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  • Updated 7 February 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    Since 2014, UNHCR has undertaken a comprehensive revision of the framework for monitoring UNHCR Livelihoods and Economic Inclusion programs. Since 2017, mobile data collection (survey) tools have been rolled out globally, including in Guinea. The participating operations conducted a household survey to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline (211 observations) and endline data (139 observations) from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact. Empty values can occur for several reasons (e.g. no occurrence of agricultural interventions among the beneficiaries will result in empty variables for the agricultural module).
  • Updated 7 February 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    Since 2014, UNHCR has undertaken a comprehensive revision of the framework for monitoring UNHCR Livelihoods and Economic Inclusion programs. Since 2017, mobile data collection (survey) tools have been rolled out globally, including in Ghana. The participating operations conducted a household survey to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline (142 observations) and endline data (130 observations) from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact.
  • Updated 7 February 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    Since 2014, UNHCR has undertaken a comprehensive revision of the framework for monitoring UNHCR Livelihoods and Economic Inclusion programs. Since 2017, mobile data collection (survey) tools have been rolled out globally, including in Burkina Faso. The participating operations conducted a household survey to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of endline (100 observations) data, empty variables might refer to questions which were not relevant for this survey (e.g. baseline questions).
  • Updated 7 February 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    Since 2014, UNHCR has undertaken a comprehensive revision of the framework for monitoring UNHCR Livelihoods and Economic Inclusion programs. Since 2017, mobile data collection (survey) tools have been rolled out globally, including in Somalia. The participating operations conducted a household survey to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline (236 observations) and endline data (201 observations) from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact.
  • Updated 7 February 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    Since 2014, UNHCR has undertaken a comprehensive revision of the framework for monitoring UNHCR Livelihoods and Economic Inclusion programs. Since 2017, mobile data collection (survey) tools have been rolled out globally, including in Kenya. The participating operations conducted a household survey to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline (115 observations) and endline data (105 observations) from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact.
  • Updated 7 February 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    Since 2014, UNHCR has undertaken a comprehensive revision of the framework for monitoring UNHCR Livelihoods and Economic Inclusion programs. Since 2017, mobile data collection (survey) tools have been rolled out globally, including in Chad. The participating operations conducted a household survey to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline (331 observations) and endline data (308 observations) from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact.
  • Updated 7 February 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    Since 2014, UNHCR has undertaken a comprehensive revision of the framework for monitoring UNHCR Livelihoods and Economic Inclusion programs. Since 2017, mobile data collection (survey) tools have been rolled out globally, including in Argentina. The participating operations conducted a household survey to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline (21 observations) and endline data (6 observations) from the same sample beneficiaries.
  • Updated 7 February 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    Since 2014, UNHCR has undertaken a comprehensive revision of the framework for monitoring UNHCR Livelihoods and Economic Inclusion programs. Since 2017, mobile data collection (survey) tools have been rolled out globally, including in Ethiopia. The participating operations conducted a household survey to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of endline (147 observations) data.
  • 100+ Downloads
    Updated 5 August 2020 | Dataset date: January 01, 2020-January 01, 2020
    This dataset updates: Every six months
    IRC’s GIS unit created this database to allow for a more sustained approach to producing relevant mapping products and geospatial analysis for regions undergoing emergencies, and will fill gaps in information sharing and management between OFDA, IRC, and other implementing partners during emergency response. IRC’s GIS services provide OFDA/Ethiopia with the information and analysis required to monitor the evolution of project / program results and to track project and program impacts across implementing agencies and geographic locations. This dataset contains boundaries of Ethiopian administrative Woredas which are roughly consistent with the actual administrative boundaries for the year 2019. The Woreda boundary contains attribute data (implementing Partners, Situation and Sector Fields)for Hotspot woredas in the nation by the different sectors as of 30 June 2020.
  • 100+ Downloads
    Updated 14 May 2020 | Dataset date: January 31, 2020-January 31, 2020
    This dataset updates: Every six months
    Hotspot Woredas in Ethiopia for Nutrition, Health, Agriculture, Market, Water, Education, Protections/GBV and Over all hotspot classifications by Priorities Jan 2020 Updates
  • 70+ Downloads
    Updated 10 April 2020 | Dataset date: February 26, 2020-February 26, 2020
    This dataset updates: Every month
    Agriculture cluster partner operational presence to the administrative boundary 3 (Woreda) level. The datasets cover partner operational presence by woreda Level (Admin 3) in all five crisis affected regions which are Afar, Amhara, Oromia, SNNPR and Somali.
