Journal articles: 'Stochastic frontier analysis (SFA)'

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Lechtenberg, Christian. "Stochastic Frontier Analysis (SFA)." Controlling 23, no. 12 (2011): 682–83. http://dx.doi.org/10.15358/0935-0381-2011-12-682.

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Sakouvogui, Kekoura, Saleem Shaik, Curt Doetkott, and Rhonda Magel. "Sensitivity analysis of stochastic frontier analysis models." Monte Carlo Methods and Applications 27, no. 1 (February 2, 2021): 71–90. http://dx.doi.org/10.1515/mcma-2021-2083.

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Abstract The efficiency measures of the Stochastic Frontier Analysis (SFA) models are dependent on distributional assumptions of the one-sided error or inefficiency term. Given the intent of earlier researchers in the evaluation of a single inefficiency distribution using Monte Carlo (MC) simulation, much attention has not been paid to the comparative analysis of SFA models. Our paper aims to evaluate the effects of the assumption of the inefficiency distribution and thus compares different SFA model assumptions by conducting a MC simulation. In this paper, we derive the population statistical parameters of truncated normal, half-normal, and exponential inefficiency distributions of SFA models with the objective of having comparable sample mean and sample standard deviation during MC simulation. Thus, MC simulation is conducted to evaluate the statistical properties and robustness of the inefficiency distributions of SFA models and across three different misspecification scenarios, sample sizes, production functions, and input distributions. MC simulation results show that the misspecified truncated normal SFA model provides the smallest mean absolute deviation and mean square error when the true data generating process is a half-normal inefficiency distribution.

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Tsolas, Ioannis E. "Mine Performance Assessment by Means of Stochastic Frontier Analysis." Mathematical Problems in Engineering 2019 (March 11, 2019): 1–7. http://dx.doi.org/10.1155/2019/8657348.

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This paper employs stochastic frontier analysis (SFA) in assessing efficiency at the mine level. An SFA model is derived using annual operational data from the Kardia Field mine of the Greek Public Power Corporation (PPC) S.A. for the 1984-2006 period and the causes of inefficiency are investigated by means of regression techniques. The proposed two-stage model can be used as a diagnostic tool to identify causes of mine inefficiency and as a tool for designing and specifying interventions to improve mine performance.

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Nguyen, Hung T. "A closer look at stochastic frontier analysis in economics." Asian Journal of Economics and Banking 4, no. 3 (October 8, 2020): 3–28. http://dx.doi.org/10.1108/ajeb-07-2020-0032.

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Purpose While there exist many surveys on the use stochastic frontier analysis (SFA), many important issues and techniques in SFA were not well elaborated in the previous surveys, namely, regular models, copula modeling, nonparametric estimation by Grenander’s method of sieves, empirical likelihood and causality issues in SFA using regression discontinuity design (RDD) (sharp and fuzzy RDD). The purpose of this paper is to encourage more research in these directions. Design/methodology/approach A literature survey. Findings While there are many useful applications of SFA to econometrics, there are also many important open problems. Originality/value This is the first survey of SFA in econometrics that emphasizes important issues and techniques such as copulas.

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Arsad, Roslah, Zaidi Isa, and Siti Nabilah Mohd Shaari. "Estimating Efficiency Performance of Decision-Making Unit by using SFA and DEA Method: A Cross-Sectional Data Approach." International Journal of Engineering & Technology 7, no. 4.33 (December 9, 2018): 25. http://dx.doi.org/10.14419/ijet.v7i4.33.23478.

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In this paper, a cross-sectional samples data of 115 Malaysian stocks have been employed to compare both Data Envelopment Analysis (DEA) method and Stochastic Frontier Analysis (SFA) method. These approaches are used to provide a review of frontier conceptual measurement, strength and limitation of the parametric and non-parametric models. Stochastic frontier production function of Cobb-Douglas type was utilized for the estimation. The function was estimated using the maximum likelihood estimation technique. Two models in DEA, DEA-CCR and DEA-BCC are applied in this study and the ranking correlation between SFA method and both models DEA are determined by using the Spearman rank method. The result revealed using SFA, the mean technical efficiency of sample consumer product companies is 37.5% and implies that companies operating at means level of technical efficiency could produce 80.1% more output for given level of inputs if they become technically more efficient. From empirical results of the SFA method, we determined that the deviations from the efficient frontiers of production functions are largely attributed to inefficiency effects (technical inefficiency). Finally, the findings also showed that the difference in ranking stocks performance using DEA-CCR, DEA-BCC and SFA methods. The main contribution of the paper is showing the comparative performance based on both model, DEA and SFA method using financial ratio.

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Ferruz Agudo, Luis, João Serafim Tusi da Silveira, Daniel Knebel Baggio, Isoé Nícolas Schneider, and Maria Margarete Baccin Brizolla. "Stochastic frontiers of efficiency for Brazilian investment funds: a panel data analysis." Investment Management and Financial Innovations 16, no. 4 (December 26, 2019): 352–65. http://dx.doi.org/10.21511/imfi.16(4).2019.30.

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Foundations, methodological and empirical possibilities of measurement and analysis in the performance of financial investments within investment funds have been developed since they were once introduced in the 1970s, thus establishing a path of growing acceptance in financial markets and universities’ academies. The first approaches over the efficiency of these funds, considering their stochastic implications, occurred in the late 1990s and have evolved with the help of SFA – Stochastic Frontier Analysis, although it still needs more careful verification. This article measured and analyzed the stochastic frontier of efficiency over 33 different Brazilian investment funds from 2012 to 2015. For doing so, Battese and Coelli’s (1995) specifications was used. It shows the effects of inefficiencies, which are defined as explicit functions of specific factors in the context of panel data funds. They are estimated by the maximum likelihood method. Sharpe ratios (SR) were also calculated for comparative purposes. Based on these two indicators (SFA and SR), the most recommendable funds to invest and the ones in which the application should not be performed were identified. Such procedures have stimulated the necessary and promising studies, as well as future researches, which, in turn, may establish new methodological formulation as an efficient and effective instrument to choose the best and the safest funds to invest.

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Acquah, Henry de-Graft. "Sensitivity of technical efficiency estimates to estimation methods: an empirical comparison of parametric and non-parametric approaches." Applied Studies in Agribusiness and Commerce 8, no. 1 (August 31, 2014): 67–72. http://dx.doi.org/10.19041/apstract/2014/1/8.

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This paper highlights the sensitivity of technical efficiency estimates to estimation approaches using empirical data. Firm specific technical efficiency and mean technical efficiency are estimated using the non parametric Data Envelope Analysis (DEA) and the parametric Corrected Ordinary Least Squares (COLS) and Stochastic Frontier Analysis (SFA) approaches. Mean technical efficiency is found to be sensitive to the choice of estimation technique. Analysis of variance and Tukey’s test suggests significant differences in means between efficiency scores from different methods. In general the DEA and SFA frontiers resulted in higher mean technical efficiency estimates than the COLS production frontier. The efficiency estimates of the DEA have the smallest variability when compared with the SFA and COLS. There exists a strong positive correlation between the efficiency estimates based on the three methods.

