Some comments on The Great Cross-Border Bank Deleveraging: Supply Side Characteristics. by Eugenio Cerutti and Stijn Claessens.

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1 Some comments on The Great Cross-Border Bank Deleveraging: Supply Side Characteristics by Eugenio Cerutti and Stijn Claessens Ralph De Haas European Bank for Reconstruction and Development Tilburg University

2 Summary Analysis of the driving forces of international bank deleveraging around two events : Lehman Brothers collapse and eurozone crisis Data: BIS country-level bilateral lending flows Distinguish between cross-border lending and affiliate lending Main result: Pre-shock vulnerability indicator (SRISK) explains subsequent deleveraging quite well. Bilateral variables less important

3 General comments Important topic Straightforward and well-executed empirical analysis Nice: Stability characteristics of cross-border vs. affiliate lending Some data and related interpretation issues Some suggestions to exploit the data further and to better pin down the paper s contribution

4 Main contribution? Others have looked into the same issue, applying the same identification strategy, while using bank-level and loan-level data Control more thoroughly for demand (at the borrower instead of country level) Also highlight the role of exogenous shocks to bank capital Also highlight the role of bilateral variables such as distance and prior lending experience So: convince the reader about your contribution...

5 Contribution: Better data? You: We use better data as we adjust for series breaks and exchange rate movements Me: Others didn t have those issues in the first place... You : Analyze changes in stocks so we capture both new flows and maturing loans Me : Is that an advantage? Focus on new flows more informative You : Syndicated loans only part of total cross-border lending Me : But your sample seems limited to a small number of rich countries. What about South-South banking...? You : Banking systems from various source countries all face the same demand conditions in the destination country Me: That is a (strong) assumption and a weakness of your aggregation level (split data up in flows to banking vs real sector?)

6 Data description What are the creditor countries?

7 Data description Banking systems from the Americas and Asia

8 Data European Bank of Reconstruction and Development

9 Table 2 and 3 (Panel B, local affiliates) How to interpret these interactions? Are the WH and Asia dummies included separately too? What is the base group: ROW? Is that Europe? And how to interpret the WH and Asia results if each country group only contains two countries? And how to explain them in a less ad hoc way?

10 Contribution: affiliate funding Nice data feature: Ultimate risk basis means you can properly distinguish between cross-border and local claims (footnote 3) But you also have data on FX vs LC claims by affiliates (fn 1) More to explore w.r.t. stability effects of local funding structure Your current explanations for different behavior of local and crossborder claims are not entirely convincing This suggests that bank s capacity to internally reallocate available resources within groups was limited Goes against some recent anecdotal and survey evidence

11 Contribution: affiliate funding Fund flows between parents and subsidiaries during the years by region CEB Credit/Liquidity to subsidiary Dividend to parent SEE Credit/Liquidity to parent Source: De Haas and Kirschenmann (2013) European Bank of Reconstruction and Development

12 Contribution: affiliate funding Regulatory or information frictions?? More likely: Large portion of affiliate claims is locally funded and denominated in the local currency. Less dependent on parent-bank funding Regional variation to exploit, e.g. affiliates in Latin America (cf. Kamil and Rai, 2010) vs. Emerging Europe European Bank of Reconstruction and Development

13 Policy implications? FSAPs and other vulnerability assessments should make more use of market based/forward-looking measures such as SRISK But can we rely on SRISK if the correlation with subsequent international lending varies so much across crises and across regions...?

14 Minor issues and suggestions 1. Effect systemic crisis is not the same as a regulatory-driven home bias. Measure regulatory interventions more directly? At least be more careful in interpreting this effect 2. Eurozone crisis: Role banking system exposures to GIPS (different from average pre-crisis exposure effect?) 3. Explain choice specific timing of event windows (2008Q2-2009Q2 and 2011Q3-2011Q4) and show some robustness tests 4. Lehman collapse is an event, Eurozone crisis more a protracted, painful period. Event methodology less applicable?

15 Nice paper! Thank you