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Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks

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Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks. / Kumbhakar, Subal C.; Tsionas, Michael.
In: Empirical Economics, Vol. 34, No. 3, 01.06.2008, p. 585-602.

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

Harvard

Kumbhakar, SC & Tsionas, M 2008, 'Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks', Empirical Economics, vol. 34, no. 3, pp. 585-602. https://doi.org/10.1007/s00181-007-0137-2

APA

Kumbhakar, S. C., & Tsionas, M. (2008). Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks. Empirical Economics, 34(3), 585-602. https://doi.org/10.1007/s00181-007-0137-2

Vancouver

Kumbhakar SC, Tsionas M. Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks. Empirical Economics. 2008 Jun 1;34(3):585-602. doi: 10.1007/s00181-007-0137-2

Author

Kumbhakar, Subal C. ; Tsionas, Michael. / Scale and efficiency measurement using a semiparametric stochastic frontier model : evidence from the U.S. commercial banks. In: Empirical Economics. 2008 ; Vol. 34, No. 3. pp. 585-602.

Bibtex

@article{189212e71d7c4691ad13125c495a6e36,
title = "Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks",
abstract = "In this paper, we use the local maximum likelihood (LML) method proposed by Kumbhakar et al. (J Econom, 2007) to estimate stochastic cost frontier models for a sample of 3,691 U.S. commercial banks. This method relaxes several deficiencies in the econometric estimation of frontier functions. In particular, we relax the assumption that all banks share the same production technology and provide bank-specific measures of returns to scale and cost inefficiency. The LML method is applied to estimate the cost frontiers in which a truncated normal distribution is used to model technical inefficiency. This formulation allows the cost frontier, inefficiency effects and heteroskedasticity in both noise and inefficiency components to be quite flexible.",
keywords = "Data envelopment analysis , Cost efficiency , Local maximum likelihood estimation , U.S. commercial bank",
author = "Kumbhakar, {Subal C.} and Michael Tsionas",
year = "2008",
month = jun,
day = "1",
doi = "10.1007/s00181-007-0137-2",
language = "English",
volume = "34",
pages = "585--602",
journal = "Empirical Economics",
issn = "0377-7332",
publisher = "Springer-Verlag",
number = "3",

}

RIS

TY - JOUR

T1 - Scale and efficiency measurement using a semiparametric stochastic frontier model

T2 - evidence from the U.S. commercial banks

AU - Kumbhakar, Subal C.

AU - Tsionas, Michael

PY - 2008/6/1

Y1 - 2008/6/1

N2 - In this paper, we use the local maximum likelihood (LML) method proposed by Kumbhakar et al. (J Econom, 2007) to estimate stochastic cost frontier models for a sample of 3,691 U.S. commercial banks. This method relaxes several deficiencies in the econometric estimation of frontier functions. In particular, we relax the assumption that all banks share the same production technology and provide bank-specific measures of returns to scale and cost inefficiency. The LML method is applied to estimate the cost frontiers in which a truncated normal distribution is used to model technical inefficiency. This formulation allows the cost frontier, inefficiency effects and heteroskedasticity in both noise and inefficiency components to be quite flexible.

AB - In this paper, we use the local maximum likelihood (LML) method proposed by Kumbhakar et al. (J Econom, 2007) to estimate stochastic cost frontier models for a sample of 3,691 U.S. commercial banks. This method relaxes several deficiencies in the econometric estimation of frontier functions. In particular, we relax the assumption that all banks share the same production technology and provide bank-specific measures of returns to scale and cost inefficiency. The LML method is applied to estimate the cost frontiers in which a truncated normal distribution is used to model technical inefficiency. This formulation allows the cost frontier, inefficiency effects and heteroskedasticity in both noise and inefficiency components to be quite flexible.

KW - Data envelopment analysis

KW - Cost efficiency

KW - Local maximum likelihood estimation

KW - U.S. commercial bank

U2 - 10.1007/s00181-007-0137-2

DO - 10.1007/s00181-007-0137-2

M3 - Journal article

VL - 34

SP - 585

EP - 602

JO - Empirical Economics

JF - Empirical Economics

SN - 0377-7332

IS - 3

ER -