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Putri, Devy Ariesta, and Sylva Alif Rusmita. "ANALISIS TINGKAT EFISIENSI BIAYA BANK UMUM SYARIAH DENGAN METODE STOCHASTIC FRONTIER ANALYSIS PERIODE 2015-2018." Jurnal Ekonomi Syariah Teori dan Terapan 7, no. 1 (June 11, 2020): 199. http://dx.doi.org/10.20473/vol7iss20201pp199-206.

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This study aims to determine the cost efficiency level of Sharia Commercial Banks registered in the OJK for the 2015-2018 period. This study uses a quantitative approach. This study uses a parametric approach to measure the cost efficiency of Islamic banking with the stochastic frontier analysis (SFA) method. The value of cost efficiency using the SFA method is in the form of a value of 100%, the closer it is to the value of 100%, the more efficient the bank works. The analysis technique used is the cross-section model and panel model. This study uses 7 Sharia Commercial Bank samples. Data obtained from each of the Sharia Commercial Bank Financial Report websites. The results of the Cross-Section Stochastic Frontier Analysis analysis on cost efficiency show the average value of the efficiency of Islamic banking in Indonesia approaching 95.92%. The results of the cost-efficiency analysis show that Islamic banking in the 2015-2018 period tended to be less efficient in controlling costs.Keywords: Cost efficiency, Islamic commercial banks, Stochastic Frontier Analysis (SFA).

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Cardoso, Catarina Moura e. Sa, and Geetha Ravishankar. "Productivity growth and convergence: a stochastic frontier analysis." Journal of Economic Studies 42, no. 2 (May 11, 2015): 224–36. http://dx.doi.org/10.1108/jes-08-2013-0121.

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Purpose – The purpose of this paper is to assess the effect of human capital development on regional productivity growth and convergence in the Spanish provinces over the period 1991-2006. Design/methodology/approach – The stochastic frontier analysis (SFA) methodology is used to estimate production inefficiencies. This approach enables the assessment of the degree to which a given region’s observed output deviates from the maximal possible. Therefore, the resulting region specific productive efficiencies are modelled as outcomes of the level of human capital. A β-convergence equation for the regional efficiency levels is also estimated to detect any signs of regional catching-up. Findings – The results show that increasing levels of human capital development are associated with lower regional inefficiency. All levels of education contributed to reduce the inefficiency levels, however, secondary schooling played a stronger role than primary and even higher education. There is also evidence of regional convergence towards the best practice frontier through a process that is beneficially aided by human capital development. Originality/value – The paper combines the use of the SFA to study the effect of human capital on regional productivity with the estimation of a β-convergence equation for the obtained regional efficiency levels.

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Ngo, Thanh, and David Tripe. "Stochastic cost frontier analysis – a sensitivity analysis on cost measures." Pacific Accounting Review 28, no. 4 (November 7, 2016): 401–10. http://dx.doi.org/10.1108/par-03-2016-0028.

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Purpose This paper aims to examine alternative methods for recording and treating costs in studies of bank efficiency. Design/methodology/approach This study used stochastic frontier analysis (SFA) models with core costs and total costs to estimate the cost efficiency of banks in two different economies, Vietnam where the banking system is under-developed (and thus is dominated by traditional banking activities) and New Zealand where the banking system is well-developed (and thus non-traditional banking activities play an important role). Findings The authors found that models using total cost tend to underestimate the banks’ cost efficiency. This underestimation relates to the extent of modern activities in a banking system: it is larger in an advanced banking system (i.e. New Zealand) and smaller in a less-developed banking system (i.e. Vietnam). Research limitations/implications Research is limited to two countries, and it would be useful to apply the same technique to other data sets. Practical implications The paper suggests a new approach to cost SFA studies in banking. Originality/value The paper provides a much more searching analysis of costs in banking than has generally been seen in previous research.

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Puji Astuti, Ririn, M. Syirod Saleh, and Muhammad Subardin. "Efisiensi belanja administrasi pemerintah Kota Palembang: Pendekatan Stochastic Frontier Analysis." Jurnal Ekonomi Pembangunan 15, no. 2 (July 3, 2019): 85–91. http://dx.doi.org/10.29259/jep.v15i2.8833.

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This study aims to find out the efficiency of the administration of Palembang City, 2002 – 2016 period in building the area with and components that caused whether or not administrative expenditure of an area was efficient. This study uses data secondary data that is realization data of administrative expenditure, average employe’s expenditure, capital expenditure and local revenue. This data was tested by stochastic frontier analysis (SFA). The results of estimation from the stochastic frontier analysis (SFA) found that the administrative expenditure of the city of Palembang was inefficiency. The average variable of employee expenditure has a negative related and has a significant effect to administration costs in Palembang City. The relationship of variable capital expenditure with the administration costs of the regional government in the city of Palembang has a positive and significant effect. And the Local Revenue variables have a positive and significant effect to administration costs in Palembang City.

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Mitsel, Arthur, Aliya Alimkhanova, and Marina Grigorieva. "Advancing the multifactor model of Stochastic Frontier Analysis." Eastern-European Journal of Enterprise Technologies 3, no. 4 (111) (June 29, 2021): 58–64. http://dx.doi.org/10.15587/1729-4061.2021.235316.

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The concept of efficiency is important in economic science; at present, its role in every sector of the economy is growing. Evaluating an enterprise’s efficiency makes it possible to implement a correct and profitable strategy of resource allocation, which shows its potential level Given an annual increase in the number of bankrupt enterprises, the issue of estimating the efficiency of enterprises is relevant for both their owners and managers, as well as for creditors. There are various methods and models for estimating the performance of enterprises. This work has assessed the efficiency of enterprises in the industrial sector over the period of 2017‒2018. Stochastic Frontier Analysis is based on the stochastic model of production function. The classic SFA method is based on the production function of the company, which relates the volume of output to the volume of resources consumed. At the same time, the SFA model uses several inputs (volumes of resources consumed) and only one output parameter ‒ the volume of production. In order to achieve more precise results, a given model has been modified. The model allows several key financial indicators to be taken into consideration as outputs at the same time, based on which the financial activities of the studied economic entities are assessed. The result of the work involving open sources has revealed how the efficiency of different enterprises in the same industry changes over several years. It is shown that the modified Stochastic Frontier Analysis model could be used to assess financial stability and predict bankruptcy.

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Sakouvogui, Kekoura. "A comparative approach of stochastic frontier analysis and data envelopment analysis estimators: evidence from banking system." Journal of Economic Studies 47, no. 7 (May 4, 2020): 1787–810. http://dx.doi.org/10.1108/jes-01-2019-0051.

