From 1 - 10 / 16
  • Given that marginality is a complex and multifaceted phenomenon, we included a broad set of variables covering ecological, social, and economic dimensions of human well-being in the focus regions. These “marginality dimensions” were based on the “spheres of life” defined in Gatzweiler et al. (2011, 13), including: “Economy”; “Quality of life”; “Landscape design and infrastructure”; “Ecosystems, natural resources, and climate”; “Public domain and institutions”; and “Demography.” For the purpose of this mapping exercise, single indicators were used to represent each of the spheres. Here the spheres “Landscape design, land use, and location” and “Infrastructure” are both captured by the single indicator “accessibility”, and the sphere “Behavior and quality of life” is represented by stunting. For each dimension a cut-off point along a range of indicator values was used to define the threshold below which an area was considered to be marginal. Indicator layers for each of the different dimensions of marginality were overlaid to find the areas where multiple layers of marginality overlap. We defined a ‘marginality hotspot’ as an area in which at least three dimensions of marginality overlapped. The maps were based on national and sub-national data published by the World Bank, the Food and Agriculture Organization of the United Nations (FAO), Harvest Choice, and others. Method and results are described in detail in the following publication: https://link.springer.com/chapter/10.1007/978-94-007-7061-4_5/fulltext.html

  • Categories  

    Degree of socio-economic marginality in Ethiopia, using the following positional indicators of the education sector: 1. Access to education (no. of primary schools related to population density) 2. Access to information (% of households without radio) 3. Access to information (% of households without television) Data source: 1. Central Statistical Agency (CSA), Ethiopian Development Research Institute (EDRI), International Food Policy Research Institute (IFPRI) (2006): Atlas of the Ethiopian Rural Economy. Washington DC, USA. 2./3. Central Statistical Agency (CSA) (2007): Population and Housing Census. Atlas of Ethiopia 2007. Washington DC, USA

  • Categories    

    In a randomized field experiment action- and outcome-based payments for environmental services (PES) were examined. The main aim of the study was to investigate the effect of the outcome-based contracts in conservation auctions, and to prove the theoretical prediction on their improved environmental performance. In addition, the study examined gendered behavior. The data sheet contains data from the (i) baseline survey, (ii) experimental auction, (iii) environmental performance (tree survival) and tree watering monitoring, and (iv) evaluation survey. (i) All households at both right and left riverbanks of the Kapingazi River, in the demarcated research sites, were targeted for the study. In total 427 households received invitation to participate in our study, out of which 411 provided data for an extensive baseline survey. Aiming at a gender-balanced study, a random draw was used to determine whether a male or female household representative is to be approached. (ii) The auctions took place on December 14, 2011. In total, 234 landholders participated in the conservation auctions. The participants were stratified upon income level and gender, and from each stratum the farmers were randomly assigned to one of the two treatments - either the auction for action- or outcome-based contracts. The total budget for both auctions was approximately 1,770,000 KES (around 20,000 US$) while aiming at an equal number of contracts for each treatment. Consequently, 60 contracts in each of the two auctions could be offered. Due to number of farmers opting for a drop-out, 44 action-based and 54 outcome-based contracts were finally signed. The conservation contracts requested to plant 30 indigenous trees on the riparian area, without any further limitations on the land use. In the action-based contract the payments were conditional on finding the soil around the trees to have sufficient levels of soil moisture at the time of monitoring. Under the outcome-based contracts the payments depended on the tree survival after the six-month period, independently of the actions taken. (iii) During the contract period, the landholders with action-based contracts were monitored twice on the compliance with the tree-watering requirement. Farmers with the outcome-based contracts were monitored on the tree survivals at the end of the contract period, in June 2012. At the same time, tree survival rates of the action-based PES scheme were recorded for the research purpose. (iv) The conservation payments were awarded in July 2012, and subsequently an evaluation survey with the contract holders was conducted.

  • Categories  

    Degree of socio-economic marginality in Ethiopia, using the following economic, health and educational positional indicators: 1. Economy 1.1 Access to markets (travel time to next city > 50.000 capitals) 1.2 Transportation infrastructure (average all-weather road density m/km2) 1.3 Information infrastructure (% of households without telephone) 2. Health: 2.1 Access to education (no. of primary schools related to population density) 2.2 Access to information (% of households without radio) 2.3 Access to information (% of households without television) 3. Education: 3.1 Access to education (no. of primary schools related to population density) 3.2 Access to information (% of households without radio) 3.3 Access to information (% of households without television) Data source: 1.1/1.2/1.3/2.2/2.3/3.2/3.3: Central Statistical Agency (CSA) (2007): Population and Housing Census. Atlas of Ethiopia 2007. Washington DC, USA 2.1/3.1 Central Statistical Agency (CSA), Ethiopian Development Research Institute (EDRI), International Food Policy Research Institute (IFPRI) (2006): Atlas of the Ethiopian Rural Economy. Washington DC, USA

  • Categories  

    Data on investment licenses from Ethiopia's Licensing office in Addis Abeba (Feb 2011). For each investment, country of origin, requested land size, some information on planned production, as well as employment and capital is contained (N=2814). Data quality: This data-set was received from the Ethiopian Investment Authority during a field visit in 2011. It contains data from investors that invested in the agricultural sector and requested some land. Unfortunately the land size information was very noisy (Units not clearly specified and missing values). Some land was requested in ha, some in sq.m. Processing: The data set attached was filtered based on size-capital assumptions, leaving out those investments that are purely processing (less land intensive). A cut-off point of 100 ha was chosen and 2814 observations for the period 1992 to Dec 2010 remained. This data set was used for Baumgartner (2012) Large-scale investments in Ethiopia, in (eds.) Allan et al.: Handbook of Land and Water Grabs in Africa, Routledge; and in Baumgartner et al. (2015) Poverty impacts of Large-scale land acquisitions, WDev.

