XXX CONFERENZA ITALIANA DI SCIENZE REGIONALI
THE EFFECT OF BANK CONCENTRATION ON INDUSTRIAL GROWTH: EVIDENCE
FROM EASTERN AND CENTRAL EUROPEAN TRANSITION COUNTRIES.
Very preliminary draft – please do not quote without authors’ approval
Angela Stefania BERGANTINO1 e Claudia CAPOZZA1
1 Dipartimento di Scienze Economiche e Metodi Matematici, Università degli Studi di Bari, via C. Rosalba, 53,
70124 Bari
SOMMARIO
This paper investigates the effect of concentration in the banking sector on industrial growth.
Rajan and Zingales (1998) find that while industries’ growth rate is higher in countries with
more developed financial markets, in countries where these are underdeveloped, the
industries’ growth rate is lower. This accelerating or depressive effect is enhanced for
industries more dependent on external funding as, generally, transition countries’ industries
are. In the last decade, both theoretical and empirical literature on this subject has flourished,
however, the main evidence refers to industrialised economies and reaches differing results.
The aim of this paper is to explore the effect of banking market structure on the different
industrial sectors of Eastern and Central European countries. These countries are
characterised by a lower development level of the financial sector and a more concentrated
banking market than the traditionally industrialised economies. Our empirical investigation
yields evidence supporting the hypothesis that, in order to promote industrial growth in
transition economies, it is necessary to stimulate competition in the banking industry and to
1
improve the development of alternative forms of financing such as capital markets in order to
accelerate growth.
2
INTRODUZIONE
The debate on the role of the financial system in boosting economic growth started
almost a century ago. Shumpeter (1911) argues that services provided by financial
intermediaries stimulate long run growth. The first empirical study is realized by
Goldsmith (1969) using a sampling of 30 countries for the period 1860-1963,
however, this work, although showing a positive correlation between financial
development and growth, did not clear the question of causality. Several years after,
King and Levine (1993), make a determinant contribution: they check the
Schumpeterian theory of economic development examining a cross section of 80
countries for the period 1960-1989 and they found robust evidence that the
«financial development precedes growth». The level of financial development at the
beginning of the period considered fosters economic growth, capital accumulation
and firms’ productivity growth of the following thirty years. In the light of results
obtained, King and Levine affirm that «Schumpeter might be right» because
«finance matters».
A fundamental empirical contribution explaining the role of financial development
is by Rajan and Zingales (1998). This seminal paper investigates the effect of
financial development on industries’ growth, starting from the assumption that well
developed financial markets reduce the costs sustained by firms to obtain external
financial resources. The authors find that well developed financial systems promote
industries growth; in particular industries more in need of external resources grow
faster in countries with well developed financial markets. They use different
measures of financial development in order to check the robustness of the results.
The financial economics literature classifies financial systems in two types: the
relationship system, which is a bank dominated system and the arm’s length system
which is, instead, a market oriented system. In a theoretical paper Rajan and
Zingales (2001) explore in detail the features of the two systems. According to the
authors, the relationship-based system assures a return to banks giving them a
monopoly power on the firms they finance. In these systems, when evaluating the
financial requirement and the capacity to pay interests, banks take into account the
3
long run capacity to repay the debt rather than the present, therefore the interest rate
is not related to the project risk and can change upon the borrowers financial
situation. In the arm’s length system, instead, the market orientation grants
transparency. Loans have to be repaid by firms until the expiry foreseen by
contracts; the interest rate is market interest, so it exactly rewards banks for the risk
assumed and for the contract length. Comparing the financial systems, the authors
point out that disregarding market signals, as the relationship-based system does,
can bring an inefficient resources allocation, i.e. funding is not granted to the firm
able to create greatest value for society, so it has a negative impact on growth.
Differently in economies based on arm’s length financial system, investment
decisions are market driven and the resources allocation taking place is the efficient
one.
The cooperation between lenders and borrowers taking place in relationship-based
system imply that firms share their profits with banks paying higher interest rate
when financial situation is good, in return of lower interest rate during start-up phase
or financial distress. However, if funded projects are based on intangible assets as
intellectual property, this implicit profits sharing can reduce the efforts and the
investment in innovations made by firms, weakening the entrepreneurial activities in
high technologies industries. Consequently relationship based system is better for
financing traditional industries; on the contrary arm’s length system is better in
financing industries with intangible assets because these industries are supported in
investing in R&D when the financial system is transparent.
