Determinants of efficiency in South East Asian banking

Gardener, Edward P. M.; Molyneux, Philip; Nguyen, Linh

doi:10.1080/02642069.2010.512659

Cited by 79 publications

(69 citation statements)

References 88 publications

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“…Previous studies show that bank efficiency is driven positively by bank size [64][65][66], indicating that bank efficiency varies for different regions or different bank types. By simultaneously incorporating a non-convex metafrontier, undesirable outputs and super-efficiency into a dynamic network SBM model, this paper proposes a new DEA model to reflect the bank production process, providing more a comprehensive and reasonable efficiency evaluation of banks in China.…”

Section: Determinants Of Bank Efficiency and Estimation Resultsmentioning

confidence: 99%

The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression

Huang

Shao

2019

Sustainability

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This paper develops a new network data envelopment analysis (DEA) model that simultaneously integrates the non-convex metafrontier and undesirable outputs and which is super efficient at performing dynamic network slacks-based measures. The model is employed to discuss the efficiency of 36 commercial banks in China during the years 2010–2014. The efficiency of these banks shows significant heterogeneity and the efficiency of most foreign banks has much room for improvement. Regarding both the non-convex metafrontier and the group frontier, state-owned banks perform the best, followed by joint-stock banks, with foreign banks performing the worst; the same is true for the technology gap ratios. The empirical results produced by the feasible generalized least squares estimation method indicate that liquidity and scale effects exert positive impacts on bank efficiency. An alternative estimation method confirmed that the conclusions were robust.

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Section: Determinants Of Bank Efficiency and Estimation Resultsmentioning

confidence: 99%

The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression

Huang

Shao

2019

Sustainability

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“…This includes studies on how the crisis impacted bank efficiency in Malaysia and Thailand (Casu and Girardone, 2006), a Data Envelopment Analysis (DEA) study of Thailand's bank efficiency from 1998 to 2008 (Nguyen and Williams, 2003) and changes in the Indonesian banking system's productivity, risk and profitability (Hadad et al, 2011, Kapopoulos andSiokis, 2005). There are also ASEAN-based studies which focused on financial systems development post-Asian Financial Crisis (Shimada and Yang, 2010), bank efficiency across different bank sizes (Karim, 2001) and ownership structures (Gardener et al, 2011, Demirguc-Kunt et al, 2004.…”

Section: Introductionmentioning

confidence: 97%

Market structure, institutional framework and bank efficiency in ASEAN 5

Chan

Koh

Zainir

et al. 2015

Journal of Economics and Business

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“…Research on what factors affect bank efficiency using a two-stage DEA method has been commonly used by researchers. Variables that included in the investigation model in international literature can be grouped in four categories, macroeconomic factors, market concentration or market share, internal bank variables, and ownership structure (Sufian & Habibullah, 2010;Gardener, Molyneux, & Nguyen-Linh, 2011;Castellanos, Del Angel, & Garza-García, 2013). The effect the variable included present different result.…”

Section: Felisitas Defungmentioning

confidence: 99%

Determinants of Bank Efficiency during Financial Restructuring Period: Indonesian Case

Defung

2018

Jurnal Keuangan Dan Perbankan

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The banking sector in Indonesia had been through many challenges aftermath the 1997 Asian financial crisis. The restructuring programs aimed to strengthen and improve the performance of the banking system. Empirical researches around the world, however, present various result with regard to the effect of the policy on bank efficiency. We investigated the determinants of the relative efficiency of the Indonesian banking industry. Using panel data of 101 Indonesian commercial banks, this study employs a non-parametric frontier method, Data Envelopment Analysis (DEA), to measure the efficiency score. In the second stage, the Tobit regression model used to analyze the factors that potentially determine the variation of efficiency score. The finding indicated the bank was technically inefficient particularly during financial restructuring. The improvement was evidence toward the end of the period. Bank size, macroeconomic factors, and three bank groups were strongly associated with bank efficiency level. There was no strong evidence that merger, which typically the form of restructuring policy output, positively associated with bank efficiency.

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Determinants of efficiency in South East Asian banking

Cited by 79 publications

References 88 publications

The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression

The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression

Market structure, institutional framework and bank efficiency in ASEAN 5

Determinants of Bank Efficiency during Financial Restructuring Period: Indonesian Case

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