Semi-nonparametric spline modifications to the Cornwell–Schmidt–Sickles estimator: an analysis of US banking productivity

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dc.citation.firstpage169en_US
dc.citation.issueNumber1en_US
dc.citation.journalTitleEmpirical Economicsen_US
dc.citation.lastpage191en_US
dc.citation.volumeNumber48en_US
dc.contributor.authorAlmanidis, Pavlosen_US
dc.contributor.authorKaragiannis, Giannisen_US
dc.contributor.authorSickles, Robin C.en_US
dc.date.accessioned2015-02-27T21:50:06Zen_US
dc.date.available2015-02-27T21:50:06Zen_US
dc.date.issued2015en_US
dc.description.abstractThis paper modifies the Cornwell, Schmidt and Sickles [CSS (J Econom 46:185–200, 1990)] time-varying specification of technical efficiency to allow for switching patterns in temporal changes, which may occur more than once during the sample period. For this purpose, we move from the (second-order) polynomial specification of the standard CSS to a spline function setup, while keeping CSS’s flexibility regarding the cross-sectional dimension. The spline function specification of the temporal pattern of technical efficiency can accommodate more than one turning point and thus can be non-monotonic. This allows the modeler to account for firm or individual efficiency gains that can occur relatively quickly, for example, changes related to regulation or policy changes, as well as those related to ownership/organization changes (e.g., merger or acquisitions).en_US
dc.identifier.citationAlmanidis, Pavlos, Karagiannis, Giannis and Sickles, Robin C.. "Semi-nonparametric spline modifications to the Cornwell–Schmidt–Sickles estimator: an analysis of US banking productivity." <i>Empirical Economics,</i> 48, no. 1 (2015) Springer: 169-191. http://dx.doi.org/10.1007/s00181-014-0890-y.en_US
dc.identifier.doihttp://dx.doi.org/10.1007/s00181-014-0890-yen_US
dc.identifier.urihttps://hdl.handle.net/1911/79048en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Springer.en_US
dc.subject.keywordCornwell-Schmidt-Sickles Estimatoren_US
dc.subject.keywordtime-varying efficiencyen_US
dc.subject.keywordspline functionsen_US
dc.subject.keywordsemi-parametric estimationen_US
dc.titleSemi-nonparametric spline modifications to the Cornwell–Schmidt–Sickles estimator: an analysis of US banking productivityen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpost-printen_US
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