In the last decade the related literature has flourished. One of the most debated
issues regards the banking market structure and its effect on the growth rate of other
industries. Banks foster industrial growth providing financial resources that firms
need. It is obvious that the market result in terms of allocative and productive
efficiency differs depending on the degree of competition in the banking market, but
is not trivial asking what is the optimal market structure for banking industries.
Northcott (2004) does an extensive review on this issue and provides valuable
elements to answer the question. The traditional theory of industrial organization
provides arguments in favour of competition. In a competitive environment banks
are price takers, minimize costs and offer the maximum quantity of credit at the
lower interest rate. Oppositely when market power exists, banks can set price higher
than marginal cost and offer a smaller quantity of credit; consequently a
4
concentrated banking industry has a detrimental effect on industries’ growth.
Instead, an alternative theoretical approach claims that banking industry has specific
features, different from non-financial industries, for which market power does not
necessarily has negative effects on industrial growth. In particular, the latter
statement is based on the consideration that the amount of financial resource banks
offer is related not only to market structure but also to internal factors among which
the net value of the institute: a profitable bank can provide more credit. This is true
also in the presence of a balance shock, moreover, its lending relations are sturdy.
In a competitive market, where profits are pushed down, this can’t happen. Another
relevant internal factor is the capital requirement that sets the capital to assets ratio.
If it becomes too low, banks can either increase capital or reduce assets; because the
first options is too costly banks, in general, cut down lending relationships. An
additional reason in support of the positive impact of concentration on industrial
growth comes from the consideration that more concentrated banks are more incline
to engage relationships with young firms because it is easier to internalize their
benefits (Petersen and Rajan, 1995). Generally young firms are more risky, therefore
in perfect competition banks ask to them higher interest rates. If banks have market
power, the interest rate asked could be lower than the one fixed on the market and
the higher risk assumed is compensated by sharing the future profits. Consequently
in less competitive banking market the credit available for young firms and the
growth opportunities are greater.
Cetorelli and Peretto (2000) develop a model where credit is supplied by an
oligopolistic banking industry. The authors consider that the number of banks
influences the level of capital accumulation in two channels. It influences both the
quantity of credit available for firms and banks decision to collect information on
potential borrowers. The model show a trade-off between the amount of credit
available and quality of borrowers1: if the number of banks in the market decreases,
the amount of credit supplied decreases but banks are fostered to better select firms,
granting the credit to high quality borrowers. The model’s results show that the
banking market structure able to maximizes growth is neither competition nor
monopoly, but an intermediate oligopoly.
1
The quality of borrowers is defined observing their credit history
5
In this paper we investigate the effect of banking market structure on the industrial
sectors of Eastern and Central European countries. Rajan and Zingales’ (1998)
pioneer paper has been the reference point for the following empirical analysis
exploring the issue of financial market and growth. Indeed on this work the other
economists have modelled their empirical specification. Keeping on the topic of our
paper, in the empirical analysis a few different measures of bank concentration (or
competition) are implemented by authors that directly or indirectly test its effect on
industrial growth. The main works focusing exactly on the effect on industrial
growth produced by banking market structure, i.e. Cetorelli and Gambera (2001) and
Claessens and Laeven (2004), conduct the analysis considering an heterogeneous
sample of countries. Instead we provide evidence for Central and Eastern European
countries. In order to draw a good picture of the current state, we point out many
aspect that could enhance or reduce the general and the industry specific effect that
bank concentration produce on industrial growth. We consider clearly the financial
market development that the empirical literature regards as a fundamental concern;
further we investigate the role played by banking sector regulation taking into
account its different traits; we consider also the presence of foreign bank and state
owned bank; moreover we work on some aspect related to market contestability;
finally we control for many socioeconomics aspects. In the next section briefly
review the main literature. In section 3 we present the econometric model we have
estimated, then in section 4 we provide information about the industry-level data and
cross-country data. In section 5 we show the empirical findings and finally in section
6 we draw some preliminary conclusions and highlight issues for further
investigation.
