Addressing endogeneity when estimating stochastic ray production frontiers:a Bayesian approach

Tsionas, Mike and Izzeldin, Marwan and Henningsen, Arne and Paravalos, Evaggelos (2021) Addressing endogeneity when estimating stochastic ray production frontiers:a Bayesian approach. Empirical Economics. ISSN 0377-7332

[img]
Text (SRPF_Bayesian)
SRPF_Bayesian.pdf - Accepted Version
Restricted to Repository staff only until 2 May 2022.
Available under License Creative Commons Attribution-NonCommercial.

Download (586kB)

Abstract

We propose a Bayesian approach for inference in the stochastic ray production frontier (SRPF), which can model multiple-input–multiple-output production technologies even in case of zero output quantities, i.e., if some outputs are not produced by some of the firms. However, the econometric estimation of the SRPF—as the estimation of distance functions in general—is susceptible to endogeneity problems. To address these problems, we apply a profit-maximizing framework to derive a system of equations after incorporating technical inefficiency. As the latter enters non-trivially into the system of equations and as the Jacobian is highly complicated, we use Monte Carlo methods of inference. Using US banking data to illustrate our innovative approach, we also address the problems of missing prices and the dependence on the ordering of the outputs via model averaging.

Item Type:
Journal Article
Journal or Publication Title:
Empirical Economics
Additional Information:
The final publication is available at Springer via http://dx.doi.org/10.1007/s00181-021-02060-0
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
ID Code:
156039
Deposited By:
Deposited On:
11 Jun 2021 10:45
Refereed?:
Yes
Published?:
Published
Last Modified:
06 Oct 2021 08:18