Controlling for spatial heterogeneity in nonparametric efficiency models: An empirical proposalFrancesco Vidoli and Jacopo Canello () European Journal of Operational Research, 2016, vol. 249, issue 2, 771-783 Abstract: This paper introduces an original methodology, derived by the robust order-m model, to estimate technical efficiency with spatial autocorrelated data using a nonparametric approach. The methodology is aimed to identify potential competitors on a subset of productive units that are identified through spatial dependence, thus focusing on peers located in close proximity of the productive unit. The proposed method is illustrated in a simulation setting that verifies the territorial differences between the nonparametric unconditioned and the conditioned estimates. A firm-level application to the Italian industrial districts is proposed in order to highlight the ability of the new method to separate the global intangible spatial effect from the efficiency term on real data. Keywords: Productive efficiency; Conditional nonparametric efficiency; Spatial heterogeneity; Industrial districts (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:249:y:2016:i:2:p:771-783 DOI: 10.1016/j.ejor.2015.10.050 Access Statistics for this article European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati More articles in European Journal of Operational Research from Elsevier |
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