2. LITERATURE REVIEW AND MAIN RESULTS
Starting from the work of Rajan and Zingales (1998), Cetorelli and Gambera (2001)
and Claessens and Laeven (2004) realize an industry level analysis testing the effect
of banking market structure on growth. In particular, Cetorelli and Gambera (2001)
consider a sample of 41 countries in the entire world. The dependent variable, the
growth rate of industries, is the average for 1980-1990; the measure of bank
concentration is the sum of the assets of three largest banks as a share of assets of all
commercial banks. The results obtained show a significant and negative impact of
bank concentration on industries growth; furthermore the authors find a significant
and positive coefficient of the interaction term between external financial
6
dependence and bank concentration. Consequently a concentrated banking market
produces generally a negative effect on industrial growth but it emerges an industry
specific effect: bank concentration promotes growth of industries more financial
dependent. Claessens and Laeven (2004) use two measure of banking competition.
The first is the same of Cetorelli and Gambera (2001), the second one is the Hstatistic2. Cetorelli and Gambera (2001) and Claessens and Laeven (2004) differ one
from each other for the period cosidered, Claessens and Laeven (2004) test the effect
of banking market structure on the average growth rate of industries for 1980-1997.
At first the authors used the same measure of bank concentration chosen by Cetorelli
and Gambera (2001). They find a non significant interaction effect between bank
concentration and external financial dependence; they explain it could be due to the
difference in time-frame. Secondly they use H-statistic measure, in this case the
results are the same of Cetorelli and Gambera (2001). Cetorelli (2001) deeps the
work above exploring the effect of banking market structure on the market structure
of industrial sectors, computing 17 OECD countries. He finds that bank
concentration enhances industries’ market concentration, especially in sectors highly
dependent on external finance.
A relevant empirical contribution is offered by Beck et al (2003). Including both
industrialized and developing countries, the authors examine the effects of banks
concentration on credit availability taking into account the regulatory policies. The
obtained results show that in general firms find obstacles to access credit in
concentrated banking market; nevertheless this effect is mitigate in countries where
there is less corruption and the legal system is efficient. In particular the negative
effect of bank concentration becomes not significant for countries with well
developed financial market.
Bonaccorsi di Patti and Dell’Arriccia (2004) test the effect that competition in
banking produce on firms creation, taking into account the information asymmetry.
Their analysis regards 103 Italian provinces for the period 1997-1999. They find a
bell-shaped relation between bank market power and non-financial firms creation;
the effect is positive and significant but for high level of bank power it become
negative and significant. Moreover this effect is heterogeneous across industries
The H-statistic measure the sum of the elasticities of the total revenue of the banks respect to the bank’s
input prices. If H < 0 there is monopoly; if H=1 there is perfect competition; if 0<H<1 there is monopolistic
competition
2
7
characterized by different degree of asymmetric information3. Bank competition is
more favourable to relatively more transparent industries. This result is consistent
with Rajan and Zingales (2001) theoretical analysis. A recent paper close to this is
Ratti at al. (2008) examining the effect of bank concentration on financial constraint
of firms’ investment decisions in 14 European countries between 1992-2005. The
authors find evidence that financial constraints are less severe in countries with
highly concentrated banking markets. If firms creation is dependent also on how
much the access to credit is easy, this results is consistent with Bonaccorsi di Patti
and Dell’Arriccia (2004). However, when Ratti el al. (2008) take into account the
measure of opaqueness4 the results differ. When bank concentration increases, there
is a reduction in credit constraints for firms in less opaque industries. This result are
consistent with the idea that market power increases bank’s incentive to produce
information on potential borrowers and credit is granted to high quality borrowers.
Finally, Deidda and Fattouh (2005) basing on Cetorelli and Gambera (2001) find
that bank concentration is detrimental for industries’ growth; nevertheless dividing
the sample in two subsamples, high-income countries and low-income countries,
they find that the effect is not yet significant for the former subsample, whereas
remain negative and significant for the latter.
