Threshold Effect of Bank-specific Determinants of Non-performing Assets: An Application in Indian Banking
Bardhan, Samaresh
Threshold Effect of Bank-specific Determinants of Non-performing Assets: An Application in Indian Banking - 1S-34S P.
The article investigates role of bank-specific factors on non-performing assets (NPAs) in Indian banking system in a panel threshold framework (Hansen, 1999, Journal of Econometrics, 93(2), 345–368), using an unbalanced panel of 82 scheduled commercial banks over the period of 1995–1996 to 2010–2011. We consider capital to risk-weighted assets ratio (CRAR) and credit growth as alternative threshold variables (and regime dependent) along with relevant bank-specific variables treated as regime independent. Findings reveal that CRAR exerts negative and significant impact on NPAs once it reaches a critical threshold. Possible implication is that banks extend less risky loans in a high CRAR regime than in low CRAR regime that helps reduce NPAs. With credit growth as threshold as well as regime dependent, we observe statistically significant non-linear effect of credit growth on NPAs. Beyond threshold, credit growth exerts significant negative effect on NPAs that may imply that banks extend good quality loans. However, we cannot rule out the possibility of evidence of ‘ever-greening hypothesis’ of bad debts in Indian banking, that is, banks just roll over previous bad debts into fresh performing loans.
Banks, non-performing assets, threshold regression, panel data models
Threshold Effect of Bank-specific Determinants of Non-performing Assets: An Application in Indian Banking - 1S-34S P.
The article investigates role of bank-specific factors on non-performing assets (NPAs) in Indian banking system in a panel threshold framework (Hansen, 1999, Journal of Econometrics, 93(2), 345–368), using an unbalanced panel of 82 scheduled commercial banks over the period of 1995–1996 to 2010–2011. We consider capital to risk-weighted assets ratio (CRAR) and credit growth as alternative threshold variables (and regime dependent) along with relevant bank-specific variables treated as regime independent. Findings reveal that CRAR exerts negative and significant impact on NPAs once it reaches a critical threshold. Possible implication is that banks extend less risky loans in a high CRAR regime than in low CRAR regime that helps reduce NPAs. With credit growth as threshold as well as regime dependent, we observe statistically significant non-linear effect of credit growth on NPAs. Beyond threshold, credit growth exerts significant negative effect on NPAs that may imply that banks extend good quality loans. However, we cannot rule out the possibility of evidence of ‘ever-greening hypothesis’ of bad debts in Indian banking, that is, banks just roll over previous bad debts into fresh performing loans.
Banks, non-performing assets, threshold regression, panel data models