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Returns to Scale in Electricity Generation: Revisited and Replicated

Author

Listed:
  • David H. Bernstein

    (University of Miami)

  • Christopher F. Parmeter

    (University of Miami)

Abstract
We replicate the findings of two infuential studies on returns to scale in the electricity generation market in the United States. The main results are also contrasted using local linear nonparametric regression, a technique robust to functional form assumptions. While the quantitative findings differ somewhat regarding the magnitude of returns to scale, we find that there is a substantial shift in returns to scale across the electricity generation market of 1955 to that of 1970.

Suggested Citation

  • David H. Bernstein & Christopher F. Parmeter, 2017. "Returns to Scale in Electricity Generation: Revisited and Replicated," Working Papers 2017-08, University of Miami, Department of Economics.
  • Handle: RePEc:mia:wpaper:2017-08
    as

    Download full text from publisher

    File URL: https://www.herbert.miami.edu/_assets/files/repec/WP2017-08.pdf
    File Function: First version, 2017
    Download Restriction: no
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    References listed on IDEAS

    as
    1. RITTER, Christian & SIMAR, Léopold, 1994. "Another Look at the American Electrical Utility Data," LIDAM Discussion Papers CORE 1994007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Henderson, Daniel J. & Kumbhakar, Subal C. & Li, Qi & Parmeter, Christopher F., 2015. "Smooth coefficient estimation of a seemingly unrelated regression," Journal of Econometrics, Elsevier, vol. 189(1), pages 148-162.
    3. David C. Wheelock & Paul W. Wilson, 2012. "Do Large Banks Have Lower Costs? New Estimates of Returns to Scale for U.S. Banks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 171-199, February.
    4. Henderson,Daniel J. & Parmeter,Christopher F., 2015. "Applied Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521279680, January.
    5. Hayfield, Tristen & Racine, Jeffrey S., 2008. "Nonparametric Econometrics: The np Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i05).
    6. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    7. Henningsen, Arne & Hamann, Jeff D., 2007. "systemfit: A Package for Estimating Systems of Simultaneous Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 23(i04).
    8. Dhrymes, Phoebus J, 1971. "Equivalence of Iterative Aitken and Maximum Likelihood Estimators for a System of Regression Equations," Australian Economic Papers, Wiley Blackwell, vol. 10(16), pages 20-24, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. 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).
    2. Li, Gao & Ruonan, Li & Yingdan, Mei & Xiaoli, Zhao, 2022. "Improve technical efficiency of China's coal-fired power enterprises: Taking a coal-fired-withdrawl context," Energy, Elsevier, vol. 252(C).

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    More about this item

    Keywords

    System Estimation; Shepard's Lemma; Seemingly Unrelated Regression; Nonparametric. Publication Status: Submitted;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    NEP fields

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