3. METHODOLOGY
In this paper we investigate the effect of banking market structure on the industrial
sectors of Eastern and Central European countries. Rajan and Zingales’ (1998)
pioneer paper has been the reference point for the following empirical analysis
exploring the issue of financial market and growth. Indeed on this work the other
economists have modelled their empirical specification. Keeping on the topic of our
paper, in the empirical analysis a few different measures of bank concentration (or
competition) are implemented by authors that directly or indirectly test its effect on
industrial growth. Cetorelli and Gambera (2001), Cetorelli (2001) Beck et al. (2003),
Deidda and Fattouh (2005) and Ratti at al. (2008) use the sum of market share on
3
The measure of opaqueness used is based on the assumption that industry opaqueness is negatively
correlated with the relative importance of fixed and tangible assets in each industry. As much as the share of
these assets in the balance sheet is larger, more transparent is the industry. The authors use the ratio of gross total
assets to gross physical assets as indicator of opaqueness.
4
The authors follow Bonaccorsi di Patti and Dell’Arriccia (2004)
8
total asset of the three largest banks5. Claessens and Laeven (2004) adopted two
measure: the first one is the H-statistics and the second one is the same of the works
just mentioned. Furthermore Bonaccorsi di Patti and Dell’Arriccia (2004) implement
different measures6 among which two are similar to that used in the paper above: the
Herfindahl index of deposits and the share of deposits held by locally chartered
banks.
Following what is suggested by previous empirical works, we use as indicator of
bank concentration the sum of market share on total asset of the three largest banks.
In this way our results can be easily comparable with the results of papers cited.
Among the papers that takes into account the external financial dependence, some of
these7 use directly bank concentration as dependent variable in order to capture the
general effect of banking market structure on industries’ growth rate. Moreover an
interaction term between bank concentration and external financial dependence is
introduced to check evidence for an industry specific effect. Other papers 8 are
interested only in highlighting the industry specific effect, so it is regressed only the
interaction term. We find interesting to introduce in our specification both aspects
and check for general and industry specific effects.
Rajan and Zingales (1998) suggest that industries grow because the number of
enterprises rather than the enterprises size increases. So we deepen our analysis
decomposing the sources of growth with the aim to identify which is the prevalent
effect produced by banking market concentration. On this issue there is the
5
Cetorelli and Gambera (2001) implement also the measure of bank concentration using the sum of
market share on total asset of the five largest banks in order to check the robustness of theirs results. The
obtained results with this measure do not change.
6
Analyzing the Italian banking market structure, the authors use other measure of banking
concentration: the 1 minus the absolute change of the Herfindahl index; the sum of absolute values of annual
changes in market shares and the number of branches of banks not present in the market in year t-1 divided by
the total number of branches in year t.
7
See Cetorelli and Gambera (2001). Even if they do not consider external financial dependence,
Bonaccorsi di Patti and Dell’Arriccia (2004) introduce a measure of opaqueness; they consider the variable bank
competition and the interaction term between bank competition and opaqueness in order to capture the general
and the industry specific effect.
8
See Cetorelli (2001), Claessens and Laeven (2004), Ratti et al (2008). Claessens and Laeven (2004)
write the basic model estimated considering only the interaction term between bank competition and external
financial dependence but in some specifications, they include the competitiveness measure directly, starting from
the assumption that it could be considered as an indicator of the economic development, rather than an indicator
of the banking system specifically.
9
contribution of Cetorelli (2001) that tests the effect of banking market structure on
the average enterprises size. A paper of Rajan et al. (2001) find that countries that
have better institutional development, measured by the efficiency of their judicial
system, have larger firms. Further they find little evidence that richer countries or
countries with better developed capital markets have larger firms.
The main works focusing exactly on the effect on industrial growth produced by
banking market structure, i.e. Cetorelli and Gambera (2001) and Claessens and
Laeven (2004), conduct the analysis considering an heterogeneous sample of
countries. Considering evidence for a more homogeneous group of countries in
order to draw a good picture of the current state, we point out many aspect that
could enhance or reduce the general and the industry specific effect that bank
concentration produce on industrial growth. We consider clearly the financial
market development that the empirical literature regards as a fundamental concern;
further we investigate the role played by banking sector regulation taking into
account its different traits; we consider also the presence of foreign bank and state
owned bank; moreover we work on some aspect related to market contestability;
finally we control for many socioeconomics aspects.
