Estimating efficiency in the presence of extreme outliers: A logistic-half normal stochastic frontier model with application to highway maintenance costs in England

Stead, AD orcid.org/0000-0002-7836-3827, Wheat, P orcid.org/0000-0003-0659-5052 and Greene, WH (2018) Estimating efficiency in the presence of extreme outliers: A logistic-half normal stochastic frontier model with application to highway maintenance costs in England. In: Greene, WH, Khalaf, L, Makdissi, P, Sickles, RC, Veall, MR and Voia, M-C, (eds.) Productivity and Inequality. Springer Proceedings in Business and Economics . Springer International Publishing , pp. 1-19. ISBN 978-3-319-68677-6

Abstract

Metadata

Item Type: Book Section
Authors/Creators:
Editors:
  • Greene, WH
  • Khalaf, L
  • Makdissi, P
  • Sickles, RC
  • Veall, MR
  • Voia, M-C
Copyright, Publisher and Additional Information:

(c) 2018, Springer International Publishing AG. This is a pre-print of a contribution published in 'Greene, WH, Khalaf, L, Makdissi, P, Sickles, RC, Veall, MR and Voia, M-C, (eds.) Productivity and Inequality. Springer Proceedings in Business and Economics,' published by Springer. The definitive authenticated version is available online via https://doi.org/10.1007/978-3-319-68678-3_1

Keywords: Efficiency analysis; Efficiency; Stochastic frontier analysis; Logistic distribution; Highway maintenance; Costs
Dates:
  • Published: 2018
  • Published (online): 3 February 2018
  • Accepted: 17 August 2017
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)
Funding Information:
Funder
Grant number
Measure2Improve
M2I
Depositing User: Symplectic Publications
Date Deposited: 21 Sep 2017 16:13
Last Modified: 03 Feb 2019 01:38
Published Version: http://www.springer.com/gb/book/9783319686776
Status: Published
Publisher: Springer International Publishing
Series Name: Springer Proceedings in Business and Economics
Identification Number: 10.1007/978-3-319-68678-3_1
Open Archives Initiative ID (OAI ID):

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