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Ethiopia

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    Regional borders in Ethiopia Data source: GADM version 1.0, March 2009

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    There is an increasing interest of acquiring farmland abroad, especially following the food price crisis in 2007/08. East Africa is a hotspot of activities, and given the high prevalence of poor people in the area, impacts on rural livelihoods are expected to be substantial. Following significant primary data collection in Ethiopia and Uganda, the study analyses the impact of two such large-scale land acquisitions on the rural economy and the local population’s livelihood, using Theory-based Impact Evaluations (Hemmer 2011) within an analytical framework of layered social analysis (Williamson 2000). Impact is assumed to manifest through five major channels: land, labour, natural resources, technological & organisational innovation and institutional change. The study consists of five chapters: The introduction surveys the global trend, reviews existing evidence and relevant theory to elaborate a conceptual and an analytical framework for the research. The second chapter takes stock of trend and types of large-scale land acquisitions in Eastern Africa, using national official data from Ethiopia and Uganda. While there is a clear increase in number of land transactions, media reports are only confirmed in a small fraction. Investors are coming from Europe, the Arabic peninsula as well as other emerging economies in the global South (South Africa and India, specifically). However, a surprisingly large number of acquisitions is done by domestic investors. The third chapter analyses the early stage impact of a large scale land acquisition in the far western lowlands of Ethiopia. A Saudi-Ethiopian investor tries to develop 10,000 ha for irrigated rice production. Building on primary household data and qualitative information gathered in the area in 2010, a mathematical programming model is calibrated to quantify likely impacts ex-ante. The investment is found to have poverty reducing potential, mainly due to employment creation and growth of the rural non-farm economy. However, the local population has to bear uncompensated costs of lost forestland and local inequalities are likely to widen in consequence of unequal participation on employment and business opportunities. The fourth chapter examines a forty year old large-scale investment in Uganda to understand long-term impacts, especially regarding technological and organisational innovation, as well as institutional change. Using an institutional economic analysis, changes at the organisational structure of the investment can be related to broader changes in the surrounding rural economy, indicating the significant impact a LSLAs can have on rural transformation. Again, the investment has overall contributed to poverty reduction, but organisational flaws and the collapse of a contract farming scheme indicate the difficulties to govern the large farm well. The emergence of a land market for wetlands, adoption of rice as a new crop and organisational improvements among smallholders can be considered as major outcomes of the investment’s activities. The fifth chapter synthesises the early three empirical chapters and locates the findings within a broader set of trends regarding the commercialisation of the agri-food system, the discussion on optimal farm size for production and poverty reduction, and the importance of functioning land and labour markets for poverty reduction and rural transformation in developing economies.

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    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

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    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.

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    The potential of different business approaches to reduce poverty and marginality depends on the characteristics of different regions and people living in these regions. Here, (a) population density, (b) accessibility, e.g. in terms of mobile phone, internet and road connections, as well as (c) the predominant form of livelihood and/or farming systems may be important factors determining market sizes and transaction costs and thus incentives to invest in these markets. This map is an overlay of these different indicators. Greenish colors show irrigated or perennial areas, brownish colors pastoralist, agro-pastoralist and arid areas and reddish colors indicate areas dominated by different other farming patterns. The lighter the color the lower the population and road density. For the classification of population and connectivity values being ‘high’ or ‘low’ the national mean value is used as threshold. Data: Population density: CIESIN (2011) Connectivity: CSA et al. (2008) Farming systems: HarvestChoice (2001)

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    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

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    In four kebeles (smalles administrative unit in Ethiopia: Bonda Megela, Gaba, Wabo, Wangene) in Oromia district gender-disaggregated focus group discussions on socio-economic aspects of farming communities were conducted. Aspects have been the institutional network of the village (with the help of the Venn Diagram tool, income and livelihood sources (with land, without land, with irrigation, without irrigation) with a focus on cash and food crops and vegetable production, market access, marketing structure and prices, land titles and inheritance arrangements, role of extension services, access to credit, contractfarming and future plans of children. Discussions were part of the NutriHAF project, which aims at diversifying diets and livelihoods through the promotion of multi-storey cropping in biosphere hotspots in Ethiopia and Madagascar.

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    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

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    The persistence of poverty in some parts of the society across the globe inspired recent studies in development economics to embrace the use of multidisciplinary tools and concepts to better understand the situation of the poor. This thesis employs one of the recent conceptual tools, the aspirations-failure framework, which links the situation of the poor and their (under)investment behavior to aspirations failure. Based on individual and household level data collected from a sample of farm households in rural Ethiopia, the thesis first econometrically examines the effect of social interactions on aspirations (with respect to income, wealth, social status and education). The findings are in line with the theory which suggests that aspirations are socially determined through observations and social interactions. In particular, results indicate that social network size is an important determinant of aspirations and especially that of women’s, attesting to the importance of widening the ‘aspirations window’ – a person’s cognitive world that shapes their aspirations. One of the channels in which aspirations may affect behavior is through their effect on risk aversion. The thesis finds that the ‘aspirations-gap’ (AG) – the difference between the aspired and present status – indeed relaxes risk aversion, and the association is non-linear. Results also indicate that the effect of AG on risk preferences is stronger for women. Social interactions may also enhance diffusion of innovations and productivity. Based on social networks data collected using ‘random matching within sample’ procedure, the thesis identifies strong evidence of network externalities in the adoption of row-planting and also in farm productivity. The novelty of the thesis is also the identification of aspirations (or AG) as one of the key determinants of farmer innovativeness or the adoption of innovation products such as chemical fertilizers. The main goal of the thesis is ultimately to try to understand the implications of aspirations by examining their interactions not only with the underlying drivers of well-being (such as the adoption of agricultural innovations and risk behavior) but also their interactions with the well-being outcomes themselves. The thesis uses various outcome indicators including income and consumption expenditure, various triangulating measures of food security, and subjective well-being defined in terms of life satisfaction and happiness. In nearly all outcome indicators, the thesis finds suggestive evidence that aspirations are important predictors of household well-being in rural Ethiopia. The overall findings of the thesis clearly demonstrate that beyond the resource-related deprivations, low aspirations also play a role in rural households’ decision-making in Ethiopia, with consequences on well-being outcomes. Targeting the determinants of aspirations may therefore be a useful policy strategy.

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    Degree of socio-economic marginality in Ethiopia, using the following conditional indicators of the economic sector: 1. Regional poverty headcount indices (% of population whose income/consumption is below the poverty line = 3781 birr) 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) 3. Wealth index (% of population being part of the lowest/2.lowest wealth quintile) Data source: 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 3. Central Statistical Agency(CSA), ICF International (2012): Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia; Calverton, USA