Analysis of Technical Efficiency: Lessons and Implications for Wheat Producing Commercial Farms in Ethiopia

This paper analyzes technical efficiency of wheat production under commercial farms in Ethiopia. The study also attempted to determine some farm specific, institutional and socio-economic characteristics which influence technical efficiency of wheat production. A stochastic frontier model is applied on cross sectional data of 32 commercial farms that were surveyed during 2010 production year. Cobb-Douglas type production function was found to best fit the data set. The maximum likelihood estimates of the stochastic frontier production function indicated that the elasticities of output with respect to seed, agrochemicals, tractor hours and DAP are positive and significant. On the contrary, the coefficients of area and labour are negative and significant. The production function associated with the commercial farms was characterized by constant returns to scale. The mean technical efficiency of wheat production is 82 percent. It was also revealed that 99 percent of the variations in wheat output from the best practice are due to inefficiency. Factors significantly affecting efficiency level of the commercial farms are found to be experience of managers, distance of the farm from main road, value of farm machineries owned by the farms and provision of mechanization services by the farms. Average age of farm machineries is the only factor that has a significant negative effect on the level of technical efficiency. Key words: Technical efficiency, Stochastic Frontier model and Returns to scal

Mapping child growth failure across low- and middle-income countries

Child growth failure (CGF), manifested as stunting, wasting, and underweight, is associated with high 5 mortality and increased risks of cognitive, physical, and metabolic impairments. Children in low- and middle-income countries (LMICs) face the highest levels of CGF globally. Here we illustrate national and subnational variation of under-5 CGF indicators across LMICs, providing 2000–2017 annual estimates mapped at a high spatial resolution and aggregated to policy-relevant administrative units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the World Health 10 Organization’s ambitious Global Nutrition Targets to reduce stunting by 40% and wasting to less than 5% by 2025. Large disparities in prevalence and rates of progress exist across regions, countries, and within countries; our maps identify areas where high prevalence persists even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where subnational disparities exist and the highest-need populations reside, these geospatial estimates can support policy-makers in planning locally 15 tailored interventions and efficient directing of resources to accelerate progress in reducing CGF and its health implications