Running for the Exit International Banks and Crisis Transmission

1. Running for the Exit International Banks and Crisis Transmission Ralph De Haas (EBRD) Joint with Neeltje Van Horen (DNB) 17th Dubrovnik Economic Conference June 2011

3. Introduction: aim of the paper • Cross-border bank lending singled out as a key channel of crisis transmission • Lehman Brothers collapse: syndicated cross-border lending declined by 53 per cent on average compared to pre-crisis levels… • … but some countries suffered more than others from a ‘sudden stop’

4. IntroductionDistribution of post-Lehman ‘sudden stop’

5. We look at differences across banks to explain this cross-country heterogeneity in the sudden stop (keeping all else equal) Specifically: does access to borrower information affect stability of bank lending? Using loan-level data, we find that cross-border lending is more stable if: Destination country is geographically close Bank has a network of domestic co-lenders in destination country Bank has prior experience in destination country Bank has subsidiary in (EM) destination country Introduction: aim of the paper

6. Contribution to literature on transmission of current financial crisis Role US$ funding vulnerability banking systems (Cetorelli and Goldberg 2010) Role average profitability banking systems (McGuire and Tarashev 2008) Role stock-market performance banking system (Herrmann and Mihaljek 2010) Previous work based on (bilateral) BIS data We are first to use loan-level data Introduction: contribution of the paper

7. Introduction: background literature • Screening and monitoring varies across borrowers • opaque borrowers rationed more (Stiglitz and Weiss 1981) • Screening and monitoring varies over time • marginal benefit increases during crisis or recession (Ruckes 2004) when agency problems increase as net worth of firms declines (Rajan 1994) • So: opaque borrowers are rationed disproportionally during an adverse shock (‘flight to quality’; Bernanke et al. 1996)

8. Introduction • We expect a more severe ‘sudden stop’ when banks are unable to sufficiently increase the screening of foreign borrowers: • Distance between international bank and the borrower • Presence of a subsidiary of the international bank • Cooperation of international bank with domestic banks • Experience of the international bank in a country

9. 1. Distance • Theory • Information costs increase with distance, in particular for ‘soft’ info (Stein 2002) • Screening and monitoring more difficult when distance increases: geographical credit rationing (Jaffee and Modigliani 1971) • Empirical literature • Negative relationship between geographical distance and amount of lending (Buch 2005; Portes et al. 2001) • Negative relationship between cultural distance and amount of lending (Giannetti and Yafeh 2009) • Negative relationship between distance and pricing power of banks (spatial price discrimination, Degryse and Ongena 2005) • Impact on the stability of bank lending?

10. 2. Presence of a local subsidiary • Theory • Local subsidiary reduces distance between loan officer and borrower (Mian 2006) • Local subsidiary improves collection and processing of soft information • But establishing a local subsidiary creates ‘functional’ distance between loan officer and HQ (Aghion and Tirole 1997) • New problem: transmitting ‘soft’ info from subsidiary to HQ… Involves not only transportation costs but also intrabank agency costs (Rajan et al. 2000) • Empirical literature • Greater functional distance reduces credit availability (Alessandrini et al. 2009) • Impact on cross-border lending stability?

11. 3. Cooperation with domestic banks • Theory • Domestic banks may have a comparative advantage in reducing information asymmetries vis-à-vis local firms (Mian 2006, Carey and Nini 2007) • Repeated co-lending with domestic banks may allow foreign banks to increase local know-how as well • Empirical literature • (Contemporaneous) local bank participation leads to larger, longer and cheaper syndicated loans (Nini, 2004) • Impact on lending stability?

12. 4. Previous lending experience • Theory • Repeated interaction reduces information asymmetries and agency problems • Empirical literature • Repeat lending reduces information asymmetries in the syndicated loan market (De Haas and Van Horen, 2010) • Impact on lending stability?

13. Required characteristics of data • Loan flows: • From individual banks… • … to individual countries… • … over a prolonged period of time • Lending by one bank to various countries (exploit within-bank variation) • Lending by multiple banks to one country (control for credit demand) • Information about the underlying individual deals • Important market (to generalize results) Syndicated loan data have all of these characteristics

14. Novel dataset: sample of 118 largest international banks Only commercial, savings, cooperative or investment banks Each covers at least 0.01% of the cross-border syndicated loan market Participated in at least 20 cross-border loans in 2006 Banks from 36 countries (43 banks from emerging markets) Lending cross-border to 60 advanced and emerging countries 2,146 bank-country pairs Data

