𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Inference in dynamic stochastic frontier models

✍ Scribed by Efthymios G. Tsionas

Publisher
John Wiley and Sons
Year
2006
Tongue
English
Weight
87 KB
Volume
21
Category
Article
ISSN
0883-7252

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

An important issue in models of technical efficiency measurement concerns the temporal behaviour of inefficiency. Consideration of dynamic models is necessary but inference in such models is complicated. In this paper we propose a stochastic frontier model that allows for technical inefficiency effects and dynamic technical inefficiency, and use Bayesian inference procedures organized around data augmentation techniques to provide inferences. Also provided are firm‐specific efficiency measures. The new methods are applied to a panel of large US commercial banks over the period 1989–2000. Copyright Β© 2006 John Wiley & Sons, Ltd.

πŸ“œ SIMILAR VOLUMES

Dynamic stochastic copula models: estima
Dynamic stochastic copula models: estimation, inference and applications
✍ Christian M. Hafner; Hans Manner πŸ“‚ Article πŸ“… 2010 πŸ› John Wiley and Sons 🌐 English βš– 389 KB

## SUMMARY We propose a new dynamic copula model in which the parameter characterizing dependence follows an autoregressive process. As this model class includes the Gaussian copula with stochastic correlation process, it can be viewed as a generalization of multivariate stochastic volatility model

Stochastic frontier models with random c
Stochastic frontier models with random coefficients
✍ Efthymios G. Tsionas πŸ“‚ Article πŸ“… 2002 πŸ› John Wiley and Sons 🌐 English βš– 185 KB

## Abstract The paper proposes a stochastic frontier model with random coefficients to separate technical inefficiency from technological differences across firms, and free the frontier model from the restrictive assumption that all firms must share exactly the same technological possibilities. Inf

Finite sample inference methods for dyna
Finite sample inference methods for dynamic energy demand models
✍ Jean-Thomas Bernard; Nadhem Idoudi; Lynda Khalaf; ClΓ©ment YΓ©lou πŸ“‚ Article πŸ“… 2007 πŸ› John Wiley and Sons 🌐 English βš– 147 KB

## Abstract This paper considers finite sample motivated inference methods in dynamic energy demand models, in which case commonly used econometric methods remain asymptotic. We focus on structural stability, and on exact confidence set estimation of elasticities. We account for intractable and nui