Semi-nonparametric Spline Modifications to the Cornwell-Schmidt-Sickles Estimator: An Analysis of U.S. Banking Productivity

Pavlos Almanidis, Giannis Karagiannis and Robin Sickles

Working Papers from Rice University, Department of Economics

Abstract: This paper modifies the Cornwell, Schmidt and Sickles (CSS) (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 set up while keeping CSS's flexibility regarding the cross section 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).

JEL-codes: C13 C21 C23 D24 G21 (search for similar items in EconPapers)
Date: 2015-06
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Citations: View citations in EconPapers (2)

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Journal Article: Semi-nonparametric spline modifications to the Cornwell–Schmidt–Sickles estimator: an analysis of US banking productivity (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:ecl:riceco:15-008

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