In the specific, we specify our model following the methodology developed by
Rajan and Zingales (1998) and then taken up by Cetorelli and Gambera (2001) and
Claessens and Laeven (2004) analysing the effect of banking market structure on
industrial growth. The equation we estimate is:
Growth
in
value
added
.j;k 

Indicators
0
1Industry
j


Controls
2Country
k


of
Total
Manufactur
ing
v
.a
.j;k
3Fraction


Concentrat
ion
4Bank
k
External


Dependence
Concentrat
ion

5
j Bank
k
(1)


External
Dependence
Developmen
tk
6
j Financial

Error
j;k
1
0
where index j refers to industry and index k refers to country. The dependent
variable is the average annual real growth rate in value added of industry j in
country k for the period 2000-2006. As Rajan and Zingales (1998) suggest we
restrict our analysis to manufacturing industries to reduce the dependence on
country specific factors, i.e. natural resources.
Industry Indicators correct for industry specific effect and Country Controls are
included in order to avoid bad model specification, we introduce them once at a
time. We take into account a country indicator useful to capture country fixed effects
and the GDP per capita at the beginning of the period capture the convergence
effects. Moreover we consider the financial markets development; the regulatory
environment; the presence of foreign bank and some socio-economics aspects.
These variable are extensively explained in the following section describing data.
The variable Fraction of industries j in Total Manufacturing value added in country
k, at the beginning of the period considered, captures the industries specific
convergence effect. Industrial sectors that have already experienced a remarkable
growth rate in the past are expected to grow less in the future; consequently β3
would have a negative sign.
The most relevant explanatory variable of our analysis is Bank Concentration that
point out the effect that banking market structure produces on industrial growth. As
we have underlined in the previous section, the theoretical and empirical
contributions on the theme are contrasting and do not give an unambiguous answer
to the question. So we cannot make a prediction on the sign of β4.
Moreover there are two interaction terms. The first one is between Bank
Concentration and External Financial Dependence. The aim is to verify if industries
more dependent of external financial resources grow faster or slower in countries
with concentrated banking markets. Also in this case we cannot make a prediction
on β5 sign. The second interaction term is between bank concentration and financial
development. As Rajan and Zingales (1998, 2001) underline well developed
financial markets promote industrial growth, bur if financial markets are
1
1
underdeveloped the effect on growth is detrimental. So the sign of β6 depends on
financial market development level of countries considered.
4. DATA
Data on the number of enterprises come from the Industrial Statistic (INDSTAT)
database (Rev.3) realized by United Nations Industrial Development Organization
(UNIDO). INDSTAT data are classified according to the International Standard
Industrial Classification of All Economic Activities (ISIC) Rev. 3. We use data at a
mixed of 3 and 4 digit level. The analysis regards voices from 1511 to 3699 that
refer to manufacturing sectors. Firstly we use the producer or wholesale price index
by International Financial Statistic (IFS) to deflate value added and then we
calculate the average annual growth rate and the average size of enterprises. We
have data over the period 2000-2006, but for some countries there are not data for
the first year or the latest year. Starting from data available in INDSTAT, we
construct a sample of 11 countries of Central and Eastern Europe. The Table 1
reports the list of our sample’s countries and their level of Bank Concentration.
Data on External Financial Dependence of each industries come from the database
by Klapper et al (2006) in accordance to ISIC Rev. 3 at 2 digit level, but this
measure9 was initially developed by Rajan and Zingales (1998). These data are the
average for 1990-2000 and refer to the External Financial Dependence of USA
industries. Rajan e Zingales (1998) observe that there are technological reason why
an industry is more dependent on external resources and this aspect is valid for every
countries. Moreover the External Financial Dependence remains rather stable over
the years. Consequently USA industries financial dependence is a good proxy for
the other countries, furthermore the problem of endogeneity is a priori removed.
The GDP per capita at constant price in 2000 is obtained from World Development
Indicator (WDI) realized by the World Bank. With regards to financial development,
traditional measure is used. Domestic credit to private sector % GDP in 2000 refers
9
The External Financial Dependence is computed as the ratio of capital expenditure minus cash flow
from operation divided by capital expenditure; in practice it points out the fraction of capital expenditure not
financed by cash flow.
