Executing cost DEA of banks using Data Envelopment Analysis Program (DEAP)

The cost efficiency analysis or cost data envelopment analysis or cost DEA is evaluated when information on prices and costs are available from the source of the data collected for input and output variables (Cooper, Seiford, & Zhu, 2011). Cost efficiency test helps to improve in cost related performances of the organization and shows if the organization should lower or increase the inputs.

In case of cost efficiency testing in the case banks, it shows if the bank should decrease or increase their interest rates. Cost efficiency is defined as, “efficiency that gives a measure of how close a bank´s cost is to what a best-practice bank´s cost would be for producing the same bundle of output under the same conditions” (Kocisova, 2014, p.48). Moreover, it presents a bank’s efficient performance modulated by the costs or prices. In addition, a number of inputs provide proportional outputs in case of cost efficiencies. Cesaroni, (2017), mentioned it “cost minimizing industry structure”, where the efficiency shows that the prices of the industry can either lower or increase to become cost-effective.

Difference between Cost DEA and Multi-Stage DEA

Cost DEA

Multi-Stage DEA

Only when prices of products are available, restricted variables only cost related Most commonly used and no barriers for input and output variables
Includes prices in addition for evaluation Does not need price variables
Shows both technical and cost efficiency Only Technical efficiency
No Slacks, Target summary, peers or projected values Interpretations are based on; Slacks, Target summary, peers or projected values
Only Input oriented evaluation Both Input and Output oriented evaluations
Shows technical, allocative and cost efficiency Only technical efficiency

Table for the difference between Cost DEA and Multi-Stage DEA.

The most important difference is the restrictions of price values in Multi-stage DEA but not in Cost DEA (Coelli, 2008). However, to assess the minimizing cost of the products cost DEA is performed. In this process, the only input oriented analysis is possible because the evaluations show cost minimizing input quantities (Cooper, Seiford, & Tone, 2007). However, both constant returns to scale (CRS) and variable returns to scale (VRS) frontier models can be executed for multi-stage and cost DEA.

Extracting data and representing in DEAP

Even though price variables are very important in conducting Cost DEA, however, inputs and outputs variable are mandatory. Henceforth, same inputs and outputs used in finding cost-efficiency. The input variables are Total Capitals and Deposits while output variables are Total Loans and Profits.

Input, Output and Variable for Price

Input, output, and variable for price

The variables of price adopted from the review article by Kocisova, (2014). Here, “average costs to labor” and “fixed deposit prices” are for finding cost efficiency. In addition, costs to labors are dependent on profits of the bank which in turn is dependent on capitals and deposits. Similarly in the case of fixed deposits, which is dependent on interest rates are directly dependent on loans and profits which are directly proportional to capitals and deposits. Thereby, costs to labor and fixed deposit rates considered as the price values in conducting cost-DEA.

Furthermore, the values represented not calculated manually but by using the automated machines and tools. The banks or the DMU (Decision Making Units) are the same as in the previous articles.

Formulae

Average costs to labor calculated by the ratio of total expenses on wages, payroll taxes and trainings to the number of employees.

Price of labour or costs to labour= total personnel expenditure/ number of employees

Fixed deposit price can be calculated using the formula, A= P(1+(r/n)^nt)

Where; 
A = Final Amount received, 
P = Principal Amount (i.e. initial investment), 
r = Annual nominal interest rate (if interest is paid at 5.5% pa, then it will be 0.055) (not in percentage), 
n = number of times the interest is compounded per year
t = number of years.

Datasets

Dataset pasted in Notepad

Dataset pasted in Notepad

The image is the format for dataset similar to the one presented in previous articles. Henceforth, output columns followed by input columns and then price variables is the format in this DEA.

Executing Cost DEA

The changes made in the instructions file are;

  1. Change the result output file as required.
  2. Shift to input oriented by instructing “0” (since we cannot conduct an output-oriented Cost DEA).
  3. Change to Cost DEA in the last line to “1” (since we are conducting cost efficiencies).
Instructions file in Notepad for cost DEA

Instructions file in Notepad (check the changes in the image)

Henceforth, after making changes in the instructions file run the DEA program with the file name DEAP.EXE.

Cost efficiency has a big role in defining a bank’s influence in stock returns of banks (Akeem & Moses, 2014). Cost efficiencies show poor cost management. Furthermore, poor cost management leads to low bank profits. Moreover, a bank which shows cost efficiency, it means that the bank has efficiently focused on input and thereby leading to efficient outputs (Akeem & Moses, 2014).

References

  1. Cesaroni, G. (2017). Industry cost efficiency in data envelopment analysis. Socio-Economic Planning Sciences. https://doi.org/10.1016/j.seps.2017.01.001.
  2. Coelli, T. J. (2008). A Guide to DEAP Version 2.1: A Data Envelopment Analysis (Computer) Program. CEPA Working Papers, 1–50. Retrieved from https://absalon.itslearning.com/data/ku/103018/publications/coelli96.pdf.
  3. Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data Envelopment Analysis. Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software: Second Edition. https://doi.org/10.1007/978-0-387-45283-8.
  4. Cooper, W. W., Seiford, L. M., & Zhu, J. (2011). Handbook on Data Envelopment Analysis. In Chapter 1:Data Envelopment Analysis (pp. 1–39). https://doi.org/10.1007/978-1-4419-6151-8_1.
  5. Kocisova, K. (2014). Application of Data Envelopment Analysis to Measure Cost, Revenue and Profit Efficiency. Statistika, 94(3), 47–94.
Avishek Majumder

Avishek Majumder

Research Analyst at Project Guru
Avishek is a Master in Biotechnology and has previously worked with Lifecell International Private Limited. Apart from data analysis and biological research, he loves photography and reading. He loves to play football and basketball in his spare time with an avid interest in adventure and nature. He was also a member of the Scouts in his school and has attended Military training.
Avishek Majumder

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