Bootstrap DEA and hypothesis testing

Arbeitspapier

Bootstrapping non-parametric models is a fairly complicated exercise which is associated with implicit assumptions or requirements that are not always obvious to the non-expert user. Bootstrap DEA is a significant development of the past decade; however, some of its assumptions and properties are still quite unclear, which may lead to mistakes in implementation and hypothesis testing. This paper clarifies these issues and proposes a hypothesis testing procedure, along with its limitations, which could be extended to test almost any hypothesis in bootstrap DEA. Moreover, it enhances the intuition behind bootstrap DEA and highlights logical and theoretical pitfalls that should be avoided.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Cardiff Economics Working Papers ; No. E2012/18

Classification and Topics

• Classification: Wirtschaft ; Hypothesis Testing: General ; Semiparametric and Nonparametric Methods: General ; Statistical Simulation Methods: General ; Optimization Techniques; Programming Models; Dynamic Analysis ; Input-Output Models
• Subject: Data Envelopment Analysis ; Efficiency ; Bootstrap ; Bootstrap DEA ; Hypothesis Testing

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Tziogkidis, Panagiotis
• Event: Veröffentlichung
• (who): Cardiff University, Cardiff Business School
• (where): Cardiff
• (when): 2012

Further information

• Handle: http://hdl.handle.net/10419/65746
• Last update: 10.03.2025, 11:41 AM CET