Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models

In this paper we describe the use of modern numerical integration methods for making posterior inferences in composed error stochastic frontier models for panel data or individual cross-sections.Two Monte Carlo methods have been used in practical applications.We survey these two methods in some detail and argue that Gibbs sampling methods can greatly reduce the computational difficulties involved in analyzing such models.

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Year of publication:	1996
Authors:	Osiewalski, J. ; Steel, M.F.J.
Institutions:	Tilburg University, Center for Economic Research
Subject:	Monte Carlo Technique \| Numerical Integration

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Extent:	application/pdf
Series:	Discussion Paper.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series CentER Discussion Paper Number 1996-03
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011091739