Controlling for spatial heterogeneity in nonparametric efficiency models: an empirical proposal

Vidoli, Francesco and Canello, Jacopo (2016) Controlling for spatial heterogeneity in nonparametric efficiency models: an empirical proposal. European Journal of Operational Research, 249 2: 771-783. doi:10.1016/j.ejor.2015.10.050

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Author Vidoli, Francesco
Canello, Jacopo
Title Controlling for spatial heterogeneity in nonparametric efficiency models: an empirical proposal
Journal name European Journal of Operational Research   Check publisher's open access policy
ISSN 0377-2217
1872-6860
Publication date 2016-03-01
Sub-type Article (original research)
DOI 10.1016/j.ejor.2015.10.050
Open Access Status File (Author Post-print)
Volume 249
Issue 2
Start page 771
End page 783
Total pages 13
Place of publication Amsterdam, Netherlands
Publisher Elsevier BV
Language eng
Formatted 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.
Keyword Conditional nonparametric efficiency
Industrial districts
Productive efficiency
Spatial heterogeneity
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Economics Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 3 times in Scopus Article | Citations
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Created: Sun, 17 Jan 2016, 10:24:30 EST by System User on behalf of Learning and Research Services (UQ Library)