Consequences of omitting relevant inputs on the quality of the data envelopment analysis under different input correlation structures
This paper establishes the consequences of a wrong specification on the quality of the data envelopment analysis. Specifically, the case of omitting a relevant variable in the input oriented problem is analyzed when there are different correlation structures between the inputs. It is established tha...
- Autores:
-
Ramírez Hassan, Andrés
- Tipo de recurso:
- Fecha de publicación:
- 2008
- Institución:
- Universidad EAFIT
- Repositorio:
- Repositorio EAFIT
- Idioma:
- eng
- OAI Identifier:
- oai:repository.eafit.edu.co:10784/556
- Acceso en línea:
- http://hdl.handle.net/10784/556
- Palabra clave:
- Efficiency
Data Envelopment Analysis
Monte Carlo Simulation
Input Correlation Structure
- Rights
- License
- Acceso abierto