Determinants of efficiency of vegetable production in smallholder farms: The case of Ethiopia

Improving production efficiency remains as a plausible means of increasing productivity when resource reallocation, and the creation and adoption of new technologies are limited. Technical, allocative and economic efficiencies are derived from a sample of smallholder vegetable farmers in Ethiopia using parametric and non-parametric methods. The results reveal that the two methods yield similar estimates and the existence of substantial inefficiencies in production as well as efficiency differentials among farmers. The analysis of the determinants of efficiency of vegetable production using regression models show that low asset ownership, illiteracy, large family size, inadequate extension contacts, small farm size, age, low off/non-farm income and high consumer spending are the major socio-economic factors causing inefficiency of vegetable production in the study areas. A comparison of the market-driven (vegetables) with the whole-farm (crops and livestock) production efficiency indicates that lower economic efficiency scores for the former might be related to the limited access to capital markets, high consumer spending, and large family size. Keywords: Parametric and non-parametric methodsregression analyseswhole-farm versus enterpriseefficiency differentialsEthiopiaView correction statement:Corrigendum to Jema Haji and Hans Andersson "Determinants of efficiency of vegetables production in smallholder farms: The case of Ethiopia". Food Economics – Acta Agriculturæ Scandinavica, 3, 125–137 (2006). We thank Bo Ohlmer and Helena Johansson for their useful comments. We also thank the Swedish International Development Cooperation Agency (Sida) for the financial and logistic support for the project through its Department for Research in collabration with the Swedish University of Agricultural Sciences, SLU (Sweden) and the Haramaya University, HU (Ethiopia). Notes 1. The input-oriented and output-oriented efficiency measures will coincide when the technology exhibits CRS, but are likely to differ otherwise. In this study, an input-oriented efficiency measure is used because input quantities appear to be primary decision variables for most of the farmers. Moreover, this choice is not expected to considerably affect the result because farmers in the sample operate small farms and hence the technology is unlikely to be substantially affected by variable returns to scale (Coelli et al., 2002). 2. Input price variation is observed across districts, PAs and households with in the PAs. This could be a seasonal effect or a differential in access to input markets. Since it seems unlikely that input price variation would reflect differences in resource availability across households, the average input prices were chosen as a measure of resource scarcity for each farm households. 3. The standard measure of economic efficiency which is obtained in two stages: first by estimating the minimum price-adjusted resource usage given technological constraints, and secondly by comparing this minimum to the actual or observed costs will be reduced to the DEA problem (6) with the assumption of identical prices. 4. First, a Tobit model was fitted to technical, allocative and economic efficiencies using a constant and 18 variables and a restricted model was fitted by excluding 7 variables (experience, plot ownership, crop diversification, market distance, extension distance, road distance and district) that were not individually statistically significant in the model. The log-likelihood functions for the unrestricted and restricted models were calculated for the technical, allocative and economic efficiencies. A likelihood ratio test was performed for testing the null-hypotheses that all the seven coefficients are zero and could not be rejected at the 1% significance level. Hence the analysis of the data proceeded by using the 11 restricted variables defined above. 5. Descriptive statistics of input-output variables and efficiency factors for the whole-farm are found in the paper by Jema (forthcoming). 6. Only regression results obtained using DEA efficiency scores is presented because of the high correlation between SFA and DEA efficiency scores.