arbiter
JournalsPricingAccount

Data Envelopment Analysis: From Foundations to Modern Advancements

Zhichao Wang & Valentin Zelenyuk

Foundations and Trends in Econometrics2024https://doi.org/10.1561/0800000040article
AJG 1ABDC C
Weight
0.50

What the paper says

Data envelopment analysis (DEA) is a mainstream method for efficiency and productivity analysis, widely applied in numerous fields, including the healthcare sector, banking, energy generation and distribution, and cross-country economic growth analysis. In this monograph, we aim to provide a compendious overview of DEA. We start with the DEA estimators in various scenarios, such as for estimating technology, cost, revenue, profit functions and related efficiency measures, and its popular variants based on different assumptions about the shape of technology. The statistical properties and extensions on DEA, such as analysis on covariates of efficiency, are also discussed and the practical tips for computations are provided.

2 citations

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1561/0800000040

Or copy a formatted citation

@article{zhichao2024,
  title        = {{Data Envelopment Analysis: From Foundations to Modern Advancements}},
  author       = {Zhichao Wang & Valentin Zelenyuk},
  journal      = {Foundations and Trends in Econometrics},
  year         = {2024},
  doi          = {https://doi.org/https://doi.org/10.1561/0800000040},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Data Envelopment Analysis: From Foundations to Modern Advancements

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.49 × 0.4 = 0.20
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.