Banking Models

As a consequence of the complexity of the banking industry, banking efficiency is proposed to be measured in three different levels under three separate models. Each model has its primary objectives and the subsequent model is built on the foundation of the previous but has an expanded series of research objectives. In the end, the final model captures the overall measure of banking efficiency. This proposal is consistent with an earlier suggestion by Cooper et al (2006).

The most immediate consideration in measuring banking efficiency under DEA is the choice of inputs and outputs but in the context of small economies with smaller number of banks, the number of inputs and outputs are equally or even more

important. Barr et al (1999) and Dyson et al (2001) suggest the criteria for selecting the inputs and outputs for DEA to include: the factors cover the full range of

resources used; the factors capture all activity levels and performance measures; and factors are common to all units. In addition, the literature suggests the number of observations should be greater than (3* sum of inputs and outputs variables).

The focus for Model 1 is the cost of intermediation, model 2 shifts the focus towards commercial banks traditional intermediation, and model 3 captures the overall production process by the commercial banks. These three models are explored on a national basis and regional basis. Both approaches are used in the literature separately but in this context each approach has a role to play in assisting the construct of

banking efficiency and more importantly in explaining the potential causes for the variation in banking efficiency scores. This in turn provides greater potential for a more comprehensive series of validation procedures for efficiency scores derived from the local frontier in one hand and the regional or common frontier in the other. Therefore, resulting efficiency scores are expected to be more reliable and meaningful. 4.4.1.1 Model 1 - Cost of the Intermediation Process

The main objective for this model is to bridge the gap between efficiency and

profitability since the only difference between the inputs and the outputs is the income statement resulting profits (except variation in tax obligations between countries and

abnormal items are usually uniquely different from case to case). The input variables are interest expense (IEX) and non-interest expense (NIEX); and the output variables include interest income (IINC) and non-interest income (NIINC).

This simple model can also be used to track down how resulting efficiency scores change as the variables (inputs and outputs) in the other models are added. This aspect explains the isotone or more precisely, cd-directional isotone property of efficiency, previously discussed in chapter 2. In that context, variation in efficiency scores from this model is not analysed and in depth analysis is conducted on model 2 and 3. 4.4.1.2 Model 2 - Traditional Banking Activities

The focus of this model is to investigate the efficiency of the traditional banking activities based on the transformation of deposits into loans, and consequently, the intermediation process is the dominant feature of this model. This process also takes into consideration the impact of three primary data features earlier discussed:

commercial banks annual growth, intermediation process, and asset quality. Another consideration is to capture the potential impact of CAR on efficiency. The inclusion of the CAR in this discussion as opposed to model 3 is based on the notion that this prudential requirement is primarily expected to counter the possibility of over-lending by banking institutions and the likelihood of excessive credit risk. The inputs variables are: total deposit (TD) and non-interest expense (NIEX); and the output variables consist of: gross loan (GL), net interest income (NTIC), and non- interest income (NIINC). The obvious difference between this model and the earlier model is evident in the expanded number of variables included: customer deposits is the dominant input, gross loans is the main output and interest based items are replaced by the net interest income variable as an output. In addition, the resulting efficiency scores from this model are further analysed to explain the potential determinants of banking efficiency variations. This analysis is conducted in both the national and the cross country frameworks. Finally, the resulting efficiency scores from both frameworks are validated to strengthen the reliability and economic contribution of the results.

4.4.1.3 Model 3 - Banking Production Process

This model is the most important component of the three models and it is expected to investigate some of the most challenging aspects of this research. The difference between this model and the earlier models are the expanded number of variables. The inputs variables are: deposit available for loans (DAL), defined as total deposits plus purchased funds minus SRD; non-interest expense (NIEX). The output variables consist of: gross loan (GL); non-interest income (NIINC); net-interest income (NTIC), it is the total interest income minus interest expense; and other earning assets (OEA) defined as net interbank position plus government debts and investment securities. Similar to model 2, the resulting efficiency scores from this model are further analysed to explain the potential determinants of banking efficiency variations. Contrary to model 2, the impact of LAR, macro economic effects, and bank stability are the main considerations. Again, this analysis is conducted in both the national and the cross country frameworks. The resulting efficiency scores from both frameworks are also validated to strengthen the reliability of the resulting efficiency scores. However, the validation procedure for model 3 is more stringent than model 2 and this procedure is also repeated in both frameworks.