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

Pavlos Almanidis, Giannis Karagiannis and Robin Sickles

Empirical Economics, 2015, vol. 48, issue 1, 169-191

Abstract: This 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). Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Cornwell–Schmidt–Sickles estimator; Time-varying efficiency; Spline functions; Semi-parametric estimation; C13; C21; C23; D24; G21 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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Working Paper: Semi-nonparametric Spline Modifications to the Cornwell-Schmidt-Sickles Estimator: An Analysis of U.S. Banking Productivity (2015)
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DOI: 10.1007/s00181-014-0890-y

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