Optimal Credit Guarantee Scheme and SME Finance in Asia

Farhad Taghizadeh-Hesary, Ph.D.Assist. Professor, Waseda University, Tokyo, Japan

Visiting Professor, Keio University, Tokyo, Japan

Naoyuki Yoshino, Ph.D.Dean & CEO, ADBI

Professor Emeritus, Keio University, Japan

LEVERAGING SME FINANCE THROUGH VALUE CHAINSIN THE CAREC LANDLOCKED ECONOMIES,

ADB-ADBI-CAREC INSTITUTENazarbayev University, Astana, Kazakhstan

Nov 29, 2018

The views expressed in this presentation are the view s of the authors and do not necessarily reflect the views or policies of the AsianDevelopment Bank Institute (ADBI), the Asian Development Bank (ADB), its Board of Directors, or the governments they represent.ADBI does not guarantee the accuracy of the data included in this paper and accepts no responsibility for any consequences of theiruse. Terminology used may not necessarily be consistent with ADB official terms.

2

https://www.adb.org/adbi/research/call-for-papers

Deadline for submission of abstract: Dec 30, 2018

Outline

I. SMEs’ Difficulties in Raising Money in Asia

II. Credit Guarantee Schemes and SME Finance

III. Optimal Credit Guarantee Ratio

IV. Conclusion and the Policy Recommendations

V. Next step project

3

4

I. SMEs’ Difficulties in Raising Money in Asia

I. SMEs’ Difficulties in Raising Money

5

Bank of Japan (2016) – TANKAN

Lending Attitude of Financial Institutions

Limited bank lending to SMEs in Central Asia is a Challenge

6

CAM

BAN

MONINO

PRC

KAZMAL

THA

KOR

ageAver

21.1

0

5

10

15

20

25

30

35

40

45

50

2007 2008 2009 2010 2011 2012 2014*2013

BAN = Bangladesh, PRC = People’s Republic of China, IND = India, INO = Indonesia, KAZ = Kazakhstan, KOR = Republic of Korea,MAL = Malaysia, MON = Mongolia, PHI = Philippines, SRI = Sri Lanka, and THA = Thailand.Source: Asia Finance Monitor (2015)

Bank loans to SMEs to total loans (%)

Credit to the private sector in Central Asia remains comparatively modest

7

Domestic credit to private sector in Central Asia

Source: (World Bank, 2017), (EBRD, 2017), (RAEX, 2017), (OECD, 2018)

34%

21%

58%

19% 15%

44%

148%

0

20

40

60

80

100

120

140

160

Kazakhstan Kyrgyzstan Mongolia Tajikistan Uzbekistan Lower middleincome

OECDmembers

Domestic credit to private sector (% of GDP)

Non-performing loans remain high in the region

8

20.4%

8.5%

6.7%

0.4%

9.4%

4.2%

2.7%

0.6%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Tajikistan* Kyrgyzstan Kazakhstan Uzbekistan RussianFederation

Lower middleincome

OECD members Canada

Bank nonperforming loans to total gross loans (%)

Note: * Data for Tajikistan is from 2014 Sources: (World Bank, 2017; Bank of Mongolia, 2016; OECD, 2018)

Bank nonperforming loans to total gross loans (%)

Credit conditions are tight with high interest rates in the region

9

Interest rates in Central Asia, 2016

22%

20%

26%

16% 16%

3%4%

5%

-5%

0%

5%

10%

15%

20%

25%

30%

Kyrgyzstan Mongolia Tajikistan* Kazakhstan* Uzbekistan Canada Czech Republic Poland

Lending interest rate (%) Inflation Rate (CPI)

Note: *lending interest rates for Kazakhstan and Tajikistan (2015)

Source: (World Bank, 2017; CIA, 2018; State Committee of Uzbekistan on Statistics, 2018; Ministry of National Economy of Kazakhstan, 2017; OECD, 2018)

Lending interest rate and inflation rate

More than a third of SMEs are discouraged from applying loans due to tight credit conditions in the region, compared to less than a fifth in selected OECD countries.

