Pricing in the Norwegian Interbank Market – the Effects of Liquidity and Implicit Government Support

AuthorQ. Farooq Akram,Casper Christophersen
DOIhttp://doi.org/10.1111/obes.12147
Published date01 April 2017
Date01 April 2017
165
©2017 The Department of Economics, University of Oxford and JohnWiley & Sons Ltd.
Pricing in the Norwegian Interbank Market –
the Effects of Liquidity and Implicit Government
Support*
Q. Farooq Akram† and Casper Christophersen
Research Department, Norges Bank, Bankplassen 2, P. O. Box 1179 Sentrum, Norway
(e-mail: farooq.akram@norges-bank.no)
European Insurance and Occupational Pensions Authority (EIOPA), Westhafenplatz 1,
60327 Frankfurt am Main, Germany (e-mail: casper.christophersen@eiopa.europa.eu)
Abstract
We investigate the effects of central bank liquidity and possible implicit government guar-
antees against default on Norwegian overnight interbank interest rates. We conduct an
econometric study of these interest rates over the period 2006–09, which includes the
sharp fall in interbank trading during the financial crisis. Our findings suggest relatively
lower funding costs for banks of systemic importance, particularly for banks with many
and valuable linkages to other banks. Moreover, interest rates are found to depend not
only on overall liquidity in the interbank market, but on its distribution among banks as
well. There is also evidence of stronger effects on interest rates of systemic importance,
creditworthiness and liquidity demand and supply factors during the financial crisis.
I. Introduction
A well-functioningmoney market is important for banks’ payment and credit intermediation
and trading for investment and risk management. It is also important for the effectiveness
of the monetary policy transmission mechanism and achieving monetary policy objectives
(see Acharya and Merrouche, 2013; Benos, Garratt and Zimmermann, 2014). Changes in
the policy rates are generally transmitted to money market interest rates and thereby to
lending and borrowing rates faced by firms and households, affecting their investment and
consumption decisions and (thereby) macroeconomic target variables(see e.g. Acharya and
Merrouche, 2013). Central banks influence money market interest rates not only through
their policy rates, but also by regulating the liquidity stance in money markets (see e.g.
Nautz and Scheithauer, 2009).
JEL Classification numbers: G21, E43, E58
*This paper should not be reported as representing the views of Norges Bank or EIOPA.The views expressed
are those of the authors and do not necessarily reflect those of Norges Bank or EIOPA. We are grateful to three
anonymous referees for comments and suggestions. We especially thank Asbjørn Fidjestøl, StevenOngena, Kimmo
Soram¨aki, Olav Syrstad and other colleagues for useful comments on the earlier version of this paper.
OXFORD BULLETIN OF ECONOMICSAND STATISTICS, 79, 2 (2017) 0305–9049
doi: 10.1111/obes.12147
166 Bulletin
Analyses of interbank interest rates’ responses to various factors are required for man-
aging money market liquidity and influencing money market rates. Such analyses are also
of interest for credit-risk assessments and financial stability policies (see e.g. Rochet and
Tirole, 1996; Furfine, 2001). When overnight lending in the interbank market is uncollat-
eralized, interest rates paid by a bank may indicate the solvency of the borrowing bank and
the credit risk associated with corresponding loans. In particular, banks perceived to be
of systemic importance may benefit from possible implicit government guarantees against
default and thereby face relatively lower borrowing rates than their peers considered to
lack systemic importance (see e.g. Passmore, 2005; Lucas and McDonald, 2006; Reiss,
2008; Gapen, 2009). However, beneficiaries and benefits of such guarantees are usually
ambiguous and depend generally on authorities’ and market’s perceptions of the systemic
importance of financial institutions.
Weinvestigateeconometrically therelationship betweenunsecured Norwegian overnight
interbank interest rates and various market and bank characteristics, focusing especially
on their variation with the aggregate level and the distribution of central bank liquidity
and measures of banks’ systemic importance. While an increase in overall liquidity in the
interbank market is expected to lower interest rates, its effect can weaken if it becomes
concentrated among a few banks. It has been argued that skewed liquidity distributions
may give rise to higher interbank interest rates through exploitation of market power
by banks with surplus liquidity (see e.g. Nyborg and Strebulaev, 2004; Fecht, Nyborg
and Rocholl, 2011; Acharya, Gromb and Yorulmazer, 2012). A skewed liquidity distribu-
tion could also reflect liquidity hoarding by banks in uncertain times and higher liquidity
premia, which may become reflected in interbank interest rates (see Acharya and
Merrouche, 2013). Central banks can influence liquidity distribution among banks through
altering the design and terms of central bank liquidity auctions and remuneration of banks’
deposits at central banks. Empirical evidence on the possible importance of liquidity
distribution for the level of interbank interest rates has implications for the choice
between alternative liquidity supply and remuneration schemes.
