Robust Nonparametric Partial Frontier Input Distance Function Estimates: Testing and Rejecting Convexity

Shirong Zhao (), Kristiaan Kerstens () and Tiantian Ren ()
Additional contact information
Shirong Zhao: School of Finance, Dongbei University of Finance and Economics, Dalian, Liaoning, 116025, China
Kristiaan Kerstens: IESEG School of Management, Univ. Lille, CNRS, UMR 9221 - LEM - Lille Economie Management, F-59000 Lille, France
Tiantian Ren: IESEG School of Management, Univ. Lille, CNRS, UMR 9221 - LEM - Lille Economie Management, F-59000 Lille, France

No 2026-EQM-02, Working Papers from IESEG School of Management

Abstract: Statistical tests of the convexity assumption for full frontier technologies are still rather rarely applied. We employ existing order-a and order-m partial frontier estimators for production technologies. Since these partial frontier technology estimators have favourable statistical properties, this permits testing convexity using a simple statistical test comparing densities. Using a panel of electric power generation plants in the US we find strong evidence against convexity for most years using both order-a and order-m partial production frontiers. These new empirical results imply that empirical researchers must be cautious about invoking the –mostly implicit– convexity assumption when estimating technologies. Anyway, it is clear that convexity needs to be tested.

Keywords: Convexity; Technology; Robust frontier; Partial frontier; Order-m; Order-a. (search for similar items in EconPapers)
JEL-codes: C12 D24 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2026-04
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.ieseg.fr/wp-content/uploads/2026/04/2026-EQM-02.pdf (application/pdf)

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:ies:wpaper:e202604

Access Statistics for this paper

More papers in Working Papers from IESEG School of Management Contact information at EDIRC.
Bibliographic data for series maintained by Lies BOUTEN ().