Page 145 - Contributed Paper Session (CPS) - Volume 7
P. 145

CPS2048 Md Zobaer H. et al.
               Table  2:  Regression  Analysis  between  Efficiency  (derived  from  DEA,  SFA  and
               CDS) and Profit Risk
                           Model      Constant    Coefficients     S.E    p-value
                                        ( 0 )    (1)
                           DEA         -1.765      0.461 *      4.317     0.018
                           CDS        -10.591      0.54 *       6.687     0.004
                           SFA        0.307        0.273 @      6.386     0.177
                                     * 5% significant, @ insignificant

               4.  Discussion and Conclusion
                   The study concentrates on three methods, SFA, DEA, and combination of
               DEA and SFA (CDS) on a sample of financial companies that are listed in Bursa
               Malaysia for finding most efficient method. The result shows that CDS has the
               most significant relationship with profit risk. However, all models present the
               unique conclusion that ACSM is the most efficient company. Additionally, this
               study finds most efficient method is CDS. All the companies’ efficiency scores
               lies  between  0.9819  and  0.7693.  Considering  no  consistency  on  different
               efficiency  scores  across  the  different  methods,  this  study  will  help  to
               investigate the efficiency of the financial sector and other sectors of Bursa
               Malaysia.

               References
               1.  Aigner, D., Lovell, C. K., & Schmidt, P. (1977). Formulation and estimation
                   of  stochastic  frontier  production  function  models.  Journal  of
                   econometrics, 6(1), 21-37.
               2.  Altunbas, Y., Carbo, S., Gardener, E. P., & Molyneux, P. (2007). Examining
                   the relationships between capital, risk and efficiency in European banking.
                   European Financial Management, 13(1), 49-70.
               3.  Battese,  G.  E.,  &  Coelli,  T.  J.  (1988).  Prediction  of  firm-level  technical
                   efficiencies  with  a  generalized  frontier  production  function  and  panel
                   data. Journal of econometrics, 38(3), 387399.
               4.  Cobb,  C.  and Douglas,  P.  H.  (1928).  A  theory of  production.  American
                   Economic Review, Vol. 18 No.1, 139–165.
               5.  Coelli, T., Rao, D.S.P. and Battese, G.E. (1998), An Introduction to Efficiency
                   Analysis, Kluwer Academic Publishers, Boston.
               6.  Coelli, T. (1996). A guide to DEAP version 2.1: a data envelopment analysis
                   (computer)  program.  Centre  for  Efficiency  and  Productivity  Analysis,
                   University of New England, Australia.
               7.  Coelli, T. J. (1996). A guide to FRONTIER version 4.1: a computer program
                   for stochastic frontier production and cost function estimation (Vol. 7, pp.
                   1-33). CEPA Working papers.


                                                                  132 | I S I   W S C   2 0 1 9
   140   141   142   143   144   145   146   147   148   149   150