Kang Tae Soo -- Riksbank Macroprudential Conference Stockholm, Sweden, November 2014

Kang Tae Sooat Riksbank Macroprudential

Conference Stockholm, Sweden, November 2014

Owner

Typewritten Text

(a review of selected Kang Tae Soo Macroprudential presentations)

http://www.riksbank.se/en/Financial-stability/Macroprudential-Policy-Conference-November-2014/Tae-Soo-Kang/

Contents• Macroprudential Policies in Korea:

Toolkits and Experiences, April 14 2014, New York

• Macroprudential Policy Framework: The Case of Korea, IMF March 22~23, 2012, Tokyo

• Macroprudential Policy Framework: Framework: The Case of Korea, IMF, March 1~2, 2012, Uruguay

www.riksbank.se/en/Financial-stability/Macroprudential-Policy-Conference-November-2014/

http://www.riksbank.se/en/Financial-stability/Macroprudential-Policy-Conference-November-2014/

www.riksbank.se/en/Financial-stability/Macroprudential-Policy-Conference-November-2014/

www.adbi.org/files/2012.03.14.cpp.sess.b1.mccauley.risk.on.risk.off.pdf





http://www.paris-europlace.net/ny2014/RT3_Tae_Soo_Kang.pdf

Macroprudential Policies in Korea

- Toolkits and Experiences

Tae Soo Kang

Bank of Korea

Disclaimer

This presentation represents the views of the author and not

necessarily those of the BOK or BOK policy.

Paris Europlace Financial Forum

New York, April 14, 2014

Contents

Ⅰ. Monitoring and Measuring Macroprudential Conditions

Ⅱ. Macroprudential Toolkits

� LTV, DTI Caps

� FX-related

� Loan to Deposit Cap

Ⅲ. Ongoing Discussions

2/25

I. Monitoring and Measuring Macroprudential Conditions

� 「Financial stability」 : New mandate to the BOK(Bank of Korea Act amendments (Dec. 2011))

� BOK concerns with macroprudential aspects

� A framework for monitoring and measuring macroprudential conditions

3/25

Background

Financial Stability Report

Systemic Risk Assessment Model for Macroprudential Policy (SAMP)

1

2

I- Financial Stability Report

① Analyze and evaluate the potential systemic risk

② Provide early warning of risk

③ Suggest policy alternatives

� Published twice a year, and submitted to the National Assembly

� FSR attempts to …

4/25

1

� Feedback mechanism with domestic and overseas advisor groups

5/25

� Forthcoming FSR (April 2014) identifies five key risks

� To help identify the potential risk factors, BOK conducts Survey of financial

market participants (90 experts) twice a year

① Tapering off of US quantitative easing (77%)

② Slowdowns in growth of China (72%)

③ Household debt problem (70%)

④ Financial instability in emerging market countries (57%)

⑤ Increase in corporate credit risk (41%)

Why

a Model

Needed?

BOK has developed its own systemic risk assessment model

Cannot manage what you cannot measure

InterconnectednessProcyclicality

Sources for Systemic Risk

2

� Examine resilience of financial system (macro stress test)

� Measure individual banks’ contributions to systemic risk (D-SIBs)

I- SAMP

Tail risks unobservable

⇒ For the 2013 FSAP for Korea, SAMP was used to conduct

macro stress test

6/25

Macro

shocks

1st round

loss

2nd round losses due

to default contagion

2nd round losses due

to liquidity contagion

⑤ Multi-period module

• Dynamic update of banks’ B/S

④Funding liquidity contagion module

• Estimation of funding costs and

deleveraging/liquidity withdrawals

• Contagious defaults due to liquidity

withdrawals

① Macro-risk factor module

• Generation of macro-economic

scenarios

③ Default contagion module

• Estimation of 2nd round losses due

to fire sales and credit crunch

• Contagious defaults due to

interbank loan losses

② Bank profit and loss module

• Calculation of bank profits and

losses based on macro scenarios

⑥Systemic riskmeasurement module

• Systemic risk indicators

- Value at Risk

- Expected shortfall

- Probability of systemic crisis

1st & 2nd round

losses

Chart: SAMP Structure

7/25

8/25

Ⅱ. Macroprudential Toolkits

1 LTV, DTI Caps

FX-related

Loan to Deposit Cap

2

3

9/25

II- LTV, DTI Caps

Background

� Real estate in total assets : Korea 73.3% (March 2013)

� Housing booms in early and mid 2000s fueled by rapid increases in home mortgage lending by banks

Household Loans

1

Housing Booms and Bank Lending

Housing price

LTV Cap [September 2002]

� LTV has been adjusted a total of 9 times

(6 times for tightening and 3 times for relaxing)

� Limitation : Housing price → Collateral value

→ Affordable additional borrowing

→ Procyclicality amplified

10/25

DTI Cap [August 2005]

11/25

� Curbs possible procyclical behaviour resulting from LTV Cap

� Puts limit on ratio of annual debt repayment amount to debtor’s annual income

� DTI ratio =

��

��

�� × 100

� DTI has been adjusted a total of 8 times

(6 times for tightening and 2 times for relaxing)

① Procyclical behavior could be reinforced

Unintended Consequence : LTV Cap

� Boom phase: Mortgage collateral → Affordable additional borrowing

→ Countercyclical?

� Downturn phase: LTV moves above threshold (violation of Cap)

→ Pressure on loan recovery → Housing price (fire sales)

→ Procyclicality amplified

Boom

LTV regulation : Procyclicality worsening

12/25

LTV regulation : Countercyclical ?

