How to improve the performances of DEA/FDH estimators in the presence of noise?

By Léopold Simar. 2007

118 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/87c323742ddc1148b615bceef4a6df746ce578bd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Mika Kortelainen
2. Timo Kuosmanen
3. Léopold Simar
4. Subal C. Kumbhakar
5. Efthymios G. Tsionas
6. William H. Greene
7. Byeong U. Park
8. Paul Wilson

In Management Science and Operations Research

1. Timo Kuosmanen
2. Mika Kortelainen
3. Léopold Simar
4. Efthymios G. Tsionas
5. Subal C. Kumbhakar
6. William H. Greene
7. Byeong U. Park
8. Paul Wilson

Citations in the corpus

• Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints (2012, methodology): “Using this DGP, Simar and Zelenyuk construct six altenative scenarios corresponding to different values of sample size n and parameter nts .”
• Nonparametric stochastic frontiers: A local maximum likelihood approach (2007, background): “The introduction of noise in a full nonparametric setup is problematic due to identification problems (see Hall and Simar, 2002 and Simar, 2003).”