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    Rights statement: This is the peer reviewed version of the following article: Tsionas, E. G. and Michaelides, P. G. (2016), A Spatial Stochastic Frontier Model with Spillovers: Evidence for Italian Regions. Scottish Journal of Political Economy. doi: 10.1111/sjpe.12081 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/sjpe.12081/abstract . This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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A spatial stochastic frontier model with spillovers: evidence for Italian regions

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

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A spatial stochastic frontier model with spillovers: evidence for Italian regions. / Tsionas, Efthymios; Michaelides, Panayotis G.
In: Scottish Journal of Political Economy, Vol. 63, No. 3, 07.2016, p. 243-257.

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

Harvard

Tsionas, E & Michaelides, PG 2016, 'A spatial stochastic frontier model with spillovers: evidence for Italian regions', Scottish Journal of Political Economy, vol. 63, no. 3, pp. 243-257. https://doi.org/10.1111/sjpe.12081

APA

Tsionas, E., & Michaelides, P. G. (2016). A spatial stochastic frontier model with spillovers: evidence for Italian regions. Scottish Journal of Political Economy, 63(3), 243-257. https://doi.org/10.1111/sjpe.12081

Vancouver

Tsionas E, Michaelides PG. A spatial stochastic frontier model with spillovers: evidence for Italian regions. Scottish Journal of Political Economy. 2016 Jul;63(3):243-257. Epub 2015 Jun 13. doi: 10.1111/sjpe.12081

Author

Tsionas, Efthymios ; Michaelides, Panayotis G. / A spatial stochastic frontier model with spillovers : evidence for Italian regions. In: Scottish Journal of Political Economy. 2016 ; Vol. 63, No. 3. pp. 243-257.

Bibtex

@article{d77e07720d12499196751479e24b7646,
title = "A spatial stochastic frontier model with spillovers: evidence for Italian regions",
abstract = "Efficiency measurement using stochastic frontier models is well established in applied econometrics. However, no published work seems to be available on efficiency analysis using spatial data dealing with possible spatial dependence between regions. This article considers a stochastic frontier model with decomposition of inefficiency into an idiosyncratic and a spatial, spillover component. Exact posterior distributions of parameters are derived, and computational schemes based on Gibbs sampling with data augmentation are proposed to conduct simulation-based inference and efficiency measurement. The new method is illustrated using production data for Italian regions (1970–1993). Clearly, further theoretical and empirical research on the subject would be of great interest.",
keywords = "Spatial econometrics, Stochastic frontier, econometrics",
author = "Efthymios Tsionas and Michaelides, {Panayotis G.}",
year = "2016",
month = jul,
doi = "10.1111/sjpe.12081",
language = "English",
volume = "63",
pages = "243--257",
journal = "Scottish Journal of Political Economy",
issn = "0036-9292",
publisher = "Wiley-Blackwell",
number = "3",

}

RIS

TY - JOUR

T1 - A spatial stochastic frontier model with spillovers

T2 - evidence for Italian regions

AU - Tsionas, Efthymios

AU - Michaelides, Panayotis G.

PY - 2016/7

Y1 - 2016/7

N2 - Efficiency measurement using stochastic frontier models is well established in applied econometrics. However, no published work seems to be available on efficiency analysis using spatial data dealing with possible spatial dependence between regions. This article considers a stochastic frontier model with decomposition of inefficiency into an idiosyncratic and a spatial, spillover component. Exact posterior distributions of parameters are derived, and computational schemes based on Gibbs sampling with data augmentation are proposed to conduct simulation-based inference and efficiency measurement. The new method is illustrated using production data for Italian regions (1970–1993). Clearly, further theoretical and empirical research on the subject would be of great interest.

AB - Efficiency measurement using stochastic frontier models is well established in applied econometrics. However, no published work seems to be available on efficiency analysis using spatial data dealing with possible spatial dependence between regions. This article considers a stochastic frontier model with decomposition of inefficiency into an idiosyncratic and a spatial, spillover component. Exact posterior distributions of parameters are derived, and computational schemes based on Gibbs sampling with data augmentation are proposed to conduct simulation-based inference and efficiency measurement. The new method is illustrated using production data for Italian regions (1970–1993). Clearly, further theoretical and empirical research on the subject would be of great interest.

KW - Spatial econometrics

KW - Stochastic frontier

KW - econometrics

U2 - 10.1111/sjpe.12081

DO - 10.1111/sjpe.12081

M3 - Journal article

VL - 63

SP - 243

EP - 257

JO - Scottish Journal of Political Economy

JF - Scottish Journal of Political Economy

SN - 0036-9292

IS - 3

ER -