Artikel
Stochastic frontier models with dependent errors based on normal and exponential margins
Following the recent work of Gómez-Déniz and Pérez-Rodríguez (2014), this paper extends the results obtained there to the normal-exponential distribution with dependence. Accordingly, the main aim of the present paper is to enhance stochastic production frontier and stochastic cost frontier modelling by proposing a bivariate distribution for dependent errors which allows us to nest the classical models. Closed-form expressions for the error term and technical efficiency are provided. An illustration using real data from the econometric literature is provided to show the applicability of the model proposed.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Revista de Métodos Cuantitativos para la Economía y la Empresa ; ISSN: 1886-516X ; Volume: 23 ; Year: 2017 ; Pages: 3-23 ; Sevilla: Universidad Pablo de Olavide
- Klassifikation
-
Wirtschaft
Econometrics
Estimation: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Model Construction and Estimation
- Thema
-
technical and cost efficiencies
stochastic frontier
marginal distribution
dependence
Sarmanov model
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Gómez-Déniz, Emilio
Pérez-Rodríguez, Jorge V.
- Ereignis
-
Veröffentlichung
- (wer)
-
Universidad Pablo de Olavide
- (wo)
-
Sevilla
- (wann)
-
2017
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Gómez-Déniz, Emilio
- Pérez-Rodríguez, Jorge V.
- Universidad Pablo de Olavide
Entstanden
- 2017
Ähnliche Objekte (12)
Stochastic Frontier Production Function With Errors-In-Variables
Exponential families of stochastic processes
Spatial Stochastic Frontier Models
Computation of compound distributions i: Aliasing errors and exponential tilting
Estimating Stochastic Ray Production Frontiers
Frontiers and boundaries: encounters on China’s margins
Pseudolikelihood estimation of the stochastic frontier model
Pseudolikelihood Estimation of the Stochastic Frontier Model
International Labor Underpayment: A Stochastic Frontier Approach
Robust Bayesian inference in stochastic frontier models
Pseudolikelihood estimation of the stochastic frontier model
New insights into the stochastic ray production frontier
Stochastic Frontier Production Function With Errors-In-Variables
Exponential families of stochastic processes
Spatial Stochastic Frontier Models
Computation of compound distributions i: Aliasing errors and exponential tilting
Estimating Stochastic Ray Production Frontiers
Frontiers and boundaries: encounters on China’s margins
Pseudolikelihood estimation of the stochastic frontier model
Pseudolikelihood Estimation of the Stochastic Frontier Model
International Labor Underpayment: A Stochastic Frontier Approach
Robust Bayesian inference in stochastic frontier models
Pseudolikelihood estimation of the stochastic frontier model
New insights into the stochastic ray production frontier
Stochastic Frontier Production Function With Errors-In-Variables
Exponential families of stochastic processes
Spatial Stochastic Frontier Models
Computation of compound distributions i: Aliasing errors and exponential tilting
Estimating Stochastic Ray Production Frontiers
Frontiers and boundaries: encounters on China’s margins
Pseudolikelihood estimation of the stochastic frontier model
Pseudolikelihood Estimation of the Stochastic Frontier Model
International Labor Underpayment: A Stochastic Frontier Approach
Robust Bayesian inference in stochastic frontier models
Pseudolikelihood estimation of the stochastic frontier model