Decompositions of profit change: With an application to Taiwanese banking
Date Issued
2011
Date
2011
Author(s)
Juo, Jia-Ching
Abstract
In the framework of data envelopment analysis (DEA), there are two different measures of efficiency: radial and non-radial. The radial measure originated from the CCR model (Charnes et al., 1978), whereas the non-radial DEA methodology is represented by the slack-based measure (SBM) (Tone, 2001). Regarding the studies on decompositions of profit change, Grifell-Tatjé and Lovell (Grifell-Tatjé, E., Lovell, C.A.K., 1999. Profits and productivity. Management Science 45, 1177-1193) decompose profit change of banks into six exclusive components using the radial DEA framework so as to consider the linkage between productivity change and profit change. Sahoo and Tone (Sahoo, B.K., Tone, K., 2009. Radial and non-radial decompositions of profit change: With an application to Indian banking. European Journal of Operational Research 196, 1130-1146) adopt SBM to decompose profit change of a bank so as to address the concerns of non-radial slacks. However, both the above two studies never consider the input side when decomposing the productivity effect. In fact, the change in operating profit can be traced from the change in revenue (the output side) and the change in cost (the input side).
Therefore, the study will propose two DEA approaches, directional distance function (DDF) and non-oriented SBM, to extract more complete drivers of profit change and illustrate the decompositions with these two approaches. The former is set as a kind of radial DEA framework. Both the two approaches illustrate the decompositions of profit change to Taiwanese banks during the period 1994-2002 and arrive at the following results. First, in the process of decomposing the productivity effect, both of them can extract the additional effect (i.e. the input side) which cannot be found in previous papers. Second, the DEA approach of Grifell-Tatjé and Lovell (1999) analysis (GLA) and DDF of our study exhibit the same direction of contribution by the technical change effect and the operating efficiency effect over the entire period. Third, when we use DDF to decompose the productivity effect, we find that the negative contribution of the output side slightly outweighs that of the input side over the entire period. Fourth, with regard to the additional components extracted by the non-oriented SBM, the study finds that the output side outweighs the input side within the productivity effect during some of our sample periods.
Subjects
banks
profit change
decomposition
data envelopment analysis
directional distance function
DEA
slacks
SBM
Type
thesis
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