• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.665-679
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• 2017

When measuring productive efficiency, often it is necessary to have knowledge of the production frontier function that shows the maximum possible output of production units as a function of inputs. Canonical parametric forms of the frontier function were initially considered under the framework of stochastic frontier model; however, several additional nonparametric methods have been developed over the last decade. Efforts have been recently made to impose shape constraints such as monotonicity and concavity on the non-parametric estimation of the frontier function; however, most existing methods along that direction suffer from unnecessary non-smooth points of the frontier function. In this paper, we propose methods to estimate the smooth frontier function with monotonicity for stochastic frontier models and investigate the effect of imposing a monotonicity constraint into the estimation of the frontier function and the finite dimensional parameters of the model. Simulation studies suggest that imposing the constraint provide better performance to estimate the frontier function, especially when the sample size is small or moderate. However, no apparent gain was observed concerning the estimation of the parameters of the error distribution regardless of sample size.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.292-302
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• 2018

This study proposes a Bayesian stochastic frontier model that is well-suited to productivity/efficiency analysis particularly using panel data. A unique feature of our proposal is that both production frontier and efficiency are estimable for each individual firm and their linkage to various firm characteristics enriches our understanding of the source of productivity/efficiency. Empirical application of the proposed analysis to Human Capital Corporate Panel data enables identification and quantification of the effects of Human Resource factors on firm efficiency in tandem with those of firm types on production frontier. A comprehensive description of the Markov Chain Monte Carlo estimation procedure is forwarded to facilitate the use of our proposed stochastic frontier analysis.

• The Journal of Fisheries Business Administration
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• v.43 no.2
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• pp.67-77
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• 2012

Based on the survey on aquaculture management status in Nohwa-eup, Bogil-myeon, Wando-eup in Wando region, this study aimed to estimate productive efficiencies of abalone aquaculture production using a stochastic frontier approach (SFA) and to find out their determinants. In the analysis, a Cobb-Douglas production function with an inefficiency term that follows an halfnormal distribution was assumed for the estimation of productive efficiencies. Then, based on the outcomes of productive efficiencies, determinants of productive efficiency were investigated using a tobit regression model. Results showed that the average inefficiency was estimated to be 10% and the production size would be a statistically significant variable for the production. In addition, it was shown that the cage installing method would be an important factor affecting to the level of productive efficiency.

• Economic Analysis
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• v.17 no.1
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• pp.103-130
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• 2011

This paper intends to provide applied economists which study the effects of research and development with valuable information on econometric model selection. It includes extensive discussion on econometric models which have been applied for the study on the relationship between research and development and productivity. In particular, it compares various stochastic production frontier models which have been developed recently. The discussion decomposes them into models with scaling property and the ones with nonscaling property as well as models with monotonic and nonmonotonic relationships between research and development and productivity. Finally, this paper applies the models to two different panel data sets (firm level data and country level data) and compare estimation results from competing econometric models.

• Korean Journal of Agricultural Science
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• v.37 no.3
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• pp.509-514
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• 2010

The purpose of this study is to analyze the technical efficiency and its determinants for Korean Apiculture farming by using from door to door and e-mail inquiry data. The analysis was implemented through the Cobb-Douglas stochastic frontier production function (SFPF) model including the technical inefficiency effect model for cross-sectional data. To measure the SFPF model, honey production was used for a dependent variable, and for input variables labor cost, preventive cost, material cost, feeding cost, depreciation cost were used. Farmer's age, farmer's career, farming scale, full-time or half-time firm and movement or fixed firm variables were used to measure the inefficiency effect model. The average technical efficiency on apiculture farming in Korea is estimated to be 0.8112. It means that there were technical inefficiency of about 18.88% in Korea apiculture farming. In this study there are some suggestions which could increase the technical efficiency of Korean apiculture farming.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8719-8727
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• 2015

The purpose of this study is to examine the production efficiency of Rose farm and to explain the factors of the inefficiency. To analysis the production efficiency, SFA(Stochastic Frontier Analysis) and DEA(Data Envelopment Analysis) methods are measured, and then, Tobit regression model is used to analysis the influential factors on the production efficiency. As a result, first, the production efficiency by SFA is 88.4%, and by DEA, results are 78.5% and 85.2% in the CRS and VRS model, respectively. In particular, the production efficiency of the measurement results of the two methods are complementary, it is described in the same order of efficiency of each management body. Second, the results of tobit model shows that 6 input-factors are significant, and seed/nursery and material costs, which have the largest regression coefficient value and positive effect on production efficiency, are the most influential factors. Therefore, the results of this study indicates Rose farm can enhance their management efficiency by increasing amount of the seed/nursery and material costs.

