ROBUST STOCHASTIC PRODUCTION FRONTIER TO ESTIMATE TECHNICAL EFFICIENCY OF RICE FARMING IN SULAWESI SELATAN

The stochastic production frontier (SPF) is the stochastic frontier analysis (SFA) method used to estimate the production frontier by accounting for the existence of inefficiency. The standard SPF assumes that the noise component follows a Normal distribution and the inefficiency component follows a...

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Main Authors: Ismail Pranata, Anik Djuraidah, Muhammad Nur Aidi
Format: Article
Language:English
Published: Universitas Pattimura 2023-04-01
Series:Barekeng
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Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7398
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author Ismail Pranata
Anik Djuraidah
Muhammad Nur Aidi
author_facet Ismail Pranata
Anik Djuraidah
Muhammad Nur Aidi
author_sort Ismail Pranata
collection DOAJ
description The stochastic production frontier (SPF) is the stochastic frontier analysis (SFA) method used to estimate the production frontier by accounting for the existence of inefficiency. The standard SPF assumes that the noise component follows a Normal distribution and the inefficiency component follows a half-Normal distribution. The presence of outliers in the data will affect the inaccuracy in estimating the parameters and leads to an exaggerated spread of efficiency predictions. This study uses two alternative models, the first with SPF Normal-Gamma and the second with SPF Student's t-half Normal, then the results are compared with standard SPF. This study uses data from statistics Indonesia on the cost structure of paddy cultivation household survey in 2014. This study aims to examine the effect of changes in distribution assumptions on the standard SPF model in estimating parameter value and the technical efficiency score in the presence of outliers. The parameter coefficient estimates similar results that apply to three SPF models. Only the standard error value in the alternative SPF model tends to be smaller than the standard SPF model. The Normal-Gamma model performs better in assessing residual with smaller root mean square error (RMSE) than the others, but the results of the estimated technical efficiency still contain outliers. The Student's t-half Normal model estimates technical efficiency no longer contains outliers, the range is shorter than the other models, and the results of estimating technical efficiency are not monotonous in the distribution of residual tails.  The SPF Student's t-half Normal model is more robust in presence outliers than SPF Normal-half Normal and SPF Normal-Gamma.
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spelling doaj-art-c2e0a950f68d432fa37ed93f2949ef412025-08-20T03:37:33ZengUniversitas PattimuraBarekeng1978-72272615-30172023-04-011710391040010.30598/barekengvol17iss1pp0391-04007398ROBUST STOCHASTIC PRODUCTION FRONTIER TO ESTIMATE TECHNICAL EFFICIENCY OF RICE FARMING IN SULAWESI SELATANIsmail Pranata0Anik Djuraidah1Muhammad Nur Aidi2Department of Statistics, Faculty Mathematics and Natural Sciences, IPB University, IndonesiaDepartment of Statistics, Faculty Mathematics and Natural Sciences, IPB University, IndonesiaDepartment of Statistics, Faculty Mathematics and Natural Sciences, IPB University, IndonesiaThe stochastic production frontier (SPF) is the stochastic frontier analysis (SFA) method used to estimate the production frontier by accounting for the existence of inefficiency. The standard SPF assumes that the noise component follows a Normal distribution and the inefficiency component follows a half-Normal distribution. The presence of outliers in the data will affect the inaccuracy in estimating the parameters and leads to an exaggerated spread of efficiency predictions. This study uses two alternative models, the first with SPF Normal-Gamma and the second with SPF Student's t-half Normal, then the results are compared with standard SPF. This study uses data from statistics Indonesia on the cost structure of paddy cultivation household survey in 2014. This study aims to examine the effect of changes in distribution assumptions on the standard SPF model in estimating parameter value and the technical efficiency score in the presence of outliers. The parameter coefficient estimates similar results that apply to three SPF models. Only the standard error value in the alternative SPF model tends to be smaller than the standard SPF model. The Normal-Gamma model performs better in assessing residual with smaller root mean square error (RMSE) than the others, but the results of the estimated technical efficiency still contain outliers. The Student's t-half Normal model estimates technical efficiency no longer contains outliers, the range is shorter than the other models, and the results of estimating technical efficiency are not monotonous in the distribution of residual tails.  The SPF Student's t-half Normal model is more robust in presence outliers than SPF Normal-half Normal and SPF Normal-Gamma.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7398student’s tgammaoutlierstochastic production frontierstochastic frontier analysis
spellingShingle Ismail Pranata
Anik Djuraidah
Muhammad Nur Aidi
ROBUST STOCHASTIC PRODUCTION FRONTIER TO ESTIMATE TECHNICAL EFFICIENCY OF RICE FARMING IN SULAWESI SELATAN
Barekeng
student’s t
gamma
outlier
stochastic production frontier
stochastic frontier analysis
title ROBUST STOCHASTIC PRODUCTION FRONTIER TO ESTIMATE TECHNICAL EFFICIENCY OF RICE FARMING IN SULAWESI SELATAN
title_full ROBUST STOCHASTIC PRODUCTION FRONTIER TO ESTIMATE TECHNICAL EFFICIENCY OF RICE FARMING IN SULAWESI SELATAN
title_fullStr ROBUST STOCHASTIC PRODUCTION FRONTIER TO ESTIMATE TECHNICAL EFFICIENCY OF RICE FARMING IN SULAWESI SELATAN
title_full_unstemmed ROBUST STOCHASTIC PRODUCTION FRONTIER TO ESTIMATE TECHNICAL EFFICIENCY OF RICE FARMING IN SULAWESI SELATAN
title_short ROBUST STOCHASTIC PRODUCTION FRONTIER TO ESTIMATE TECHNICAL EFFICIENCY OF RICE FARMING IN SULAWESI SELATAN
title_sort robust stochastic production frontier to estimate technical efficiency of rice farming in sulawesi selatan
topic student’s t
gamma
outlier
stochastic production frontier
stochastic frontier analysis
url https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7398
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