J. Service Science & Management, 2009, 2: 378-383
doi:10.4236/jssm.2009.24045 Published Online December 2009 (www.SciRP.org/journal/jssm)
Informal Financing of Small – Medium Enterprise
Sector: The Case of Greece
Panagiotis Petrakis 1,*, Konstantinos Eleftheriou 2
1Department of Economics, University of Athens, Stadiou Street, Athens, Greece; 2D epartment of Economics, University of Piraeus,
Karaoli & Dimitriou St reet, Piraeus, Greece.
Received July 17, 2009; revised August 23, 2009; accepted September 29, 2009.
ABSTRACT
In this paper, we attempt to find a “ channel ” through which Greek economy can exhibit a relative “ resistance ” in a
credit crunch. For this purpose, we specify an error correction model so as to test the relation
ship between corpo-
rate bank loans and commercial papers comprised of
post-dated cheques and bills of exchange. The results show that
corporate
bank loans and cheques - bills of exchange are substitutes. This finding combined with the fact that in
Greece, the issuance of these papers is positively connected with the informal economic activity which in turn rises dur-
ing economic downturns, has a strong economic implication regarding
the ability of Greek economy to partly “ amor-
tize
” the shocks connected with the current financial crisis.
Keywords: Corporate Finance, Credit Crunch, Shadow Financing
1. Introduction
Is there an interrelation betw een bank loans and commer-
cial papers (cheques, bills of exchange) as a source of ex-
ternal debt financing for firms in Greek economy, and if
yes, are they substitutes or complements? Which is the
economic intuition between such an interrelation and can
it offer a safety net to the current credit crunch? These are
the main crucial questions we try to answer in this paper.
One of the main factors which determine the level of
“resistency” of an
economy in a bank credit crunch is the
ability of the economic system to cre
ate multiple “chan-
nels” of financing and exploit them properly. In modern
economies, firms have a variety of debt financing tools at
their disposal. However, each of these tools has a different
rank in firm’s preferences. According to the traditional
“pecking order” hypothesis of corporate finance [1], bor-
rowing firms prefer to finance their debts through external
resources (securities, bank loans) rather than equity issu-
ance. Equity issuance is less preferred since the funds it
provides are generally limited by the scale of expenditures
(dividends) and it is considered by investors, as a “bad”
signal for the economic performance and viability of the
firm. Hence, firms mainly choose between bank b or ro w in g
and debt securities issuance, when it comes to finance
the ir co rp orate expenditures. Greenspan [2,3], emphasized
the importance of such a choice under a credit crisis re-
gime. More specifically, he suggested that there is a rate of
substitutionality between the market of bank loans and that
of bonds which smoo th es th e n ega tive imp act tha t a f ina n-
cial crisis has o n real econo my. On th e o th er h an d , Ho lm-
strom and Tirole [4], stressed that “multiple avenues of
intermediation” (availability of t he aforementioned sources
of external debt financing) for corporations are character-
ized by complementarity. Their analysis is based on a
principal-agent prob lem with monitoring costs. When the
supply of intermediary capital falls due to a credit crunch,
the q uantity of informed (banks) finance which is available
to firms decreases. This also means that less uninformed
(securities) finance can be attracted since the level of moni-
toring undertaken is lower1. The findings of Holmstrom and
Tirole [4], were empirically verified for U.S. economy by
Davis and Ioannidis [ 5].
Gertler and Gilchrist [6], argu ed that the salutar y effects
stemming from the substitutionality between the main al-
ternative “chan nels” of corpor ate debt financing are limited
when the market is dominated by small firms. This occurs,
since large firms have access to short-term sources of
redit (e.g. commercial
papers market) unavailable to
*This paper is based on an ongoing research project titled: “Economic
Growth and Development in the Greek Economy”. We would like to
thank an anonymous referee for useful comments and suggestions.
Any remaining errors are ours.
1Uninformed investors are less willing to offer their funds when the
level of monitoring connected with the informed finance is low. c

