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Estimation of Productivity in Korean Electric Power Plants: A Semiparametric Smooth Coefficient Model

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  • Heshmati, Almas

    ()
    (Jönköping University, Sogang University)

  • Kumbhakar, Subal C.

    ()
    (Binghamton University, New York)

  • Sun, Kai

    ()
    (Aston University)

Abstract

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 compare 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 implication for generation policy in Korea as outlined in this study.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 7277.

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Length: 24 pages
Date of creation: Mar 2013
Date of revision:
Handle: RePEc:iza:izadps:dp7277

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Keywords: semiparametric estimation; smooth varying-coefficient model; electricity generation; generator level panel data;

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  1. Racine, Jeff & Li, Qi, 2004. "Nonparametric estimation of regression functions with both categorical and continuous data," Journal of Econometrics, Elsevier, Elsevier, vol. 119(1), pages 99-130, March.
  2. Zvi Griliches, 1979. "Issues in Assessing the Contribution of Research and Development to Productivity Growth," Bell Journal of Economics, The RAND Corporation, The RAND Corporation, vol. 10(1), pages 92-116, Spring.
  3. Fan, Yanqin & Li, Qi, 1996. "Consistent Model Specification Tests: Omitted Variables and Semiparametric Functional Forms," Econometrica, Econometric Society, Econometric Society, vol. 64(4), pages 865-90, July.
  4. Li, Qi & Racine, Jeffrey S., 2010. "Smooth Varying-Coefficient Estimation And Inference For Qualitative And Quantitative Data," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 26(06), pages 1607-1637, December.
  5. Li, Qi, et al, 2002. "Semiparametric Smooth Coefficient Models," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(3), pages 412-22, July.
  6. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, Econometric Society, vol. 56(4), pages 931-54, July.
  7. Lee, Byoung-Hoon & Ahn, Hyeon-Hyo, 2006. "Electricity industry restructuring revisited: the case of Korea," Energy Policy, Elsevier, Elsevier, vol. 34(10), pages 1115-1126, July.
  8. Park, Soo-Uk & Lesourd, Jean-Baptiste, 2000. "The efficiency of conventional fuel power plants in South Korea: A comparison of parametric and non-parametric approaches," International Journal of Production Economics, Elsevier, Elsevier, vol. 63(1), pages 59-67, January.
  9. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, Princeton University Press, edition 1, volume 1, number 8355.
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