Stochastic Frontier approach and Data Envelopment Analysis to Total Factor Productivity and efficiency measurement of Bangladeshi rice.
The objective of this paper is to apply the Translog Stochastic Frontier production model (SFA) and Data Envelopment Analysis (DEA) to estimate efficiencies over time and the Total Factor Productivity (TFP) growth rate for Bangladeshi rice crops (Aus, Aman and Boro) throughout the most recent data a...
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2012-01-01
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doaj-8815f9e0f27c4af5bde9259692eddcc62020-11-25T02:26:58ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-01710e4608110.1371/journal.pone.0046081Stochastic Frontier approach and Data Envelopment Analysis to Total Factor Productivity and efficiency measurement of Bangladeshi rice.Md Kamrul HossainAnton Abdulbasah KamilMd Azizul BatenAdli MustafaThe objective of this paper is to apply the Translog Stochastic Frontier production model (SFA) and Data Envelopment Analysis (DEA) to estimate efficiencies over time and the Total Factor Productivity (TFP) growth rate for Bangladeshi rice crops (Aus, Aman and Boro) throughout the most recent data available comprising the period 1989-2008. Results indicate that technical efficiency was observed as higher for Boro among the three types of rice, but the overall technical efficiency of rice production was found around 50%. Although positive changes exist in TFP for the sample analyzed, the average growth rate of TFP for rice production was estimated at almost the same levels for both Translog SFA with half normal distribution and DEA. Estimated TFP from SFA is forecasted with ARIMA (2, 0, 0) model. ARIMA (1, 0, 0) model is used to forecast TFP of Aman from DEA estimation.http://europepmc.org/articles/PMC3471888?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Md Kamrul Hossain Anton Abdulbasah Kamil Md Azizul Baten Adli Mustafa |
spellingShingle |
Md Kamrul Hossain Anton Abdulbasah Kamil Md Azizul Baten Adli Mustafa Stochastic Frontier approach and Data Envelopment Analysis to Total Factor Productivity and efficiency measurement of Bangladeshi rice. PLoS ONE |
author_facet |
Md Kamrul Hossain Anton Abdulbasah Kamil Md Azizul Baten Adli Mustafa |
author_sort |
Md Kamrul Hossain |
title |
Stochastic Frontier approach and Data Envelopment Analysis to Total Factor Productivity and efficiency measurement of Bangladeshi rice. |
title_short |
Stochastic Frontier approach and Data Envelopment Analysis to Total Factor Productivity and efficiency measurement of Bangladeshi rice. |
title_full |
Stochastic Frontier approach and Data Envelopment Analysis to Total Factor Productivity and efficiency measurement of Bangladeshi rice. |
title_fullStr |
Stochastic Frontier approach and Data Envelopment Analysis to Total Factor Productivity and efficiency measurement of Bangladeshi rice. |
title_full_unstemmed |
Stochastic Frontier approach and Data Envelopment Analysis to Total Factor Productivity and efficiency measurement of Bangladeshi rice. |
title_sort |
stochastic frontier approach and data envelopment analysis to total factor productivity and efficiency measurement of bangladeshi rice. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2012-01-01 |
description |
The objective of this paper is to apply the Translog Stochastic Frontier production model (SFA) and Data Envelopment Analysis (DEA) to estimate efficiencies over time and the Total Factor Productivity (TFP) growth rate for Bangladeshi rice crops (Aus, Aman and Boro) throughout the most recent data available comprising the period 1989-2008. Results indicate that technical efficiency was observed as higher for Boro among the three types of rice, but the overall technical efficiency of rice production was found around 50%. Although positive changes exist in TFP for the sample analyzed, the average growth rate of TFP for rice production was estimated at almost the same levels for both Translog SFA with half normal distribution and DEA. Estimated TFP from SFA is forecasted with ARIMA (2, 0, 0) model. ARIMA (1, 0, 0) model is used to forecast TFP of Aman from DEA estimation. |
url |
http://europepmc.org/articles/PMC3471888?pdf=render |
work_keys_str_mv |
AT mdkamrulhossain stochasticfrontierapproachanddataenvelopmentanalysistototalfactorproductivityandefficiencymeasurementofbangladeshirice AT antonabdulbasahkamil stochasticfrontierapproachanddataenvelopmentanalysistototalfactorproductivityandefficiencymeasurementofbangladeshirice AT mdazizulbaten stochasticfrontierapproachanddataenvelopmentanalysistototalfactorproductivityandefficiencymeasurementofbangladeshirice AT adlimustafa stochasticfrontierapproachanddataenvelopmentanalysistototalfactorproductivityandefficiencymeasurementofbangladeshirice |
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