Estimating a Changepoint, Boundary, or Frontier in the Presence of Observation Error
By Peter Hall, Léopold Simar. 2002
116 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/f693e9dc94e875db4f5f57b93040e20670b7d41f
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
- Mika Kortelainen
- Timo Kuosmanen
- Léopold Simar
- Subal C. Kumbhakar
- Efthymios G. Tsionas
- William H. Greene
- Byeong U. Park
- Paul Wilson
In Management Science and Operations Research
- Timo Kuosmanen
- Mika Kortelainen
- Léopold Simar
- Efthymios G. Tsionas
- Subal C. Kumbhakar
- William H. Greene
- Byeong U. Park
- Paul Wilson
In Statistics and Probability
- Mika Kortelainen
- Léopold Simar
- Timo Kuosmanen
- Subal C. Kumbhakar
- Efthymios G. Tsionas
- Byeong U. Park
- Paul Wilson
- Athanasios Kottas
Citations in the corpus
- 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).”
- Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints (2012, methodology): “However, in the cross-sectional setting it is impossible to distinguish between inefficiency and noise without imposing some distributional assumptions (see Hall and Simar 2002, for a detailed analysis).”
- How to improve the performances of DEA/FDH estimators in the presence of noise? (2007, unknown): “We know from Hall and Simar (2002) that under a so general setup, the model is not identified.”