This is a paper that focuses on the estimate the technical efficiency scores using Data Envelopment Analysis. The paper also provides further instructions to follow in the assignment.
Estimate the technical efficiency scores using Data Envelopment Analysis
This assignment provides you with a balanced panel of financial data for a sample of 63 banks over the last 7 years. The variables provided represent the factors needed to estimate bank efficiency for the sample of banks. You can access the data by logging in to Blackboard and download the file named
Assignment_banks_data.xlsx to start work on the following requirements.
1. Firstly, estimate the technical efficiency scores for each bank using Data Envelopment Analysis (DEA) under the following assumptions
a. Constant returns to scale (CRS)
b. Variable returns to scale (VRS)
Briefly explain the difference between the two assumptions.
2. Secondly, estimate the cost efficiency for each bank using the VRS assumption. Now, estimate the allocative efficiency scores.
Compare the cost efficiency, technical efficiency, and allocative efficiency scores for each ownership group and briefly explain your results.
3. Thirdly, managerial ability is an unobservable trait of an organization, and it is often estimated by the residual claim on bank efficiency after controlling for bank characteristics. For example, bank efficiency = firm characteristics +
managerial ability. Use the bank efficiency scores you obtained in Part 1 above, under VRS assumption, to estimate managerial ability for the banks, and provide a density distribution for it. Compare the managerial ability
The assignment consists of three distinct tasks above. Your paper should be presented in the form of a report with a 250 words executive summary of your findings. However, this does not count against the word count. Each task should contain a short section or subsection header that alerts the reader on what is being done in that (sub)section.
Use the information provided in the data file to group the data accordingly in accord with the requirements above.
Note that the data provided is in 000$ dollars. So, you should scale the data before estimating the DEA models.
You can use Excel, Stata, R, DEAP or any other software to compute estimates. Attach the computer output you generated in a clearly labelled Appendix. For example, Appendix A (what is contains); Appendix B (what it contains), etc. The same goes for any charts, plots, etc., that you choose to place in an appendix instead of the body of the main paper.
Refer to the lecture slides and seminar hand-outs for more guidance on how to utilise the software required to compute the estimates above. For example, you may simply wish to edit one of the sample R programs or Stata programs given in lectures as a starting point, and use that to conduct your analysis.