10

Source: (EBRD, 2017; OECD, 2018)

Percentage of SMEs that are discouraged to apply for a loan by credit conditions

14%

18%

42%

35%

37%

37%

44%

56%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Czech Republic

Poland

Russia

Tajikistan

Uzbekistan

Kazakhstan

Kyrgyzstan

Mongolia

Discouraged by credit conditions No need

High and systematic collateral requirements limit access to finance for SMEs

11

140%

150%

160%

170%

180%

190%

200%

210%

220%

230%

60% 65% 70% 75% 80% 85% 90% 95% 100% 105%

Val

ue

of

colla

tera

l nee

ded

fo

r a

loan

(%

of

th

e lo

an a

mo

un

t)

Proportion of loans requiring collateral (%)

Mongolia

Lower middle income

Kyrgyzstan

Kazakhstan

Tajikistan

Uzbekistan

OECD average

High and systematic collateral requirements

Average but systematic collateral requirements

Source: (EBRD, 2017; World Bank, 2017, OECD, 2018)

Figure 5. Collateral requirements in Central Asia

II. Credit Guarantee Schemes and SME finance

12

Source: Yoshino and Taghizadeh-Hesary (2015)

SMEs, CRD, CGCs and Banks

13

Example: Credit Guarantee Scheme of Japan

14

LocalGovernments

National GovernmentMinistry of Finance

Ministry of Economy, Trade and Industry(Small and Medium Enterprise Agency)

Private Financial

Institutions

SMEs and Micro-

enterprises

Japan Finance Corporation (JFC)

Japan Federation of Credit Guarantee Corporations (JFG)

Credit Guarantee Corporations (CGCs):

51 CGCs

Contributions/ Loans

Supervision

Subsidies forCGC’s fund

Supervision Supervision Subsidies for compensation assets

Compensation for the loss Fund for Credit Insurance

Supervision

Insurancecontracts

Credit Guarantee Consignment Contract

Loans

Repayments

GuaranteeContract

Source: Japan Federation of Credit Guarantee Corporations (JFG 2014)Note: above figure is reproduced by the authors

CGS reduces the expected default lose of banks on SME

loan and increase bank lending to SMEs

15

credit guarantee scheme and SME loan supply𝑟𝑆𝑀𝐸

𝐿𝑆𝑀𝐸

Normal loan supply curve to SMEs with existence ofcredit guarantee scheme

Backward bending loan supply curve

Source: Yoshino and Taghizadeh-Hesary (2018)Note: rSME = lending interest rate to SMEs; LSME= amount of loan to SMEsSME= small and medium-sized enterprises;

16

SMEs Access to Credit Guarantees

Source: ACSIC (2012), The 25th Anniversary Publication of ACSIC – The 25-year History of ACSIC

1.0

5.3

1.90.0

36.7

7.4

26.7

1.7

8.9

0.1

10.9

1.5

0

5

10

15

20

25

30

35

40

0

1

2

3

4

5

6

7

8 Outstanding Guaranteed Liabilities (% of GDP) [left]

SME Access to Guarantee (% of total SMEs) [right]

( )% (%)

Japan

Source: Japan Federation of Credit Guarantee Corporations (JFG)

1. Following the introduction of credit guarantee scheme (CGS) in Japan in 1937, their use spread first throughout Europe and the Americas in the 1950s, and then to Africa, Asia and Oceania in the 1960s and 1970s.

2. At present, there are 51 CGCs, one for each prefecture and one in each of the cities of Nagoya, Yokohama, Kawasaki, and Gifu.

3. At the end of 2013, their total liabilities stood at approximately 30 trillion yen.

17Copyright: Yoshino & Taghizadeh-Hesary (2017)

Eligible SMEs for the Credit Guarantee in Japan

CGCs define the scope of MSMEs eligible to receive credit guarantees asfollows. MSMEs which either meet the requirements in terms of number ofregular employees or paid-up capital as given in the table below are eligible forcredit guarantees (excluding some special industries).

