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Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia

Ali M. Oumer (), Amin Mugera, Michael Burton and Atakelty Hailu
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Ali M. Oumer: University of Western Australia
Amin Mugera: University of Western Australia
Michael Burton: University of Western Australia
Atakelty Hailu: University of Western Australia

Journal of Productivity Analysis, 2022, vol. 57, issue 2, No 6, 213-241

Abstract: Abstract This study estimates the technical efficiency measures of maize producing farm households in Ethiopia using stochastic frontier (SF) panel models that take different approaches to model firm heterogeneity. The efficiency measures are found to vary depending on how the estimation model treats both unobserved and observed firm heterogeneity. Estimates from the ‘true’ random effects (TRE) models that treat firm effects as heterogeneity are found to be identical to those from pooled SF models. Those results differ from the ones generated from the basic random effects (RE) models that treat firm effects as part of overall technical inefficiency. The more flexible generalised ‘true’ random effects (GTRE) model that splits the error term into firm effects, persistent inefficiency, transient inefficiency, and a random noise component indicates the presence of higher levels of persistent inefficiency than transient inefficiency. The basic truncated-normal RE model and heteroscedastic RE model yields similar efficiency estimates. The GTRE model predict persistent efficiency measures similar to those from the basic RE and flexible RE model with environmental variables incorporated in the variance function as well as in the deterministic production frontier. These results imply that the RE and GTRE panel models provide reliable efficiency estimates for our data compared to the TRE models. All the estimated SF models generate comparable production function parameters in terms of magnitude and sign. Overall, the results underscore the importance of scrutinising stochastic frontier models for their reliability of analytical results before drawing policy inferences.

Keywords: Stochastic frontier models; Panel data; Technical efficiency; Firm heterogeneity; Maize production; Sub-Saharan Africa (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11123-022-00627-2

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