Informal Financing of Small – Medium Enterprise Sector: The Case of Greece379
Table 1. Greek commercial papers in circulation and bank finance (in million euros)
Year Bounced
cheques Unpaid bills of exchange Total Credit
delinquency
rates (%)
Nominal estimated
amount of cheques and
bills of exchange in
circulation
Yearly adjustment
of (D) Nominal domestic MFI loans to domestic enterprises
(A) (B) (A)+(B) (C) (D) (E)=(D)/3 (F)
2004 1024.8 169.2 1194 2.64 45227.3 15075.8 4587
2005 1464.4 180.7 1645.1 3.04 54115.1 18038.4 5716.6
2006 1202.1 188.1 1390.2 4.02 34582.1 11527.4 5376.9
2007 921.9 177.5 1099.4 3.57 30795.5 10265.2 13095.3
2008 1291.3 170.2 1461.5 3.73 39182.3 13060.8 15488.7
small firms and therefore they respond more effectively
to a cash flow squeeze. In Greece, the market of com-
merc ial pap ers as a source of short-term financing has not
been adequately developed. Instead, there is a market of
post-dated cheques2 and bills of exchange. The maturity
period of a post-dated cheque is not the date of issue but
the due date specified by
the drawer.
Transactions through post-dated cheques involve high
risk for the payee. Therefore, the operation of this
“quasi-commercial” papers market is based on long-term
relationships (mutual trust) between engaged parties. This
characteristic can be proven quite beneficial for an
economy during business cycle downturns. According to
a survey conducted by International Monetary Fund in
2006 [7], countries with a higher degree of relation-
ship-based lending (low degree of arm’s length transac-
tions) may experience a less sharp decrease in the level of
nonresidential business fixed investments during a
downward phase of the business cycle. The rationale be-
hind this conclusion is that the lender gives a greater
weight to the long-run gains from maintaining an existing
relationship with a borrower and thus he provides a
short-term assurance that financing will be available in case
of a credit crisis. Another advantage of the market of
post-dated cheques and bills of exchange compared with the
traditional market of commercial papers is that small firms
have ac cess to it. On e more intere sting featur e of the Greek
market of commercial papers is its positive relation with
the size of shadow economy. The fact that post-dated
cheque s can b e endors ed an d tra n sf err ed by th e pa yee me a n s
that the “traces” of a trans action canno t be tracked very eas-
ily by tax authorities. Hence, firms have an incentive to
evade taxes by issuing iconic invoices. A recent work by
Schneider [8], shows that Greece had and still has the
largest informal economy between 21 OECD countries
over the last twenty years3.
This result is an indication for the expected large size of
the Greek “quasi-commercial” papers market. The above
analysis implies that if there is substitutionality between
bank loans and post-dated cheques an d bills of exchange,
then Greek economy may have an arrow left in its quiver
against the current financial crisis.
The rest of the paper is organized as follows. In the
next section we set
out our empirical methodology and
give our main empirical results. Section 3 concludes.
2. Quantitative Analysis
In order to conduct our analysis, we obtained monthly
data over 2004-2008
(more precisely from 2004/07 to
2008/12) for: 1) bounced cheques and unpaid bills of ex-
change (in million euros) from Hellenic Credit Profile Da-
tabank (Tire
sias Bank Information Systems S.A.), 2)
Consumer Price Index (CPI) from
General Secretariat of
National Statistical Service of Greece, 3) outstanding
balances (in million euros) of domestic Monetary Finan-
cial Institut ions (MFI) loans to domestic enterprises and 4)
interest rates on euro-denominated loans w it h ou t a d e f in e d
maturity by domestic MFIs to euro area non-financial
corporations. Data for 3) and 4) were obtained from Bank
of Greece (Bulletin of Conjunc tural Indic a tors).
2
Post-dated cheques facilitate the interindustry financial relations with-
out being recognized as a formal financial instrument, since che-
ques are officially defined as a bill of exchange payable on de-
mand. This kind of financial instruments usually “covers” un-
der-the-table real sector financial transactions (shadow economy
transactions).
3
Schneider used the Multiple industries and multiple courses proce-
dure (MIMIC) (for an overview see Aigner et. al [9]) and currency
demand approach (see Schneider [10]) in order to obtain his estimates
about the size of the shadow economy.
Moreover, we used firms’ credit delinquency rates from
ICAP Group, in order to calculate the value of commercial
papers (cheques and bills of exchange) in circulation4.
4
We assume that firms’ credit delinquency rate is a good approxima-
tion of the percentage of bounced cheques and unpaid bills of ex-
change to commercial papers in circulation.

