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On the estimation of marginal cost

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On the estimation of marginal cost. / Delis, Manthos D.; Iosifidi, Maria; Tsionas, Mike.
In: Operations Research, Vol. 62, No. 3, 2014, p. 543-556.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Delis, MD, Iosifidi, M & Tsionas, M 2014, 'On the estimation of marginal cost', Operations Research, vol. 62, no. 3, pp. 543-556. https://doi.org/10.1287/opre.2014.1264

APA

Delis, M. D., Iosifidi, M., & Tsionas, M. (2014). On the estimation of marginal cost. Operations Research, 62(3), 543-556. https://doi.org/10.1287/opre.2014.1264

Vancouver

Delis MD, Iosifidi M, Tsionas M. On the estimation of marginal cost. Operations Research. 2014;62(3):543-556. Epub 2014 Apr 29. doi: 10.1287/opre.2014.1264

Author

Delis, Manthos D. ; Iosifidi, Maria ; Tsionas, Mike. / On the estimation of marginal cost. In: Operations Research. 2014 ; Vol. 62, No. 3. pp. 543-556.

Bibtex

@article{758582e7aa344575a5876d08607b72db,
title = "On the estimation of marginal cost",
abstract = "This article proposes the estimation of the marginal cost of individual firms using semiparametric and nonparametric methods. These methods have a number of appealing features when applied to cost functions. The empirical analysis uses data from a unique sample of the California electricity industry for which we observe the actual marginal cost and estimate the marginal cost from these data. We compare the actual values of marginal cost with the estimates from semiparametric and nonparametric methods, as well as with the estimates obtained through conventional parametric methods. We show that the semiparametric and nonparametric methods produce marginal cost estimates that very closely approximate the actual. In contrast, the results from conventional parametric methods are significantly biased and provide invalid inference.",
keywords = "estimation of marginal cost, parametric models, semiparametric models, nonparametric models, California electricity industry, actual and simulated data",
author = "Delis, {Manthos D.} and Maria Iosifidi and Mike Tsionas",
year = "2014",
doi = "10.1287/opre.2014.1264",
language = "English",
volume = "62",
pages = "543--556",
journal = "Operations Research",
issn = "0030-364X",
publisher = "INFORMS Inst.for Operations Res.and the Management Sciences",
number = "3",

}

RIS

TY - JOUR

T1 - On the estimation of marginal cost

AU - Delis, Manthos D.

AU - Iosifidi, Maria

AU - Tsionas, Mike

PY - 2014

Y1 - 2014

N2 - This article proposes the estimation of the marginal cost of individual firms using semiparametric and nonparametric methods. These methods have a number of appealing features when applied to cost functions. The empirical analysis uses data from a unique sample of the California electricity industry for which we observe the actual marginal cost and estimate the marginal cost from these data. We compare the actual values of marginal cost with the estimates from semiparametric and nonparametric methods, as well as with the estimates obtained through conventional parametric methods. We show that the semiparametric and nonparametric methods produce marginal cost estimates that very closely approximate the actual. In contrast, the results from conventional parametric methods are significantly biased and provide invalid inference.

AB - This article proposes the estimation of the marginal cost of individual firms using semiparametric and nonparametric methods. These methods have a number of appealing features when applied to cost functions. The empirical analysis uses data from a unique sample of the California electricity industry for which we observe the actual marginal cost and estimate the marginal cost from these data. We compare the actual values of marginal cost with the estimates from semiparametric and nonparametric methods, as well as with the estimates obtained through conventional parametric methods. We show that the semiparametric and nonparametric methods produce marginal cost estimates that very closely approximate the actual. In contrast, the results from conventional parametric methods are significantly biased and provide invalid inference.

KW - estimation of marginal cost

KW - parametric models

KW - semiparametric models

KW - nonparametric models

KW - California electricity industry

KW - actual and simulated data

U2 - 10.1287/opre.2014.1264

DO - 10.1287/opre.2014.1264

M3 - Journal article

VL - 62

SP - 543

EP - 556

JO - Operations Research

JF - Operations Research

SN - 0030-364X

IS - 3

ER -