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Technical efficiency of Kansas arable crop farms: a local maximum likelihood approach |
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| Authors: | Bouali Guesmi Teresa Serra Allen Featherstone |
| Affiliation: | 1. Ecole Supérieure d'Agriculture de Mograne, Zaghouan, Tunisia;2. Department of Agricultural and Consumer Economics, University of Illinois at Urbana‐Champaign, Urbana, IL, USA;3. Department of Agricultural Economics, Kansas State University, KS, USA |
| Abstract: | This study uses local maximum likelihood (LML) methods recently proposed by Kumbhakar et al. (2007) to assess the technical efficiency of arable crop Kansas farms. LML techniques overcome the most relevant limitations associated to mainstream parametric stochastic and nonparametric frontier models. LML allows deriving farm‐level frontier parameter estimates. The relevance of using localized estimates is evidenced by the observed heterogeneity in production technologies. Technical efficiency scores derived from the LML approach [0.905] are higher than those of the DEA model under CRS [0.808] and SFA [0.804] and close to DEA‐VRS [0.917] ratings. Deriving reliable information about farm efficiency performance is relevant to identify inefficient farms and define adequate policy and management strategies. The use of refined methods has thus important implications. |
| Keywords: | C14 Q12 D24 Technical efficiency Nonparametric Local maximum likelihood approach |