Informal Financing of Small – Medium Enterprise Sector: The Case of Greece 380
Table 2. Summary statistics: Monthly RL, RCP and RR data from July 2004 to December 2008
Summary statistics RL RCP RR
No. of observations 54 54 54
Mean 0.746884 1.135214 0.038768
Median 0.620918 1.020567 0.038218
Maximum 4.184875 3.069930 0.052121
Minimum -2.276165 0.608280 0.026796
Stan dar d de via t io n 1.102762 0.450345 0.006904
Skewness 0.409230 1.772342 0.158600
Kurtosis 4.146723 7.768323 2.069039
Jarque-Bera 4.465909 79.42880 2.176434
J-B P-valuey 0.107211 0.000000 0.336817
y J-B P-value is the probability that a Jarque-Bera statistic exceeds (in
absolute value) the observed value
under the null hypothesis of a nor mal distribution. The negative minimum value of RL implies that the
amount of new loans given is less than the part of the past loans which are paid off.
Table 3. Stationarity tests
ADF test ( lags)
Variable s in le vels
RL -2.93 (2)
RCP -0.52 (5)
RR -2.59 (3)
Variables in first difference
RL -12.14 *** (1)
RCP -5.92*** (2)
RR -6.65 *** (0)
Notes: Boldface values denote sampling evidence in favour of unit roots. *** Signifies rejection of the unit
root hypothesis at the 1% level of significance. The numbers in parentheses for the ADF test are the op timal
lag lengths, which are determined using AIC (Akaike Information Criterion). Trend and constant were included
in the test equation.
Three variables are constructed from the above data: RL,
RCP and RR, where RL and RCP are the real new do-
mestic MFI loans to domestic enterprises (this variable is
constructed by taking
the first differences of 3) and de-
flating by the CPI) and the real est imated
amount of new
cheques and bills of exchange issued each month5 respec-
tively. RR denotes the real interest rate on RL (RR is de-
rived by subtracting inflation rate fr om 4 ) . In fl at io n r at e is
derived by the use of CPI). The variables RL and RCP
are expressed in billion euros. In Table 1, we present a
comparison of the two alternative sources of firm’s fi-
nancing examined in this paper; bank loans and the “paral-
lel financial system” of posted-dated cheques and bills of
exchange. As we note from Table 1, the Greek “quasi-
commercial” papers market plays a n importa nt ro l e (a lmost
the same as bank loans) in corporate financing. Mo reo ver ,
it can be easily ascertained from Table 1, that the most
important component of the Greek commercial papers
market is that of cheques.
Table 2 shows the descriptive statistics of the variables
under consideration. For RL and RR series displayed in
Table 2, we do not reject the hypothesis of normal distri-
bution at the 10% significance level. The first step of our
analysis is to test whether RL, RCP and RR are stationary.
Table 3 reports unit root test statistics of the augmented
Dickey and Fuller test [11]. The results in Table 3, indi-
cate that all series are non-stationary and contain a unit
root. In order to examine whether they are integrated of
order one, I(1), we perform the augmented Dickey-Fuller
(ADF) test on first differences. The results suggest that all
variables are stationary in first differences.
Engle and Granger [12] argued that even if a set of eco-
nomic series is not stationary, there may exists some lin-
ear combinations of the variables that are stationary. If
the separate series are I(1) (i.e. non-stationary in their lev-
els but stationary in their first differences) but a linear
combination of them is I(0), then these series are cointe-
grated. If series are cointegrated, an error correction model
(ECM) is appropriate for modeling their relation, as sug-
gested by Engle and Granger. More specifically, if a
5
We get RCP by dividing 1) with the product of firms’ credit de-
linquency rates and CPI and adjusting the result in yearly basis (the
amount of cheques and bills in circulation needs to be adjusted in
yearly basis, since it is a common practice for the bearer of a
cheque to accept a new cheque (bill) of the same amount instead
of cashing it in, when the maturity period ends. Hence, if we as-
sume that the mean maturity period of a post-dated cheque (bill) is
four months, we have to divide the total amount of Greek commer-
cial papers by three).

