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Is foreign-bank efficiency in financial centers driven by home or host country characteristics?

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Abstract

This paper investigates whether home or host country factors can explain differences in technical efficiency among foreign banks operating in the Luxembourg financial center. We first address heterogeneity across banks by using the group-wise bootstrap to compare DEA measures of bank efficiency between branches and subsidiaries, focused and diversified banks, and euro area and non-euro area banks. We then control for these factors in a second-stage regression indentifying the impact of country-specific regulatory and macroeconomic variables on individual bank efficiency scores. Our regulatory indicators capture the strictness of capital requirements, private monitoring, official disciplinary power and restrictions on bank activities. Our macroeconomic indicators capture GDP per capita in the home country and its position in the business cycle. Our results carry policy implications for bank regulators in both home and host countries and provide insight into banks’ choice between establishing a branch or a subsidiary to develop cross-border activities through international financial centers.

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Notes

  1. Banque et Caisse d’Epargne de l'Etat and Société Nationale de Crédit et d'Investissement.

  2. Fortuna Banque and Banque Raiffeisen (including its local caisses rurales).

  3. As an alternative to DEA, efficiency can also be measured by stochastic frontier analysis (SFA) (see references in Park et al. (2008); Simar and Wilson (2010); Simar and Zelenyuk (2010)).

  4. See Korostelev et al. (1995) and Park et al. (2010) for proof of consistency and rates of convergence of the DEA estimator under constant returns to scale.

  5. See Park et al. (2010) for details.

  6. For instance, minimization of costs or maximization of revenues/profits.

  7. The model in Simar and Wilson (2007) requires some regularity conditions, including the ‘separability’ assumption which could be relaxed in future work.

  8. It would also be possible to look at diversification in the sources of financing. However, heterogeneity among banks is higher on this side (Stragiotti and Rychtarik 2009; Curi et al. 2011) which would lead to smaller groups, creating difficulties for DEA estimation.

  9. We consider euro area those nations using the euro as their currency (i.e. Austria, Belgium, Cyprus, Estonia, Finland, France, Germany, Greece, Ireland, Italy Malta, Spain, Netherlands, Portugal, Slovenia, Slovakia). Our sample does not cover all the euro area.

  10. We follow Zelenyuk and Zheka (2006). After observing a few small bumps on the right tails of the efficiency distribution, we trim them and then test the impact of the trimming by comparing the efficiency distributions of the two samples (original sample vs. trimmed sample) using a version of Li (1996) test (adapted to DEA context by Simar and Wilson (2007)). Since the null hypothesis of equality is not rejected, we can reduce the sample without losing much of aggregate information.

  11. This is because the sample contains banks which were closed or merged and newly created banks.

  12. We thank an anonymous referee for this suggestion.

  13. The World Bank database is only available for three points in time. As our time span covers a longer period, we assume that regulatory variables remain constant within short periods. More precisely, (1) for 1999–2001 we use the year 2001, (2) for 2002–2004 we use the year 2003, (3) and for 2005–2009 the year 2006. Other studies that have used this database appear to have used similar assumptions (e.g. Lozano-Vivas and Pasiouras 2010; Demirguc-Kunt et al. 2004; Pasiouras et al. 2009). When we used interpolated values in the regression, results were qualitatively the same.

  14. Recall that we measure efficiency of Banks relative to CRS technology, i.e. relative to the productivity level of optimal scale, which usually yields higher differences in efficiency between banks than otherwise.

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Acknowledgments

The authors are grateful for comments from participants at the International Workshop on Efficiency and Productivity in honour of Professor Knox Lovell, 4-5 October 2010, and participants at the PERFILUX final conference, 28-29 March 2011. We thank Aljar Meesters, Jean-Pierre Schoder and two anonymous referees for their valuable and insightful suggestions. Financial support from the Luxembourg Fonds National de la Recherche through the PERFILUX project is gratefully acknowledged. Ana Lozano-Vivas acknowledges financial support from Ministerio de Ciencia e Innovación, Dirección General de Programas y Transferencia de Conocimiento, grant reference ECO2008-04424. Any remaining errors are solely our responsibility. The opinions expressed in this paper are those of the authors and do not necessarily reflect the view of their institutions.

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Authors and Affiliations

  1. School of Economics and Management, Free University of Bolzano, Bolzano, Italy

    Claudia Curi

  2. Central Bank of Luxembourg, Luxembourg City, Luxembourg

    Paolo Guarda

  3. University of Malaga, Malaga, Spain

    Ana Lozano-Vivas

  4. University of Queensland, Brisbane, QLD, Australia

    Valentin Zelenyuk

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  1. Claudia Curi
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  2. Paolo Guarda
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  3. Ana Lozano-Vivas
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  4. Valentin Zelenyuk
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Correspondence to Claudia Curi.

Appendix

Appendix

See Table 8.

Table 8 Construction of regulatory variables
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Curi, C., Guarda, P., Lozano-Vivas, A. et al. Is foreign-bank efficiency in financial centers driven by home or host country characteristics?. J Prod Anal 40, 367–385 (2013). https://doi.org/10.1007/s11123-012-0294-y

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