MEASURING EFFICIENCY OF MONGOLIAN COMPANIES BY SFA AND DEA METHODS
Batchimeg Bayaraa ()
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Batchimeg Bayaraa: The University of Debrecen
Annals of Faculty of Economics, 2017, vol. 1, issue 1, 39-48
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.
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) (search for similar items in EconPapers)
JEL-codes: C14 C30 L25 (search for similar items in EconPapers)
Date: 2017
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