The paper examines the role of bank-specific variables in explaining the dynamics of non-performing assets (NPAs) of Indian banks in a panel data framework over the post liberalisation period, 1995-2011. The results have been derived after controlling for macroeconomic factors like real GDP, inflation, exchange rate etc. Applying several variants of Generalized Method of Moments (GMM) technique in dynamic models, we find that that there is significant time persistence of NPAs in Indian banking system. We also find that larger banks are more prone to default than smaller banks. We find support for the 'bad management hypothesis' as we observe that an increase in profit level of the banks reduces NPAs in the next period. Lagged capital adequacy ratio as an important prudential indicator also significantly reduces current NPAs of banks. The paper also draws some important policy implications about NPA management.

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In a simple model based on political support approach, we show that poor and less egalitarian societies may impose a lower tax rate contrary to the prediction of the median voter approach. This is consistent with the available empirical findings. In the framework developed in this paper, the government can strategically design a weak governance system to promote informal activities for the poor. This constitutes an alternative redistributive strategy other than the standard tax-transfer policy. The government chooses the tax rate and the degree of governance simultaneously to maximize the average income of the poor in the informal sector of the economy, i.e. those who constitute the majority and help in winning the election.Taxation, inequality, governance, poverty,

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. JEL Classification: G21, G28, C13, C33