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PurposeThe consistency of stochastic frontier analysis (SFA) and data envelopment analysis (DEA) cost efficiency measures using a sample of 650 commercial and domestic banks in the United States is investigated based on cluster analysis while accounting for the yearly variation in banks.Design/methodology/approachDue to the importance of efficiency measures for policy and managerial decision-making, the cost efficiency measures of SFA and DEA estimators are examined according to four criteria: levels, rankings, stability over time and stability over clustering groups. In this paper, we present two clustering methods, Gap Statistic and Dindex, that involve SFA and DEA cost efficiency measures. The clustering approach creates homogeneous groups of banks offering a similar mix of efficiency levels. Hence, each evaluated bank knows the cluster to which it belongs. Furthermore, this paper provides nonparametric statistical tests of SFA and DEA cost efficiency measures estimated with and without a clustering approach.FindingsThe results suggest that the clustering approach plays a considerable role in the rankings of US banks. Furthermore, the average SFA and DEA cost efficiency measures over time of the homogeneous US banks are substantially higher than those of the heterogeneous US banks.Originality/valueThis research is the first to provide comparative efficiency measures needed for desirable policy conclusions of heterogeneous and homogeneous US banks.

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Oh, Seog-Chan, and Jaemin Shin. "The Assessment of Car Making Plants with an Integrated Stochastic Frontier Analysis Model." Mathematics 9, no. 11 (June 5, 2021): 1296. http://dx.doi.org/10.3390/math9111296.

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As global competition has intensified in the automotive industry, there is a strong need for management teams to develop methods that allow accurate and objective assessments of plant productivity and to identify productivity improvement opportunities for the best manufacturing practices. Stochastic frontier analysis (SFA) models have been used as a statistical benchmarking tool to provide a bird’s-eye view of an industrial sector. SFA models can also be adapted for plant productivity assessment. However, owing to the problem of multicollinearity, the general form of SFA is difficult to apply to the assessment of complex manufacturing systems in the automotive industry, which is characterized by many control and external factors that are intercorrelated to each other. This study proposes a method for applying SFA to vehicle manufacturing plants with a focus on gaining high accuracy in model parameter estimation, by decomposing a plant into components (i.e., shops), building an SFA model for each shop, and reintegrating the general plant system through the appropriate combination of shop-level inefficiency distributions. In particular, this study focuses on documenting the derivation of a new probability density function that integrates three different inefficiency distributions. For illustration of the proposed approach, hypothetical vehicle assembly plants are assessed as examples, where the total labor hours are split into Bodyshop, Paintshop, and General Assembly, exclusively and collectively. Finally, this study offers a solution process to clarify the reasons for underperforming plants in terms of labor productivity and identify the course of actions to cure the issues with some managerial insights emphasizing the balanced approach, incorporating people, process and technology.

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Rosli, Anita, Alias Radam, Khalid Abdul Rahim, and Amin Mahir Abdullah. "Technical Efficiency among Pepper Farmers in Sarawak, Malaysia: A Stochastic Frontier Analysis." Asian Journal of Agriculture and Rural Development 10, no. 3 (October 19, 2020): 729–39. http://dx.doi.org/10.18488/journal.ajard.2020.103.729.739.

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This study aimed to estimate the technical efficiency among pepper (Piper nigrum. L) farmers in Sarawak, Malaysia, using Stochastic Frontier Analysis (SFA). SFA involves a one-step process that can estimate technical inefficacy factors simultaneously with the production frontier. 678 pepper farmers were involved in this study, and the data were collected from 2012 to 2013. The mean score for technical efficiency was 0.518, indicating that pepper farmers were not efficient. However, the inefficiency model showed that education level, membership in farmers’ association, full-time as a pepper farmer, attending courses and visiting sample farms were factors that significantly improved inefficiency. The major problem of pepper farming in Sarawak is poor agricultural practices where farmers do not fully utilize the available agricultural inputs to produce maximum output. Based on the findings, farmers must improve their knowledge and skills in pepper farming through agronomic education.

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Kammoun, Rabeb. "The Technical Efficiency of Tunisian Ports: Comparing Data Envelopment Analysis and Stochastic Frontier Analysis Scores." Logistics & Sustainable Transport 9, no. 2 (October 1, 2018): 73–84. http://dx.doi.org/10.2478/jlst-2018-0011.

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Abstract Maritime transportation for Tunisia plays an important role in trade exchange with other countries. Therefore, the objective of this paper is to measure the efficiency scores of 7 seaports in Tunisia by applying the Stochastic Frontier Analysis (SFA) with Cobb-Douglas production function and Data envelopment analysis (DEA) with CCR and BCC models. The annual data collected cover the 2007-2017 period for each port. Thus, the sample size for the analysis comprises a total of 77 observations. The empirical result shows that the total average scores of operating efficiency scores were DEA-BCC (0.746) >SFACD (0.536)>DEA-CCR (0.334) from 2007 to 2017. Given these results, the port of Gabes can be considered as the best efficient port in the 3 models (DEA-BCC, DEA-CCR and SFA-CD).

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Asgari, Mansour. "Technical Efficiency in Iran’s Industry Sector: A Stochastic Frontier Analysis (SFA) Approach." Journal of Planning and Budgeting 24, no. 3 (December 1, 2019): 61–85. http://dx.doi.org/10.29252/jpbud.24.3.61.

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Ho, Tin H., Dat T. Nguyen, Thanh Ngo, and Tu D. Q. Le. "Efficiency in Vietnamese Banking: A Meta-Regression Analysis Approach." International Journal of Financial Studies 9, no. 3 (August 3, 2021): 41. http://dx.doi.org/10.3390/ijfs9030041.

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This study explains the differences and variances in the efficiency scores of the Vietnamese banking sector retrieved from 27 studies published in refereed academic journals under the framework of meta-regression analysis. These scores are mainly based on frontier efficiency measurements, which essentially are Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) for Vietnamese banks over the period of 2007–2019. The meta-regression is estimated by using truncated regression to obtain bias-corrected scores. Our findings suggest that only the year of publication is positively correlated with efficiency, whilst the opposite is true for the data type, and sample size.

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Mohamed Jofree, Ammar Fikree, Norayati Hashim, Fahmy-Abdullah Mohd, Wei Sieng Lai, and Sulhi Ridzuan. "Efficiency Assessment of Transport Manufacturing Firms using a Stochastic Frontier Analysis Approach." Sains Malaysiana 50, no. 8 (August 31, 2021): 2445–53. http://dx.doi.org/10.17576/jsm-2021-5008-25.

