Estimating a mixture of stochastic frontier regression models via the em algorithm: A multiproduct cost function application

By Steven B. Caudill *. 2003

64 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/bf6955e55965b1cc509ac2eae919398a46feafa2

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. Christopher F. Parmeter
2. Luis Orea
3. Subal C. Kumbhakar
4. William H. Greene
5. Lourdes Trujillo
6. C. O'Donnell
7. N. Key
8. MarI´a Manuela González

In Management Science and Operations Research

1. Christopher F. Parmeter
2. Luis Orea
3. Subal C. Kumbhakar
4. William H. Greene
5. Lourdes Trujillo
6. C. O'Donnell
7. N. Key
8. MarI´a Manuela González

Citations in the corpus

• Higher education institutions costs and efficiency: Taking the decomposition a further step (2009, unknown): “This is, in effect, the latent class estimator (Caudill, 2003).”
• Efficiency Analysis: A Primer on Recent Advances (2014, methodology): “Although the models of Caudill & Ford (1993), Caudill et al.”
• Efficiency measurement using a latent class stochastic frontier model (2004, background): “In particular, Caudill (2003) introduces an expectation-maximization (EM) algorithm to estimate a mixture of two stochastic cost frontiers in the presence of no sample separation information.”