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  4. Technical Efficiency of Financial Holding Companies: An Application of Stochastic Distance Function
 
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Technical Efficiency of Financial Holding Companies: An Application of Stochastic Distance Function

Date Issued
2016
Date
2016
Author(s)
Li, Meng-Hsi
DOI
10.6342/NTU201601818
URI
http://ntur.lib.ntu.edu.tw//handle/246246/275986
Abstract
The purpose of this study is to analyze the technical efficiency of the private financial holding companies and its subsidiary by using the input-oriented stochastic distance model and Malmquist productivity index data collected from domestic financial holding companies during the period 2006 through 2015. The results of the technical efficiency rank show that the technical efficiency between private holding companies and its bank subsidiary are not significantly correlated while the encounter part of holding companies and its securities subsidiary are negatively correlated. In addition, the results of the assets scale rank show that the assets scale between private holding companies and its banks subsidiary are significantly positively correlated. Finally, Malmquist productivity index analysis found that the average of private holding companies experienced an improvement in pure efficiency and scale efficiency, but deterioration in technical efficiency and TFP in these 10 years. The bank subsidiary has an improvement in technical change, scale efficiency and TFP, but deterioration in pure technical efficiency. The securities subsidiary has an improvement in pure technical efficiency, technical efficiency and TFP efficiency, but the same in scale efficiency. The empirical results show that part of the bank subsidiary have large scale of asset but lack of technical efficiency. Therefore, the study recommends that all financial holding companies implement a comprehensive review of all its subsidiaries to make sure to have capital efficiency, cross selling and cost saving.
Subjects
Private financial holding companies
Technical efficiency
Malmquist Productivity index
Stochastic distance function method
Type
thesis
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ntu-105-R03627021-1.pdf

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