Lookup NU author(s): Dr Francisco Areal
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
The physical environment of farming systems is rarely considered when conductingfarm level efficiency analysis, which is likely to lead to bias of performancemeasurements based on benchmarking methods such as Data Envelopment Analysis(DEA). We incorporate variations of the physical environment (rainfall and lengthof growing season) through the specifications of the linear programming in DEAto investigate performance measurement bias. The derived technical efficiency estimatesare obtained using a sub-vector DEA which ensures farms are compared in ahomogenous environment (i.e. accounting for differences in rainfall levels amongstdistinct farm units). We use the Farm Business Survey to analyse a representativesample of 245 cereal farms in the East Anglia region between 2009 and 2010. Efficiencyrankings obtained from a standard DEA model and a non-discretionary DEAmodel that incorporates the variations in the physical environment. We show thatincorporating rainfall and the length of the growing season as non-discretionaryinputs into the production function had significantly altered the farm efficiency rankingbetween the two models. Hence, to improve extension services to farmers andto reduce biased estimates of farm technical efficiency, variations in environmentalconditions need to be integral to the analysis of efficiency.
Author(s): Gadanakis Y, Areal FJ
Publication type: Article
Publication status: Published
Journal: Operational Research
Online publication date: 22/09/2018
Acceptance date: 17/09/2018
Date deposited: 23/04/2019
ISSN (print): 1109-2858
ISSN (electronic): 1866-1505
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