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The energy consumption in Ethiopia is based mainly (90%) on the traditional use of biomass for domestic needs, mostly using rudimentary cooking stoves. Against this background, the present study examines the importance of biomass for energy use of rural households and analyzes the long-term energy security. To this end, a farm household model is developed to investigate the association between the use of biomass for energy and food security. The study explores the effects of fuelwood shortages on the livelihood of the people through an examination of the decisions of households on the use of family labour and expenditures on food and energy. For this purpose, the study uses a panel dataset of Ethiopian households. Due to the endogeneity of shadow wages and prices and to selectivity biases a Fixed Effect Two-Stage Least Squares model is used with an “inverse Mills ratios” for wages, and food and energy expenditures. In addition, a Seemingly Unrelated Regression Analysis and Almost Ideal Demand System are used respectively to estimate the allocation of labour to agriculture, fuelwood collection and off-farm activities jointly. Discrete household energy choice decisions are estimated using a multinomial logit model with predicted wages and other determinants. Shadow prices of fuelwood and agricultural fuels were estimated based on their respective shadow wages and per unit labour hours expended in order to procure the respective energy sources. Furthermore, an Ordinary Least Squares and Tobit model were used to estimate the household demand for fuelwood, and charcoal and agricultural fuels respectively. A dynamic long-term model for the energy sector in Ethiopia is used to investigate the development of renewable energy for a cost-effective energy diversification at the national level. Finally, the suitability of institutional arrangements and collective actions for decentralized energy generation for remote communities are evaluated. The regression results show that fuelwood shortage or a decrease in the shadow wage for fuelwood collecting labour have negative effects on the allocation of labour on the agriculture, and a decrease in energy and food per capita expenditure. At the same time higher wages in agriculture have negative effects on the allocation of labour to the collection of fuelwood. An increase in fuelwood shortage was associated with in an increase in labour expended on fuelwood collection. The allocation of labour to the collection of fuelwood has a negative self–reward effect with an increase in shortage of fuelwood. A greater scarcity of fuelwood associated with the increase in purchase of biomass energy. An increase in the opportunity cost of fuelwood is associated with a decline in the use of this fuel with an own-price elasticity of -0.38. These evidences suggest that fuelwood shortage has negative effects on the welfare of households. Agricultural fuels and kerosene are not substitutes for fuelwood, which conforms to results of previous studies. The wealth of households, access to electricity, population density have the expected effect on the use of biomass. The energy use of households conforms to the concept of 'energy stacking' or, multiple fuel utilization'. However, access to modern forms of energy and economic growth play a central role in such a transition. Concerted policies are needed to help to improve the standard of living and the entrepreneurial skills of household. Furthermore, model results indicate that hydro-electric power will dominate the energy mix of the country without intervention in technological progress and innovations to improve efficiency. In the long term, however, it is predicted that droughts affect the reliability of this source of energy and the cost of energy will push up. To cope with these effects of drought in the hydro-electric sector in Ethiopia, Ethiopia needs to invest in the development of renewable energy resources more. This would improve both sustainability and resilience, but also increase production costs. Innovations to improve the technology and the efficiency of obtaining alternative energy, especially solar energy, increase diversity of energy sources, and reduce production costs and shadow prices and resource scarcity. Such innovations are therefore keys to reduce the risk of droughts and to improve the energy security and thus serve as an engine of economic growth. The results of a cost-benefit analysis for the development of biogas suggest that subsidies for large decentralized biogas plants could achieve higher profits than small biogas plants for households. Specific policy measures should improve energy efficiency and substitution and technical performance, tangible incentives such as capital subsidies and feed-in tariffs, ensure the availability of microcredit for the development of renewable energy and include rural households in local, smart grids.
Household Surveys performed in four villages selected from Oromia, Amhara and Southern Nations, Nationalities, and Peoples’ Region (SNNPR) following from the ‘Ethiopian Rural Household Survey’ (ERHS) conducted in 2004.It contains detailed data on household consumption and expenditures, assets, income, agricultural activities, land allocation, demographic characteristics, and other variables. From September 2011 to January 2012 another survey of 221 households was conducted in three major regions of central and southern Ethiopia. At the time of this latest survey effort the most recent ERHS survey data available was from 2004. The selection of respondents, determination of sample size, and apportionment of the sample were based on a proportional sampling technique.In addition to addressing important questions from the ERHS survey data, the field survey was designed to generate detailed information on household biomass energy production and consumption practices; as well as farming activities; labour and land allocation; economic and demographic characteristics; and expenditures on food, non-food items, and energy. The 2011 survey effort collected detailed household biomass energy use data. The measurement of household biomass energy use was obtained in traditional units and later converted into kilograms. The conversion factors for each of the biomass were collected from the closest urban centre of each of the study areas. Information obtained on household biomass energy use was collected for a time period of one week before the survey was conducted. It was then aggregated into annual figures, although household biomass energy use may vary seasonally.