Probabilistic productive technology model and partial production frontiers : an applicationfor Lithuanian agriculture

Tomas Balezentis, Alvydas Balezentis

Research output: Contribution to journalArticle

Abstract

The paper presents the non-parametric benchmarking technique, viz. Free Disposal Hull (FDH), along with its probabilistic extensions. Indeed, the frontier methods are rather sensitive to outliers. The probabilistic methodology, therefore, is useful when handling the practical problems of benchmarking. The paper aimed at analysing the patterns of efficiency of Lithuanian family farms with respect to the uncertain data. The latter aim was achieved by the virtue of the probabilistic production functions. The sensitivity of the efficiency scores estimated for the Lithuanian family farms was analysed by manipulating the numbers of randomly drawn benchmark observation estimations and thus constructing respective order—m frontiers. The livestock farms appeared to be the most efficient, or even super-efficient, independent of the model orientation or the order of the frontier. The application o f the order-alpha frontier also confirmed these results.
Original languageEnglish
Pages (from-to)141-146
JournalJournal of young scientists
Issue number1
Publication statusPublished - 2014

Fingerprint

family farms
agriculture
production functions
hulls
livestock
methodology
farms

Keywords

  • Efficiency
  • Family farms
  • Partial frontier

Cite this

@article{1278c70142474df0a7c55eba1c25f9cd,
title = "Probabilistic productive technology model and partial production frontiers : an applicationfor Lithuanian agriculture",
abstract = "The paper presents the non-parametric benchmarking technique, viz. Free Disposal Hull (FDH), along with its probabilistic extensions. Indeed, the frontier methods are rather sensitive to outliers. The probabilistic methodology, therefore, is useful when handling the practical problems of benchmarking. The paper aimed at analysing the patterns of efficiency of Lithuanian family farms with respect to the uncertain data. The latter aim was achieved by the virtue of the probabilistic production functions. The sensitivity of the efficiency scores estimated for the Lithuanian family farms was analysed by manipulating the numbers of randomly drawn benchmark observation estimations and thus constructing respective order—m frontiers. The livestock farms appeared to be the most efficient, or even super-efficient, independent of the model orientation or the order of the frontier. The application o f the order-alpha frontier also confirmed these results.",
keywords = "Efficiency, Family farms, Partial frontier",
author = "Tomas Balezentis and Alvydas Balezentis",
year = "2014",
language = "English",
pages = "141--146",
journal = "Jaunųjų mokslininkų darbai",
issn = "1648-8776",
publisher = "Šiaulių universiteto leidykla",
number = "1",

}

TY - JOUR

T1 - Probabilistic productive technology model and partial production frontiers : an applicationfor Lithuanian agriculture

AU - Balezentis, Tomas

AU - Balezentis, Alvydas

PY - 2014

Y1 - 2014

N2 - The paper presents the non-parametric benchmarking technique, viz. Free Disposal Hull (FDH), along with its probabilistic extensions. Indeed, the frontier methods are rather sensitive to outliers. The probabilistic methodology, therefore, is useful when handling the practical problems of benchmarking. The paper aimed at analysing the patterns of efficiency of Lithuanian family farms with respect to the uncertain data. The latter aim was achieved by the virtue of the probabilistic production functions. The sensitivity of the efficiency scores estimated for the Lithuanian family farms was analysed by manipulating the numbers of randomly drawn benchmark observation estimations and thus constructing respective order—m frontiers. The livestock farms appeared to be the most efficient, or even super-efficient, independent of the model orientation or the order of the frontier. The application o f the order-alpha frontier also confirmed these results.

AB - The paper presents the non-parametric benchmarking technique, viz. Free Disposal Hull (FDH), along with its probabilistic extensions. Indeed, the frontier methods are rather sensitive to outliers. The probabilistic methodology, therefore, is useful when handling the practical problems of benchmarking. The paper aimed at analysing the patterns of efficiency of Lithuanian family farms with respect to the uncertain data. The latter aim was achieved by the virtue of the probabilistic production functions. The sensitivity of the efficiency scores estimated for the Lithuanian family farms was analysed by manipulating the numbers of randomly drawn benchmark observation estimations and thus constructing respective order—m frontiers. The livestock farms appeared to be the most efficient, or even super-efficient, independent of the model orientation or the order of the frontier. The application o f the order-alpha frontier also confirmed these results.

KW - Efficiency

KW - Family farms

KW - Partial frontier

M3 - Article

SP - 141

EP - 146

JO - Jaunųjų mokslininkų darbai

JF - Jaunųjų mokslininkų darbai

SN - 1648-8776

IS - 1

ER -