A Generalized Maximum Entropy Stochastic Frontier Measuring Productivity Accounting for Spatial Dependency

A Generalized Maximum Entropy Stochastic Frontier Measuring Productivity Accounting for Spatial Dependency

In this paper, a stochastic frontier model accounting for spatial dependency is developed using generalized maximum entropy estimation. An application is made for measuring total factor productivity in European agriculture. The empirical results show that agricultural productivity growth in Europe i...

Full description

Bibliographic Details
Main Authors: Valerien Pede, Axel Tonini
Format: Article
Language:English
Published: MDPI AG 2011-10-01
Series:Entropy
Subjects:
stochastic frontier
spatial dependency
generalized maximum entropy
Online Access:http://www.mdpi.com/1099-4300/13/11/1916/
id doaj-dc80e4f2be4e4a3d8eb064695d6d4989
record_format Article
spelling doaj-dc80e4f2be4e4a3d8eb064695d6d49892020-11-24T23:41:34ZengMDPI AGEntropy1099-43002011-10-0113111916192710.3390/e13111916A Generalized Maximum Entropy Stochastic Frontier Measuring Productivity Accounting for Spatial DependencyValerien PedeAxel ToniniIn this paper, a stochastic frontier model accounting for spatial dependency is developed using generalized maximum entropy estimation. An application is made for measuring total factor productivity in European agriculture. The empirical results show that agricultural productivity growth in Europe is driven by upward movements of technology over time through technological developments. Results are then compared for a situation in which spatial dependency in the technical inefficiency effects is not accounted.http://www.mdpi.com/1099-4300/13/11/1916/stochastic frontierspatial dependencygeneralized maximum entropy
collection DOAJ
language English
format Article
sources DOAJ
author Valerien Pede
Axel Tonini
spellingShingle Valerien Pede
Axel Tonini
A Generalized Maximum Entropy Stochastic Frontier Measuring Productivity Accounting for Spatial Dependency
Entropy
stochastic frontier
spatial dependency
generalized maximum entropy
author_facet Valerien Pede
Axel Tonini
author_sort Valerien Pede
title A Generalized Maximum Entropy Stochastic Frontier Measuring Productivity Accounting for Spatial Dependency
title_short A Generalized Maximum Entropy Stochastic Frontier Measuring Productivity Accounting for Spatial Dependency
title_full A Generalized Maximum Entropy Stochastic Frontier Measuring Productivity Accounting for Spatial Dependency
title_fullStr A Generalized Maximum Entropy Stochastic Frontier Measuring Productivity Accounting for Spatial Dependency
title_full_unstemmed A Generalized Maximum Entropy Stochastic Frontier Measuring Productivity Accounting for Spatial Dependency
title_sort generalized maximum entropy stochastic frontier measuring productivity accounting for spatial dependency
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2011-10-01
description In this paper, a stochastic frontier model accounting for spatial dependency is developed using generalized maximum entropy estimation. An application is made for measuring total factor productivity in European agriculture. The empirical results show that agricultural productivity growth in Europe is driven by upward movements of technology over time through technological developments. Results are then compared for a situation in which spatial dependency in the technical inefficiency effects is not accounted.
topic stochastic frontier
spatial dependency
generalized maximum entropy
url http://www.mdpi.com/1099-4300/13/11/1916/
work_keys_str_mv AT valerienpede ageneralizedmaximumentropystochasticfrontiermeasuringproductivityaccountingforspatialdependency
AT axeltonini ageneralizedmaximumentropystochasticfrontiermeasuringproductivityaccountingforspatialdependency
AT valerienpede generalizedmaximumentropystochasticfrontiermeasuringproductivityaccountingforspatialdependency
AT axeltonini generalizedmaximumentropystochasticfrontiermeasuringproductivityaccountingforspatialdependency
_version_ 1725506571892424704

Similar Items