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Shocks Abroad, Pain at Home? Bank-Firm-Level Evidence on the International Transmission of Financial Shocks

Abstract

The paper studies the international transmission of shocks from the banking to the real sector during the global financial crisis. For identification, it uses matched bank-firm-level data, covering mainly small and medium-sized firms in Eastern Europe and Turkey, and exploits the Lehman failure. The paper finds that internationally borrowing domestic and especially foreign owned banks contract their credit more during the crisis than locally funded domestic banks do. Firms dependent on credit and with a relationship with internationally borrowing domestic or foreign banks suffer more in their financing and real performance, especially when single-bank, small or with limited tangible assets. Moreover, firms in countries with lower financial development, more reliance on foreign funding and slower contract enforcement are more affected. Overall the results suggest the existence of spillovers to the real sector through an international banking channel but with heterogeneous effects across firms and countries.

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Notes

  1. See Kalemli-Ozcan, Papaioannou, and Peydró (2010) for the determinants of banking globalization, especially in Europe and Claessens and van Horen (2014) for an overview of the trends in foreign bank ownership.

  2. For empirical evidence on differential lending by banks with high and low liquidity, and capital, see Kashyap and Stein (2000) and Jiménez and others (2012) and on differential lending by domestic vs. foreign banks, see Mian (2006), Berger and others (2008), Bruno and Hauswald (2014), Giannetti and Ongena (2009), and Gormley (2010).

  3. As shown by Kashyap, Stein, and Wilcox (1993) and Adrian, Colla, and Shin (2012).

  4. Recent studies have used syndicated loan data to examine how financial crises affect cross-border bank lending (for example, de Haas and van Horen, 2012; Giannetti and Laeven, 2012; De Haas and Van Horen, 2013). These papers use loan-level data in a multicountry setting so they can account for country-, bank- and firm-heterogeneity, but as syndicated loans are generally only granted to large firms they cannot study the impact of international transmission on SMEs. Furthermore, these studies do not provide any insights in the real effects.

  5. As shown by Khwaja and Mian (2008) and Jiménez and others (2014) once key firm observable characteristics are controlled for the inclusion of firm-level fixed effects, a prerequisite of loan-level data, has only a minor impact on the estimated coefficients. In addition, one can only control for firm-level fixed effects when firms have multiple bank relationships. Because many firms, in particular SMEs, only have a relationship with one bank (Degryse, Kim, and Ongena, 2009), controlling for firm-level fixed effects would in effect result in the exclusion of two-third of our sample and a potential correspondent loss in external validity.

  6. In contrast to Santos and Winton (2008) and Chava and Purnanandam (2011) who compare bank-dependent borrowers that have no access to public debt markets with borrowers that do have access to these markets, we exploit bank-dependency on the opposite side of the “no access-bank-public market” financing spectrum. In contrast to Rajan and Zingales (1998), and the literature that builds on this seminal paper, who consider credit-dependency to be industry-specific and technology-determined, we view credit-dependency as firm-specific and time-predetermined (that is, measured during normal times before the financial crisis hit).

  7. The Vienna Initiative was launched by the European Bank for Reconstruction and Development (EBRD) in January 2009 with the goal of preventing a large-scale bank withdrawal from Emerging Europe (with a focus on Eastern Europe) and support lending in the region. A number of large European banking groups participated in this initiative and signed country-specific commitment letters in which they pledged to continue to support their foreign affiliates by keeping them adequately capitalized and provide them with sufficient liquidity.

  8. To the best of our knowledge, only Schnabl (2012) examines both channels simultaneously. As opposed to ours, this paper does not study real effects and focuses on firms and banks in only one country (Peru).

  9. It is possible that the liquidity shock faced by internationally borrowing domestic banks led these banks to reduce interbank lending to locally funded domestic banks, with direct negative consequences for their lending as well. This makes our reported estimates conservative.

  10. A material bank relationship can exist without (much) credit (Ongena and Smith, 2000). Indeed, the breadth of bank services used by a firm is a measure of the strength of the relationship, in terms of its scope (Boot and Thakor, 2000). The array of classic banking services beyond credit comprises deposits, the management of bank balances and temporary overdrafts, foreign exchange management, and the brokering of other financial activities.

