Estimating efficiency effects in a stochastic frontier model with heteroskedastic errors

Shankar, Sriram

Estimating efficiency effects in a stochastic frontier model with heteroskedastic errors

Journal of Economic Structures, 2025, vol. 14, issue 1, 1-11

Abstract: Abstract In this paper, we introduce a stochastic frontier model that incorporates efficiency effects and a heteroskedastic error structure. The mean efficiency is specified by a logistic function of the effects variables and the distribution for the one-sided random variable representing inefficiency is left unspecified. In contrast to conventional efficiency effects models, our approach does not necessitate the use of the JLMS (Jondrow in J Econom 19:233–238, 1982) transformation for computing efficiency scores. Efficiency scores are derived directly from the estimated model parameters using feasible generalized non-linear least squares. In order to illustrate the practical applicability of our proposed model, we present an empirical example using OECD electricity generation data.

Keywords: Stochastic frontier; Heteroskedasticity; Non-linear least squares (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1186/s40008-025-00353-6 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jecstr:v:14:y:2025:i:1:d:10.1186_s40008-025-00353-6

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40008

DOI: 10.1186/s40008-025-00353-6

Access Statistics for this article

Journal of Economic Structures is currently edited by Shigemi Kagawa and Kazuhiko Nishimura

More articles in Journal of Economic Structures from Springer, Pan-Pacific Association of Input-Output Studies (PAPAIOS) Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().