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Discussant: Bilal Zia World Bank

Comments on “Bank Risk Taking and Competition Revisited: New Theory and New Evidence”, by Boyd, De Nicolo, and Al Jalal. Discussant: Bilal Zia World Bank. Quick Summary. This paper: Presents contrasting models that relate banking competition to stability

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Discussant: Bilal Zia World Bank

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  1. Comments on “Bank Risk Taking and Competition Revisited: New Theory and New Evidence”, by Boyd, De Nicolo, and Al Jalal Discussant: Bilal Zia World Bank

  2. Quick Summary This paper: Presents contrasting models that relate banking competition to stability Tests the relationship empirically Theory: CVH (Charter value hypothesis): Competition reduces bank profits and lowers “franchise value”  lower incentives for good loans (higher MH)  correlation between bank concentration and risk of failure is negative BDN (Optimal contracting): Int. rates directly influence firm project choice (MH)  correlation between bank concentration and risk of failure is positive Empirics: BDN trumps CVH

  3. Theoretical part of paper is strong and well presented Focus here on empirical section: Finding: High concentration is positively related with risk Measure of concentration: Hirschman-Hirfendahl Index Measure of risk: Z-score = (ROA + EQA) / sd(ROA) A host of controls

  4. Comments Cross-sectional data from US rural banks and Bankscope panel from developing countries – two very different datasets US data: Banks with branches in multiple counties omitted, but is bank activity concentrated to within-county clients only? Don’t banks compete across neighboring counties? (HHI is at county level) Are there different bank types (such as banks that serve specific rural-finance functions)? If so, incentive structure to lend may be different (state mandated? Perhaps not in US…) Does calculating market size using mean rather than median change results? (Can winsorize and then take mean if worried about outliers)

  5. Comments Using state FEs is useful but regression is at county level, so should do county FEs. (There is footnote in paper, but should run these as well). Can you try putting in size controls non-parametrically (size deciles)? LHS is loans / assets and size control is log(assets), so a mechanical relationship exists. Surprisingly large (and significant) coefficient on “Farm” coefficient. Seasonality? IV – need to show first stage. Not immediately obvious why state dummy is a good instrument for bank size?

  6. Comments International Sample: 2700 banks from 134 developing countries Major issue: No mention of differences between government owned, private, and foreign banks. Large literature on “politicization” of loans through government banks. Could large govt. banks be driving results? Does sample include ALL banks, or only banks above a certain size? HHI measurement will be affected. Need a better control for demand conditions. GDP per capita is very imprecise. Do you have any measures of business development? Need to show results using relative size of banks rather than absolute size across countries.

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