The EM algorithm for standard stochastic frontier models

• Autor(a) principal: Andrade, Bernardo Borba de
• Data de Publicação: 2019
• Outros Autores: Souza, Geraldo da Silva e
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UnB
• Texto Completo: https://repositorio.unb.br/handle/10482/36305; https://doi.org/10.1590/0101-7438.2019.039.03.0361; http://orcid.org/0000-0003-4688-9733
• topic: Eficiência; Aceleração EM; Probabilidades; Algoritmos

The Expectation-Maximization (EM) algorithm is developed for the stochastic frontier models most used in practice with cross-section data. The resulting algorithms can be easily programmed into a computer and are shown to be worthy alternatives to general-purpose optimization routines currently used. The algorithms for the half normal and the exponential models have closed-form expressions whereas those for the truncated normal and gamma models will require the numerical solution of a nonlinear equation. Implementations of the EM algorithm either as a stand-alone routine or in accelerated form and also combined with Newton-like methods are discussed. We provide illustrations, along with R tools, for cost and production frontiers.