• Journal of Navigation and Port Research
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• v.29 no.1 s.97
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• pp.105-111
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• 2005

Recently, global terminal operotors are struggling to attract more cargoes into their ports through enlarging facilities and trying to be more efficient operotion Many researches on container terminal efficiency have been conducted, but most of the traditional studies are focused on the partial efficiency of the container terminal using quantitative questionnaires and basic statistical data In this paper, the Stochastic Frontier Model of the interaction among the variables was employed to execute numerical analysis on the efficiency of terminal. The objective of this paper is to measure the level of efficiency in the container terminals every year and to assess the influence in container terminal's efficiency on domestic and foreign terminals by changing the terminal scales and the level of input factors.

• The Journal of Fisheries Business Administration
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• v.47 no.2
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• pp.1-14
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• 2016

This study applied the Stochastic Frontier Analysis to estimate which independent variable affects to efficiency of aquaculture household. This study used wage and facility scale as input variables, sales volume as an output variable to estimate efficiency. Also, the study used region, species, water quality to estimate technical inefficiency factors of the model. The data used for this study were obtained by the operating costs survey using 1:1 interview method. The study selected translog production model with technical inefficiency term estimated as half-normal distribution. In addition, the study used pearson and spearman correlation coefficient among efficiency estimating models. Also, the study analysed differences among estimated efficiencies through t-test, and showed us 0.1793 in species, 0.4677 between Geojae and Masan.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2005.10a
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• pp.521-532
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• 2005

IT 기업의 기술적 효율성의 정도를 추정하고, 그 결정요인을 알아보기 위해 Coelli(1995)의 확률적프론티어(Stochastic Frontier model) 중 초월대수 변경생산함수(translog stochastic frontier production function)를 설정한다. 분석견과 연구개발투자, 기업의 재무구조, 설비투자효율, 노동소득분배율 등은 기업의 비효율을 감소시키는 역할을 하는 반면, 기업규모, 재고자산증가율, 자기자본증가율 등은 기업의 비효율성을 더 높여주는 것으로 나타났다. 1990년부터 2004년까지 국내 제조업 전체의 생산의 기술적 효율성은 평균 0.5311로 이는 생산효율성이 $53.11\%$임을 의미하고, 비효율성은 $46.89\%$에 달한다고 볼 수 있다. IT 기업의 기술적 효율성은 0.5337회 제조업과 비슷하지만, IT 대기업은 0.61, IT 중소기업은 0.511로 대기업과 중소기업의 격차가 크게 발생하고 있다.

• Korean Journal of Agricultural Science
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• v.33 no.2
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• pp.179-193
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• 2006

Technical efficiency of semiforcing watermelon growers is 0.8248 on average, and distributed between 0.6744 and 0.9268. The result showed that semiforcing watermelon growers had by 18% of technical inefficiency and could be assumed that increasing technical efficiency could induce watermelon production more increase. Consequently, if growers' technical efficiency were improved while other environments were constant, watermelon production could be increased. Following the results from the inefficiency effect model, all assumption coefficient such as growers age etc, are significant at 10% level. Estimate of dispersion parameter ${\gamma}$ is 0.89, which confirms those differences between practical output and frontier output were derived from the technical efficiencies among growers. Differences of production system between high and low level growers in production efficiency were showed at side altitude, ventilation and heat-retaining in section of facilities and automation, soil test and calcium application in section of environment management, transplant preparation and duration of pollination in section of crop management and shipment place, sorting degree and management record analysis in section of business management respectively. As a result of analyzing consulting data by using standard diagnosis table of watermelon cultivation under structure which cultivated on semi-forced watermelon growers, gap between high and low level growers was 7.0 points in facility automation section, 7.1 points in environment section, 8.8 points in crop management section and 13.6 points in business management section, respectively, which were the biggest one among them. In case of excluding information-related items from the evaluation index of business management section, changes of business achievement are to occur. Therefore, it is recommended for us to review the standard diagnostic table of watermelon cultivation under structure by dividing evaluation index of management section into management and information.