  11. Using data on borrowing by Pakistani firms, Khwaja and Mian (2008) find that credit shocks matter for small but not for large firms.

  12. The firm balance-sheet channel implies that larger firm size and tangible assets may reduce agency frictions and thus support credit availability during a crisis or when GDP contracts (see Bernanke and Gertler (1989) and the large literature following this seminal paper).

  13. Kompass does not provide bank relationships for firms in Moldova and did not include Latvia and Macedonia in the package set of countries it provided. Resource constraints prevented us from acquiring (and then matching with four other data sets) records from more countries outside of this covered area.

  14. We employ a dummy instead of a continuous variable as our goal is to clearly demarcate between banks that have access to the international capital market and those that do not. Obviously, banks can also access international wholesale funding through different avenues like bilateral interbank borrowing, borrowing from money market funds, and through the use of derivatives markets. Bank-level information on these exposures is not available for our set of countries. Nevertheless, the total amount of syndicated loans and bonds outstanding in our sample of countries at year-end 2007 as reported by Dealogic equals 20 percent of the total amount of cross-border liabilities outstanding to banks at year-end 2007 as reported to the BIS, a fraction similar to syndicated loans over total loans for European banks as reported in Acharya and others (2014). Given that attracting capital from the international capital market using syndicated loans is in general a first step for financial and nonfinancial firms toward accessing bond and other types of market financing, we surmise that borrowing activity in the international syndicate and bond markets is a good proxy for a bank’s overall access to international wholesale funding.

  15. Kompass is no longer able to supply historic firm records. The overlap with the 2005 vintage of the database we had access to from an earlier study is unfortunately too small for a meaningful analysis. This small overlap also suggests that most firms in our sample were included in the database after 2005 and that the bank relationship information we have is not stale.

  16. If the relationship information predates the crisis and firms managed to switch from shocked to unaffected banks to mitigate the transmitted contraction, our estimates will be conservative (as we will incorrectly link these potentially better financed and performing firms to the shocked banks). If the relationship information is recent, our estimates will also be conservative if worse financed and performing firms were in the end able to switch from shocked to unaffected banks. As explained in the previous section we will exploit differences between firms in the probability that they will be able to switch banks. This allows us to use observable firm characteristics to proxy for the probability of switching and provides an additional layer of confidence in our evidence.

  17. We were able to match more than 100,000 firms, but many firms in Amadeus do not have any balance sheet information available as they are mere legal entities with limited economic activity.

  18. Results are similar if we use for the control variables the corresponding dummy variables for values below and above the relevant median (results are available on request).

  19. Results are unaffected if we winsorize at the 5th and 95th percentile and qualitatively unchanged if we do not winsorize.

  20. Following Cameron, Gelbach, and Miller (2008) and for improved inference with only a limited number of clusters we employ the Wild cluster-bootstrap percentile-t procedure. Estimates are mostly unaffected if we do not cluster.

  21. As in the tables, ***, **, and * indicates statistical significant at the 1, 5, and 10 percent level, respectively.

  22. Results are similar if for the last four variables we use the corresponding dummy variables for values below and above the relevant median (results are available upon request).

  23. We also experimented using country × industry fixed effects to allow for differences in the impact of the crisis within a country across industries. Results remain largely unchanged.

  24. Results are unaffected if we winsorize at the 5th and 95th percentile and qualitatively unchanged if we do not winsorize.

  25. The firm characteristics are: The rate of growth in the firm’s short-term debt, the change in return on assets, the rate of growth in operational revenue, the rate of growth in assets in 2007 (all winsorized at the 1st and 99th percentile), dummies that capture if the firm is credit-dependent, has export activities, or is foreign owned, and firm age, total assets, liquidity, and solvency. All variables are measured in 2007.

  26. Results are very similar when we do not include firm-level controls. If anything the estimated coefficients are larger (in absolute value) when firm characteristics are controlled for. This suggests that it is unlikely that our results are upward biased because we are unable to control for unobserved firm characteristics.

