Estimation of TFP growth: a semiparametric smooth coefficient approach

Subal Kumbhakar, Kai Sun

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Pages (from-to)1-24
Number of pages24
JournalEmpirical Economics
Issue number1
Early online date27 Mar 2011
Publication statusPublished - Aug 2012

Bibliographical note

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  • TFP growth
  • semiparametric smooth coefficient model
  • input distance function


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