Download public credit guarantees and sme finance

PUBLIC CREDIT GUARANTEES
AND SME FINANCE
Salvatore Zecchini
University of Tor Vergata
Rome
and
Marco Ventura
Institute for Studies and
Economic Analyses
ISAE, Rome
The World Bank Conference: 13-14 March 2008
Partial Credit Guarantee Schemes – Experiences and Lessons
Is State intervention or a State-funded guarantee scheme
an effective instrument to promote lending to small firms?
• Contrasting views in economic literature
• Against:
costly, financially unsustainable, no conclusive evidence of
additional lending to SMEs, no substitute for correction of system
failure.
• In favour:
new access to credit
lower funding cost
need of tight financial criteria.
• Our aim is to test the impact of a State-funded guarantee scheme on
SME financing in terms of credit additionality, borrowing costs,
financial sustainability.
The focus of our empirical tests is Italy’s Fund for
Guarantee to SME (SGS or Fund)
• We will present in turn:
• A brief review of the economic literature on the subject of SME
financial constraints
• Eligibility and selection criteria of the Fund
• Fund’s performance from the SME financing viewpoint
• Fund’s financial sustainability
• Our econometric approach as compared to that of other authors
• Econometric test of guarantee impact on SME borrowing cost
• Empirical evidence on credit additionality
• Conclusions: this public guarantee instrument has had a positive
effect on SME credit access and borrowing cost, albeit limited.
SME financial constraints in the economic literature and in
Italy
• Some empirical evidence shows financial constraints are inversely
related to firm size (Bagella-Becchetti-Caggese 2001)
• Start-up firms, young enterprises, smaller ones, innovative ones,
with fewer tangible assets and an uncertain track record are subject
to much tighter financial constraints than other firms, especially,
under the form of credit rationing by the banking system, BergerUdell, 1998.
• Small firms are subject to impact of imperfections in bank credit
market more than other firms, due to ex ante asymmetric information
between bank lenders and borrowers, agency problems, relatively
high evaluation and monitoring costs for the lender.
• The interest rate cannot often serve as a tool to distinguish good
borrowers from bad ones, since info asymmetries can lead to
adverse selection (Stiglitz-Weiss, 1981).
Under certain conditions, the provision of collateral can
lessen credit rationing and borrowing costs (Coco,2000).
•
Can the provision of outside guarantees be a tool to overcome market
imperfections and lack of inside collateral, thereby giving SMEs broader
access to bank financing?
•
The guarantee value is a function of length and cost of legal procedures, as
well as of the loan recovery rate.
•
Given financial market imperfections and institutional weaknesses,
Governments in general resort to various industrial policy tools to improve
credit allocation to the advantage of SMEs.
•
One of them is credit guarantees.
An outline of Italy’s guarantee system and the role of
mutually-based guarantee institutions and the Fund
•
•
•
•
Multi-pillar and multi-layer system, based on a mix of private and public
funds.
3 pillars: a) mutual guarantee institutions (MGI)
b) banks and other financial institutions
c) State- or Region Government-sponsored guarantee
Funds.
Multi-layer structure:
grassroots level = MGIs and banks
second level = second-tier MGIs (credit reinsurance) and regional
reinsurance institutions
third level = 3 State guarantee Funds for SME credit, namely SGS, Fund for
crafts credit, and Fund for Farm credit.
Italy’s MGI system is the largest one in Europe. About 600 MGI, 37 % ot
total outstanding guarantees in 2005 and 46 % of beneficiary SMEs.
Italy’s State Fund for Guarantee to SMEs
• In 2005, equity base was € 233.5 millions.
• In 6 years, € 4.6 billion of guaranteed loans, equal to 3% of total
lending to small firms that are eligible.
• Eligibility criteria:
- Eligibility
conditions
-Only small and medium size firms, as defined by EU regulations, and SME consortia.
-Sound economic and financial conditions.
-The following sectors are excluded: coal and steel, shipbuilding, synthetic fibres, automobile,
transport. Guarantee ceilings are applied to the following sectors: car components, food industry and
related trade.
