An analysis of net farm income to guide agricultural policies in the Ethiopian highlands

Agriculture & Food Security

Research

C. L. van Beek¹  Mekonnen Tolla²  Melkamu Mamuye³  Eyasu Elias⁴  Yemane Gebremeskel⁵  P. F. Okoth⁶  J. J. Stoorvogel⁷  E. M. A. Smaling⁸  H. I. M. Heesmans⁸  Amha Besufkad⁹ 

[1] Bayer Crop Science, Wageningse Afweg 31, 6702 PD, Wageningen, The Netherlands;College of Agriculture and Environmental Science, Bahir Dar University, P.O. Box 79, Bahir Dar, Ethiopia;College of Agriculture and Veterinary Medicine, Jimma University, P.O. Box 307, Jimma, Ethiopia;College of Natural and Computational Sciences, Centre for Environmental Science, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia;Department of Land Resource Management and Environmental Protection, Mekelle University, P.O. Box 231, Mekelle, Ethiopia;New Scape Agro Systems Ltd, P.O. Box 27303, 00100, Nairobi, Kenya;Soil Geography and Landscape Group, Wageningen University, P.O. Box 47, 6700AA, Wageningen, The Netherlands;Department of Environmental Sciences, Open Universiteit, P.O. Box 2960, 6401DL, Heerlen, The Netherlands;Wageningen University & Research, Wageningen Environmental Research, P.O. Box 47, 6700AA, Wageningen, The Netherlands;World Vegetable Center, ILRI Campus, P.O Box 5689, Addis Ababa, Ethiopia;

关键词: Farm inventory;    Farming system;    Fertilizer;    Gender;    Net farm income;    Ethiopian highlands;   

DOI  :  10.1186/s40066-022-00404-2

 received in 2022-05-31, accepted in 2022-11-21,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundAs part of a larger food security project under Ethiopia’s Agricultural Growth Program (CASCAPE), 928 farms in the Ethiopian Highlands were surveyed between 2012 and 2017. The aim was to determine whether the Net Farm Income (NFI) is a relevant indicator that drives food security at the household and the farm level, and to determine its drivers across six study regions of Ethiopia (i.e., Addis Ababa, Hawassa, Haramaya, Bahir Dar, Jimma, and Mekelle). The effect of different socio-economic and environmental drivers on NFI was determined using descriptive statistics, correlation analysis, k-means clustering and comparison of high and low NFI quartiles per region.ResultsThe average annual NFI in Ethiopia was just below 1000 US$ per farm household, with Addis Ababa region leading. Jimma and Bahir Dar were just above average, and the others were at the lower end. In the correlation analysis, NFI was best explained by farm size, net cash flow and the use of nitrogen fertilizer. Male-headed households earned considerably more than female-headed households. The k-means clustering yielded two major farm types on the basis of significant differences in rainfall, farm size, education level, crop diversity, cash flow and N fertilizer use. An analysis of richest 25% versus poorest 25% per region showed Addis Ababa, Bahir Dar, Jimma and Mekelle regions all had significant differences between the two quartiles in farm size, crop diversity and N fertilizer use, whereas Hawassa and Haramaya regions seem more homogeneous.ConclusionsThe survey results present new entry points for informed decision making through targeted, area-specific food security policies in the Ethiopian Highlands by virtue of insight in the regional spread of NFI and its driving forces. Important deductions from the results are policy actions that are obtainable from the results. For example, the farm-size variable provides an indicator on the type of policy action that is required to determine the farm sizes that generate sufficient returns on the overall farming investment. Next, cash-flow is a variable that speaks to the idea on the amount of hard-cash needed by a household to enable it get meaningful returns on cash invested on farming, or a guaranteed minimum return on any specific crop(s) or animal production. Nitrogen fertilizer as an analysis variable is predominantly a crop productivity indicator. In order for the farming to be sustainable, there is need for policy articulation on the amount of nitrogen required for specific yields and crops. Finally, location and rainfall parameters require recommendations on location specific crop management policies that correspond to the rainfall amount, soil types, ecological zones and distance from the markets as maybe gleaned from the results.

【 授权许可】

CC BY   
© The Author(s) 2022

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