Partial local and global returns to scale in efficiency analysis with different technologies

Local and global returns to scale are two different characteristics of production frontiers. The former is a marginal characteristic that reflects the elasticity of response of the vector of outputs to small proportional changes of the vector of inputs. In contrast, the latter is indicative of the direction of the movement for the unit under the assessment towards its optimal scale known as the most productive scale size. It is known that, if the technology is convex, the local and global characterizations of returns to scale are identical. However, in a nonconvex technology, the two characterizations are generally different. The purpose of this paper is to extend these results to scenarios in which returns to scale are evaluated only with respect to selected subvectors of inputs and outputs, for example, those that are considered discretionary for the unit under the assessment.

Authors

Institutions

Publication Details

Journal
Journal of Productivity Analysis
Published
2025-11-11
DOI
https://doi.org/10.1007/s11123-025-00791-1
Primary Topic
Efficiency Analysis Using DEA
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Partial local and global returns to scale in efficiency analysis with different technologies

Grammatoula Papaioannou, Victor V. Podinovski
Journal of Productivity Analysis
Efficiency Analysis Using DEA
article

Partial local and global returns to scale in efficiency analysis with different technologies

Grammatoula Papaioannou, Victor V. Podinovski
article en

Abstract

Local and global returns to scale are two different characteristics of production frontiers. The former is a marginal characteristic that reflects the elasticity of response of the vector of outputs to small proportional changes of the vector of inputs. In contrast, the latter is indicative of the direction of the movement for the unit under the assessment towards its optimal scale known as the most productive scale size. It is known that, if the technology is convex, the local and global characterizations of returns to scale are identical. However, in a nonconvex technology, the two characterizations are generally different. The purpose of this paper is to extend these results to scenarios in which returns to scale are evaluated only with respect to selected subvectors of inputs and outputs, for example, those that are considered discretionary for the unit under the assessment.

Journal of Productivity AnalysisVol. 65(1)
Loughborough University (GB)
Openalex Percentile: Top 60%
Efficiency Analysis Using DEA
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.