  • Categories  

    Degree of socio-economic marginality in areas with capabilitiy gaps Socio-economic marginality: Socio-economic marginality in Ethiopia was defined by the following economic, health and educational conditional indicators: 1. Economy: 1.1 Regional poverty headcount indices (% of population whose income/consumption is below the poverty line = 3781 birr) 1.2 Food poverty headcount indices (% of population whose income/consumption for food is below the cost of 2.200 kcal/day per adult food consumption) 1.3 Wealth index (% of population being part of the lowest/2.lowest wealth quintile) 2. Health: 2.1 Child mortality rate (no. of deaths out of 1000 live births <5 years) 2.2 Nutritional status of children (% of children <5 years being stunted) 2.3 Nutritional status of adults (% of men/women age 15-49 with BMI <18.5 = acute under nutrition) 3. Education: 3.1 Illiteracy rate (% of population not being able to read/write in their native language) 3.2 Net enrolment ratio primary school 3.3 Net enrolement ratio high school Data source: 1.1/1.2: Ministry of Finance and Economy Development (2012): Ethiopia‘s Progress Towards Eradicating Poverty: An Interim Report on Poverty Analysis Study (2010/11). Addis Ababa, Ethiopia 1.3/2.1/2.2/2.3: Central Statistical Agency(CSA), ICF International (2012): Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia; Calverton, USA Capability gap: Areas with good agro-ecological suitability, but limited socio-economic capabilities of farmers to make use of this suitability. Agro-ecological suitability in Ethiopia was defined from the raster data set of agro-ecological suitability for rainfed crops (Fischer et al. 2002) Data source: Fischer et al. (2002): Global Agro-ecological Assessment for Agriculture in the 21st Century: Methodology and Results. International Institute for Applied Systems Analysis, Laxenburg, Austria The socio-economic capabilities of farmers were defined by the following indicators: 1. Access to technology (% of holders applying inorganic fertilizer to any crop during Meher season) 2. Access to credit (% of holders utilizing credit services) 3. Access to knowledge (% of holders utilizing advisory services) Data source: Central Statistical Agency (CSA) (2002): Ethiopian Agricultural Sample Enumeration. Addis Ababa, Ethiopia

  • Categories  

    Capability gap in Ethiopia: difference between conditional and positional marginality classes of the agro-ecological dimension. Classes in blue define capability gaps, where agro-ecological suitability is good while socio-economic conditions of farmers are poor in these areas. Classes in orange/red show areas in which socio-economic possibilities of farmers are good, while agro-ecological suitability is poor. Conditional marginality classes where defined from the raster data set of agro-ecological suitability for rainfed crops (Fischer et al. 2002) Data source: Fischer et al. (2002): Global Agro-ecological Assessment for Agriculture in the 21st Century: Methodology and Results. International Institute for Applied Systems Analysis, Laxenburg, Austria Positional marginality classes where defined by socio-economic capabilities of farmers: 1. Access to technology (% of holders applying inorganic fertilizer to any crop during Meher season) 2. Access to credit (% of holders utilizing credit services) 3. Access to knowledge (% of holders utilizing advisory services) Data source: Central Statistics Agency (CSA) (2002): Ethiopian Agricultural Sample Enumeration. Addis Ababa, Ethiopia

  • Categories    

    The data included were collected from three villages of Chongqing, China in 2011. Topics related to land rental market participation were the theme of survey.

  • Categories  

    MODIS provides the Land Cover Type Product MCD12Q1 (Friedl et al., 2002) with 500m grid resolution which represents the same pixel size also used for the MODIS NDVI time-series analysis. Annually data provision and a matching pixel size with the MODIS NDVI data used earlier in this study were key elements for choosing this dataset. The Map shows the number of LULC changes as calculated based on the methods described in chapter II.3.3. Stable areas – where land cover changes are zero – can be identified in southern Kenya, Kajiado County in particular, but also in western Kenya north of Lake Victoria, around Lake Turkana, and in the northeastern part of Kenya bordering Ethiopia. Around 33.16% of the total land area experience zero changes from 2001-2011 while 16.11% changed once and 22.92% show two changes. Three (13.98%), four (9.53%) and five (3.42%) changes can still be observed in Map III.11 while areas experiencing more than five changes are occurring in less than 1% of the total land area. The different classes show the number of land cover changes within the observation period.

  • Categories  

    Household survey (N=121) of local communities surrounding one large-scale land acquisition. Data on household composition, land cultivation, labour market participation, source of food & income. Stratified random sampling at village level (kebele), representating about 1600 hhs and 8000 people surrounding the investement (35km radius). Data collected in Feb 2011, following survey testing and prior qualitative research. Two ethnic groups (Anyuak and Highlander settler from Derg time). Used in Baumgartner et. al. (2015) Impacts of Large-Scale Land Acquisitions in Ethiopia (WDev.). Data set was collected during villagisation programme of Ethiopian government. Only one settlement affected.