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This paper aims to analyze the level of technical efficiency and determinants of technical inefficiency of transport manufacturing firms in Malaysia using Stochastic Frontier Analysis (SFA) approach from 2005 to 2010. Through SFA approach, hypothesis test is conducted in order to select Cobb-Douglas or Translog production function and testing the effects of technical inefficiencies. While the determining factors that been taken into account include the capital-labor ratio, training expenses, education level ratio, wage rate, information and communication technology expenditure, and firm size. Hypothesis test results show that the Cobb-Douglas production function is rejected. While the test for the effect of technical inefficiency shows its existence. Training expenses, secondary and tertiary education level ratios, wage rates and information and communication technology expenses are significant determinants for transportation manufacturing firms. However, the capital-labor ratio was found that it has reduced the level of technical efficiency. The implications of these results show that firms need to focus on investing in human capital, information technology and increase motivation among employees such as rising wage rates and reducing the use of capital appropriate to the technology.

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Rahmawati, Rafika. "Strategi Peningkatan Efisiensi Biaya pada Bank Umum Syariah Berbasis Stochastic Frontier Approach dan Data Envelopment Analysis." Buletin Ekonomi Moneter dan Perbankan 17, no. 4 (October 7, 2015): 457–80. http://dx.doi.org/10.21098/bemp.v17i4.506.

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Entering the ASEAN Economic Community (AEC) in 2015, the Islamic banking in Indonesia is expected to have better performance to compete sustainably with local banks and foreign. The performance of the banks using the cost efficiency approach with a focus on two inputs (cost of fund and cost of labor) and the two outputs (total financing and owned securities). Using Stochastic Frontier Approach (SFA) and Data Envelopment Analysis (DEA) on Islamic Banks during the period of January 2010 to December 2013, the result shows that the level of efficiency of the Islamic banks in Indonesia is not optimal. Our calculation shows different result for both method (SFA and DEA), where the highest efficiency levels using SFA methodis Bank Mega Syariah, while with the DEA method is Bank Muamalat Indonesia. Leaving some option of strategies to improve their cost efficiency; this includes increasing their assets, increasing deposits, and cut cost the unnecessarily cost. More strategy includes product innovation, reducing the salary of the board of directors, and put the funds in profitable portfolio. For the authorities, this paper has demonstrated the use of frontier approach as good alternative in assessing the performance of the banks.

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Hsiao, Wen-Ling, Jin-Li Hu, Chan Hsiao, and Ming-Chung Chang. "Energy Efficiency of the Baltic Sea Countries: An Application of Stochastic Frontier Analysis." Energies 12, no. 1 (December 29, 2018): 104. http://dx.doi.org/10.3390/en12010104.

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Using the stochastic frontier analysis (SFA) model, this research measures total-factor energy efficiency (TFEE) and disaggregate input efficiency for 10 countries across the Baltic Sea from 2004 to 2014. Real capital, labor, energy use, and carbon dioxide (CO2) are input variables, real gross domestic product (GDP) is the output variable, and renewable energy consumption and urban population are the environmental variables. The results provide not only the TFEE scores, in which statistical noise is considered, but also the determinants of inefficiency, which show the following. (i) Norway, Sweden, Finland, and Latvia perform better with respect to energy efficiency than other countries in the Baltic Sea Region. (ii) Interestingly, the average energy use efficiency scores from 2004 to 2014 in the 10 Baltic countries exhibit a gradual upward trend except for 2009. (iii) For the inefficiency estimates, higher renewable energy consumption and urban population correspond to higher TFEE scores.

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Hendrawan, Riko, Gayuh T. Permana, and Kristian WA Nugroho. "Efficiency analysis of telecommunications companies in Southeast Asia using Stochastic Frontier Analysis (SFA) method." Jurnal Siasat Bisnis 23, no. 2 (July 1, 2019): 104–12. http://dx.doi.org/10.20885/jsb.vol23.iss2.art3.

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Rusmita, Sylva Alif, and Devy Ariesta Putri. "Indonesian Islamic Commercial Banks’ Efficiency: A Stochastic Frontier Analysis." Shirkah: Journal of Economics and Business 5, no. 3 (December 28, 2020): 386. http://dx.doi.org/10.22515/shirkah.v5i3.283.

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Islamic banks in Indonesia are continuously experiencing a rapid growth; thus, it results in a competitive financial sector. Consequently, maintaining an excellent performance is a prerequisite to gain customers’ trust and loyalty, one of the ways is enhancing productivity and efficiency performance. Drawing on this issue, the present study aims to examine the efficiency of Islamic banks listed in the Financial Services Authority (OJK) in the period of 2015 to 2019. Employing Stochastic Frontier Analysis (SFA) as a parametric approach, this study measured the efficiency level of cost and profit efficiency of the Indonesian Islamic commercial banks. The data were a cross-section and panel data obtained from financial reports established by seven Indonesian Islamic commercial banks. The result of frontier analysis on the efficiency costs showed that the value of sharia banks’ average efficiency in Indonesia was approximately 93.41%, while the efficiency of profit resulted in 55.35%. These results suggest that Islamic banks tend to be efficient in controlling costs from the year of 2015 to 2019. It is a worth saying that this study’s results contribute to providing fruitful insights for Islamic banks to increase their efficiency by controlling their cost of production such as the cost of funds and cost of operation.

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Jarboui, Sami, Pascal Forget, and Younes Boujelben. "EFFICIENCY EVALUATION IN PUBLIC ROAD TRANSPORT: A STOCHASTIC FRONTIER ANALYSIS." TRANSPORT 30, no. 1 (May 23, 2013): 1–14. http://dx.doi.org/10.3846/16484142.2013.785019.

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This paper measures the technical efficiency of 54 public road transport operators and investigates the degree to which various factors influence efficiency levels in these firms. The study makes an attempt to provide an overview of the general status of different operators in 18 countries. Stochastic Frontier Analysis (SFA) methods are applied to our sample over a twelve year period from 2000 to 2011. To our knowledge, this is the first comprehensive analysis of technical efficiency of public road transport operators in 18 countries using parametric method. Our empirical results indicate that investment, operating profit and firm size have a significant influence on technical efficiency levels. We find that technical efficiency level of public road transport operators varies between 0.458 and 0.95. We also observe that large-size operators with more investment capacity tend to be more technically efficient than small-size operators. Finally, we find that operators from developed countries are technically more efficient than those of developing countries.

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Waryanto, Budi. "Environmental Efficiency Analysis with one Detrimental Input Variable through A Stochastic Frontier Analysis Approach (A Case Study of Shallot Farming System)." Informatika Pertanian 24, no. 2 (December 26, 2016): 233. http://dx.doi.org/10.21082/ip.v24n2.2015.p233-244.