- Guarantee
coverage rates
- In less developed areas: up to 80% loan for direct guarantees; up to 90% for MGIs’ guarantees, that
cannot, however, go beyond 80% loan.
- In rest of the country: up to 60% of loan for direct guarantees; up to 90% for MGIs’ guarantees, that
cannot, however, go beyond 60% loan.
- Fees
- No fee in the less developed areas.
- In areas in economic decline, once only: 0.125% of loan for micro firms; 0.125% for equity and
participatory debt, and 0.25% loans to small firms; 0.25% for equity and participatory debt, and 0.50%
of loans to medium firms and consortia of firms.
- In the rest of the country, once only: 0.25% of loan for micro firms; 0.25% for equity and
participatory debt, and 0.50% loans to small firms; 0.50% for equity and participatory debt, and 1.00%
of loans to medium firms and consortia of firms.
Types of
guarantee
-Direct guarantee to banks
-Counter-guarantee to mutual guarantee institutions
-Co-guarantee with MGIs
-On equity participation or participatory debt
Priority sectors
-MGIs
-Southern regions
-Women entrepreneurship
-Micro firms
-Start-up
-Digital economy firms
Nature of the
guarantee
-Subsidiary, after debt recovery procedure is completed.
-Since 2006, direct
Funding
-Annual allocations from State budget, and levied fees.
The economic performance of the Fund
• The Fund is run according to tight criteria
• Eligibility criteria lead to low rejection rate (83% of applications)
• Guarantee coverage rate was on average about 50 % of debt
principal, with a 25-88% dispersion range
• Some preference was given to disadvantaged groups (women in
business, micro firms)
• Manufacturing and construction industry received 71% of
guarantees
• Investment projects received 54% of total guarantee. But rising
share of guarantees against lending for working capital
• Loan maturity structure: concentrated on medium-term loans (48%)
• Regional distribution: industrial regions got 60%; South 26%
• Emphasis on counter-guaranteeing MGIs (61 % of total)
• Overall, significant degree of risk aversion, guarantees were driven
to a significant extent by credit supply institutions, support to mutual
credit guarantees .
Distribution by
Fund’s loan repayment
Guaranteed loans
Guaranteed loans
in default
SIZE:
100.00
100.00
100.00
- Medium-size firm
40,59
50,39
49.00
- Small-size firm
36,84
29,39
27.00
- Micro firm
22,45
20,22
24.00
- Consortia of firms
0.12
-
-
-
-
-
- Equity participation
0,19
4,51
35,56
- SMEs (with lower credit score)
25,43
36,86
24,44
- Women entrepreneurship
3,79
3,89
0
- Start-ups
11,76
12,75
24,44
- SMEs (with higher credit score)
28,82
19,13
4,44
- MGIs (top of the group)
29,49
22,86
11,11
- Micro credit
0,52
0
0
CATEGORIES OF FIRM:
MATURITY:
100.00
100.00
100.00
9,09
40,91
13,64
- Short-term loan
23,26
22,86
- Medium-term loan
48,18
49,92
- Long-term loan
28,37
22,55
- Equity participation
0,19
4,67
36,36
TYPE OF GUARANTEE:
100.00
100.00
100.0
- Direct guarantee
37,71
41,37
43.00
- Counter-guarantee
60,78
58,16
57.00
- Co-guarantee
1,52
0,47
0
ECONOMIC SECTOR
100.00
100.00
100.00
- Industry & Construction
70,00
74.00
85.00
- Tourism
11,14
11.00
10.00
- Trade & other services
17,98
15.00
5.00
BY AREAS:
100.00
100.00
100.00
- North-West
45,74
55,21
64.00
- North-East
14,31
13,53
2.00
- Centre
13,65
9,95
17.00
- South (Mezzogiorno)
26,30
21,31
17.00
Financial sustainability of the Fund
• The degree of financial sustainability is assessed through the
following equation
[1] L + A + I = F + O + S
where
L = loan losses
A = administration expenses
I = public debt service cost (cost of use of borrowed capital)
F = guarantee fees
O = other income, such as the return from the investment of
reserves
S = the amount of public subsidy to cover any losses.
