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Corruption and Bank Conduct: International Evidence

Corruption and Bank Conduct: International Evidence. Rajeev K. Goel Illinois State University Iftekhar Hasan Rensselaer Polytechnic Institute & Bank of Finland. Introduction.

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Corruption and Bank Conduct: International Evidence

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  1. Corruption and Bank Conduct: International Evidence Rajeev K. Goel Illinois State University Iftekhar Hasan Rensselaer Polytechnic Institute & Bank of Finland

  2. Introduction • We use recent data for more than 100 nations to examine effects of economy-wide institutional quality (corruption) and banking sector institutions across 4 dimensions of financial performance: • (i) bank non-performing loans to total loans; • (ii) bank capital to assets ratio; • (iii) bank liquid reserves to assets ratio; and • (iv) interest rate spread.

  3. Conduct of banks and financial markets is driven partly by internal factors and partly by exogenous. • Internal factors are institutions specific to financial sector, whereas external factors are economy-wide institutions.

  4. In the financial sector, corruption can proxy for a number of exogenous influences including institutional quality and riskiness. • Monitoring and enforcement institutions are weaker in corrupt nations (Becker and Stigler (1974)). • Bad institutional quality can increase risk of default for banks • Banking sector institutions account for guidelines dictating transparency and governance by taking account of sector-specific factors.

  5. Theoretical background • Financial literature has paid relatively little attention to the nexus between corruption and financial performance (see Beck et al. (2006) and Huang and Wei (2006) for exceptions) • One would expect bad loans (BadLoan) to increase in more corrupt nations. Some borrowers default because they think that they can bribe their way out of apprehension and/or punishment. Corrupt bankers might also be eager to sanction bad loans. • In our 2007 sample, bank non-performing loans to total loans ratio was highest in Kenya (22.7%) and lowest in Australia and Luxembourg (0.2% each).

  6. Bank capital to assets ratio (CapAsset) is likely to increase in corrupt nations when banks increase investments to hedge against uncertainty. • Bank capital to asset ratio was highest in Armenia (22.5%) and lowest in the Netherlands (3.3%).

  7. Bank liquidity (LiqRes) might increase with corruption – (i) greater liquidity is a hedge against risk; and (ii) in corrupt nations, potential bribe givers might demand more cash frequently when they know that they have to pay bribes, but the amount of each bribe is not set. • Average liquid reserves to assets ratio across nations was 11.79%. • Corruption might boost interest rate spreads (IntSpread) as banks try to hedge against increased risk. • Interest rate spread varied from a high of 457.46% (Zimbabwe) to a low of 0.71% (Netherlands).

  8. Estimated equation • Estimated equations take following general form • Financial conductij = f(Economic growthi, Country sizei, Corruptionik, Banking institutionsim) (1) • i = 1,…,112 • j = BadLoan, CapAsset, LiqRes, IntSpread • k= CorruptCPI, CorruptWB • m= EURO, CBauto

  9. Main measure of cross-country corruption is corruption perceptions index by Transparency International (CorruptCPI). • Denmark, Finland and New Zealand were rated least corrupt nations, while Afghanistan and Chad were rated most corrupt. • As robustness check, we employ corruption measure from the World Bank (CorruptWB). • Data used include annual country level observations for more than 100 countries for 2007.

  10. Results • Overall fit of models in Table 2 is decent. Further, RESET test shows an absence of significant specification errors. • Results show that economic growth lowers bad loan ratio and interest rate spread, while it boosts the capital assets. Its effect on liquid reserves, while positive, is statistically insignificant. • These relations make intuitive sense: in times of economic prosperity there is less loan default and lower interest rate spreads capture lower potential defaults.

  11. Greater corruption increases bad loans, capital assets, liquid reserves and interest rate spread. Effects of corruption on capital assets, liquid reserves and interest rate spreads are consistent with hedging against additional risk, while the effect on bad loans may be seen in the context of corruption reducing potential costs of loan default. • Turning to banking-specific institutional quality, central bank autonomy fails to be significant. However, membership in the European Monetary Union has a sobering effect on capital assets, liquid reserves and interest rate spread. The negative coefficient on EURO might be seen as consistent with the notion of a conservative central banker (Huang and Wei (2006)).

  12. Simultaneity aspects • There might be simultaneity between corruption and bad loans: greater corruption might increase bad loans, on the other hand, bad loans might increase corrupt practices as defaulters try to avoid penalties (Boerner and Hainz (2004)). • Table 3 presents instrumental variable results with corruption taken as an endogenous variable. A country’s ethnic, language and religious fractionalization (Alesina et al. (2003)), and democracy (Goel and Nelson (2005), Tavares (2007)) are taken as instruments.

  13. Results from Table 3 support the positive effect of corruption on bad loans from Table 2. • Greater economic growth, as earlier findings, lowers bad loans. However, the effects of country size and EURO are now statistically insignificant. Higher interest rate is also shown to lower bad loans.

  14. Conclusions • Results show that corruption significantly affects all 4 dimensions of financial performance, albeit with significant qualitative and quantitative differences. • Specifically, greater corruption increases non performing loans, bank capital, bank liquidity and interest rate spread. • Membership in the European Union seems to generally have a stabilizing effect, while autonomy of the central bank does not seem to matter. • These findings are robust to an alternate measure of corruption and to potential endogeneity of corruption.

  15. From a policy perspective, policies strengthening institutional quality by lowering corruption would have payoffs in terms of lowering bad loans, and by freeing up banking resources away from capital and liquidity investments aimed at hedging against risk. • Greater autonomy to central bankers does not seem to significantly affect performance, while membership in the European Monetary Union seems to have a stabilizing effect. • This line of investigation can be fine tuned through detailed theoretical models and via alternate measures of institutional quality.

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