15. We download all syndicated loans to private borrowers between January 2005 and October 2009 Each loan has multiple lenders, so we determine for each bank the share of the loan it provided: ± 25% sample: we have data on loan distribution ± 75% sample: we assume equal loan distribution (and show robustness tests) Identify all the loan portions that are ‘cross-border’ Cross border means: nationality of bank (parent) is different from nationality of borrower) Result: per bank, per month, total cross-border lending to each country Data: calculation of cross-border lending flows

16. Example Loan to US borrower signed in October 2008 Syndicate members: • Citigroup • Deutsche Bank • Nomura • Erste Group Source: Dealogic Loan Analytics

17. Number of loans: 23,237

18. Number of loan portions: 108,530 Citigroup DeutscheBank Nomura Erste Group

19. Erste Group Erste Group Erste Group Erste Group + Total cross-border lending Erste in October 2008 to U.S.

20. We compare lending from bank i to country j in two periods: Post-Lehman (Oct 08-Oct 09) versus pre-crisis (Jan 05-Jul 07) Dependent variables Change in cross-border lending volume from bank i to country j Change in cross-border number of loans from bank i to country j Sudden stop dummy: loan volume decline <-75 per cent Empirical strategy

21. Empirical strategy • Information variables • Distance: Km distance (in logs) between the country of bank i and borrower country j • Subsidiary: Presence • Domestic lenders: Number of different domestic lenders with whom bank i participated in loans to country j since 2000 (as a % of all domestic lenders) • Experience: Number of loans by bank i to country j since 2000 that had matured by September 2008

22. Challenge is to control properly for changes in credit demand Khwaja & Mian (AER, 2008) technique: Multiple banks lending to one firm: use firm fixed effects to control for credit demand at firm level In our case, multiple banks lending to same country: use country fixed effects to control for credit demand at the host-country level (cf. Cetorelli & Goldberg 2010) Banks active in multiple countries: we can also use bank fixed effects (or bank-specific controls) OLS (logit for SS dummy) with standard errors clustered by bank Empirical strategy

23. Empirical strategy • Controls • Bank solvency – 2006 and Δ(2009-2006) • Bank liquidity – 2006 and Δ(2009-2006) • Bank size • Pre-crisis exposure to country j • State support (‘financial protectionism’)

24. Empirical strategy In sum: we control for time invariant country variables, changes in credit demand, and bank-specific variables Allows us to focus on pairwise bank-country determinants

25. Empirical results: baseline results • Economic impact • Distance: 19% higher reduction lending for borrowers at mean distance compared to borrowers at minimum distance • Domestic lenders: 9% lower reduction lending to country with mean level of cooperation compared to country without domestic bank network

26. Empirical results: baseline results (II)

27. Empirical results: baseline results (III)

28. Some evidence banks retrenched from non-core (emerging) markets Banks that reduced lending the most: Supported Small Low solvency (2006) Banksthat had to increase liquidity But economic effect limited compared to information variables Results: controls

29. Robustness checks

30. Empirical results: What is distance?

31. Omitted variables that are correlated both with info variables and stability of lending? But problem not as pronounced as Control for all unobserved country variables (e.g. growth potential country) Control for all unobserved bank variables (e.g. bank strategy) Main bank-country pair variables already included in model Strategy to test if results are biased Only very weak bank-country pair instruments, so leave IV Control for additional bank-country pair variables: trade, (banking) FDI, differences in supervisory power, and stringency of capital regulation Findings: results unchanged when adding these variables to the model Results: endogeneity

32. Empirical results: endogeneity

33. First-time vs repeat borrower Impact of access to borrower information is same for repeat and first-time borrowers Except Experience which is particularly important for first-time borrowers Probability of Sudden stop higher for lending flows to first-time borrowers Bank vs non-bank borrower Access to borrower information had no impact on stability of lending to bank borrowers Agency problems and mistrust in inter-bank market were too large Probability of Sudden stop higher for bank borrowers Results: extensions

34. Conclusions • We know little about what affects the stability of cross-border lending. Especially not about banks’ behavior across different countries • Our results suggest that information asymmetries not only affect the level but also stability of cross-border lending • Resilience cross-border lending depends on ability of banks to limit increase in agency problems • Even in a ‘hard information’ market access to (supplementary) ‘soft information’ matters • Specific role for distance to borrower, cooperation with domestic banks, presence subsidiary (in EMs), and lending track-record

35. Policy implications • Banks further away from customers may be less reliable sources of funding especially when they have no local presence • Suggests that countries that want to open up their economy to cross-border lending flows • Should consider to also allow foreign subsidiaries and branches • Attract debt funding from lenders that are geographically close (or at least not only from remote lenders) • Also develop the domestic banking system to not become completely reliant on the kindness (and stability) of strangers…

36. Finally: domestic syndicated lending was unable to cushion much of the decline in cross-border inflows…

37. Thank you!