Estimation of TFP growth:a semiparametric smooth coefficient approach

Abstract

This article uses a semiparametric smooth coefficient model (SPSCM) to estimate TFP growth and its components (scale and technical change). The SPSCM is derived from a nonparametric specification of the production technology represented by an input distance function (IDF), using a growth formulation. The functional coefficients of the SPSCM come naturally from the model and are fully flexible in the sense that no functional form of the underlying production technology is used to derive them. Another advantage of the SPSCM is that it can estimate bias (input and scale) in technical change in a fully flexible manner. We also used a translog IDF framework to estimate TFP growth components. A panel of U.S. electricity generating plants for the period 1986–1998 is used for this purpose. Comparing estimated TFP growth results from both parametric and semiparametric models against the Divisia TFP growth, we conclude that the SPSCM performs the best in tracking the temporal behavior of TFP growth.

Publication DOI: https://doi.org/10.1007/s00181-011-0468-x
Divisions: College of Business and Social Sciences > Aston Business School > Economics, Finance & Entrepreneurship
College of Business and Social Sciences > Aston Business School
Additional Information: The original publication is available at www.springerlink.com
Uncontrolled Keywords: TFP growth,semiparametric smooth coefficient model,input distance function,Economics and Econometrics,Social Sciences (miscellaneous),Mathematics (miscellaneous),Statistics and Probability
Publication ISSN: 1435-8921
Full Text Link: http://www.spri ... mj30705w752532/
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2012-08
Published Online Date: 2011-03-27
Authors: Kumbhakar, Subal
Sun, Kai

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