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Discrepancy in efficiency scores due to sampling error in data envelopment analysis methodology: evidence from the
Kishore L1, Geetha E1, Shivaprasad S P2
1Department of Commerce, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
F1000Research
|February 17, 2025
Summary
This study reveals that sampling errors can significantly impact bank performance evaluations using Data Envelopment Analysis (DEA). Researchers must take preventive measures to avoid misleading results in DEA studies.
Area of Science:
- Financial analysis
- Econometrics
- Statistical modeling
Background:
- Data Envelopment Analysis (DEA) is a preferred method for bank efficiency assessment.
- Traditional ratio analysis may be less effective than DEA.
- Sampling errors can compromise DEA performance evaluations.
Purpose of the Study:
- To provide statistical evidence of sampling errors in DEA.
- To demonstrate how sampling errors affect bank efficiency scores.
- To highlight the need for error mitigation in DEA studies.
Main Methods:
- Utilized secondary data from Indian banks' financial reports (2014-2017).
- Included 15 public and 5 private sector banks.
- Applied non-parametric statistical tests to analyze efficiency measures.
Main Results:
- Statistically significant discrepancies in DEA efficiency scores were observed.
- Inclusion or exclusion of specific samples led to significant efficiency differences.
- Outlier values demonstrably affected DEA calculations.
Conclusions:
- Sampling error is a critical concern in DEA performance evaluations.
- Novel statistical evidence confirms the potential for sampling error in DEA.
- Preventive measures are essential to ensure accurate DEA results.
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