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Sustainable agriculture having high complexity, especially related to the choice of using inputs that could potentially harm the environment or often called a detrimental input. In order to realize sustainable agriculture, the level of efficiency of the use of these inputs must be able to measure, especially from the aspect of environmental efficiency. The objective of this research in to analyze the environmental efficiency (EEnv) with a detrimental input variable namely the Nitrogen surplus in shallot farming through approach Stochastic Frontier Analysis (SFA). At the initial stage has been built translog stochastic frontier regression model consisting of the response variable namely the production of onion, five independent variables, namely land, seed, Phospor fertilizer, Kalium fertilizer, labor and pesticides, as well as one independent variable is a surplus of nitrogen as a detrimental input. Stochastic frontier translog regression models were built to explain some of the interactions between several independent variables affect the production of shallot. Some interactions are significant, namely seeds and pesticides, fertilizer P with a surplus of nitrogen, and the interaction between K fertilizer with nitrogen surplus. From the regression model can also be calculated value of elasticity, where the elasticity of independent variables namely seed is the highest, equal to 0.1687. Furthermore stochastic frontier translog model can be calculated value EEnv, the results show the value of EEnv still low at only at 0.2765. This may imply inefficient shallot farmers from the aspects of the environment, especially if associated with the use of nitrogen fertilizer. Although technically shallot farmers have achieved a level of technical efficiency (ET), which is indicated on the ET value of 0.9475.

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NAZARKO, Joanicjusz, and Ewa CHODAKOWSKA. "Labour efficiency in construction industry in Europe based on frontier methods: data envelopment analysis and stochastic frontier analysis." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 23, no. 6 (June 22, 2017): 787–95. http://dx.doi.org/10.3846/13923730.2017.1321577.

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The primary problems pertaining to productivity or – more precisely – efficiency are: how to define it and how to measure it. This article studies technical efficiency in Stochastic Frontier Analysis (SFA) – the input-oriented frontier model – in the construction industry and compares it with Data Envelopment Analysis (DEA) results. The models explored in this paper were constructed on the basis of two outputs and personnel cost as an input. The research sample consisted of European countries. The aim was to determine whether there are substantial differences in estimation of efficiency derived from those two alternative frontier approaches. The comparison of results according to the models may translate into higher reliability of the undertaken labour efficiency analysis in construction and its conclusions. Although the results are not characterized by high compatibility, the conducted analysis indicated the most attractive countries taking into account labour cost to profit and turnover ratios of enterprises. One of the determinants which should not be ignored when analysing the labour efficiency is the level of development of a country; however, it is not the sole factor affecting the efficiency of the sector.

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Li, Bao Yang, and Ya Ting Zhou. "Empirical Analysis of Technical Efficiency in Information Services." Applied Mechanics and Materials 738-739 (March 2015): 460–64. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.460.

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With the high development of knowledge-based economy, information service industry plays an important role in driving economic transition. We use stochastic frontier analysis (SFA) method to estimate the technical efficiency in seven cities of Zhejiang Province in China. We find that the average technical efficiency of information services industry is high and have different developed trends among the cities. The human capital、industrial concentration degree, openness and urbanization have significant impact on technical efficiency, while government behaviors do not show significant effect.

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Nure, Gazmend. "Cost Efficiency Analysis in the Banking Industry." International Journal of Corporate Finance and Accounting 7, no. 2 (July 2020): 1–20. http://dx.doi.org/10.4018/ijcfa.2020070101.

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The efficiency of commercial banks is essential for the stability of banks by implying that banks that take higher risks are more inefficient. This paper builds on a stochastic heteroscedastic boundary model, where one will analyze a sample of 70 banks in Western Balkan countries such as Albania, Northern Macedonia, Serbia, Kosovo, and Montenegro for the period 2007-2017, highlighting determinants of bank cost efficiency. Banks with less liquidity, with a lower solvency rate and a higher credit risk, are more ineffective than prudent credit institutions. The paper also aims to address the relative lack of studies on the efficiency of banks in the region through the use of the stochastic frontier analysis (SFA).

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Delfin Ortega, Odette Virginia, and José César Lenin Navarro Chávez. "Ports Efficiency in APEC Region, 2005-2013: A Measurement through Stochastic Frontier Analysis (SFA)." México y la Cuenca del Pacífico 6, no. 16 (January 1, 2017): 19–50. http://dx.doi.org/10.32870/mycp.v6i16.519.

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Dewi, Dian Ayunita N. N., B. A. Wibowo, and Iqbal Ali Husni. "KEBERLANJUTAN USAHA PENANGKAPAN PURSE SEINE DI PEKALONGAN DITINJAU DARI ASPEK EFISIENSI USAHA." Akuatik: Jurnal Sumberdaya Perairan 11, no. 2 (August 21, 2018): 7–13. http://dx.doi.org/10.33019/akuatik.v11i2.238.

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Tujuan dari penelitian ini adalah menghitung efiensi teknis usaha penangkapan purse seine di PPN Pekalongan secara stokastik dan deterministik dan menganalisis efisiensi teknis untuk mengetahui prospek keberlanjutan usaha penangkapan purse seine di PPN Pekalongan. Metode analisis menggunakan Stochastic Frontier Analysis (SFA) dan Deterministic Frontier Analysis (DFA). SFA dan DFA merupakan model parametrik yang digunakan untuk mengukur efisiensi teknis. Model 1: DFA dengan data cross-section akan diestimasi dengan COLS. Model 2: SFA dengan data cross-section akan diestimasi dengan ML (Maximum Likelihood). Model 3: SFA dengan data panel diestimasi dengan proses ML. Variabel independent yang digunakan pada penelitian ini adalah lama trip (fishing days atau X1), GRT (Gross Registered Tonnage atau X2) kapal, jumlah ABK (crew members atau X3) sebagai faktor determinan yang digunakan oleh penangkapan purse seine di lokasi penelitian. Dan variabel terikat (Y) adalah output yaitu produksi tangkapan per tahun dari tahun 2015-2017. Fokus penelitian pada kapal purse seine berukuran 60-90 GT. Hasil dari penelitian ini adalah efisiensi teknis dari kedua kelompok kapal menunjukkan nilai inefisiensi dalam penggunaan ketiga variabel input. Hal ini diperkuat dengan hasil nilai korelasi (R) pada metode Deterministik Frontier dan Stokastik Frontier dengan data cross section serta panel data yang rendah (0,39 dan 0,311). Variabel X1 (lama trip) memiliki hubungan negatif dengan variabel Y (produksi) sedangkan X2 dan X3 memiliki hubungan positif terhadap Y. Pada armada penangkapan purse seine ukuran 60-90 GT, ketiga variabel input tidak mempunyai pengaruh yang signifikan terhadap perubahan jumlah produksi penangkapan.

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Gai, Weidong, Lei Zhou, and Chun Chen. "Evaluation of Manufacturing Competitiveness of Hubei Province Based on Stochastic Frontier Analysis." Discrete Dynamics in Nature and Society 2021 (September 15, 2021): 1–10. http://dx.doi.org/10.1155/2021/3364968.