1
2
to financial resources provided to the private sector; it can be considered as a proxy
of bank development.
Bank concentration is the average over the period 2000-2006. This index is the sum
of the assets of three largest banks as a share of assets of all commercial banks and it
comes from A New Database of Financial Structure and Growth updated 2008
realized by Beck et al (2000). The Bank Regulation and Supervision database and
realized by Barth et al (2001) updated 2007 provide a lot of information on banking
sector. Starting from this database and following the methodological suggestion of
Barth et al (2001) we construct some indicators regarding bank industry.
To describe the regulatory environment we use the Activity Restriction that measure
the regulatory restrictiveness for activities that bank could conduct. The activities
are securities, insurance and real estate and they could be unrestricted, permitted,
restricted or prohibited. The indicator assigns higher value if restrictiveness is
greater and it is computed as the average of the data contained into the surveys of
the year 2001, 2003 and 2007.
The database Bank Regulation and Supervision provides also data on foreign banks.
We implemented the variable Foreign Bank Ownership, that is the fraction of the
banking system’s assets that are 50% or more foreign owned, and State-Owned
Banks: the fraction of the banking system’s assets that are 50% or more government
owned. We compute this variable again as the average of the data contained into the
survey of the year 2001, 2003 and 2007. Moreover using information on the number
of accepted application for commercial banking licences received by each countries
we realize a market contestability index.
5. ESTIMATION RESULTS
We have ran an OLS regression using 824 observations. The dependent variables is
the number of enterprices. The estimation has been done taking robust standard
errors as heteroskedasticity has been found.
1
3
Table 1: results of OLS estimation
variables
coefficients
const
2,121**
(0,5461)
Dummy Industry
1,460e-05
(1,196e-05)
Dummy Country
0,06277**
(0,01088)
Fraction of Total Manufacturing value added
-1,444**
(0,6332)
l_Pil_procapite
-0,2794**
(0,07261)
Bank_Developmen
0,3082**
(0,1099)
Bank_Concentrat
-3,674**
(0,4727)
Bank_Concentration*external fin dep
0,7810
(1,419)
Bank_development*ecternal fin dep
-0,03514
(0,3209)
Bank Conc*activity restriction
0,7979**
(0,1249)
Bankcon*activity*external fin dip
-0,2790
(0,3851)
Bankconc*foreign
2,708**
(0,3289)
Bankconc*foreign*external fin dep
-0,2324
(0,8737)
n
R2
R2adj
lnL
824
0,3046
0,2943
-350,734
5. CONCLUSIONS AND ISSUES FOR FURTHER RESEARCH
1
4
In this paper we have investigated the effect of concentration in the banking sector
on industrial growth. Using a dataset relating to Eastern and Central European
countries we have explored the effect of banking market structure on the different
industrial sectors. These countries are characterised by a lower level of development
of the financial sector and a more concentrated banking market than the traditionally
industrialised economies. Our empirical investigation yields evidence supporting the
hypothesis that, in order to promote industrial growth in transition economies, it is
necessary to stimulate competition in the banking industry and to improve the
development of alternative forms of financing such as capital markets in order to
accelerate growth.
6. Bibliografia
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Works Best?” University of Minnesota, Carlson School of Management; World Bank
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Development and Structure.” World Bank Economic Review 14, 597-605.
Beck, T., A. Demirgüç-Kunt, e V. Maksimovic. 2003. “Bank Competition, Financing
Obstacles and Access to Credit.” World Bank Policy Research Working Paper No.
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Bonaccorsi di Patti E. and G. dell'Ariccia. 2004. “Bank Competition and Firm creation.”
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Cetorelli, N. 2001. “Does Bank Concentration Lead to Concentration in Industrial
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Cetorelli,
Nicola
and
Peretto,
Pietro
F.,Oligopoly
Banking
and
Capital
Accumulation(December 2000). FRB of Chicago Working Paper No. 2000-12; Duke
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Economic Growth: Explaining the Links, Chapter 3, pp. 66-105, Palgrave
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Deidda L. and B. Fattouh, 2005. “Banks, Financial Markets and Growth Working Paper
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