THE EM ALGORITHM FOR STANDARD STOCHASTIC FRONTIER MODELS
AUTOR(ES)
Andrade, Bernardo B. de
FONTE
Pesqui. Oper.
DATA DE PUBLICAÇÃO
02/12/2019
RESUMO
ABSTRACT 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.
