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Are Competitive Banking Systems More Stable

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Title: Are Competitive Banking Systems More Stable


1
Are Competitive Banking Systems More Stable?
The Architecture of Financial System
Stability From Market Micro Structure to
Monetary Policy 24 26th May, 2006, Capri,
Italy
Klaus Schaeck School of Management University of
Southampton
Martin Cihak International Monetary
Fund Washington, DC
Simon Wolfe School of Management University of
Southampton
DISCLAIMER This papers findings,
interpretations, and conclusions are entirely
those of the authors and do not necessarily
reflect the views of the International Monetary
Fund, its Executive Directors, or the countries
they represent.
2
Are Competitive Banking Systems More Stable?
Outline (1) Literature Review (2)
Rationale/Contributions of this Research
(3) Methodological Approach (4) Econometric
Analysis (5) Sensitivity Tests (6)
Conclusion and Future Research
3
(1) Literature Review
Theoretical literature - diametrically opposite
views Competition less stability Smith
(1984), Besanko and Thakor (1993), Cordella and
Yeyati (1998), Matutes and Vives (2000), Hellman
et al. (2000) Competition more
stability Caminal and Matutes (2002), Nagaraja
and Sealey (1995), Perotti and Suarez (2002)
Complex relationship of competition and
stability Allen and Gale (2004), Boyd et al.
(2004) Instabilities can arise in any market
structure Matues and Vives (1996)
Empirical literature is characterised by studies
that focus on one or two countries Keeley
(1990) - US Staikouras and Wood (2000) Greece
and Spain Bordo et al. (1995) Canada and
US Hoggarth et al. (1998) Germany and UK Capie
(1995) - UK
4
(1) Literature Review
Lack of cross-country datasets on competitive
behavior made both policymakers and researchers
rely heavily on concentration as a proxy for
competition. Theoretical studies Concentration
increases fragility Boyd and de Nicolo (2005),
Mishkin (1999) Concentration decreases
fragility Allen and Gale (2000, 2004), Boot and
Greenbaum (1993)
Empirical studies Concentration increases
fragility De Nicolo and Kwast (2001), De Nicolo
et al. (2004), Boyd and Graham (1991, 1996)
US Concentration decreases fragility Paroush
(1995), Benston et al. (1995), Craig and Santos
(1997) US Beck et al. (2005a, 2005b) Cross
country (69 jurisdictions)
Impact of the regulatory environment is equally
disputed Liberalization and deregulation
decrease stability Fischer and Chenard (1997)
Greater contestability and less activity
restrictions increase stability Barth et al.
(2004) Beck et al. (2005a, 2005b)
5
(2) Rationale
  • Relying on concentration as a proxy for
    competition gives rise to several
  • problems
  • (1) The inverse relationship between competition
    and concentration is not empirically
  • substantiated (Claessens and Laeven, 2004 also
    Beck et al., 2005a, 2005b)
  • (2) It propels misleading inferences and gives
    rise to measurement problems as the
  • level of concentration is overstated in small
    countries and when the number of
  • banks is small (Bikker, 2004).
  • (3) It does not measure competitive conduct of
    financial institutions on the marginal level. It
    is not derived from profit-maximizing conditions
    (Shaffer, 2004).

Development in the recent literature to
distinguish between concentration and
competition (Berger et al., 2004) However, no
study specifically tests for the relationship
between banks competitive conduct and its
implications for systemic risk in a
cross-country setting.
6
(2) Contributions
Contributions of this study (1) First empirical
analysis of the link between competitive
conduct of banks, measured by the Panzar and
Rosse (1987) H-Statistic, and systemic risk
using cross-country data (38 countries,
19802003). (2) Re-examination of the
relationship between concentration,
competition, and crises. (3) Methodological
advancement on modelling systemic risk using a
parametric duration model with time-varying
covariates. (4) Examination of the impact of
the regulatory environment on the timing of
systemic banking crises.
7
(3) Methodological Approach
The Panzar and Rosse (1987) H-Statistic Measures
market power by the extent to which a change in
factor input prices translates into equilibrium
revenues by bank i.
Ri equilibrium value of revenue of bank i wi
vector of m input prices H 0 monopoly
equilibrium 0 lt H lt1 monopolistic competition H
1 perfect competition Data on H-Statistic
obtained from Claessens and Laeven (2004).
8
(3) Methodological Approach
Measuring competition The Panzar and Rosse
(1987) H-Statistic (Shaffer, 2004) (1) H-Statist
ic is analytically superior to previously used
measures of competition, because it is derived
from profit-maximizing equilibrium
conditions. (2) It is robust with respect to
the market since it only draws upon
characteristics of reduced-form revenue equations
at the firm level.
  • Measuring banking sector stability
  • We use a dummy variable indicating a systemic
    banking crisis
  • (1) Demirgüç-Kunt and Detragiache (2005) dating
    scheme is used as
  • the basic one (it is based on presence of
    emergency measures,
  • large nationalizations, high NPLs, and high
    fiscal costs of rescues). It
  • shows 28 systemic crises in 1980-2003 for our
    sample.
  • Honohan and Laeven (2005) used as an alternative
    dating scheme

