Inferences from Cross-Sectional, Stochastic Frontier Models
By Léopold Simar, Paul Wilson. 2009
125 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/31d926263ec1877095f88d2c294c34481e0cc2e0
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
- W. Horrace
- Peng Zhou
- Timo Sipiläinen
- Antti Saastamoinen
- Liwei Fan
- Xun Zhou
In Management Science and Operations Research
- Timo Kuosmanen
- Mika Kortelainen
- W. Horrace
- Timo Sipiläinen
- Antti Saastamoinen
- Peng Zhou
- Natalia Kuosmanen
- Andrés J. Picazo‐Tadeo
Citations in the corpus
- Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints (2012, methodology): “In light of these complications, the parametric bootstrap method similar to Simar and Wilson (2009) would appear to be the best suited approach to statistical inference in the present context.”
- Moments of the truncated normal distribution (2015, background): “In a random sample from an unknown distribution a negative skewness may indicate that the distribution is not truncated normal (e.g., Waldman 1982; Carree 2002; Simar and Wilson 2009; Alamanidis and Sickles 2011; Almanidis et al. 2014).”