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Impact of macroeconomic cyclical indicators and country governance on bank non-performing loans in Emerging Asia

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Abstract

Non-performing loans (NPLs) is an important credit risk in Emerging Asia, namely China, Hong Kong, Indonesia, India, Malaysia, Philippines, Singapore, South Korea, Thailand, and Vietnam, for banks there trying to find ways to minimise this. This research extends previous works on macroeconomic cyclical model by examining the impact of macroeconomic cycle indicators and country governance on bank NPL. The paper introduces a new empirical model to analyse the role of country governance in mitigating the negative effects of macroeconomic cycles on bank credit risk. This study employs panel regression analysis methods to examine the relationship between microeconomics and governance variables on bank NPL through baseline and interactions models. The baseline analysis shows unemployment rate and real interest rate have a positive and significant impact on NPLs in the countries studied, while total external debt/GDP and inflation rate have a negative impact. The interaction analysis provides new insights on the role of country governance in minimising bank NPL risks. The findings point to the role of country governance and macroeconomic variables on reducing NPLs. This research adds to the body of knowledge on NPLs, specifically in the area of theory, practice and policy in Emerging Asia.

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Authors and Affiliations

  1. Faculty of Business and Management Department, Universiti Teknologi MARA, Kota Kinabalu, Sabah, Malaysia

    Nurfilzah Arham, Mohd Shamlie Salisi, Rozita Uji Mohammed & Jasman Tuyon

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  1. Nurfilzah Arham
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  2. Mohd Shamlie Salisi
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  3. Rozita Uji Mohammed
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Correspondence to Nurfilzah Arham.

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Appendix

Appendix

Results of POLS, random effects and fixed effects

Variables

POLS

Random Effects

Fixed Effects

Baseline Model (1)

 Constant

− 0.1564 (0.5039)

− 0.482 (0.2127)

− 0.6783* (0.0760)

 DEB

0.1676*** (0.0001)

0.1020 (0.1547)

0.0290 (0.7396)

 UNEM

− 0.1380 (0.2885)

0.6161** (0.0018)

0.9586*** (0.0001)

 INF

0.2248** (0.0169)

− 0.0376 (0.5153)

− 0.0513 (0.3800)

 RIR

0.0797 (0.4544)

0.0406 (0.5150)

0.0687 (0.2832)

 R2

0.2360

0.1251

0.8213

 Adjusted R2

0.20009

0.0848

0.7915

 F

6.7190*** (0.0000)

3.1092** (0.0193)

27.5737*** (0.0000)

Corruption Control Interaction Model (2)

 Constant

− 0.2642 (0.2164)

− 0.4519 (0.2451)

− 0.5565 (0.1663)

 DEB*COR

0.0715*** (0.0000)

0.0436 (0.1550)

0.0087 (0.8249)

 UNEM*COR

− 0.0444 (0.3507)

0.2227*** (0.0030)

0.3498*** (0.0002)

 INF*COR

0.0863** (0.0145)

− 0.0199 (0.3839)

− 0.0273 (0.2373)

 RIR*COR

0.0351 (0.3813)

0.0127 (0.6002)

0.0229 (0.3602)

 R2

0.2756

0.1194

0.8175

 Adjusted R2

0.2423

0.0790

0.7871

 F

8.2759*** (0.0000)

2.9503** (0.0245)

26.8723*** (0.0000)

Corruption Control Interaction Model (3)

 Constant

− 0.2805 (0.1879)

− 0.5526 (0.1616)

− 0.6853* (0.0964)

 DEB*COR

0.0848*** (0.0000)

0.0587* (0.1060)

0.0218 (0.6404)

 UNEM*COR

− 0.0503 (0.3613)

0.2703*** (0.0019)

0.4192*** (0.0001)

 INF*COR

0.1017** (0.0128)

− 0.0188 (0.4746)

− 0.0270 (0.3116)

 RIR*COR

0.0392 (0.3942)

0.0130 (0.6377)

0.0245 (0.3895)

 R2

0.2812

0.1336

0.8207

 Adjusted R2

0.2482

0.0938

0.7909

 F

8.5096*** (0.0000)

3.3552** (0.0133)

27.4711** (0.0000)

Corruption Control Interaction Model (4)

 Constant

− 0.2467 (0.2531)

− 0.4194 (0.3090)

− 0.6441 (0.1517)

 DEB*COR

0.0795*** (0.0000)

0.0455 (0.1760)

0.0149 (0.7242)

 UNEM*COR

− 0.0533 (0.3234)

0.2456*** (0.0062)

0.4068*** (0.0004)

 INF*COR

0.1011** (0.0115)

− 0.0164 (0.5311)

− 0.0244 (0.3571)

 RIR*COR

0.0358 (0.4267)

0.0107 (0.6982)

0.0237 (0.4057)

 R2

0.2174

0.0968

0.8127

 Adjusted R2

0.2379

0.0552

0.7815

 F

8.1002*** (0.0000)

2.3297* (0.0623)

26.0309*** (0.0000)

This table provides the full panel regressions results estimated for baseline and interaction models. Numbers in parentheses below the coefficient are the probability levels of significance. *,**,*** indicate significance levels of 10, 5, 1% respectively.

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Arham, N., Salisi, M.S., Mohammed, R.U. et al. Impact of macroeconomic cyclical indicators and country governance on bank non-performing loans in Emerging Asia. Eurasian Econ Rev 10, 707–726 (2020). https://doi.org/10.1007/s40822-020-00156-z

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