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The manufacturing level directly manifests the comprehensive strength of a country or region. Production efficiency provides an important metric of the competitiveness of the manufacturing industry. Based on the data of China’s industrial enterprises of 1999–2011, this paper estimates the production efficiency of manufacturing in Central China’s Hubei Province through stochastic frontier analysis (SFA) and thus characterizes the differences between prefectures of Hubei in manufacturing competitiveness. The results show that, on the prefecture level, Xianning and Wuhan saw a decline in manufacturing competitiveness, while Xiangfan and Xiaogan witnessed an increase in manufacturing competitiveness. To enhance local manufacturing competitiveness and make Hubei the forerunner and cornerstone of Central China, different prefectures should adopt different industrial promotion policies, pay attention to cultivating the technological innovation capabilities of enterprises, and strengthen the integration of production, education, and research.

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Celen, Aydin. "Technical Efficiency in Turkish Electricity Distribution Market: An Application of Stochastic Frontier Analysis (SFA)." Ekonomik Yaklasim 27, no. 101 (2016): 161. http://dx.doi.org/10.5455/ey.35948.

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Sarkar, Jyotirmoy, Bidisha Goswami, Snehanshu Saha, and Saibal Kar. "CD-SFA: stochastic frontier analysis approach to revenue modelling in large cloud data centres." International Journal of Communication Networks and Distributed Systems 21, no. 3 (2018): 315. http://dx.doi.org/10.1504/ijcnds.2018.094453.

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Kar, Saibal, Snehanshu Saha, Jyotirmoy Sarkar, and Bidisha Goswami. "CD-SFA: stochastic frontier analysis approach to revenue modelling in large cloud data centres." International Journal of Communication Networks and Distributed Systems 21, no. 3 (2018): 315. http://dx.doi.org/10.1504/ijcnds.2018.10015052.

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Louati, Salma, and Younes Boujelbene. "Banks’ stability-efficiency within dual banking system: a stochastic frontier analysis." International Journal of Islamic and Middle Eastern Finance and Management 8, no. 4 (November 16, 2015): 472–90. http://dx.doi.org/10.1108/imefm-12-2014-0121.

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Purpose – The purpose of this paper is to examine and compare the market power and the efficiency-stability of Islamic and conventional banks in the MENA zone and South East Asia during the 2005-2012 period. Design/methodology/approach – The author applied an empirical approach in two steps. First, the author estimates the Lerner indicator, which is a measure of competition. Then, this measure is regressed and other explanatory variables on the banking “stability-efficiency” are derived simultaneously from the estimation of a stability stochastic frontier. Findings – The author concludes that increased competition in the Islamic banking sector promotes the overall banking stability. Besides, whether there is a low or high competitiveness, the size of an Islamic bank is positively related to financial stability. However, large conventional banks operating in market with limited competitiveness become more involved in the risk behavior. The author concludes that capitalization has a positive effect on stability only in case of low competitiveness. Originality/value – The originality of this research lies in the application of the stochastic frontier approach (SFA) on the Z-score indicator. This methodology enables to take into account the differences between the current and the optimum stability that each bank can achieve, thus creating a new measure of financial stability called “efficiency-stability”.

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Dewi, Ivana Rosediana, and Bayu Arie Fianto. "EFISIENSI BANK SYARIAH ASEAN TAHUN 2013-2013: TWO-STAGE STOCHASTIC FRONTIER ANALYSIS." Jurnal Ekonomi Syariah Teori dan Terapan 7, no. 3 (June 25, 2020): 585. http://dx.doi.org/10.20473/vol7iss20203pp585-601.

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This study aims to determine the influences of internal and external variables of Islamic banks towards technical efficiency (TE)of Islamic banks in ASEAN 2013-2018. The data represented the sample from each country. The study was analyzed using two-step processes. The first stage is looking for technical efficiency (TE) with the Stochastic Frontier Analysis (SFA) as an intermediation approach. The second stage is conducting panel data regression analysis to determine the influence of internal and external variables of Islamic banks towards TE score. The result of the study indicates that the average TE value of Islamic banks in ASEAN at the periods of the study has very good efficiency of 0.92 (92.8 percent). Respectively, Islamic banks in Indonesia have TE score higher than Malaysia. Meanwhile, Islamic banks in Brunei Darussalam have the highest TE score, followed by Islamic banks in Thailand and the Philippines. The variable of total assets (lnTA), Degree of Capitalization (EQTA), and Bank's Financing Intensity (FINTA) have a positive and significant effect on the value of TE and the variable of economic growth (GDP) and inflation rate (CPI) have no effect on TE of sharia banks.Keywords: Technical Efficiency, Islamic Bank, ASEAN, Stochastic Frontier Analysis

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Sahoo, Auro Kumar, Dukhabandhu Sahoo, and Naresh Chandra Sahu. "Productive Performance of Indian Mining Industry: A Stochastic Frontier Decomposition." Global Journal of Business, Economics and Management: Current Issues 7, no. 1 (April 12, 2017): 80–88. http://dx.doi.org/10.18844/gjbem.v7i1.1469.

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This paper has estimated the Total Factor Productivity (TFP) growth of Indian mining Industry for the period 1989-2014 based on a decomposed formulation of stochastic production frontier. Productivity growth and its decomposed components have been compared over the study period. It is found that the annual average TFP growth of mining industry rose up from 3.66 % during 1989-2005 to 8.76 % during 2006-2014. Further, the result of decomposition reflects that the major source of productivity growth has changed from Technological Progress (TP) in initial years to Technical Efficiency Change (TEC) in recent years. In view of this, it could be suggested that mining industry in India requires to focus on investment in innovation and up-gradation of existing technology to further enhance productivity. Keywords: Total Factor productivity; Mining Industry; Panel data; Stochastic Frontier Analysis (SFA)

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Asmara, R., N. Hanani, S. Syafrial, and M. M. Mustadjab. "TECHNICAL EFFICIENCY ON INDONESIAN MAIZE PRODUCTION: FRONTIER STOCHASTIC ANALYSIS (SFA) AND DATA ENVELOPMENT ANALYSIS (DEA) APPROACH." Russian Journal of Agricultural and Socio-Economic Sciences 58, no. 10 (October 25, 2016): 24–29. http://dx.doi.org/10.18551/rjoas.2016-10.03.

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Ahmad, Wan Muhamad Amir W., Mohamad Arif Awang Nawi, and Nor Azlida Aleng. "Relative efficiency analysis industry of life and general insurance in Malaysia using stochastic frontier analysis (SFA)." Applied Mathematical Sciences 7 (2013): 1107–18. http://dx.doi.org/10.12988/ams.2013.13100.

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Sav, G. Thomas. "Efficiency Estimates and Rankings Employing Data Envelopment and Stochastic Frontier Analyses: Evaluating the Management of U.S. Public Colleges." Information Management and Business Review 4, no. 8 (August 15, 2012): 444–52. http://dx.doi.org/10.22610/imbr.v4i8.999.