Industries covered by the credit guarantee system are based on the industries designated bythe enforcement regulation under the Small and Medium-sized Enterprise Credit InsuranceAct. Agriculture, forestry, fisheries, financial industry are excluded.

Source: Japan Federation of Credit Guarantee Corporations (JFG)

18Copyright: Yoshino & Taghizadeh-Hesary (2017)

Ceiling on Guarantee in Japan

Source: Japan Federation of Credit Guarantee Corporations (JFG)

Credit Guarantee fee rate classification

19Copyright: Yoshino & Taghizadeh-Hesary (2017)

Partial Guarantee

Source: Japan Federation of Credit Guarantee Corporations (JFG)20

Copyright: Yoshino & Taghizadeh-Hesary (2017)

21

III. Optimal credit guarantee ratio

22

SME1

CREDIT GUARANTEE

CORPORATION (CGC)

lending

Optimal Credit

Guarantee Scheme

(BO

RR

OW

ER

s)

SME2

A

B

(Le

nd

ers

)

Copyright: Yoshino & Taghizadeh-Hesary (2017)

In the literature on loan guarantees has left three

important questions unanswered:

(i) What is the optimal credit guarantee ratio to fulfillgovernment’s goal for minimizing banks’nonperforming loans to SMEs while at the same timefulfilling the government policies for supporting SMEs?

(ii) Should this rate be constant regardless of themacroeconomic status?

(iii)Should this rate be same for all banks, or should it varybased on a bank’s soundness?

23

Research Questions

Copyright: Yoshino & Taghizadeh-Hesary (2017)

24

Models for the Optimal Credit Guarantee Ratio

Policy Objective Function

2*2

2*1 wLLwU

eLo YlrllL 21

Loan Demand Function

Max. DLDZMPPYgLL CDrLLr SL ,,,, ,,

Banks Profit Maximization

ADLL 1Subject to: Banks’s Balance sheet

25

LDZMPPYg

e rYll

lllL SL ,,,

1

2

1

01,,

2

Amount of loan in equilibrium

Optimal Credit Guarantee ratio: g

Depends on:

• Actual SME loans• The desired SME loans• The desired default risk ratio of loans• Fixed demand for loan• Deposit interest rate• Expected GDP• The weight for stabilizing the SME loans • The weight for reducing the non-performing loan ratio• Marginal increase of non-performing loans by increase of additional loans• Price of Land, Price of stock, GDP, money supply, • Financial profile of banks

26

ZMPPYwLlryll

lllw

wlwg SLLD

e

1

6

1

5

1

4

1

3

1

2*

1

2*

1

1

1

2

1

02

11

2

211

1

24.

4

1

Empirical Survey

No. Symbol Definition

1 L–D Total loans/total deposits

2 PR–L Properties/total loans

3 (SD+LD)–D (Saving deposits + long-term deposits)/total deposits

4 A–L Total assets/total loans

5 SC–L Securities/total loans

6 CA–D Cash/total deposits

7 CBR–D Accounts receivable from central bank/total deposits

8 OBR–D Accounts receivable from other banks/total deposits

Note: Properties are land, buildings, and other hard assets owned by banks. Securities include shares of corporate stock or mutual funds, bonds issued by corporations or governmental agencies, limited partnership units, and various other formal investment instruments that are negotiable and fungible. Accounts receivable from the central banks includes reserve requirement (or cash reserve ratio) and other sums that are normally in the form of cash stored physically in a bank vault (vault cash) or deposits made with a central bank. Accounts receivable from other banks are sums loaned to other banks.Source: Yoshino, Taghizadeh-Hesary, Nili (2015)

Variables Examined for Bank’s Soundness

27

Statistical Analysis of banks’ balance sheet data

Variables

(Financial Ratios of Banks)

Component

Z1 Z2 Z3

L–D (0.238) (0.912) (0.143)

PR–L 0.042 0.190 0.780

(SD+LD)–D (0.287) 0.819 (0.123)

A–L 0.987 0.083 0.130

SC–L (0.096) (0.140) 0.875

CA–D 0.379 (0.536) 0.039

CBR–D 0.954 (0.104) (0.102)

OBR–D 0.981 (0.011) (0.117)

( ) = negative.Note: The extraction method is principal component analysis. The rotation method is direct oblimin with Kaiser normalization.

