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

Author

Listed:
  • Heshmati, Almas

    (Jönköping 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.

Suggested Citation

  • Heshmati, Almas & Kumbhakar, Subal C. & Sun, Kai, 2013. "Estimation of Productivity in Korean Electric Power Plants: A Semiparametric Smooth Coefficient Model," IZA Discussion Papers 7277, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp7277
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    References listed on IDEAS

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    Cited by:

    1. Seifert, Stefan, 2015. "Productivity Growth and its Sources - A StoNED Metafrontier Analyis of the German Electricity Generating Sector," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112975, Verein für Socialpolitik / German Economic Association.
    2. Stefan Seifert & Astrid Cullmann & Christian von Hirschhausen, 2014. "Technical Efficiency and CO2 Reduction Potentials: An Analysis of the German Electricity Generating Sector," Discussion Papers of DIW Berlin 1426, DIW Berlin, German Institute for Economic Research.
    3. Subal C. Kumbhakar & Kai Sun & Rui Zhang, 2016. "Semiparametric Smooth Coefficient Estimation of a Production System," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 464-482, October.
    4. Stefan Seifert, 2015. "Measuring Productivity When Technologies Are Heterogeneous: A Semi-Parametric Approach for Electricity Generation," Discussion Papers of DIW Berlin 1526, DIW Berlin, German Institute for Economic Research.
    5. Dai, Xiaoyong & Cheng, Liwei, 2016. "Market distortions and aggregate productivity: Evidence from Chinese energy enterprises," Energy Policy, Elsevier, vol. 95(C), pages 304-313.
    6. Sun, Kege & Wu, Libo, 2020. "Efficiency distortion of the power generation sector under the dual regulation of price and quantity in China," Energy Economics, Elsevier, vol. 86(C).
    7. Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2022. "Estimation of varying coefficient models with measurement error," Journal of Econometrics, Elsevier, vol. 230(2), pages 388-415.
    8. Long, Xingle & Wu, Chao & Zhang, Jijian & Zhang, Jing, 2018. "Environmental efficiency for 192 thermal power plants in the Yangtze River Delta considering heterogeneity: A metafrontier directional slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3962-3971.
    9. Oh, Dong-hyun & Lee, Yong-Gil, 2016. "Productivity decomposition and economies of scale of Korean fossil-fuel power generation companies: 2001–2012," Energy, Elsevier, vol. 100(C), pages 1-9.
    10. Mamatzakis, Emmanuel & matousek, roman & vu, anh, 2019. "The interplay between problem loans and Japanese bank productivity," MPRA Paper 92960, University Library of Munich, Germany.
    11. Benjamin David, 2014. "Contribution of ICT on Labor Market Polarization: an Evolutionary Approach," EconomiX Working Papers 2014-25, University of Paris Nanterre, EconomiX.
    12. Seifert, Stefan & Cullmann, Astrid & von Hirschhausen, Christian, 2016. "Technical efficiency and CO2 reduction potentials — An analysis of the German electricity and heat generating sector," Energy Economics, Elsevier, vol. 56(C), pages 9-19.
    13. Kai Sun & Ruhul Salim, 2020. "A semiparametric stochastic input distance frontier model with application to the Indonesian banking industry," Journal of Productivity Analysis, Springer, vol. 54(2), pages 139-156, December.
    14. Kai Sun, 2015. "Constrained nonparametric estimation of input distance function," Journal of Productivity Analysis, Springer, vol. 43(1), pages 85-97, February.

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    More about this item

    Keywords

    electricity generation; smooth varying-coefficient model; semiparametric estimation; generator level panel data;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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