The subsidy element is the balancing item that allows to avoid the
exhaustion of the capital base.
Financial performance
2000
2001
2002
2003
2004
Total
(Percentages)
Guarantee coverage ratio
(1)
55.78
53.94
54.77
48.90
44.91
50.16
Loan default rate (2)
0
0,47
1,36
1,51
3,63
1,83
Repayment /Guarantees
(3)
0
0
0.11
0.38
0.47
0.25
Loss/Loans (4)
0
0
0.06
0.19
0.21
0.12
Repayment rate (5)
0
0
4.30
12.29
5.80
6.81
• Fund’s financial performance is better than similar schemes in other
European countries (losses: 0.25% vs. 2-10% of guaranteed loan
portion)
• The default ratio is lower than that of Italy’s banking system (1.83%
vs. 5.89%)
• Small firms and micro firms generated less losses for the Fund than
medium-sized firms (49% of losses in medium-sized firms)
• Loan default rates appear as being an increasing function of the
loan size and guarantee size (following figure).
• Highest default rate is in the smallest loan class (up to €10,000), but
a relatively low loss rate, because of low guarantee coverage.
• 69% of defaults are among loans for working capital needs
• 59% of defaults happens after the first 2 years of the loan
• Regional distribution of defaults is heavily dependent on sectoral
distribution.
Default and loss rates by guarantee size (2000-2004)
(percentages and euro amounts)
3,5
3
2,5
2
1,5
1
0,5
0
€ 0 – 10000
100001 –
150001 –
200001 150000
200000
250000
ST loss rate MLT default rate MLT loss rate
10001 - 50000 50001 - 100000
ST default rate
250001 and
higher
Default and Loss composition by guarantee size (2000-2004)
(percentages and euro amounts )
ST defaults
100
ST credit losses
M-LT defaults
M-LT credit losses
90
80
70
60
50
40
30
20
10
0
€ 0 – 10000
10001 - 50000 50001 - 100000
100001 –
150000
150001 –
200000
200001 250000
250001 and
higher
Subsidy rate
S/G = (( L + A + I - F - O )/G ) * 100
namely,
0.25 + 0.39 + 0.47 (~ 0.66) - 0.35 - 0.012 = 0.75 (~ 0.94)
The subsidy rate was much higher for those enterprises that were
charged no fee: it is estimated to go on average up to 1.29% of the
guarantee.
Fees did not cover either losses or operating expenses. There was in
fact a current-account deficit averaging 0.28% per guarantee, that
prevented the scheme from breaking even.
Such a deficit (0.14% per euro of guarantee[1]) looks, however, very
low compared to the other State-funded subsidy schemes for
enterprises,
[1] This is the ratio of the deficit to the amount of guaranteed loans,
and is equal to the product of the deficit ratio by the guarantee
coverage ratio (tab. 3).
Approach to credit additionality and interest cost reduction
• To carry out quantitative tests of guarantee impact, reference to
empirical literature on the presence of tighter financial constraints for
some groupings of firms and on their underlying factors.
• Applications to models of investment demand together with notion of
capital mkt imperfections and disparities in firms’ access to credit
mkt (Hubbard 1998).
• Cash flow sensitivity of investment demand (Fazzari et al. 1988,
Kaplan Zingales 1997).
• Credit rationing: some firms’ inability to get credit, even if they would
pay higher interest rate (Stliglits Weiss 1981)
• Attempts to estimate impact of Gvt credit programmes (Gale,
Boocock Shariff, Riding Haines)
• Novelty of our approach.
1. Is the Fund effective?
2. What happens once the guarantee expires?
Definition of effectiveness of the Fund:
 Guaranteed firms are charged lower financial costs
once guaranteed
and/or
 Guaranteed firms receive a greater amount of bank
loans. Additionality or incrementality effect.
Answer to question 1:
Yes it is, the Fund is effective
Answer to question 2:
Puzzling evidence formerly guaranteed firms are
charged lower financial costs, but they are not
granted higher quantity of bank loans.