  27. We alternatively employ the average borrowing over the same time period and results are virtually the same.

  28. Another reason why there may not be a difference depending on the maturity with respect to borrowing from international wholesale markets could be that in order to finance lending at the margin these banks are used to obtain international wholesale funding. When the international wholesale market dried up this additional liquidity could not be obtained, which affected both banks that could borrow short-term and long-term. For example, Spanish banks mainly financed themselves with long-term international wholesale funding through covered bonds bought by foreign investors but they still were highly affected by the dry-up of international markets after the Lehman failure (that is, even before the sovereign debt crisis).

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Authors

Additional information

*Steven Ongena is Professor of Banking in the Department of Banking and Finance at the University of Zurich and the Swiss Finance Institute, and Research Fellow of CEPR. José-Luis Peydró is ICREA Professor of Economics at Universitat Pompeu Fabra, Research Associate of CREI, Barcelona GSE Research Professor, and Research Fellow of CEPR and Neeltje van Horen is a Senior Economist at the Research Department of De Nederlandsche Bank, and Research Fellow of CEPR. The authors thank Pierre-Olivier Gourinchas, Galina Hale, Luc Laeven, Pau Rabanal, and Katheryn Russ (the editors), two anonymous referees, Nicola Borri, Martin Brown, Claudia Buch, Stijn Claessens, Hans Degryse, Robert DeYoung, Olivier De Jonghe, Linda Goldberg, Christa Hainz, Florian Heider, Vasso Ioannidou, Sebnem Kalemli-Ozcan, Karolin Kirschenmann, Gustav Martinsson, Hector Perez Saiz, Alessandro Peri, conference participants at the American Economic Association (Chicago), the Financial Intermediation Research Society Conference (Dubrovnik), the CEPR-ECB-Kelley School of Business, Indiana University-RoF Conference on Small Business Financing (Frankfurt), the CEPR-University of StGallen Conference on Finance and the Real Economy (StGallen), the DNB-EBC Conference on Banking and the Globalization of Finance (Amsterdam), the Sixteenth Annual DNB Research Conference on The Impact of Credit on the Dynamics of SMEs (Amsterdam), the Seventh Swiss Winter Conference on Financial Intermediation (Lenzerheide), the ESCB Day Ahead Conference (Malaga), the Second Conference of the E–CB Macroprudential Research Network (Frankfurt), the Multinational Finance Society Symposium (Larnaca), the University of Zurich Workshop on Financial Globalization (Zurich), the Banca d’Italia Workshop on Lending by Multinational Banks (Roma), the XXI Finance Forum (Segovia), and seminar participants at Carlos III, the Central Planning Bureau, the Deutsche Bundesbank, De Nederlandsche Bank, the Federal Reserve Bank of Chicago, KU Leuven, Sveriges Riksbank and the World Bank for useful comments. Thanks are also due to Carlos García de Andoaín, Yiyi Bai, and Chen Yeh for excellent research assistance. CAREFIN—the Bocconi Centre for Applied Research in Finance—and the European Banking Center generously sponsored this research. Peydró acknowledges financial support from project ECO2012-32434 of the Spanish Ministry of Economics and Competitiveness. This paper was partly written when Van Horen was visiting the Research Department of the Federal Reserve Bank of Chicago. The views expressed in this paper are those of the authors and do not necessarily represent those of De Nederlandsche Bank, the Eurosystem of Central Banks or any of the institutions with which the authors have been affiliated.

An erratum to this article is available at http://dx.doi.org/10.1057/s41308-017-0034-4.

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Appendix

Appendix

Table A1

Table A1 Definitions, Sources, and Summary Statistics of Bank and Firm Variables

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Ongena, S., Peydró, JL. & van Horen, N. Shocks Abroad, Pain at Home? Bank-Firm-Level Evidence on the International Transmission of Financial Shocks. IMF Econ Rev 63, 698–750 (2015). https://doi.org/10.1057/imfer.2015.34

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