Flexible mixture modelling of stochastic frontiers
Griffin, Jim E. and Steel, Mark F. J.. (2008) Flexible mixture modelling of stochastic frontiers. Journal of Productivity Analysis, Vol.29 (No.1). pp. 33-50. ISSN 0895-562XFull text not available from this repository.
Official URL: http://dx.doi.org/10.1007/s11123-007-0064-4
This paper introduces new and flexible classes of inefficiency distributions for stochastic frontier models. We consider both generalized gamma distributions and mixtures of generalized gamma distributions. These classes cover many interesting cases and accommodate both positively and negatively skewed composed error distributions. Bayesian methods allow for useful inference with carefully chosen prior distributions. We recommend a two-component mixture model where a sensible amount of structure is imposed through the prior to distinguish the components, which are given an economic interpretation. This setting allows for efficiencies to depend on firm characteristics, through the probability of belonging to either component. Issues of label-switching and separate identification of both the measurement and inefficiency errors are also examined. Inference methods through MCMC with partial centring are outlined and used to analyse both simulated and real data. An illustration using hospital cost data is discussed in some detail.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics
T Technology > T Technology (General)
|Divisions:||Faculty of Science > Statistics|
|Library of Congress Subject Headings (LCSH):||Gamma functions, Distribution (Probability theory), Stochastic models, Bayesian statistical decision theory, Production control -- Mathematical models, Industrial efficiency -- Mathematical models|
|Journal or Publication Title:||Journal of Productivity Analysis|
|Publisher:||Springer New York LLC|
|Official Date:||February 2008|
|Number of Pages:||18|
|Page Range:||pp. 33-50|
Actions (login required)