harvest losses of the Food and Agriculture Organization of the United Nations (FAO), as well as publications by other institutions, international organizations and relevant country experiences on estimating post-harvest losses.
The Global Strategy to Improve Agriculture and Rural Statistics was adopted by the United Nations Statistical Commission in 2010 with the objective to improve statistics in agriculture, livestock, aquaculture, small-scale fisheries and forestry production in developing countries and ensure that they are maintained over time. One of the key components of the Global Action Plan is its research plan, which has as one of its priorities “improving the methodology for using administrative data in agricultural statistics” (World Bank, FAO and United Nations 2010).
The System of Environmental-Economic Accounting for Agriculture, Forestry and Fisheries (SEEA Agriculture) was developed as part of the Global Strategy to Improve Agricultural and Rural Statistics (the Global Strategy). The SEEA Agriculture is a conceptual framework that enables national and international statistical systems to access the data needed for decision-making: it combines the economic and environmental dimensions of agriculture, forestry, fisheries, land use, water use and other environmental factors with the conventional treatment of agricultural, forestry and fisheries production.
These Guidelines describe a method that can be employed to accurately capture the actual contribution of small-scale fisheries and aquaculture to rural communities. In principle, the basic structure of these survey stages follows the concepts adopted by the World Census of Agriculture, including the modular approach, to enhance utility and reduce implementation costs.
The growing demand by policymakers and decision makers for statistics based on information that is interlinked in economic, social, and environmental aspects requires the large-scale expansion of national efforts to implement statistical surveys, in terms of organization and budget. Therefore, the collection of data by integrating information from different sources is becoming a crucial requirement for the production of statistics.
This Technical Report on Improving the Use of GPS, GIS and Remote Sensing in Setting Up Master Sampling Frames is the result of a comprehensive literature review on the subject, followed by a gap analysis and a development of innovative methodological proposals for addressing the various issues that arise.
A Manual to address Data Requirements for Developing Countries
This manual helps practitioners in developing countries understand the international methodologies for reporting emissions from agriculture, and provides them with a tool to better identify, build and access the minimum set of activity data needed for GHG estimation.
This technical report on Developing More Efficient and Accurate Methods for the Use of Remote Sensing is the result of a comprehensive literature review on the subject, followed by a gap analysis and, finally, the development of innovative methodological proposals for addressing the various issues arising.
This Guide presents a set of operational tools, methods and good practices that are the result of a long process, taking advantage of knowledge from country experiences and existing material developed by the World Bank and PARIS21 on household survey microdata, within the International Household Survey Network.