Further investigation
HOW TO REACH THESE ANSWERS
Before giving any sensible answer to qn. 1 & 2
one must rule out the
ANTICIPATION EFFECT:
The Fund systematically guarantees better
performers, therefore we want to make sure that:
Guaranteed firms are not charged lower
financial costs BEFORE receiving the
guarantee
and/or
Guaranteed firms do not receive higher
quantity of loans BEFORE receiving the
guarantee
(1) rt    1x1t   2x2t  3x3t  dt n  ut
where
rt Nx1 vector of (log of) financial costs in 1999;
x1t Nx1 vector of (log of) number of employees in
1999;
x2t Nx1 vector of (log of) sales in 1999;
x3t Nx1 vector of (log of) bank debt in 1999;
dt+n dummy variables, that takes on value of 1 if
the firm is guaranteed at time t+n (where t=1999)
and to 0 otherwise;
ut error term.
Table 4. Estimates of the  parameter using data prior to 1999
for firms receiving the guarantee in the following years (cost effect)
Guaran
tee
years
2000
OLS
2001
OLS
2002
IV
2003
OLS
2004
OLS
2005
OLS
2006
OLS

0.185* 0.167* 0.180* 0.149* 0.159* 0.163* 0.136**
**
**
**
**
**
**
*
(0.070) (0.039) (0.042) (0.004) (0.036) (0.034) (0.023)
R2
0.654
Prob
0.00
(F-Stat)
Instrum
ents
0.654
0.654
0.654
0.654
0.654
0.654
0.00
0.00
0.00
0.00
0.00
0.00
dt+1 dt+2
dt+4 dt+5
Standard errors in parenthesis. “***”, “**” and “*” indicate 1%, 5% and 10%
significance levels, respectively. Different regressions are reported in each column by
changing the dummy in order to account for the firms guaranteed in different years. For
instance, in column 3 we report the estimated  coefficient related to the 1999
financing cost for firms that received a guarantee in 2001.
 The dummy coefficient is always positive
and significant: =>
 guaranteed firms were not better performers
in terms of cost, they were charged higher
financial costs in 1999, wrt other SMEs
(2) y t    1x1t   2x2t  3x3t  dt n  ut
where
yt Nx1 vector of (log of) bank debt in 1999;
x1t Nx1 vector of (log of) number of employees in
1999;
x2t Nx1 vector of (log of) sales in 1999;
x3t Nx1 vector of (log of) total assets in 1999;
dt+n dummy variables, that takes on value of 1 if
the firm is guaranteed at time t+n
(where t=1999) and to 0 otherwise;
ut error term.
Table 5. Estimates of the  parameter using data prior to 1999
for firms receiving the guarantee in the following years (additionality)
2000
IV

2001
IV
2002
IV
-5.83*** -6.04*** -8.15***
(0.857) (1.399) (1.737)
2003
IV
2004
IV
-14.21*** -23.2***
(2.823)
(5.613)
2005
IV
2006
IV
2.9
( 1.79)
7.81***
(2.123)
R2
0.975
0.977
0.974
0.962
0.943
0.986
0.982
Prob
(FStat)
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Instru
ments
dt+2 dt+3
dt+1 dt+3
dt+1 dt+2
dt+3 dt+4
dt+4 dt+5
dt+1 dt+2
dt+3 dt+4
dt+1 dt+2
dt+3
Standard errors in parenthesis. “***”, “**” and “*” indicate 1%, 5% and 10%
significance levels, respectively. Different regressions are reported in each column by
changing the dummy in order to account for the firms guaranteed in different years. For
instance, in column 3 we report the estimated  coefficient related to the 1999 bank
debt for firms that received a guarantee in 2001.
EVIDENCE
The dummy coefficient, δ, is negative and significant
for 2000-2004 Guaranteed firms in those years received
a lower quantity of bank loans, i.e. they were not better
performers,
δ is not significantly different from zero for 2005.
Guaranteed firms in that year did not receive a higher
quantity of bank loans, i.e. they were not better
performers,
δ is positive and significant for 2006 Guaranteed
firms in 2006 were better performers, we rule them out
from the sample otherwise we cannot single out the
causal effect of the Fund on SMEs.