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This paper estimates and compares operating efficiencies of publicly owned associate degree granting colleges in the United States using data envelopment analysis (DEA) and stochastic frontier analysis (SFA). Comparisons are based on panel data for 698 colleges over four academic years, 2005-09. Included are both constant and variable returns to scale DEA estimates along with half and truncated normal inefficiency SFA estimates. The values 0.56 vs. 0.45 represent the largest mean DEA-SFA efficiency differential. DEA results indicate that 13% of colleges are fully (100%) efficient while SFA puts that percentage at only 1.7%. Comparisons of rankings based on efficiency performance generated a weak 0.65 correlation. Encouragingly, despite the financial turmoil initiated by the global crisis, the findings indicate that colleges have managed large efficiency gains over the four-year period. By 2008-09, DEA estimated efficiency increased to approximately 60%. Given continuing reductions in higher education public funding and increasing interest in public management reforms, the results should be of both managerial and public policy interest.

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Lazović-Pita, Lejla, and Lamija Šćeta. "A Stochastic Frontier Approach to Measuring Inefficiency of Local Communities in Bosnia and Herzegovina." South East European Journal of Economics and Business 16, no. 1 (June 1, 2021): 18–29. http://dx.doi.org/10.2478/jeb-2021-0002.

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Abstract The significance and methods of measuring inefficiency of local communities has been gaining prominence in the last decade. The purpose of this paper is to empirically investigate the level of technical inefficiency in the sample of local communities in Bosnia and Herzegovina (BiH) for the year of 2017. We implement parametric stochastic frontier analysis (SFA) to conduct an input-oriented stochastic parametric approach to measuring technical inefficiency of local communities in BiH. The results of our work are complementary to previous research indicating relative technical inefficiency of local communities in BiH. On average, BiH local communities’ total expenditures can be reduced by 46.8 percent without reducing output levels to achieve the result of the local community on the best practice frontier. Since our analysis and selection of variables are driven by data availability, the future research plans to include more variables.

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Yan, Jiao, Chunlai Chen, and Biliang Hu. "Farm size and production efficiency in Chinese agriculture: output and profit." China Agricultural Economic Review 11, no. 1 (February 4, 2019): 20–38. http://dx.doi.org/10.1108/caer-05-2018-0082.

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PurposeThe purpose of this paper is to analyze the relationship between farm size and agricultural production efficiency from the aspects of output and profit in order to find an optimal farm size that achieves both output and profit efficiency in agricultural production in China.Design/methodology/approachThis study uses the 2012 China Family Panel Studies survey data and employs the stochastic frontier analysis (SFA) models to investigate empirically the relationship between farm size and agricultural production efficiency.FindingsThe study finds that there is an inverted-U curve relationship between farm size and output efficiency and a U-shaped curve relationship between farm size and profit efficiency in agricultural production in China. Based on the empirical results, the study estimates that the appropriate farm size is around 10–40 mu and the optimal farm size is around 20–40 mu both in terms of output efficiency and profit efficiency in Chinese agricultural production under the current agricultural technology and land management system.Practical implicationsThe findings of this study suggest that appropriate land consolidation will bring more benefits to farmer households and agricultural production efficiency. There are some policy implications. First, governments should give long term and more stable land using rights to farmers through extending the period of land contract and verifying land using rights. Second, governments should encourage transfers of land using rights and promote land consolidation. But the implementation of this policy should consider regional differences and not be used for blindly pursuing increasing land size. Third, land consolidation should be accompanied with the development of specialized agricultural services.Originality/valueThe paper makes two major contributions to the literature. First, the authors use the SFA model to investigate the relationship between land size and agricultural production efficiency. Second, the authors establish two SFA models – the stochastic frontier output analysis model and the stochastic frontier profit analysis model – to estimate the optimal land size to achieve both output and profit efficiency of agricultural production in China.

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Kumar, Manoj. "A Stochastic Frontier Analysis of Exporting Small and Medium Sized Enterprises in India." International Journal of Strategic Information Technology and Applications 7, no. 3 (July 2016): 1–23. http://dx.doi.org/10.4018/ijsita.2016070101.

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This study employs a stochastic frontier analysis (SFA) and technical inefficiency effects model to predict the technical efficiency of 3,168 Indian manufacturing and exporting SMEs, analyze their returns to scale and key factors impacting on their technical efficiency. Indian manufacturing and exporting SMEs extensively rely on labor rather than capital to increase their output, including almost all exporting SME groups, except those exporting to North & South America. The production of Indian manufacturing SMEs exporting to Oceania, however, has increasing returns to scale (1.1965). The inefficiency effects model reveals that firm size, firm age, foreign ownership, location and government assistance are firm-specific factors that significantly affect the technical inefficiency of production. Finally, evidence-based policies are also provided to facilitate improvement in the technical efficiency performance of Indian manufacturing and exporting SMEs.

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Anggraeni, Anggraeni, and Iik Arie Saputri. "Diversifikasi Aset, Risiko Bank, Ukuran Bank, dan Likuiditas Bank terhadap Efisiensi Bank Syariah dengan Metode SFA." Journal of Business and Banking 10, no. 1 (October 30, 2020): 129. http://dx.doi.org/10.14414/jbb.v10i1.2182.

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The purpose of this study is to examine the effect of Asset Diversification, Bank Risk, Bank Size and Bank Liquidity on the Efficiency of Sharia Banks Using Stochastic Frontier Analysis (SFA). This research methodology uses eleven Sharia Commercial Banks in Indonesia that have been registered with the OJK for the 2014-2018 period. The results of the data obtained in the quarterly financial statements per December were analyzed using efficiency analysis using Frontier 4.1 and descriptive and statistical analysis through the SPSS 16.0 program.The results showed that ADIV-HHI, NPF, and FDR had a negative effect on efficiency. Whereas Total Assets has a positive effect on Efficiency. And ADIV-HHI, NPF, Total Assets, and FDR simultaneously have a significant effect.

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Haider, Salman, and Javed Ahmad Bhat. "Inter-state analysis of energy efficiency- a stochastic frontier approach to the Indian paper industry." International Journal of Energy Sector Management 12, no. 4 (November 5, 2018): 547–65. http://dx.doi.org/10.1108/ijesm-05-2017-0008.

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Purpose This paper aims to measure the state-level energy efficiency in Indian paper industry and simultaneously explain inter-state variation in efficiency by inefficiency effect model. Three variables, labor productivity, capital intensity and structure of paper industry, are included in inefficiency effect model to assess the likely impact on energy efficiency. Design/methodology/approach Sub-vector input distance function is derived through neo-classical production function which provides measures to estimate energy efficiency. Assuming a translog production function specification, energy efficiency is estimated by using Battese and Coelli (1995) stochastic frontier analysis (SFA). The authors also estimated four other SFA models, and energy efficiency from all the models is compared for robustness checking. Findings The results show the existence of a vast potential to improve energy efficiency. Inefficiency effect model reported a positive impact of structure of the industry and capital intensity on energy efficiency performance, while labor productivity does not have any significant impact on energy efficiency. There exists considerable energy efficiency variation among states. Uttarakhand, Punjab and Orissa are the best performing states while Rajasthan, Jharkhand and Goa have worst energy efficiency performance based on average efficiency. The ranks assigned to states according to inefficiency effects model are found contrary to the simple measure of energy efficiency, i.e. energy intensity. Thus, energy intensity may not always be a good proxy for underlying energy efficiency and need to be compared with a comprehensive possible measure. Originality/value To the best of the authors’ knowledge, this is the first study which measures energy efficiency of Indian paper industry through stochastic frontier model using region-level data. Instead of relying on traditional energy efficiency indicators (energy-output ratio), total-factor energy efficiency approach is used to conduct the empirical exercise. Deviations from the frontier because of factors beyond the scope of producers are also incorporated into analysis to portray the magnitude of random factors in influencing the efficiency performance.

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Blatnik, Patricia, Štefan Bojnec, and Matej Tušak. "Measuring efficiency of secondary healthcare providers in Slovenia." Open Medicine 12, no. 1 (July 6, 2017): 214–25. http://dx.doi.org/10.1515/med-2017-0031.

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AbstractThe chief aim of this study was to analyze secondary healthcare providers' efficiency, focusing on the efficiency analysis of Slovene general hospitals. We intended to present a complete picture of technical, allocative, and cost or economic efficiency of general hospitals.MethodsWe researched the aspects of efficiency with two econometric methods. First, we calculated the necessary quotients of efficiency with the stochastic frontier analyze (SFA), which are realized by econometric evaluation of stochastic frontier functions; then, with the data envelopment analyze (DEA), we calculated the necessary quotients that are based on the linear programming method.ResultsResults on measures of efficiency showed that the two chosen methods produced two different conclusions. The SFA method concluded Celje General Hospital is the most efficient general hospital, whereas the DEA method concluded Brežice General Hospital was the hospital to be declared as the most efficient hospital.ConclusionOur results are a useful tool that can aid managers, payers, and designers of healthcare policy to better understand how general hospitals operate. The participants can accordingly decide with less difficulty on any further business operations of general hospitals, having the best practices of general hospitals at their disposal.

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Rezaei, Satar, Hamed Zandian, Akram Baniasadi, Telma Zahirian Moghadam, Somayeh Delavari, and Sajad Delavari. "Measuring the Efficiency of a Hospital based on the Econometric Stochastic Frontier Analysis (SFA) Method." Electronic physician 8, no. 2 (February 25, 2016): 2025–29. http://dx.doi.org/10.19082/2025.

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Amelda, Banon, and Erna Bernadetta Sitanggang. "Analysis of Banking Industry Performance Efficiency in Indonesia Using Parametric and Nonparametric Methods." Winners 19, no. 1 (March 31, 2018): 53. http://dx.doi.org/10.21512/tw.v19i1.4760.

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This research aimed to measure the efficiency performance of the banking industry in Indonesia by using parametric and nonparametric methods, as measured by the stabilization of bank performance efficiency based on the time series from year to year and to identify which variables to the value of efficiency. The analytical method applied the parametric method with cross section approach of Stochastic Frontier Analysis (SFA) while for nonparametric method used intermediation approach from Data Development Analysis (DEA) CRS and VRS model. The data of this research was the financial statements of banks listed on the stock exchange for the period 2012-2016 with 29 databanks processed with the help of Stata 12. From the results of the analysis using the three measures of efficiency, it is known that the efficiency value with Cross Section Stochastic Frontier Analysis shows a stable and high efficient conditions for all banks. While nonparametric methods show different efficiency levels for each bank, which with DEA CRS model not all banks show an efficient performance, only 26,90% on average each year banks have efficient performance, and 99,31% of banks perform efficiently according to VRS model.

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Sabur, Abdus, and Abu Sina. "STOCHASTIC FRONTIER APPROACH OF VALUE ADDED MEASURES OF SUGAR PRODUCTION IN BANGLADESH: AN EMPIRICAL ANALYSIS." International Journal of Research -GRANTHAALAYAH 6, no. 5 (May 31, 2018): 289–99. http://dx.doi.org/10.29121/granthaalayah.v6.i5.2018.1451.

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An attempt has been taken to explore the causes of inefficiency of management of sugar industry in Bangladesh by applying Stochastic Frontier Approach (SFA) that contains three steps of estimation. According to value of output measurement by SFA, parameter was found with positive values indicating potential production deferred from actual production. The return to scale of the sample was estimated 1.84 implied increasing returns to scale. The parameter () of OLS for the sample was found less than that of MLE for the cause of below position of potential output. (Lambda) was the ratio of variance of industry specific production behaviors (u) to the variance of statistical noise (v). Here that ratio was found 1.69 and 1.11 for the half-normal and truncated normal distribution which indicated that there were impacts due to inefficiency of the management dominated by random disturbances of the sugar industry in Bangladesh. The value of was estimated 74 percent and 55 percent for half normal and truncated normal indicating 74 percent and 55 percent output in sugar production were due to inefficiency of the management. The parameter () was found negative for both the methods which indicated that the technical efficiency was decreasing over the time. The mean technical efficiency of sample was 54.45 percent and 35.45 percent for the half normal and truncated normal distribution. This further indicated that the management could increase the production level by 45.55 percent and 64.55 percent respectively using same level of inputs. The suggestion and recommendation has been provided to improve managerial skills, increase skilled manpower, introduce higher sucrose content cane, modernization of machineries and reduction of overhead cost.

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Pevcin, Primož. "Efficiency levels of sub-national governments: a comparison of SFA and DEA estimations." TQM Journal 26, no. 3 (April 8, 2014): 275–83. http://dx.doi.org/10.1108/tqm-12-2013-0127.

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Purpose – By utilizing the two most commonly used approaches to generate “best practice frontier” to estimate efficiency of observed units, the purpose of this research paper is to estimate technical efficiency for total population of 200 Slovenian municipalities for the 2011 fiscal year. Design/methodology/approach – Stochastic frontier analysis (SFA) and data envelopment analysis (DEA) methods are used to estimate technical efficiency levels. Namely, the majority of studies have utilized these two “traditional” approaches. Since the advantages of one method often represent the disadvantages of the other method, the two methods have been selected to compare the results obtained on the technical efficiency levels. Findings – The results suggest that mean technical inefficiency should be approximately 22-25 percent (SFA method), whereas DEA method suggests the inefficiency in the range 12-18 percent. The DEA approach also suggests that the paper has many more technically efficient units compared to the SFA estimates. Nevertheless, the SFA assessment has revealed that, although on average the inefficiency should be larger compared to the DEA assessment, more than one-third of municipalities should exhibit relatively low levels of inefficiency (less than 5 percent). Originality/value – This study utilizes both parametric as well as non-parametric approaches to assess the technical efficiency, which is not very common in the empirical literature. Besides, it focusses on the local government efficiency in a post-socialist country.

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Journal articles on the topic 'Stochastic frontier analysis (SFA)'

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