  • 100+ Downloads
    Updated 18 July 2019 | Dataset date: June 30, 2019-June 30, 2019
    This dataset updates: As needed
    Using 10m resolution multispectral imagery from the Sentinel-2A satellite, a relativized burn ratio (RBR) was calculated and used for burned land classification to assess and quantify areas which have been burned between 4 May and 30 June 2019 in the governorates of Al-Hasakeh, Deir-ez-Zor, Ar-Raqqa, Aleppo, Idleb and Northern Hama. The before and after images are composites ranging from 6 April to 3 May 2019 and 27 to 30 June 2019.
  • 700+ Downloads
    Updated 16 March 2019 | Dataset date: February 05, 2018-February 05, 2018
    This dataset updates: Never
    The AFDB Statistical Data Portal has been developed in response to the increasing demand for statistical data and indicators relating to African Countries. The Portal provides multiple customized tools to gather indicators, analyze them, and export them into multiple formats. With the Data Portal, you can visualize Socio-Economic indicators over a period of time, gain access to presentation-ready graphics and perform comprehensive analysis on a Country and Regional level
  • 100+ Downloads
    Updated 10 December 2018 | Dataset date: January 02, 2013-December 31, 2017
    This dataset updates: Never
    Value of Purchased Agricultural Inputs, 2013-2017
  • 100+ Downloads
    Updated 10 December 2018 | Dataset date: January 02, 2013-December 31, 2017
    This dataset updates: Never
    Recorded Marketed Agricultural Production at Current Prices, 2013-2017
  • 100+ Downloads
    Updated 10 December 2018 | Dataset date: January 02, 2013-December 31, 2017
    This dataset updates: Never
    The dataset shows the aggregate value of sales of agricultural produce from large and small farms for the last five years. Total value of sales increased by 8.2 per cent from KSh 413.2 billion in 2016 to KSh 446.9 billion in 2017. The value of output from small farms increased by 8.2 per cent from KSh 301.7 billion in 2016 to KSh 326.3 billion in 2017. Sales from large farms similarly increased from KSh 111.6 billion in 2016 to KSh 120.7 billion in 2017. The share of sales from small farms to total marketed production remained the same at 73.0 per cent in 2017.
  • 100+ Downloads
    Updated 10 December 2018 | Dataset date: January 02, 2013-December 31, 2017
    This dataset updates: Never
    The dataset details the average gross commodity prices paid to farmers for various commodities for the period 2013 to 2017. Tea prices increased by 23.9 per cent from KSh 24,732.35 per 100 kilogram in 2016 to KSh 30,652.18 per 100 kilogram in 2017. Coffee prices paid to farmers improved by 16.5 per cent from KSh 40,815.54 per 100 kilogram in 2016 to KSh 47,547.71 per 100 kilogram in 2017. Favourable prices were also realized for maize, sugarcane, milk, beef and pork.
  • 1500+ Downloads
    Updated 4 December 2018 | Dataset date: October 01, 1998-October 01, 2018
    This dataset updates: Every year
    Biomass Production (in tonnes) for Admin 2 Level. Source: 10-day images of Dry Matter Productivity (DMP) from Proba V Satellite. Data processed by Flemish Institute of Technology (VITO) through the Copernicus Global Land Service.
  • 500+ Downloads
    Updated 15 August 2018 | Dataset date: March 30, 2016-March 30, 2016
    This dataset updates: Every three months
    Hotspot woreda classification is derived using six multisector indicators, including agriculture and nutrition, agreed at regional and federal levels. A hotspot matrix is often used as a proxy for the acute Integrated Phase Food Security Classification (IPC) and is indicative of food security and nutrition status. Hotspot woredas require urgent humanitarian response.
  • 400+ Downloads
    Updated 16 August 2016 | Dataset date: June 01, 2016-December 31, 2016
    This dataset updates: Every three months
    List of projects being developed currently in Haiti in the context of the drought response. The data of this document was collected only for 4 towns, that are considered to be in IPC phase 3 by the National coordination of Food Security (CNSA) The dataset contains the list of projects organized by sectors: Food Security, Agriculture, Nutrition and WASH. The document also contains the estimated populations in need by commune and sector. The caseload for the nutrition projects corresponds only to children under five years old. An analysis document developed with this data is available at: https://goo.gl/NBHRZI
  • 300+ Downloads
    Updated 12 April 2016 | Dataset date: April 12, 2016-April 12, 2016
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on April 12, 2016. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: EA201304_ML1 Most likely food security outcome for January-March 2016 EA201304_ML2 Most likely food security outcome for April-June 2016 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 50+ Downloads
    Updated 14 October 2015 | Dataset date: September 30, 2015-September 30, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on September 30, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: westafrica201304_ML1 Most likely food security outcome for July-September 2015 westafrica201304_ML2 Most likely food security outcome for October-December 2015 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated 14 October 2015 | Dataset date: October 01, 2013-October 01, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa. It was last updated on November 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: xx201304_ML1 Most likely food security outcome for October-December 2013 xx201304_ML2 Most likely food security outcome for January-March 2014 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)