• 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.

• Asia-Pacific Journal of Business
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• v.6 no.2
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• pp.1-17
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• 2015

This study compares the most widely used parametric and non-parametric techniques to measure cost and profit efficiency of banks, namely the Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). We formulate the specification form of both stochastic cost and profit frontier models and constant return to scale Cost DEA and Profit DEA models and provide an empirical assessment of the cost and profit frontiers based on a panel dataset of National Commercial Banks (NCBs) and Private Banks (PBs) in Bangladesh over the 2001-2010 period. The cost inefficiency and profit efficiency are slightly higher for PBs than NCBs in case of both SFA and DEA. The coefficients of advance and off-balance sheet items are significant that positively influence the banks in stochastic cost frontier model while the advance, other earning assets, price of borrowed fund are significant and negative effects on the banks in stochastic profit frontier model. The average cost inefficiency and average profit efficiency are recorded with 16.3% and 91% respectively. The highest and lowest cost inefficiency are observed for Janata Bank and United Commercial Bank Limited whilst the highest and lowest profit efficiency are recorded for Eastern Bank Limited and Janata Bank respectively. The average technical and allocative efficiency are 68.8% and 35.9%, respectively in case of CRS cost-DEA model whereas they are 70.3% and 31.8% in case of CRS profit-DEA model. The average cost inefficiency is recorded 6.3% by SFA whereas it is 24.5% by DEA. The average profit efficiency is found 91% by SFA while it is 22.1% by DEA, and SFA method shows better bank efficiency than DEA.

• Journal of Korean Academy of Nursing
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• v.42 no.1
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• pp.48-55
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• 2012

Purpose: The aim of this study was to compare statistical methods to control response bias in nursing activity surveys. Methods: Data were collected at a medical unit of a general hospital. The number of nursing activities and consumed activity time were measured using self-report questionnaires. Descriptive statistics were used to identify general characteristics of the units. Average, Z-standardization, gamma regression, finite mixture model, and stochastic frontier model were adopted to estimate true activity time controlling for response bias. Results: The nursing activity time data were highly skewed and had non-normal distributions. Among the 4 different methods, only gamma regression and stochastic frontier model controlled response bias effectively and the estimated total nursing activity time did not exceeded total work time. However, in gamma regression, estimated total nursing activity time was too small to use in real clinical settings. Thus stochastic frontier model was the most appropriate method to control response bias when compared with the other methods. Conclusion: According to these results, we recommend the use of a stochastic frontier model to estimate true nursing activity time when using self-report surveys.

• Korean Management Science Review
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• v.19 no.1
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• pp.117-128
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• 2002

In this Paper we investigate the performance of the five efficiency estimation methods which include the stochastic frontier model estimated by maximum likelihood (SFML), the stochastic frontier model estimated by corrected ordinary least squares (SFCOLS), the data envelopment analysis (DIA) model, the combined estimation of SFML and DEA (SFML + DEA), and the combined estimation of SFCOLS arid DIA (SFCOLS+ DEA) using Monte Carlo analysis. The results include: 1) SFML provides most accurate efficiency estimates for the sample sloe 150 or over,2) SFML+DEAor SFCOLS + DIA Perform better for the cases with sample sloe 25, 50, and low random errors, 3) SFCOLS performs better for the close with sample sloe 25, 50, and very high random errors.

• Asia-Pacific Journal of Business
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• v.7 no.1
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• pp.31-42
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• 2016

Small and Medium Enterprises (SMEs) are suitable to provide employment with lower investment in densely populated countries like Bangladesh. A stochastic frontier model is used to evaluate performance of SME Banking of the commercial banks in Bangladesh. Input (Total Deposit, Cost of Fund and Salary Expenditure) and output (Finance to SME) data are collected on 45 banks which are dealt with SME for 13 quarters from $1^{st}$quarter of 2010 to $2^{nd}$quarter of 2013. Average performance of the SME banking is 0.716 in Bangladesh. That is, banks have opportunity to increase 30% performance in SME banking from the same inputs. Bangladesh Development Bank has lowest performance (0.540) while Eastern bank has the highest performance (0.753). Highest (0.743) and lowest (0.662) performance is observed during the second quarter of 2013 and fourth quarter of 2010 respectively. Inefficient Bank might be benefited by following the rules of efficient banks.

• 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.

• Korean Journal of Organic Agriculture
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• v.24 no.3
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• pp.355-368
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• 2016

There are growing interests in environmental friendly cultivation for the matter of health concern. This study analyzes an economic efficiency of strawberry and tomato farming by considering the role of environmentally friendly cultivation. The Database of Rural Development Administration is used for strawberry and tomato farming households. We adopt a Bayesian stochastic frontier model to resolve a small sample property of the data. Empirical finding is that environmentally friendly cultivation improves the revenue of farming but the effect on net profit is not conclusive which calls for future research.

• 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.

• Journal of the Korea Safety Management & Science
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• v.22 no.1
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• pp.61-68
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• 2020

The purpose of this study was to measure the job aspiration and examine the relationship between that and job satisfaction for wage-earners using the fourth Korean Working Conditions Survey(KWCS). We use the stochastic frontier model for measuring the job aspiration and testing its effect on the job satisfaction. Fstochastic frontier model is introduced to explain that each company potentially produces less than it might due to a degree of job aspiration, measured by decomposing the residuals. In this model framework, it can be regard that the upper bound of the job satisfaction is the ideal frontier, and the bias between the ideal condition and the reality is the job aspiration. If this concept is applicable to the job aspiration, we can measure this bias and investigate a relationship with the job satisfaction. We find that there exists the job aspiration, and it is significantly negatively correlated with the job satisfaction. This result supports that if job aspiration increases, job satisfaction level decreases.