Informal Financing of Small – Medium Enterprise Sector: The Case of Greece381
t
u
group of variables is non-stationary (random walks), then
by regressing one variable against the others can lead to
spurious results in the sense that conventional signifi-
cance tests will tend to indicate a relationship between
the variables when in fact none exists. This problem can
be solved if we use in our modeling process the first dif-
ferences of the above variables after verifying that these
differences are stationary (integrated of order one, I(1),
variables). However, even though this approach is correct
in the context of univariate modeling [e.g. Autoregres-
sive – Moving Average (ARMA) processes], it is inad-
visable when we try to examine the relationship between
variables. The main drawback of this, in other respects,
statistically valid app roach is th at it has no long-run solu-
tion (common problem in pure first difference models).
More specifically, one definition of the long run that is
employed in econometrics implies that variables have
converged upon some long term values and are no longer
changing. Hence, all the first difference terms will be
zero and by simply regressing the one against the others
gives results which say nothing about whether the vari-
ables under consideration have an equilibrium relation-
ship. However, this problem can be overcome by using a
combination of the first differenced and lagged levels of
cointegrated variables. This formulation is known as an
error correction model. Through this model, we can ex-
amine the short run dynamic relationship between the
variables under consideration by taking into account their
deviations from their equilibrium/long run relationship
(residuals of the cointegrating regression).
In order to test for cointegration, we use the maximum
likelihood methodology proposed by Johansen [13]. Ac-
cording to Johansen a Vector Autoregression (VAR)
model of order , can be written as follows: p
1
()
ttpt
YLYY



  (1)
where is the vector of RL , RCP and RR ,
t
Y
12
(, 3 , )

 


, ()L

is a polynomial of order 1p

,
is a vector of independent Gaussian errors with zero
mean and covariance matrix , is th e first difference
operator and
t
u
 

is a matr ix of the form



 where

and

are 3×r matrices each with rank r, with

being the matrix of the r cointegrating vectors (i.e. the
columns of

represent the r cointegrating relations)
and

being the matrix of adjustment coefficients. As
stated above, the existence of cointegration has implica-
tions about the way we should model the relationships
between RL and RCP, RR.
The results of Johansen cointegration test are pre-
sen ted in Tab le 4. S ince Johansen’s procedure is sensitive
to the lag length of the Vector Autoregression (VAR)
(Banerjee et al. [14]), we determine the lag length by us-
ing the appropriate criteria.
The max eigenvalue statistic supports the existence of
one cointegrating vector. More specifically, the cointe-
grating equation is:
1.23 35.52RLRCP RR

 (2)
This finding implies that there is a long run equilibrium
relat ionship betw een RL, RCP and RR. Equation (2) indi-
cates that the real value of newly issued Greek commer-
cial papers in circulation and the real interest rates of
corporate bank loans are negatively correlated to the real
amount of corporate bank loans (in the long-run), with the
estimated coefficients of -1.23 and -35.52, respectively.
Table 4. Johansen cointegration test
Hypothesized # of cointegrated equations (r) Max eigenvalue statistic Critical values at 5%
None 31.99**21.13
At most 1 4.4514.26
At most 2 2.883.84
Note: ** Indicates the rejection of the hypothesis about the number of cointegrated equations at the 5% level. The
sequential modified LR test statistic, the final prediction error (FPE) and the Schwarz information criterion indi-
cate that the optimal lag length of the VAR is equal to one. Moreover, the VAR residual Portmanteau test for
autocorrelations does not reject the null hypothesis of no r e sidual aut ocorrelations.
Table 5. TSLS estimates of the ECM
Parameter Coefficient t-value

-0.075 -0.364
0

-2.66** -2.049
0

-56.92 -0.39
1

-1.2*** -7.026
2
R
0.56
Note: *** and ** denote statistical significance at 1% and 5%, respectively. The following series were used as instru-
ments: constant.
161214 121 12
,, ,,,,,
tttttt tt
ECT ECT ECTRCPRCPRLRRRR
 
