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A Simultaneous Stochastic Frontier Model with Dependent Error Components and Dependent Composite Errors: An Application to Chinese Banking Industry

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Faculty of Economics, Shandong University of Finance and Economics, Jinan 250000, China
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Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand
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Institute of Economics, Yunnan Academy of Social Sciences, Kunming 650031, China
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Plymouth Business School, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(2), 238; https://doi.org/10.3390/math8020238
Received: 16 January 2020 / Revised: 9 February 2020 / Accepted: 10 February 2020 / Published: 13 February 2020
(This article belongs to the Special Issue Statistics 2020)
The paper develops a simultaneous equations stochastic frontier model (SFM) with dependent random noise and inefficiency components of individual equations as well as allowing dependence across all equations of the model using copula functions. First, feasibility of our developed model was verified via two simulation studies. Then the model was applied to assess cost efficiency and market power of the banking industry of China using a panel data of 37 banks covering the period 2013–2018. Results confirmed that our simultaneous SFM with dependent random noise and inefficiency components outperformed its predecessor, which is a simultaneous SFM with dependent composite errors but with independent random noise and inefficiency components of individual SFMs as well as the conventional single-equation SFM. Apart from the statistical and computational superiority of our developed model, we also see that Chinese banks in general have a high level of cost efficiency and that competition in the banking industry of China mainly exists in state-owned banks and joint stock banks. Presence of economies of scales as well as diseconomies of scales were found in different banks. Also, the state-owned banks embraced most sophisticated technologies thereby allowing them to operate with the highest level of cost efficiency.
Keywords: simultaneous SFM; dependent error components; copula functions; simulation study; market power; cost efficiency; technology gap ratio simultaneous SFM; dependent error components; copula functions; simulation study; market power; cost efficiency; technology gap ratio
MDPI and ACS Style

Liu, J.; Wang, M.; Ma, J.; Rahman, S.; Sriboonchitta, S. A Simultaneous Stochastic Frontier Model with Dependent Error Components and Dependent Composite Errors: An Application to Chinese Banking Industry. Mathematics 2020, 8, 238.

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