Reduction of non-performing loans in the banking industry: an application of data envelopment analysis

    Chih-Ching Yang Info

Abstract

The increase in non-performing loans around the world has had quite a negative impact on many nations’ banking systems. To address these problems, many creative regulatory solutions and well-designed risk techniques have been utilized in the hope of reducing non-performing loans to an acceptable level. The purpose of this study is to apply a newly developed data envelopment analysis model to suggest the most efficient plan (called Plan 4) to reduce non-performing loans that can maximize the efficiency of the entire banking industry’s control over the bad debts. For comparison purpose, three other reduction plans are also represented. The four plans are presented using data from Taiwan’s banking industry. The empirical results show that among the plans presented, Plan 4 shows the most effective allocation of the industry-wide reduction target. The plan focuses on a finite number of banks, helping identify the key units to improve industry-wide efficiency. The findings implicitly suggest that the regulator should devise more incentive measures to encourage target banks to perform the non-performing loan reduction task. Our results also suggest that for the regulator, forcing banks to cut their non-performing loans by the same ratio will not help improve the relative efficiency of the industry.

Keywords:

banking industry, non-performing loan, risk management, data envelopment analysis, undesirable output, Taiwan

How to Cite

Reduction of non-performing loans in the banking industry: an application of data envelopment analysis. (2017). Journal of Business Economics and Management, 18(5), 833–851. https://doi.org/10.3846/16111699.2017.1358209

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October 27, 2017
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2017-10-27

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How to Cite

Reduction of non-performing loans in the banking industry: an application of data envelopment analysis. (2017). Journal of Business Economics and Management, 18(5), 833–851. https://doi.org/10.3846/16111699.2017.1358209

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