 ,

Informal Financing of Small – Medium Enterprise Sector: The Case of Greece 382
Table 6. Diagnostic tests
Value of test statistic P-value
JB 5.295 [0.071]
Reset test 0.455 [0.504]
Hansen’ s J statistic test 5.449 [0.363]
1
/2
L
MLM test 0.071/1.212 [0.789/0.545]
BDS test
Dimension
2 -0.0053 [0.7908]
3 -0.01389 [0.2847]
4 -0.00601 [0.5855]
5 -0.00222 [0.8633]
6 -0.00329 [0.3745]
Note: Figures in brackets represent asymptotic P – values associated with the tests. JB denotes the Jarque-Bera normality
test of errors. The Reset test tests the null hypothesis of functional form misspecification. 1 /2
L
MLMis the Lagrange
multiplier test for first and second order serial correlation (under the null there is no serial correlation in the residuals up
to the specified order). Hansen’ s J statistic test is a general version of the Sargan test, a test of overidentifying restric-
tions (under the null hypothesis the overidentifying restrictions are satisfied). For the relationship between J statistic and
Sargan test see Murray [15]. Finally the BDS [16] test tests the null hypothesis that the errors are independently and
identically distributed (In our test we set the value of distance between the pair of the elements of a time series, equal to
0.7. Since our sample is relatively small, we use boo tstrap P - values ).
As RL, RCP and RR are cointegrated, it is necessary to
specify an ECM in order to examine the short-run rela-
tionship of these variables. We specify an error correction
model of the followi ng type:
110 0ttt
RLECTRCP RRtt



 
t = 1, 2, …. T (3)
where ECT is the error correction term and t

is a dis-
turbance term. Since and current values
appear in the above equation, Ordinary Least Squares
(OLS) estimation produces inconsistent estimators. In
or de r t o o ve r come this problem, w e apply a two stag e leas t
squares (TSLS) estimation procedure. Table 5 presents the
TSLS estimates of Equation (3). Moreover, we check the
specification of our estimated model by performing various
diagnostic tests. These tests are reported in Table 6. Our
results indicate that th e ECM seems to be quite well speci-
fied and free from specification error.
t
RCPt RR
As we note from Table 5, the coefficient of the ECT has
the correct sign, is statistically significant and is rather
large indicating rapid adjustment of RL, RCP and RR to
the proceeding imbalance () in a short ru n period.
In order to investigate the relationship between the provi-
sion of corpora te bank loans and issuance of cheques and
bills, we turn our attention to the short-run elasticity .
1t
ECT 
Table 5, indicates that γ0 is negative and statistically sig-
nificant. More specifically, if the issuance of new Greek
commercial papers increases by 100 million euros then
the provision of corporate bank loans decreases, ceteris
paribus, by 266 million euros within a month. This find-
ing implies that there is substitutionality between bank
loans and post-d ated cheques and bills of exch ange. If we
take into consideration that during a credit crunch, there
are bank credit shortages, there is a tendency for informal
economy to increase [17] and the fact that (as mentioned
above) there is a positive relation between the size of Greek
commercial papers market and that of shadow economy,
then we conclude that Greek economy may alleviate the
negative impact of economic downturns caused by finan-
cial crisis.
3. Conclusions and Policy Implications
In our analysis, we showed that the Greek market of cheques
and bills of exchange can serve as a substitute for bank
loans. By combining this result with the distinctiveness in
the structure of the commercial papers market in Greece,
whi ch allows small firms to have access to short-term fund-
ing and the close connection of the size of this market with
that of informal economy, we can argue that Greek economy
can partly “amortize” the shocks connected with the current
financial crisis. Thus, monetary policy exhibits only indi-
rect effects on real enterprise sector. In case of an interest
rate fall, someone would expect that the positive effects
will find the way out to the real sector. On the other hand,
when interest rates rise during a credit crunch due to the
segmentation of the financial sector (low interbank and
interindustry trustiness), the enterprise sector will substi-
tute the absence of financial credit with interindustry fi-
nancing. Therefore, the IMF argument, that economies with
low degree of arm’s length transactions can smooth the
negative credit crunch effects and regenerate economic
activity during the easing of a credit crisis, is confi rmed.
The main deficiency of our analysis is that, although we