ESTIMATION STRATEGY
To isolate the causal effect of the Fund we use the DID estimator:
 once defined an appropriate outcome variable the DID
compares the average time difference of the treated to the
average time difference of the control group.
 We exploit a twofold counterfactual
1. guaranteed firms before receiving the guarantee, 1999
2. non guaranteed firms
When the anticipation effect did not occur the
underlying hypothesis of the DID are satisfied.
We can isolate the causal effect of the Fund on
the treated unit ATT
The proves of answers to questions 1 and 2:
Table 6 - DID estimate of the causal effect of the guarantee on the (log of)
financial costs 1999-2005 (cost effect)
Year 1999

#
employ
ees
Sales
Post 1999
Bank
debt
#
employ
ees
Sales
Bank
debt
δ
0.016
(0.01)
0.125
(0.287)
0.107
***
(0.014)
0.283
***
(0.033)
0.425
***
(0.040)
0.068
***
(0.013)
0.298
***
(0.025)
0.468
***
(0.02)
4.652
***
(0.646)
0.048
**
(0.020)
0.362
***
(0.033)
0.143
***
(0.043)
-0.027
(0.021)
0.514
***
(0.03)
0.052
(0.05)
Expir
ed
0.01
(0.02)
Inv.
Mills
1.884
***
(0.241)
R2
Fstat
0.94
0.00
0.94
0.00
Robust standard errors in parenthesis. “***”, “**” and “*” indicate 1%, 5% and 10%
significance levels, respectively. S.E. are computed through the SUR (PCSE) coefficient
covariance matrix to account for both cross-section heteroskedasticity and correlation.
 The dummy coefficient is not significantly different
from zero, therefore financial costs charged to
guaranteed SMEs are in line with non guaranteed.
 Recall: before the Fund started operating guaranteed
firms were charged higher financial costs, other
things being equal. See anticipation effect.
 The effect persists once the guarantee expires
Table 6 - DID estimate of the causal effect of the guarantee on the (log of)
bank debt 1999-2005 (additionality effect)
Year 1999

#
employe
es
Sales
Post 1999
Total
asset
#
employe
es
Sales
Total
asset
δ
0.129
***
(0.02)
-2.302
***
(0.383)
0.013
(0.032)
-0.005
(0.060)
1.120
***
(0.042)
0.051*
(0.026)
-0.046
(0.038)
1.111
***
(0.03)
-2.647
***
(0.500)
0.088*
(0.047)
-0.092*
(0.050)
1.225
***
(0.06)
0.033
(0.054)
-0.107
**
(0.046)
1.223
***
(0.03)
Expired
-0.241
***
(0.07)
R2
Fstat
0.86
0.00
0.89
0.00
Robust standard errors in parenthesis. “***”, “**” and “*” indicate 1%, 5% and 10%
significance levels, respectively. S.E. are computed through the SUR (PCSE) coefficient
covariance matrix to account for both cross-section heteroskedasticity and correlation.
 The dummy coefficient is positive and significant, =>
guaranteed firms are granted a higher quantity of bank
loans, 13.77% computed as [exp(δ)-1]*100. In the same
direction Bocock Sharif (2005), Gale (1991), Riding
Madill Haines (2006).
 Recall: before the Fund started operating guaranteed
firms were granted a lower quantity of bank loans (see
estimates of anticipation effect for additionality).
 Once the guarantee expires no traces are left, guaranteed
SMEs go back to the previous situation of lower bank
loans.
SUMMING UP:
 THE FUND HAS BEEN PROVED TO BE
EFFECTIVE IN:
1. DECREASING FINANCIAL COSTS FOR
GUARANTEED FIRMS
2. INCREASING THE AMOUNT OF BANK
LOANS
 ONCE THE GUARANTEE EXPIRES
1. THERE ARE TRACES OF PERSISTENCE IN
THE COST EFFECT, WHILE
2. THERE IS NO EVIDENCE OF PERSISTENCE IN
THE ADDITIONALITY EFFECT.