RT Generic
T1 Stochastic frontier models: a bayesian perspective
A1 Koop, Gary
A1 Osiewalski, Jacek
A1 Steel, Mark F.J.
A1 Broeck, Julien Van den
A2 Universidad Carlos III de Madrid. Departamento de Economía, 
AB A Bayesian approach to estimation, prediction and model comparison in composed error production models is presented. A broad range of distributions on the inefficiency term define the contending models, which can either be treated separately or pooled. Posterior results are derived for the individual efficiencies as well as for the parameters, and the differences with the usual sampling-theory approach are highlighted. The required numerical integrations are handled by Monte Carlo methods with Importance Sampling, and an empirical example illustrates the procedures.
SN 2340-5031
YR 1992
FD 1992-04
LK https://hdl.handle.net/10016/2823
UL https://hdl.handle.net/10016/2823
LA eng
DS e-Archivo
RD 1 sept. 2024