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

Research output: Contribution to journalJournal articlepeer-review

Standard

Addressing endogeneity when estimating stochastic ray production frontiers : a Bayesian approach. / Tsionas, Mike; Izzeldin, Marwan ; Henningsen, Arne; Paravalos, Evaggelos .

In: Empirical Economics, Vol. 62, 2022, p. 1345–1363.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Tsionas, M, Izzeldin, M, Henningsen, A & Paravalos, E 2022, 'Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach', Empirical Economics, vol. 62, pp. 1345–1363. https://doi.org/10.1007/s00181-021-02060-0

APA

Tsionas, M., Izzeldin, M., Henningsen, A., & Paravalos, E. (2022). Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach. Empirical Economics, 62, 1345–1363. https://doi.org/10.1007/s00181-021-02060-0

Vancouver

Tsionas M, Izzeldin M, Henningsen A, Paravalos E. Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach. Empirical Economics. 2022;62:1345–1363. https://doi.org/10.1007/s00181-021-02060-0

Author

Tsionas, Mike ; Izzeldin, Marwan ; Henningsen, Arne ; Paravalos, Evaggelos . / Addressing endogeneity when estimating stochastic ray production frontiers : a Bayesian approach. In: Empirical Economics. 2022 ; Vol. 62. pp. 1345–1363.

Bibtex

@article{e5d1afaaf98f4afcb6fee6dfffa5472b,
title = "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach",
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.",
author = "Mike Tsionas and Marwan Izzeldin and Arne Henningsen and Evaggelos Paravalos",
year = "2022",
doi = "10.1007/s00181-021-02060-0",
language = "English",
volume = "62",
pages = "1345–1363",
journal = "Empirical Economics",
issn = "0377-7332",
publisher = "Springer",

}

RIS

TY - JOUR

T1 - Addressing endogeneity when estimating stochastic ray production frontiers

T2 - a Bayesian approach

AU - Tsionas, Mike

AU - Izzeldin, Marwan

AU - Henningsen, Arne

AU - Paravalos, Evaggelos

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

U2 - 10.1007/s00181-021-02060-0

DO - 10.1007/s00181-021-02060-0

M3 - Journal article

VL - 62

SP - 1345

EP - 1363

JO - Empirical Economics

JF - Empirical Economics

SN - 0377-7332

ER -

ID: 262804691