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
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
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
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
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
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
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...
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
Contribution: “Better data”?
•
You: We use “better data” as we adjust for series breaks and
exchange rate movements
•
•
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: Others didn’t have those issues in the first place...
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?)
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
Data description
What are the creditor countries?
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
Data description
•
“Banking systems from the Americas and Asia”
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
Data
© European Bank of Reconstruction and Development 2010 | www.ebrd.com
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?
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
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
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
Contribution: affiliate funding
0
.2
.4
.6
.8
1
Fund flows between parents and subsidiaries
during the years 2007-2012 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 2010 | www.ebrd.com
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 2010 | www.ebrd.com
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...?
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
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?
© European Bank of Reconstruction and Development 2013 | www.ebrd.com
Nice paper!
Thank you
© European Bank of Reconstruction and Development 2013 | www.ebrd.com