Pitching DEA against SFA in the context of Chinese domestic versus foreign banks

Avkiran, Necmi Kemal and Zhu, Yushu (Elizabeth) (2016). Pitching DEA against SFA in the context of Chinese domestic versus foreign banks. In Shiuh-Nan Hwang, Hsuan-Shih Lee and Joe Zhu (Ed.), Handbook of operations analytics using data envelopment analysis (pp. 113-143) New York, NY, United States: Springer Science+Business Media. doi:10.1007/978-1-4899-7705-2_5


Author Avkiran, Necmi Kemal
Zhu, Yushu (Elizabeth)
Title of chapter Pitching DEA against SFA in the context of Chinese domestic versus foreign banks
Title of book Handbook of operations analytics using data envelopment analysis
Place of Publication New York, NY, United States
Publisher Springer Science+Business Media
Publication Year 2016
Sub-type Research book chapter (original research)
DOI 10.1007/978-1-4899-7705-2_5
Open Access Status Not Open Access
Year available 2016
ISBN 9781489977038
9781489977052
ISSN 0884-8289
Editor Shiuh-Nan Hwang
Hsuan-Shih Lee
Joe Zhu
Volume number 239
Chapter number 5
Start page 113
End page 143
Total pages 31
Total chapters 18
Collection year 2017
Language eng
Formatted Abstract/Summary
The primary motivation is to show how the efficient fronier methods data envelopment analysis (DEA) and stochastic frontier analysis (SFA) can be used synergistically. As part of the illustration, we directly compare locally incorporated foreign banks with Chinese domestic banks. Both DEA and SFA reveal that foreign banks are less efficient. DEA shows the main source of inefficiency for foerign banks as managing interest income, whereas domestic banks are inefficient in managing non-interest income and interest expense. SFA reveals contextual variables such as interbank ratio, loan-to-deposit ratio and cost-to-income ratio are significant in explaining inefficiency. The correspondence of rankings based on DEA vs. SFA is positive and moderate in strength but efficiency estimates do not belong to the same distribution. Using DEA and SFA side-by-side can encourage more rigorous and in-depth bank efficiency studues where each method's limitation can be overcome by the other. 
Keyword Technical efficiency
Scale efficiency
Data Envelopment Analysis
Stochastic frontier analysis
Single-output Translog function
Multi-output Translog distance function
Cobb-Douglas function
Robustness testing
Chinese banks
Efficiency spillovers
Profitability
Potential improvements
Efficiency contribution measure
Q-Index Code B1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes http://link.springer.com/chapter/10.1007/978-1-4899-7705-2_5

Document type: Book Chapter
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Created: Thu, 04 Aug 2016, 15:51:21 EST by Karen Morgan on behalf of UQ Business School