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The Determinants of Cross-Border Lending in the Euro Zone

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Abstract

We investigate the determinants of cross-border lending in the euro zone with a focus on the potentially limiting role of cultural and political factors. Employing a unique data set of European cross-border loans, the study uses various specifications of gravity models, which are subsequently augmented by societal proxies. Although trade-theoretic and financial development reasoning can explain part of the surge in cross-border lending, we demonstrate that distance and borders still matter. Moreover, we identify cultural differences and different legal family origin as important barriers to further integration in the euro zone.

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Notes

  1. Baele et al. (2004) suggest this classification of the empirical literature on financial integration. For a recent overview of the evidence see Kleimeier and Sander (2007).

  2. We are not explicitly applying the recent development in trade theory, which considers heterogeneous firms with firm-level differentials (see eg Melitz, 2003; Helpman et al., 2008). But as argued by Buch and Lipponer (2007) also this new(est) trade theory might be fruitfully applied to banking as it predicts that only the most productive banking firms will engage in cross-border banking. The gravity approach therefore indirectly relates to this strand of literature. However, directly testing this theory requires firm-level data unless one follows the two-stage estimation approach recently suggested by Helpman et al. (2008). We do, however, not follow this line of research here.

  3. See, eg, Baxter and Kouparitsas (2006).

  4. A strict interpretation in the sense of Newton would demand to calculate SIZE as the product of the GDPs. Many empirical papers use, however, the (log of) the sum of the GDPs (eg Baltagi et al., 2003). This proxy allows an easier direct interpretation of the coefficients as the elasticity of bilateral trade with respect to their joint GDP.

  5. For a discussion in the context of the finance-and-growth literature, see Wachtel (2003).

  6. The results of the different estimation techniques are available in Table A2 of the working paper version of this study available as METEOR Research Memorandum RM/08/008 at http://edocs.ub.unimaas.nl/loader/file.asp?id=1306.

  7. Anderson and van Wincoop (2003) arrive at this conclusion from a market-clearing model where each country is producing a single differentiated good and customers’ preferences are following a CES-utility function. Baldwin and Taglioni (2006) also strongly advocate the use of country dummies to avoid what they call ‘gold medal error’.

  8. As we are primarily interested in estimating the influence of the time-invariant determinants we focus on the static approach and assume that the ɛ ijt are not serially correlated.

  9. See Baldwin and Taglioni (2006).

  10. More specifically, the reporting banks belong to the group of monetary financial institutions (MFIs), which includes credit institutions, central banks, money market funds, foreign branches of credit institutions (located in the respective country) and other institutions. The latter category is, however, negligible in the euro zone. As we exclude central banks as lenders, our loan volumes consist mainly of loans made by credit institutions. As borrowers, we consider only non-MFIs which include households, non-financial corporations, non-profit institutions serving households, government entities but also financial institutions such as insurance corporations or pension funds. Consequently, the types of loans that we consider are mortgages, consumer loans, corporate and public loans, subordinated debt in form of loans and financial leases. We include loans of all maturities and currencies as well as bad loans, traded loans as long as they are supported by a single document (not securitized) and traded infrequently, and collateralized loans resulting from reverse repo-type operations. Specifically excluded from the definition of loans under regulation ECB/2001/13 are loans granted on a trust basis and negotiable loans that have been restructured into a large number of identical documents and that can be traded on secondary markets. Regarding the level of (dis)aggregation of our data, note that Table 3 only distinguishes loans by (1) country-location of the borrower, and (2) MFI versus non-MFI borrowers. Thus, no further disaggregation – for example, mortgages versus corporate loans or short-term versus long-term loans – is possible. Finally, to match the country-level aggregation of the borrower, loan volumes are aggregated across all lenders of a given country.

  11. See Cecchetti (1999) and Sander and Kleimeier (2004), who identify differences in legal family heritage as a factor limiting European monetary and financial integration.

  12. We nevertheless have tried this bilateral trust variable with the 1996 values in our gravity approach. However, no significant effects could be detected.

  13. Market capitalization is highly correlated with GDP per capita and it is thus not surprising, that the results are very much in line with the reported GDP-based results. Moreover, and probably due to multicollinearity, the parameter estimate for SIZE has the wrong sign. Regarding DEPOSIT and MONEY, the distribution of both variables is more right-skewed than the distribution of credits. The same explanation holds for money, as deposits are part of the broad definition of money. However, it regardless which financial development proxy is chosen, the parameter estimates for the cultural and political variables are robust.

  14. However, these results seem to be generally in line with the results that Baltagi et al. (2003) have obtained from merchandise trade estimates when employing a similar model and using – as in our model here – importer, exporter and time dummies.

  15. When estimating our preferred model with the reduced sample but without FDI, we also find that foreign bank penetration is no longer significant.

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Acknowledgements

We benefited from comments by Evan Kraft, Paul Wachtel, Gerhard Winkler and two anonymous referees. We are grateful to the participants of the 14th Dubrovnik Economic Conference (Croatia National Bank, Dubrovnik, 25–28 June 2008, the 6th INFINITI Conference on International Finance (Trinity College Dublin, 9–10 June 2008), the International Seminar ‘International Financial Integration: Measures and Determinants’ (BBVA Foundation – Ivie, Valencia, 19 September 2008), and the Jubilee Conference on European Financial, Monetary and Fiscal Integration (Maastricht University, 3 December 2008).

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APPENDIX

APPENDIX

See Table A1.

Table a1 Description of variables

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Heuchemer, S., Kleimeier, S. & Sander, H. The Determinants of Cross-Border Lending in the Euro Zone. Comp Econ Stud 51, 467–499 (2009). https://doi.org/10.1057/ces.2009.9

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