Maximum entropy: a stochastic frontier approach for electricity distribution regulation
Elvira Silva (),
Pedro Macedo () and
Isabel Soares ()
Additional contact information
Elvira Silva: Center for Economics and Finance at UP (CEF.UP)
Pedro Macedo: University of Aveiro
Isabel Soares: Center for Economics and Finance at UP (CEF.UP)
Journal of Regulatory Economics, 2019, vol. 55, issue 3, 237-257
Abstract The literature on incentive-based regulation in the electricity sector indicates that the size of this sector in a country constrains the choice of frontier methods as well as the model specification itself to measure economic efficiency of regulated firms. The aim of this study is to propose a stochastic frontier approach with maximum entropy estimation, which is designed to extract information from limited and noisy data with minimal statements on the data generation process. Stochastic frontier analysis with generalized maximum entropy and data envelopment analysis—the latter one has been widely used by national regulators—are applied to a cross-section data on thirteen European electricity distribution companies. Technical efficiency scores and rankings of the distribution companies generated by both approaches are sensitive to model specification. Nevertheless, the stochastic frontier analysis with generalized maximum entropy results indicate that technical efficiency scores have similar distributional properties and these scores as well as the rankings of the companies are not very sensitive to the prior information. In general, the same electricity distribution companies are found to be in the highest and lowest efficient groups, reflecting weak sensitivity to the prior information considered in the estimation procedure.
Keywords: Electricity distribution regulation; Technical efficiency; Maximum entropy; Data envelopment analysis (search for similar items in EconPapers)
JEL-codes: C14 D24 L94 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1007/s11149-019-09383-y Abstract (text/html)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:kap:regeco:v:55:y:2019:i:3:d:10.1007_s11149-019-09383-y
Ordering information: This journal article can be ordered from
http://www.springer. ... on/journal/11149/PS2
Access Statistics for this article
Journal of Regulatory Economics is currently edited by Michael A. Crew
More articles in Journal of Regulatory Economics from Springer
Bibliographic data for series maintained by Sonal Shukla ().