Cookies?
Library Header Image
LSE Research Online LSE Library Services

Bayesian inference in threshold stochastic frontier models

Tsionas, Efthymios G. and Tran, Kien C. and Michaelides, Panayotis G. (2017) Bayesian inference in threshold stochastic frontier models. Empirical Economics. ISSN 0377-7332

[img] Text - Accepted Version
Restricted to Repository staff only until 15 December 2018.

Download (1MB) | Request a copy
Identification Number: 10.1007/s00181-017-1364-9

Abstract

In this paper, we generalize the stochastic frontier model to allow for heterogeneous technologies and inefficiencies in a structured way that allows for learning and adapting. We propose a general model and various special cases, organized around the idea that there is switching or transition from one technology to the other(s), and construct threshold stochastic frontier models. We suggest Bayesian inferences for the general model proposed here and its special cases using Gibbs sampling with data augmentation. The new techniques are applied, with very satisfactory results, to a panel of world production functions using, as switching or transition variables, human capital, age of capital stock (representing input quality), as well as a time trend to capture structural switching

Item Type: Article
Official URL: http://doi.org/10.1007/s00181-017-1364-9
Additional Information: © Springer-Verlag GmbH Germany
Divisions: Systemic Risk Centre
Subjects: H Social Sciences > HA Statistics
JEL classification: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C11 - Bayesian Analysis
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C13 - Estimation
Sets: Research centres and groups > Systemic Risk Centre
Date Deposited: 23 Feb 2018 14:35
Last Modified: 23 Feb 2018 14:49
URI: http://eprints.lse.ac.uk/id/eprint/86848

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics