Technical Efficiency of Smallholder Agriculture in Developing Countries: The Case of Ethiopia

Abstract

The efficient use of inputs is indispensable in many developing countries, such as Ethiopia. This study assesses the level and determinants of technical efficiency of smallholder farmers using the true fixed effects (TFE) model. The TFE model separates inefficiency from unobserved heterogeneity. Empirical data come from four rounds of panel data (1994–2009) from the Ethiopian rural household survey (ERHS). A one-step maximum likelihood estimator was employed to estimate the Cobb-Douglas stochastic frontier production function and factors influencing technical efficiency. The results indicated that the major variables affecting technical efficiency are policy responsive, albeit to varying degrees: education of the household head, family size, farm size, land fragmentation, land quality, credit use, extension service, off-farm employment, and crop share. The analyses also identify variables amenable to policy changes in the production function: labor, traction power, farm size, seeds, and fertilizer. The mean household-level efficiency for the surveyed farmers is 0.59, indicating that farmers could improve technical efficiency. This implies that smallholder farms in Ethiopia can reduce the input requirement of producing the average output by 41% if their operations become technically efficient. This study recommends that the above policy variables be considered to make Ethiopian smallholder farmers more efficient.

Agricultural Technical Efficiency of Smallholder Farmers in Ethiopia: A Stochastic Frontier Approach

“…The same result is obtained by [11,41,42]. In line with the results of [43,44], land size was found to be the most important factor of production with the highest level of elasticity (1.658). This indicates that farmers are operating in an irrational zone of production (increasing return to land).…”

“…The average TE score in the study areas is 44.33% with variation (SD = 0.211), indicating that there is wider room for increasing crop production in the study areas through mitigating the technical (in)efficiency of smallholder farmers without additional investment in novel agricultural technologies. This finding is lower than the TE scores estimated by empirical researchers in African countries (59%, 66.18%, 74% and 78% for Ethiopia by Tenaye [43], Geffersa [46], Seyoum [47] and Abate [48], respectively; 78% in Papua New Guinea by Coelli and Fleming [21]; and 82% for Rwanda by Ngango and Kim [49]). Bogale and Bogale [50] also found that TE scores range from 77 to 97% for modern and traditional irrigation scheme user farmers in Ethiopia.…”

Determinants of productivity and efficiency of teff production in southwest Ethiopia: Parametric approach

“…Therefore, it enables farmers in maximizing their output at efficient cost of production. This finding is consistent with the results reported by several authors in the literature, such as ( Kifle et.al (2017) and Tenaye (2020).…”

“…Assessing determinants of agricultural production efficiencies is more important than merely presenting a set of efficiencies indices for designing agricultural policy to improve smallholders' agricultural productivity and efficiencies and hence reduce resource waste and improve farmers' livelihoods (Tenaye, 2020). Table 5 illustrates the socio-economic, demographic, farm characteristics and institutional factors that affect inefficiency in teff production.…”

“…According to previous researches in Ethiopia, there also exists a wide teff yield gap among the farmers that might be attributed to many factors such as suboptimal genetic gain, low access to seeds of improved varieties, poor agronomic practices and lodging (Bekele et al, 2019;Abraha et al, 2017). Though there have been various empirical studies conducted to measure efficiency of agricultural production in Ethiopia, (for example, Dessale, 2019;Wassihun et al 2019;Ayele et.al, 2019;Gela et.al, 2019;and Tenaye, 2020), to the best of the author's knowledge, there were no similar studies undertaken on productivity and efficiency of teff producing household in the study area. Moreover, since social development is dynamic, it is imperative to update the information based on the current productivity and efficiency levels of farmers.…”