Factor Loadings of Financial Variables after Direct Oblimin Rotation

28

Distribution of factors

FFEE DD

CC

BB

AA

Z

YXWVU

TSRQ PO

N

L K

J

IF

E

DC

A

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

0 1 2 3 4 5 6

Co

mp

on

ent

2 (Z

2)

Component 1 (Z1)

FFEE

DD

CCBB

AAZ

YXWV

U TS

RQPO

N

L K

J

I F

E

D

C

A

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

-2.5 -2 -1.5 -1 -0.5 0 0.5 1

Co

mp

on

ent

3 (Z

3)

Component 2 (Z2)

FFEE

DD

CCBB

AAZ

YXWVU T

SRQ

PON

L K

J

I F

E

D

C

A

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6

Co

mp

on

ent

3 (Z

3)

Component 1 (Z1)

29

Clustering

Dendrogram

Bank Credit

rank

Rank

of L–D

Rank of

PR–L

Rank of

(SD+LD)

–D

Rank of

A–L

Rank of

SC–L

Rank of

CA–D

Rank of

CBR–D

Rank of

OBR–D

I 2 24 1 16 3 5 8 21 2

R 14 14 17 12 15 9 11 9 7

W 28 11 20 22 20 6 10 3 18

Robustness Check for Three Sample Banks

30

Calculated Optimal Credit Guarantee ratios

31

Group 1 of banks: 0.775Group 2 of banks: 0.683

the optimal credit guarantee ratio in our model depends on three groups of factors:

1. macroeconomic variables

2. government policies,

3. banking profile.

These three groups consist of various variables including:

price of land, price of stock, gross domestic product (GDP), money supply,actual SME loans, fixed demand for loans, deposit interest rate, expectedGDP, marginal increase of nonperforming loans by increase of additionalloans, desired SME loans, desired default risk ratio of loan, weight forstabilizing the SME loans, weight for reducing the nonperforming loan ratio,and financial profile of banks.

Robustness Check of the Optimal Credit Guarantee Model

• Stationarity test• Co-integration analysis• VECM

32

321 ,,,1,,, ZZZmcpigdpV

Impulse Response Analysis: Group 1 of banks

33

Impulse Response Analysis: Group 2 of banks

-.03

-.02

-.01

.00

.01

.02

1 2 3 4 5 6 7 8 9 10

Accumulated Response of NPL2/L2 to Z2,1

-.03

-.02

-.01

.00

.01

.02

1 2 3 4 5 6 7 8 9 10

Accumulated Response of NPL2/L2 to Z2,2

-.03

-.02

-.01

.00

.01

.02

1 2 3 4 5 6 7 8 9 10

Accumulated Response of NPL2/L2 to Z2,3

-.03

-.02

-.01

.00

.01

.02

1 2 3 4 5 6 7 8 9 10

Accumulated Response of NPL2/L2 to M

-.03

-.02

-.01

.00

.01

.02

1 2 3 4 5 6 7 8 9 10

Accumulated Response of NPL2/L2 to NPL2/L2

-.03

-.02

-.01

.00

.01

.02

1 2 3 4 5 6 7 8 9 10

Accumulated Response of NPL2/L2 to P

-.03

-.02

-.01

.00

.01

.02

1 2 3 4 5 6 7 8 9 10

Accumulated Response of NPL2/L2 to Y

Accumulated Response to Cholesky One S.D. Innovations

34

35

IV. Conclusion and Policy Recommendations

Conclusion and Policy recommendations (1)

1. The public credit guarantee scheme is a tool toreduce the supply–demand gap in SME finance.

2. In order to avoid moral hazard and for increasingthe effectiveness and sustainability of the CGS,adoption of the optimal credit guarantee ratio isneeded

3. Optimal credit guarantee ratio is determined bythree groups of variables: (i) government policiesfor NPL reduction and SME support, (ii)macroeconomic variables, and (iii) bank-levelvariables or banking behavior

36

Conclusion and Policy recommendations (2)

4. The optimal credit guarantee ratio should vary foreach bank, or for each group of banks, based ontheir financial soundness.

