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IFPRI HarvestChoice Dataverse (International Food Policy Research Institute (IFPRI))
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HarvestChoice generates knowledge products to help guide strategic decisions to improve the well-being of the poor in sub-Saharan Africa through more productive and profitable farming. To this end, HarvestChoice has developed and continues to expand upon a spatially explicit, landscape level evaluation framework. HarvestChoice’s evolving list of knowledge products includes maps, datasets, working papers, country briefs, user-oriented tools, and spatial and economic models designed to target the needs of investors, policymakers, and research analysts who are working to improve the food supply of the world's poor http://harvestchoice.org.
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1 to 10 of 21 Results
Nov 16, 2018
International Food Policy Research Institute (IFPRI), 2018, "Ghana Feed the Future Harmonized Dataset", https://doi.org/10.7910/DVN/DXMARV, Harvard Dataverse, V3, UNF:6:U5L6MtwnE/NhiNqdEo2hOg== [fileUNF]
This dataset was created by re-compiling available open, gender/sex-disaggregated Feed the Future data for Ghana and applying standard processing methods to enhance their accessibility and interoperability. This process entailed the standardization of variable names and labels, t...
Dec 5, 2017
HarvestChoice, International Food Policy Research Institute (IFPRI);University of Minnesota, 2017, "CELL5M: A Multidisciplinary Geospatial Database for Africa South of the Sahara", https://doi.org/10.7910/DVN/G4TBLF, Harvard Dataverse, V5
Spatially-explicit data is increasingly becoming available across disciplines, yet they are often limited to a specific domain. In order to use such datasets in a coherent analysis, such as to decide where to target specific types of agricultural investment, there should be an ef...
Dec 5, 2017
International Food Policy Research Institute (IFPRI);International Institute for Applied Systems Analysis (IIASA), 2016, "Global Spatially-Disaggregated Crop Production Statistics Data for 2005 Version 3.2", https://doi.org/10.7910/DVN/DHXBJX, Harvard Dataverse, V9
Using a variety of inputs, IFPRI's Spatial Production Allocation Model (SPAM) uses a cross-entropy approach to make plausible estimates of crop distribution within disaggregated units. Moving the data from coarser units such as countries and sub-national provinces, to finer units...
Sep 27, 2017
International Food Policy Research Institute (IFPRI), 2017, "BIHS Harmonized Dataset", https://doi.org/10.7910/DVN/PUK1P7, Harvard Dataverse, V3, UNF:6:d5u9Yp/+SdhwUO8E9ZfU1Q== [fileUNF]
This dataset is was created by re-compiling available open, gender/sex-disaggregated Feed the Future datasets for Bangladesh and applying standard processing methods to enhance their accessibility and interoperability. This process entailed the standardization of variable names a...
Jul 11, 2017 - International Food Policy Research Institute (IFPRI) Dataverse
Koo, Jawoo;Dimes, John, 2013, "HC27 Generic Soil Profile Database", https://hdl.handle.net/1902.1/20299, Harvard Dataverse, V5
The HC27 soil profile database consists of generic soil profiles developed by John Dimes and Jawoo Koo. The 27 soil profiles were generated based on three criteria that crop models are most responsive to: texture, rooting depth (proxy of water availability), and organic carbon co...
Apr 18, 2017
HarvestChoice, International Food Policy Research Institute, 2017, "Segmentation Data for Nigeria and India States of Bihar, Odisha, and Uttar Pradesh", https://doi.org/10.7910/DVN/K5NSAF, Harvard Dataverse, V2, UNF:6:qgWv6+TKzcJ9f5nf0W2j/w== [fileUNF]
This dataset was compiled by processing and harmonizing multiple secondary datasets, covering Nigeria and three states in India (Bihar, Odisha, and Uttar Pradesh), to help those working in the agricultural development sector identify and characterize groups of smallholder farmers...
Feb 21, 2017
HarvestChoice, International Food Policy Research Institute;International Center for Tropical Agriculture, 2017, "CGIAR Scientometrics Data for 2000-2016", https://doi.org/10.7910/DVN/ZV1JCQ, Harvard Dataverse, V3
This data files includes full metadata records of 12,131 SCI-indexed journal articles authored by CGIAR scientists published between January 2000 to November 2016, retrieved from Web of Science by Thomson Reuters. With this data, co-authorships of research outputs published by CG...
Feb 8, 2017
HarvestChoice, International Food Policy Research Institute;Association for Strengthening Agricultural Research in Eastern and Central Africa, 2017, "Spatial Data for Development Domain Analysis in East and Central Africa", https://doi.org/10.7910/DVN/FB6ZHC, Harvard Dataverse, V1
GIS dataset for constructing three-dimensional Development Domain for ASARECA's operation area in 12 East and Central Africa countries. Data layers of market accessibility, agricultural potential, and population density of 2010 at 5 arc-minute resolution were compiled from Harves...
Jan 11, 2017
HarvestChoice, International Food Policy Research Institute, 2017, "Harmonized Male/Female and Urban/Rural Subnational Expenditure, Poverty, and Inequality Indicators at 2011 PPP $1.90/day and $3.10/day for Africa South of the Sahara", https://doi.org/10.7910/DVN/FSMCTQ, Harvard Dataverse, V1
Subnational poverty headcount ratios were derived from 66 nationally representative household surveys and population census information conducted in various years around 2008 for 26 countries. Our poverty calculations are based on the comparison between the household per-capita c...
Feb 27, 2016
HarvestChoice, International Food Policy Research Institute (IFPRI), 2016, "Replication Data for: Malnutrition and Climate Patterns in the Arid and Semi-arid Lowlands of Kenya: a Resilience Analysis Based on a Pseudo-panel Dataset", https://doi.org/10.7910/DVN/FEAEJ3, Harvard Dataverse, V2, UNF:6:rFgUp/0SJszfJxE/JFkHjA== [fileUNF]
Resilience of food security in the arid and semi-arid lowlands (ASAL) in Kenya, were assessed using repeated cross-sectional data (collected in 1993, 1998, 2003, and 2008). We measure short- and long-term food security in response to changing agro-climatic conditions, using indic...
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