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    Rights statement: This is the peer reviewed version of the following article: Johnes, G, Tsionas, MG. A regression discontinuity stochastic frontier model with an application to educational attainment. Stat. 2019; 8:e242. https://doi.org/10.1002/sta4.242 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sta4.242 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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A Regression Discontinuity Stochastic Frontier Model with an Application to Educational Attainment

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A Regression Discontinuity Stochastic Frontier Model with an Application to Educational Attainment. / Johnes, Geraint; Tsionas, Mike.

In: Stat, Vol. 8, No. 1, e242, 01.09.2019.

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@article{1d78cd2121db4bfe8197772ac895cb67,
title = "A Regression Discontinuity Stochastic Frontier Model with an Application to Educational Attainment",
abstract = "We extend the regression discontinuity design model to the case in which the line of best fit is replaced by a stochastic frontier. The method allows causality issues to be examined in a context where the performance measure is subject to inefficiency, and where, in addition to the relationship between dependent and explanatory variables, there may be a discontinuity in the inefficiency measure at the break. In the tradition of Battese and Coelli (1995), the inefficiency scores are modelled as part of the system but we follow a novel non-parametric approach. We illustrate the method with an application to data from Texas on class size and pupil performance, exploiting a Maimonides rule discontinuity. We find that class size affects performance in the expected direction, but that there is a corresponding effect in the opposite direction on efficiency. This may contribute to the difficulty experienced by authors of earlier studies in identifying a class size effect. ",
keywords = "education, regression discontinuity, STOCHASTIC FRONTIER",
author = "Geraint Johnes and Mike Tsionas",
note = "This is the peer reviewed version of the following article: Johnes, G, Tsionas, MG. A regression discontinuity stochastic frontier model with an application to educational attainment. Stat. 2019; 8:e242. https://doi.org/10.1002/sta4.242 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sta4.242 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.",
year = "2019",
month = sep,
day = "1",
doi = "10.1002/sta4.242",
language = "English",
volume = "8",
journal = "Stat",
issn = "2049-1573",
publisher = "Wiley-Blackwell Publishing Ltd",
number = "1",

}

RIS

TY - JOUR

T1 - A Regression Discontinuity Stochastic Frontier Model with an Application to Educational Attainment

AU - Johnes, Geraint

AU - Tsionas, Mike

N1 - This is the peer reviewed version of the following article: Johnes, G, Tsionas, MG. A regression discontinuity stochastic frontier model with an application to educational attainment. Stat. 2019; 8:e242. https://doi.org/10.1002/sta4.242 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sta4.242 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2019/9/1

Y1 - 2019/9/1

N2 - We extend the regression discontinuity design model to the case in which the line of best fit is replaced by a stochastic frontier. The method allows causality issues to be examined in a context where the performance measure is subject to inefficiency, and where, in addition to the relationship between dependent and explanatory variables, there may be a discontinuity in the inefficiency measure at the break. In the tradition of Battese and Coelli (1995), the inefficiency scores are modelled as part of the system but we follow a novel non-parametric approach. We illustrate the method with an application to data from Texas on class size and pupil performance, exploiting a Maimonides rule discontinuity. We find that class size affects performance in the expected direction, but that there is a corresponding effect in the opposite direction on efficiency. This may contribute to the difficulty experienced by authors of earlier studies in identifying a class size effect.

AB - We extend the regression discontinuity design model to the case in which the line of best fit is replaced by a stochastic frontier. The method allows causality issues to be examined in a context where the performance measure is subject to inefficiency, and where, in addition to the relationship between dependent and explanatory variables, there may be a discontinuity in the inefficiency measure at the break. In the tradition of Battese and Coelli (1995), the inefficiency scores are modelled as part of the system but we follow a novel non-parametric approach. We illustrate the method with an application to data from Texas on class size and pupil performance, exploiting a Maimonides rule discontinuity. We find that class size affects performance in the expected direction, but that there is a corresponding effect in the opposite direction on efficiency. This may contribute to the difficulty experienced by authors of earlier studies in identifying a class size effect.

KW - education

KW - regression discontinuity

KW - STOCHASTIC FRONTIER

U2 - 10.1002/sta4.242

DO - 10.1002/sta4.242

M3 - Journal article

VL - 8

JO - Stat

JF - Stat

SN - 2049-1573

IS - 1

M1 - e242

ER -