Informal Financing of Small – Medium Enterprise Sector: The Case of Greece383
have developed our arguments about the positive relation
be t w e e n Greek market of ch eques and b ills of exch ange a n d
informal economic activity by citing the appropriate refer-
ences, we have not explicitly included the underground
economy in our analysis. The estimation and the inclusion
of a variable indicating t he size of the informal economy in
our model can further enhance the robustness of our ana-
lytical results. Moreover, the use of dummy variables
which will capture the relevant effects during periods of
economic turbulence and the expansion of o ur dat a set so as
to include the latest available data, will also reinforce our
conclusions. All these issues can be considered as topics
for future research.
REFERENCES
[1] S. Myers, “The capital structure puzzle,” Journal of Fi-
nance, Vol. 39, pp. 575–592, 1984.
[2] A. Greenspan, “Do efficient financial markets mitigate fi-
nancial crises?” Speech to the Financial Markets Conference
of the Federal Reserv e Bank of Atlan ta, 1999.
[3] A. Greenspan, “Global challenges,” Speech to the Financial
Crisis Conference, C o u n c il on Foreign Relations, New York,
2000.
[4] B. Holmstrom and J. Tirole, “Financial intermediation,
loanable funds, and the real sector,” The Quarterly Journal
of Economics, Vol. 112, pp. 663–691, 1997.
[5] P. Davis and C. Ioannidis, “External financing of US cor-
porations: Are loans and securities complements or substi-
tutes?” Economics and Finance Discussion Papers, Brunel
Univ er si t y, 2004.
[6] M. Gertler and S. Gilchrist, “Monetary policy, business
cycles, and the beha vi or of sma ll man ufact uri ng fi rms, ” Th e
Quarterly Journal of Economics, Vol. 109, pp. 309–340,
1994.
[7] World Economic Outlook, “How do financial systems
affect economic cycles?” International Monetary Fund,
2006.
[8] F. Schneider, “The size of the shadow economy in 21
OECD countries (in % of ‘official’ GDP) using the
MIMIC and currency demand approach: From 1989/90 to
2009,” Working paper, Johannes Kepler University, 2009,
(http://www.economics.unilinz.ac.at/members/Schneider/f
iles/publications/ShadowEconomy21OECD_2009.pdf).
[9] D. Aigner, F. Schneider, and D. Ghosh, “Me and my
shadow: Es timating the size of the US hidden economy
from time series data,” In
W. A. Barnett, E. R. Berndt,
and H. White, (edition), Dynamic Econometric Modeling,
Cambridge University Press, Cambridge (Mass.), pp.
224–243, 1988.
[10] F. Schneider, “Size and measurement of the informal
economy in 110 countries around the world,” The World
Bank: Rapid Response Unit, Washington D.C., 2002.
[11] D. A. Dickey and A. M. Fuller, “Likelihood ratio statistics
for autoregressive time series with a unit root,” Economet-
rica, Vol. 49, pp. 1057–1072, 1981.
[12] R. F. Engle and C. W. G. Granger, “Co-integration and er-
ror correction representation, estimation and testing,”
Econometrica, Vol. 55, pp. 251–276, 1987.
[13] S. Johansen, “Statistical analysis of cointegration vec-
tors,” Journal of Economic Dynamics and Control, Vol.
12, pp. 231–254, 1988.
[14] A. Banerjee, J. J. Dolado, F. D. Hendry, and G. W. Smith,
“Exploring equilibrium relations in econometrics through
state models: So me monte carlo evidence,” Oxford Bulletin
of Economics and Statistics, Vol. 48, pp. 253–278, 1986.
[15] M. Murray, “Avoiding invalid instruments and coping
with weak instruments,” Journal of Economic Perspec-
tives, Vol. 20, pp. 111–132, 2006.
[16] W. A. Brock, W. Dechert, and J. Scheinkman, “A Test for
independence based on the correlation dimension,” Eco-
nometrics Reviews, Vol. 15, pp. 197–235, 1996.
[17] The Economist, “The black market: Notes from the un-
derground”, 2 April 2009.