9
(3) Methodological Approach
We model crises using duration and logit
analysis. I. Duration analysis The dependent
variable measures the time to transition from a
sound banking system to a crisis episode. Since
we have multiple observations per country with up
to 23 time spans in the dataset, we estimate
the model with time-varying covariates.
Accelerated failure time models are written in
the form where ln(tj) is the log of time to
failure, xj denotes our explanatory variables, ßx
are the parameters to be estimated and tj is a
random variable that follows a distribution.
10
(3) Methodological Approach
Duration analysis (contd)
Thus, to estimate the model, we need to determine
the distribution of tj and specify it to follow
the exponential distribution. We perform a
robustness test based on the Weibull distribution
for the baseline hazard function and also employ
a Cox proportional hazards model to examine the
sensitivity of our estimates to the alternative
setups. Both additional robustness tests
confirm the results obtained with the model based
on the exponential distribution.
11
(3) Methodological Approach
  • II. Logit analysis
  • The model computes the probability that a crisis
    is observed

P(i,t) 1 if a crisis is observed, 0 otherwise.
ß vector of coefficients to be estimated X
(i,t) explanatory variables
12
Main Results (4) Econometric Analysis
Robust standard errors in parentheses.
Significance levels of 1, 5 and 10 percent are
indicated by , and .
13
Findings core results (4)
Econometric Analysis
Competitive behaviour of financial institutions
matters for both the timing and the probability
of observing systemic banking crises, when the
level of concentration, the macroeconomic
environment, deposit insurance design features
and the legal origin of the country are
controlled for. Our duration analysis indicates
that time to crisis increases in a more
competitive environment whereas the logit model
suggest that competition decreases the
probability of observing a crisis.
Concentration is insignificant in both the
duration and the logit probability models.
14
Findings core results (contd) (4)
Econometric Analysis
Among the control variables, terms of trade, the
rate of depreciation, and credit growth enter
the duration model significantly. French and
Scandinavian legal origin are also found to to be
significant, suggesting shortened survival time
of banking systems in the respective
jurisdictions. The logit model furthermore
indicates that increases in real interest rates,
inflation, credit growth are good precursors
for banking crises. The dummy for French legal
origin enters again the equation significantly
corroborating the findings from the duration
analysis.
15
Robustness tests (5) Sensitivity
Analyses
We perform a set of sensitivity analyses using
both the duration and the logit model employing
a different coding for the dependent variable in
Regression (1) and (5), excluding low income
economies in Regression (2) and (6), using first
differences rather than levels for the
macroeconomic control variables in Regression (3)
and (7), and constrain the sampling period to
the time between 1985 and 2003 in Regression (4)
and (8).
Robust standard errors in parentheses.
Significance levels of 1, 5 and 10 percent are
indicated by , and .
16
Robustness tests (contd) (5)
Sensitivity Analyses
While the alternative crisis definition (1) and
(5) does not suggest a significant relationship
between competition and systemic risk, the three
other robustness tests underscore the core
findings and reiterate the positive relationship
between competition and time to crisis and the
negative relationship between competition and
the probability of observing a systemic crisis!
Concentration never assumes any meaningful
level of significance!
17
Competitiveness, Regulation and Crises (5)
Sensitivity Analyses
We test the impact of competitiveness on the
timing and likelihood of systemic crises, whilst
controlling for a set of regulatory and
institutional variables.
Robust standard errors in parentheses.
Significance levels of 1, 5 and 10 percent are
indicated by , and .
18
Findings - Competitiveness, Regulation and
Crises (5) Sensitivity Analyses
Controlling for the effect of activity
restrictions, a capital regulatory index, and
government and foreign ownership of banks hardly
impacts upon the degree of competitive bank
behaviour on systemic risk. The significant
effect of competition on the timing of banking
crises is only rendered insignificant when
foreign ownership enters the equation. The logit
models however suggest competition increases
banking system stability across all four
specifications. Concentration remains again
insignificant across all regressions. Activity
restrictions are found to enter the logit model
significantly with a positive coefficient. This
finding is consistent with Barth et al. (2004)
and Beck et al. (2005a, 2005b).
19
(6) Conclusion
  • (1) The first empirical study on the relationship
    between competition, measured by the Panzar and
    Rosse (1987) H-Statistic, and the likelihood and
    timing of systemic banking crises.
  • (2) Higher degrees of competition in banking
    systems are associated with increased survival
    time of banking systems and go hand in hand with
    a decrease in the probability of systemic banking
    crises.
  • Results for the timing and the probability of
    suffering a systemic crisis are robust to using
    alternative samples, alternative sampling
    periods, and also hold when an alternative coding
    for the macroeconomic variables is employed.
  • These findings also hold when concentration is
    accounted for and provide empirical support to
    the assertion that concentration and competition
    are different concepts.
  • The results obtained from both methods
    empirically substantiate theoretical research on
    the competition-stability view in the
    literature.
  • No claim, that highly competitive banking systems
    are free of failures.


20
(6) Future Research
  • Relationship between competition and fragility
    has to be investigated further!
  • It is worthwhile to examine whether alternative
    measures of competitive bank conduct support our
    results and which levels of competition, if any,
    are optimal to achieve and sustain banking system
    stability.
  • Studies on the firm level, using cross-country
    data and controlling for the regulatory
    environment will help explore the linkages
    further.
  • The mechanism by which competition contributes to
    stability has to be scrutinised. For example, an
    analysis of the effects of competition in the
    short and in the long run may yield different
    outcomes for stability. As a complement to the
    0/1 measure of financial fragility, one could use
    more continuous measures, such as distance to
    default.
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