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Bank characteristics and the interbank money market: a distributional approach

Author

Listed:
  • Iori Giulia

    (City University of London, Department of Economics, Northampton Square, London EC1V OHB, UK)

  • Kapar Burcu

    (City University of London, Department of Economics, Northampton Square, London EC1V OHB, UK)

  • Olmo Jose

    (School of Social Sciences, Economics Division, University of Southampton, Room 3015, Bld 58 (Murray Bld), Highfield Campus, Southampton, SO17 1BJ, UK)

Abstract

This paper studies the relationship between bank characteristics, such as size, nationality, operating currency and sovereign debt in the parent country, and the distribution of funding spreads observed in the e-MID interbank money market during the Great financial crisis. Our setup is a pseudo-panel with a random number of international banks acting in the interbank market in each period. We develop new econometric tools for panel data with random effects and discrete covariates, such as a nonparametric kernel estimator of the distribution function of the response variable conditional on a set of covariates and a consistent test of first order stochastic dominance. Our empirical results, based on these tests, shed light on the survivorship bias in the e-Mid market, and reveal the existence of a risk premium on small banks, banks with currencies different from the Euro, and banks based on countries under sovereign debt distress in the periphery of the European Union. Finally we assess the impact of policy intervention in the aftermath of the financial crisis.

Suggested Citation

  • Iori Giulia & Kapar Burcu & Olmo Jose, 2015. "Bank characteristics and the interbank money market: a distributional approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(3), pages 249-283, June.
    • Handle: RePEc:bpj:sndecm:v:19:y:2015:i:3:p:249-283:n:6
    DOI: 10.1515/snde-2014-0030
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    References listed on IDEAS

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    Cited by:

    1. Green, Christopher & Bai, Ye & Murinde, Victor & Ngoka, Kethi & Maana, Isaya & Tiriongo, Samuel, 2016. "Overnight interbank markets and the determination of the interbank rate: A selective survey," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 149-161.
    2. Paolo Barucca & Fabrizio Lillo, 2018. "The organization of the interbank network and how ECB unconventional measures affected the e-MID overnight market," Computational Management Science, Springer, vol. 15(1), pages 33-53, January.
    3. Bednarek, Peter & Dinger, Valeriya & Schultz, Alison & von Westernhagen, Natalja, 2023. "Banks of a feather: The informational advantage of being alike," Discussion Papers 09/2023, Deutsche Bundesbank.
    4. Paolo Barucca & Fabrizio Lillo, 2015. "The organization of the interbank network and how ECB unconventional measures affected the e-MID overnight market," Papers 1511.08068, arXiv.org, revised Sep 2017.
    5. Domenico Di Gangi & Giacomo Bormetti & Fabrizio Lillo, 2022. "Score Driven Generalized Fitness Model for Sparse and Weighted Temporal Networks," Papers 2202.09854, arXiv.org, revised Mar 2022.
    6. Temizsoy, Asena & Iori, Giulia & Montes-Rojas, Gabriel, 2015. "The role of bank relationships in the interbank market," Journal of Economic Dynamics and Control, Elsevier, vol. 59(C), pages 118-141.
    7. Berardi, Simone & Tedeschi, Gabriele, 2017. "From banks' strategies to financial (in)stability," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 255-272.
    8. Katarzyna Bech & Grant Hillier, 2015. "Nonparametric testing for exogeneity with discrete regressors and instruments," CeMMAP working papers 11/15, Institute for Fiscal Studies.
    9. Anastasios Demertzidis, 2019. "Interbank transactions on the intraday frequency: -Different market states and the effects of the financial crisis-," MAGKS Papers on Economics 201932, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

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    More about this item

    Keywords

    e-mid interbank money market; nonparametric kernel estimation; panel data methods; random effects; stochastic dominance tests;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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