Abstract
AbstractRural households in Ethiopia suffer from the scarcity of grazing land and water. This article examines the economic impact of time spent looking for water and grazing lands for livestock on crop farming labor and crop output based on a nonseparable farm household model. We estimated a general Cobb-Douglas production function using 518 farmers in Ethiopia. Our results confirm a negative relationship between labor input to crop farming and resource scarcity. On average, a 1% reduction in the time spent looking for water, grazing, and straw led to an increase in food production by 0.16%, 0.28% and 0.33%, respectively.
Highlights
Land degradation in sub-Saharan Africa remains a substantial problem in aggravating poverty
We examine the link between animal resource scarcity approximated by walking distance and shadow price and the monetary value of agricultural food production using a theoretical framework that fits into a larger family of the agricultural household model (AHM) developed by Strauss (1986) and later modified by Palmer and MacGregor (2009)
What are the consequences of increasing grazing, water, and straw scarcity for crop labor input? We answer this question by examining the link between resource scarcity and labor input to crop farming in rural areas of Ethiopia using similar estimation methods as in Cooke (1998a)
Summary
Land degradation in sub-Saharan Africa remains a substantial problem in aggravating poverty. The only studies that consider the effects of scarce environmental goods on agricultural labor input are those of Cooke (1998a) and Kumar and Hotchkiss (1988) in Nepal and Mekonnen, Damte, and Deribe (2015) in Ethiopia These studies directly examine the effect of time spent on the collection of fuelwoods, leaf fodder, dung, and grass on labor time allocation but not on crop production. We hypothesized that the negative effect is high on male-headed farms as compared with female-headed farms For this purpose, a nonseparable agricultural household model was developed as a framework by integrating the time allocated to searching for grazing and watering resources and collecting straw into the model using distance level and shadow values of these resources as an indicator of scarcity.. The quantile regression proved that the effects of these scarce resources are heterogeneous across the quantile distribution of crop outputs
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