Our investigation of relationships between interbank interest rates and measures of
banks’ systemic importance tests for gains from systemic importance owing to a possible
implicit government guarantee against default.1Possible gains from such guarantees may
be detectable in the unsecured overnight interbank market despite the relatively short-
term credit risk exposures as individual loans are relatively large and uncollateralized,
in contrast with, for example, insured consumer deposits and mortgages. The unsecured
interbank market is negligible for loans beyond the overnight maturity in many countries
including Norway.2
As measures of a bank’s systemic importance, we use its size and connectedness with
other financial institutions through balance sheet linkages, as suggested by the Financial
Stability Board (2009), International Monetary Fund (2010) and Bank of England (2009).
To represent connectedness, we employ centrality measures proposed in the growing
1The Norwegian government does not offerany explicit guarantee against default to any financial institution.
2Survey information for the Norwegian money market that has become availableonly recently suggest that more
than 90% of uncollateralized lending takes place overnight and such lending beyond1-week maturity is close to zero
(see Norges Bank, 2014, 2015).
©2017 The Department of Economics, University of Oxford and JohnWiley & Sons Ltd
Effects of liquidity and implicit government support 167
literature on financial networks; see e.g.Allen and Babus (2009) and the references therein.
A challenge is to disentangle the effects of a possible implicit government guarantee from
those of other factors related to size and connectedness, such as portfolio diversification and
relationships, that may also contribute to lower interest rates.We explicitly control for the
effects of a number of bank characteristics associated with a bank’s size and connectedness
when testing for possible gains from systemic importance.
We conduct an econometric analysis based on a panel data set of banks active in the
Norwegian interbank market over the period 9 October 2006 to 6 April 2009.3As data
on actual interbank interest rates faced by individual banks is not publicly available, we
employ the procedure suggested by Furfine (1999, 2001) to infer overnight interest rates
from the real-time gross settlement (rtgs) system of Norges Bank, the central bank of
Norway. By a careful examination of the flows of funds between banks, fairly precise
information can be obtained about amounts borrowed and overnight interest rates paid by
banks; see e.g. Kovner and Skeie (2013) and Akram and Christophersen (2014) for some
recent evidence. We have obtained a novel data set on each bank’s daily liquidity position
at Norges Bank over the sample period to study the possible effects of aggregate liquidity
and its distribution among banks.
The data sample enables us to shed light on the importance of liquidity conditions and
systemic importance before and during the financial crisis, particularly during the money
market ‘freeze’ in 2007–08. Overall liquidity was substantially increased in response to
the financial crisis while its distribution became relatively skewed, possibly because of
liquidity hoarding (cf. Acharya and Merrouche, 2013). The variationin liquidity conditions
is informative for drawing inference on their importance. The financial crisis part of the
sample is also informative about the value of a possible implicit government guarantee,
which is likely to increase in a crisis. Therefore, to the extent that size and connectedness
measure systemic importance of banks and implicit government guarantees to systemically
important banks reduce credit premia, we expect possibly inverse relationships between
banks’ size and centrality and interest rates to become stronger in data samples including
the financial crisis.
To summarize our main findings: our analysissuppor ts an inverse relationship between
overall liquidity in the interbank marketand interbank interest rates. Moreover, the analysis
suggests that an increase in the inequality of liquidity distribution among banks is asso-
ciated with higher interbank interest rates. Another key finding is that banks considered
systemically important because of their financial linkages (centrality) are able to borrow
in the overnight interbank market at relatively lower overnight rates than other banks.
The relationship between bank size and overnight interest rate is found to be ambiguous,
however, as its sign and statistical significance vary across the models and data samples
considered. The observed relationship between interest rates and centrality has been found
to be relatively strong during the recent financial crisis, consistent with the presence and
expected increase in the value of an implicit government guarantee against default during
a financial crisis.
3Variousrestrictions on the availability of data has prevented us from using a longer data sample with more recent
data. Weexpect our results to be valid post-sample, at least qualitatively.
©2017 The Department of Economics, University of Oxford and JohnWiley & Sons Ltd

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