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Gerstenberger, J., Schnabl, G. The Impact of the Bank of Japan’s Low-Interest Rate Policy on the Japanese Banking Sector. Credit and Capital Markets – Kredit und Kapital, 54(4), 533-562. https://doi.org/10.3790/ccm.54.4.533
Gerstenberger, Juliane and Schnabl, Gunther "The Impact of the Bank of Japan’s Low-Interest Rate Policy on the Japanese Banking Sector" Credit and Capital Markets – Kredit und Kapital 54.4, 2021, 533-562. https://doi.org/10.3790/ccm.54.4.533
Gerstenberger, Juliane/Schnabl, Gunther (2021): The Impact of the Bank of Japan’s Low-Interest Rate Policy on the Japanese Banking Sector, in: Credit and Capital Markets – Kredit und Kapital, vol. 54, iss. 4, 533-562, [online] https://doi.org/10.3790/ccm.54.4.533
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The Impact of the Bank of Japan’s Low-Interest Rate Policy on the Japanese Banking Sector

Gerstenberger, Juliane | Schnabl, Gunther

Credit and Capital Markets – Kredit und Kapital, Vol. 54 (2021), Iss. 4 : pp. 533–562

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Article Details

Publisher Name
Duncker & Humblot
DOI
https://doi.org/10.3790/ccm.54.4.533
Language
English
Pages
30
Keywords

Author Details

Juliane Gerstenberger, Seelenberger Straße 4, 60489 Frankfurt, Germany.

Prof. Dr. Gunther Schnabl, Leipzig University, Institute of Economic Policy, Grimmaische Straße 12, 04109 Leipzig.

Cited By

  1. Niedrigzinspolitik und Sparkultur in Japan: Implikationen für die Wirtschaftspolitik

    Schnabl, Gunther

    Sepp, Tim

    ORDO, Vol. 72-73 (2023), Iss. 1 P.392

    https://doi.org/10.1515/ordo-2023-2001 [Citations: 0]

References

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  90. Golany, B./Yu, G. (1997): “Estimating returns to scale in DEA”, European Journal of Operational Research, Vol. 103 No. 1, pp. 28–37.  Google Scholar
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  94. Ishikawa, A./Tsuchiya, S./Nishioka, S. (2013): “Financial institutions’ efforts to support the business conditions of small and medium-sized firms: Intermediation services utilizing corporate information and customer networks”, Bank of Japan Review, Vol. 2013 No. January, pp. 1–7.  Google Scholar
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  98. McKillop, D. G./Glass, J. C./Ferguson, C. (2002): “Investigating the cost performance of UK credit unions using radial and non-radial efficiency measures”, Journal of Banking & Finance, Vol. 26 No. 8, pp. 1563–1591.  Google Scholar
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  102. Peek, J./Rosengren, E. S. (2005): “Unnatural selection: perverse incentives and the misallocation of credit in Japan”, The American Economic Review, Vol. 95 No. 4, pp. 1144–1166.  Google Scholar
  103. Posen, A. S. (2000): “The political economy of deflationary monetary policy”, in Mikitani, R. and Posen, A. S. (eds.), Japan’s financial crisis and its parallels to U.S. experience, Institute for International Economics, Washington, DC, pp. 149–166.  Google Scholar
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  105. Sarmiento, M./Galán, J. E. (2015): “The influence of risk-taking on bank efficiency: Evidence from Colombia”, Banco de España Working Paper, No. 1537.  Google Scholar
  106. Schnabl, G. (2015): “Monetary policy and structural decline: Lessons from Japan for the European crisis”, Asian Economic Papers, Vol. 14 No. 1, pp. 124–150.  Google Scholar
  107. Schnabl, G. (2020): Japans Banken in der Krise, Springer Gabler, Wiesbaden.  Google Scholar
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  110. Sekine, T./Kobayashi, K./Saita, Y. (2003): “Forbearance lending: The case of Japanese firms”, Monetary and Economic Studies, Vol. 21 No. 2, pp. 69–92.  Google Scholar
  111. Shephard, R. W. (1970): Theory of cost and production functions, Princeton University Press, Princeton.  Google Scholar
  112. Simar, L./Wilson, P. W. (1998): “Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models”, Management Science, Vol. 44 No. 1, pp. 49–61.  Google Scholar
  113. Simar, L./Wilson, P. W. (2000): “Statistical inference in nonparametric frontier models: The state of the art”, Journal of Productivity Analysis, Vol. 13 No. 1, 49–78.  Google Scholar
  114. Simar, L./Wilson, P. W. (2007): “Estimation and inference in two-stage, semi-parametric models of production processes”, Journal of Econometrics, Vol. 136 No. 1, pp. 31–64.  Google Scholar
  115. Tauchmann, H. (2016): “SIMARWILSON: Stata module to perform Simar & Wilson efficiency analysis“, Statistical Software Components. S458156, Boston College Department of Economics, revised 23 May 2016.  Google Scholar
  116. Weill, L. (2004): “Measuring cost efficiency in European banking: A comparison of frontier techniques”, Journal of Productivity Analysis, Vol. 21 No. 2, pp. 133–152.  Google Scholar
  117. Wilson, P. W. (2008): “FEAR. A software package for frontier efficiency analysis with R”, Socio-Economic Planning Sciences, Vol. 42 No. 4, pp. 247–254.  Google Scholar
  118. Yoshino, N./Taghizadeh-Hesary (2016): “Decline in oil prices and the negative interest rate policy in Japan”, ADBI Working Paper, No. 600.  Google Scholar

Abstract

This paper presents an analysis of the impact of the Bank of Japan’s low-interest rate policy on the banking sector in the wake of the 1998 Japanese financial crisis. We show how the low-cost liquidity provision as a means to stabilize banks has created a growing gap between deposits and loans in the financial system and how the low-interest rate policy has compressed interest margins as the traditional source of banks’ income. Efficiency scores are compiled to estimate the effect of the Bank of Japan’s monetary policy on banks’ technical efficiency. The estimation results provide evidence that the Japanese monetary policy has contributed to declining efficiency in the banking sector, despite – or possibly because of – the increasing concentration within this sector.

Table of Contents

Section Title Page Action Price
Juliane Gerstenberger / Gunther Schnabl: The Impact of the Bank of Japan’s Low-Interest Rate Policy on the Japanese Banking Sector 1
Abstract 1
I. Introduction 1
II. Japan’s Low-Interest Rate Policy and the Banking Sector 3
1. Declining Income 3
2. Alternative Sources of Income and Adjustment of Costs 6
III. Development of Japanese Banks’ Efficiency 9
1. Concept of Efficiency Measures 9
2. Input and Output Data 1
3. Results for Efficiency Scores 1
IV. Drivers of Japanese Bank Efficiency 1
1. Data and Estimation Framework 1
2. Estimation Results 2
V. Conclusion 2
References 2
A. Appendix 2
A1. Estimating Efficiency Scores 2

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