Estimation of productivity in Korean electric power plants: A semiparametric smooth coefficient model
Almas Heshmati (),
Subal Kumbhakar () and
Kai Sun ()
Energy Economics, 2014, vol. 45, issue C, 491-500
This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to assess the performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995–2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implications for generation policy in Korea as outlined in this study.
Keywords: Semiparametric estimation; Smooth varying coefficient model; Electricity generation; Generator level panel data (search for similar items in EconPapers)
JEL-codes: C14 C23 C51 D24 L25 L94 (search for similar items in EconPapers)
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Working Paper: Estimation of Productivity in Korean Electric Power Plants: A Semiparametric Smooth Coefficient Model (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:45:y:2014:i:c:p:491-500
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