5. Sound banks should receive a higher guaranteeratio from the government, and less healthy banksshould receive a lower guarantee to avoid a moralhazard problem.

6. Moreover, this rate should vary based on economicconditions. Governments should lower theguarantee ratio in good economic conditions wherethe default risk of SME loans is reduced, and raiseit in bad economic conditions to protect the SMEfinancing and economic growth.

37

Next Step:

Measuring the optimal credit guarantee ratio andoptimal credit guarantee fee for CAREC membercountries (First case: Kazakhstan)

In Recent years DAMU fund in Kazakhstan hadsignificant impact in increasing share ofguaranteed loans to SMEs.

The share of “Damu” Fund credit in priorityindustries have been steadily increasing over theyears to KZT574 bln in 2016 or 17% of the totalcredit. (DAMU, 2017).

38

Dosmagambet, Oskenbayev, Taghizadeh-Hesaryand Mukan (Forthcoming) found that the publiccredit guarantee scheme and financial systemcreditworthiness in Kazakhstan is vulnerable to oilprice movements.

In order to have a sustainable credit guaranteescheme for Kazakhstan for securing the SMEsaccess to finance, its important to adopt theoptimal credit guarantee ratio and optimal creditguarantee fee.

39

Reference:

40

1. Yoshino, N. (2012). Global Imbalances and the Development of Capital Flows among AsianCountries. OECD Journal: Financial Market Trends. Vol. 2012/1.

2. Yoshino, N. and F. Taghizadeh-Hesary (2014). An Analysis of Challenges Faced by Japan’sEconomy and Abenomics. The Japanese Political Economy 40: 1–26. DOI:10.1080/2329194X.2014.998591

3. Yoshino, N. and F. Taghizadeh-Hesary (2014). Analytical Framework on Credit Risks forFinancing SMEs in Asia. Asia-Pacific Development Journal. United Nations Economic andSocial Commission for Asia and the Pacific (UN-ESCAP). 21(2): 1-21.

4. Yoshino, N., Taghizadeh-Hesary, F., Nili, F. (2015), ‘Estimating Dual Deposit InsurancePremium Rates and Forecasting Non-performing Loans: Two New Models’. ADBI WorkingPaper 510. Asian Development Bank Institute: Tokyo

5. Kuwahara, S., N. Yoshino, M. Sagara, and F. Taghizadeh-Hesary. (2015). Role of the CreditRisk Database in Developing SMEs in Japan: Lessons for the Rest of Asia. ADBI Working Paper547. Tokyo: Asian Development Bank Institute.

6. Yoshino, N. and F. Taghizadeh-Hesary. (2015). Analysis of Credit Risk for Small and Medium-Sized Enterprises: Evidence from Asia. Asian Development Review (ADR). Vol. 32 No. 2.: 18-37, MIT Press.

7. Yoshino N., and Taghizadeh-Hesary, F. (2018). Optimal credit guarantee ratio for small andmedium-sized enterprises’ financing: Evidence from Asia. Economic Analysis and Policyhttps://doi.org/10.1016/j.eap.2018.09.011

8. OECD (2018). Enhancing Access to Finance for SMEs: The case of central Asia. UnlockingAccess to Finance for SMEs in Asia. Eds. N. Yoshino and F. Taghizadeh-Hesary. London:Routledge

Thank you for your attention!nyoshino@adbi.org

farhad@aoni.waseda.jp

www.linkedin.com/in/farhadth41

Forthcoming book, 2019

Unlocking SME Finance in Asia: Roles of credit rating and credit guarantee scheme

Farhad Taghizadeh-HesaryAssist. Professor, Waseda University, Japan

Visiting Professor, Keio University, Japan

Naoyuki YoshinoDean & CEO, ADBI

Professor Emeritus, Keio University, Japan

Editors: