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Measuring Efficiency Of Mongolian Companies By Sfa And Dea Methods

Author

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  • Batchimeg Bayaraa

    (The University of Debrecen)

Abstract

Efficiency measurement usually adopts one of the following analysis, DEA (Data Envelopment Analysis) or SFA (Stochastic Frontier Analysis), but it is not common to use and compare both models in one research. Especially, there is not any research about performance measurement which used Mongolian companies’ financial data. The aim of this research is to examine the consistency of efficiency scores from DEA and SFA methods on Mongolian public companies. The financial statements of 100 public companies were obtained from the Mongolian Stock Exchange (MSE) website, from 2012 until 2015. Financial statements were chosen which met the requirements of consistency and accuracy, out of 227 public companies. From initially selected 9 output variables, revenue was chosen as an output variable, while cost of goods sold, operating expenses, and cash are used as input variables based on the stepwise regression result. SPSS (Statistical Package for the Social Sciences) software was used for linear regression to choose the variables; Pearson correlation to examine the correlation between variables and the correlation between efficiency scores of DEA, SFA, and COLS (Corrected Ordinary Least Squares); one-way ANOVA was used to determine statistically significant difference among the methods; and unrelated T-test was used for every pair models. In contrary, Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) were performed in R- Excel statistical program. The average efficiency results indicated that the SFA model exhibited the highest score of 0.75 (TeMode), followed by DEA-VRS (Variable Return to Scale) 49.1 and DEA-CRS (Constant Return to Scale) 33.8. Due to the low-efficiency score, scale efficiency was adopted, and the result showed only 3 companies work in an optimal efficient scale, while 42 companies work below an efficient scale, and 55 companies work above an efficient scale. Unrelated T-test result showed that there was not statistically significant difference among Tej, TeBC, and COLS; TeMode and CRS; CRS and output efficiency.

Suggested Citation

  • Batchimeg Bayaraa, 2017. "Measuring Efficiency Of Mongolian Companies By Sfa And Dea Methods," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 39-48, July.
    • Handle: RePEc:ora:journl:v:1:y:2017:i:1:p:39-48
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    References listed on IDEAS

    as
    1. Robert Lensink & Aljar Meesters, 2014. "Institutions and Bank Performance: A Stochastic Frontier Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 67-92, February.
    2. James I. Price & Steven Renzetti & Diane Dupont & Wiktor Adamowicz & Monica B. Emelko, 2017. "Production Costs, Inefficiency, and Source Water Quality: A Stochastic Cost Frontier Analysis of Canadian Water Utilities," Land Economics, University of Wisconsin Press, vol. 93(1), pages 1-11.
    3. Banker, Rajiv D. & Cooper, William W. & Seiford, Lawrence M. & Thrall, Robert M. & Zhu, Joe, 2004. "Returns to scale in different DEA models," European Journal of Operational Research, Elsevier, vol. 154(2), pages 345-362, April.
    4. Peter Bogetoft & Lars Otto, 2011. "Benchmarking with DEA, SFA, and R," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7961-2, April.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Data Envelopment Analysis (DEA); Stochastic Frontier Analysis (SFA); input efficiency; output efficiency; Variable Return to Scale (VRS); Constant Return to Scale (CRS); Corrected Ordinary Least Squares (COLS);
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

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