Downturn

Housing Price Cycle and the Role of LTV Cap

② Caused Funding Liquidity Risk

13/25

Unintended Consequence : DTI Cap

� Average maturity of mortgage loans : 5.4 years (2004) → 11.3 years (2013)

� Banks’ funding maturity has not changed greatly(Composition of banks’ funding (2013) : Deposit 67%, Wholesale funding 17%, Borrowing 16%)

Mortgage loan maturities

DTI ratio =

��

+ ��

�� DTI ratio =

��

+ ��

��

� DTI caps designed in favor of

longer maturity

Pre- and Post-crisis Capital flows

14/25

II- FX-related Toolkits

Background

2

Capital Flow Volatility

� Capital flows to Korea : Volatile and procyclical

� About one half of total bank inflows during two-year period prior to Lehman Crisis flowed out within five months after it

‘06.1 ~

‘08.8

‘08.9 ~

‘09.3

Equity -683.8 -65.7

Bond 516.4 -108.5

Bank borrowing 1,084.9 -571.5

(Short-term) (998.5) (-573.8)

(100 million dollars)

Capital inflows to Korea, and GDP Growth

Background

Notes: Currency mismatches = foreign liabilities – foreign assets

Maturity mismatches = short-term foreign liabilities – short-term foreign assets

� A sharp increase in mismatch of short-term external debt through foreign

bank branches drives systemic risk

Domestic Banks Foreign Bank Branches

Currency and Maturity Mismatches

15/25

FXMarket

Pull factors

MajorShip builders

Push factorsForeign investorsForeign financial

institutions

(1) Leverage caps on banks’ FXDerivatives positions

(2) Macroprudential Stability Levy on bank’s non-core FX liabilities

� Volatility and mismatches in FX market can be understood in terms of both pull and push factors

� Pull factor Swollen hedging demand from major ship-builders amid

strong market expectations of currency appreciation

� Push factor Capital inflows resumed from second half of 2009 on back

of ample global liquidity

16/25

S-T External

Debt

(1) Leverage caps [October 2010]

� Aimed at curbing banks’ short-term external debt

Selling FX Forward

Buying $ for hedging

S-T $ Borrowing

Ship

Builders

Domestic

Banks

Foreign

Branches

Foreign

Bank

Branches

Overseas

Banks

� Caps on banks’ FX derivatives positions : 150 % of equity capital for

foreign bank branches, 30 % for domestic banks

17/25

� Aimed at curbing excessive increase in bank’s non-core liabilities

� Lower levies applied to longer-maturity liabilities

Macroprudential Stability Levy

(2) Macroprudential Stability Levy [August 2011]

Bank borrowing and Business cycle

18/25

� Leverage caps have contributed to reductions in currency and maturity mismatches

Maturity Composition of External Debt

(Foreign bank branches)

Note : 1) Black and green vertical lines refer to the dates of the introduction of the Leverage Caps and the

Macroprudential Stability Levy, respectively.

(Domestic banks)

Effects of Leverage Caps

0

20

40

60

80

100

2009Q1 2010Q1 2011Q1 2012Q1 2013Q1

Short term Long term(%)

0

20

40

60

80

100

2009Q1 2010Q1 2011Q1 2012Q1 2013Q1

Short term Long term(%)

19/25

� MSL has reduced arbitrage margin and raised FX funding costs

� Total levy collected estimated to be as large as 12 % of net profits for foreign bank branches (domestic banks : less than 1 %)

Note : 1) Interest differential (3M)-Swap rate (3M)

Arbitrage Transaction Incentives1)

(Foreign bank branches)Ratios of Levy to Net Profits

(As of end-2012)

Note : 1) Estimated ratios

Effects of MSL

0.7

12.4

0

2

4

6

8

10

12

14

Domestic banks Foreign bank branches

(%)

20/25

II- Loan-to-Deposit Cap [December 2009]

Background

3

Textbook CaseReality

(Boom period)

Funding

Lending

Lending opportunity

S-T Funding through

wholesale finance

Lending expansion based on

wholesale funding

� Procyclicality

� Interconnectedness

21/25

Loan-to-deposit ratio = KRW-denominated Loans

KRW-denominated Deposits�

≤ ��%

⇒ With LTD ratio limited to within 100%, banks are forced to reduce

reliance on wholesale funding

Wholesale funding

22/25

Loan-to-Deposit ratio

Effects of LTD Cap

� Reducing procylicality of bank lending behavior and

interconnectedness among financial institutions

23/25

III. Ongoing Discussions

24/25

� The institutional framework for macroprudential policy

� US type (FSOC) vs. UK type (BOE)

� The recent recommendation by the IMF is noteworthy, that the

establishment of a financial stability committee is necessary and that

central bank should play a key role on it

� Macroprudential vs. Capital Flow Management

� Potential conflicts with the Capital Liberalisation

25/25





https://www.imf.org/external/oap/np/seminars/2012/macroprudential/pdf/IV2Kang.pdf

http://www.imf.org/external/oap/np/seminars/2012/macroprudential/

Monetary Policy Workshop on Strengthening Macroprudential FrameworkMacroprudential Framework held by IMF Regional Office for Asia and Pacific(March 22~23, 2012, Tokyo)

MacroprudentialMacroprudential Policy Policy Framework:Framework:

The Case of KoreaThe Case of Korea

Tae Tae SooSoo Kang Kang Bank of KoreaBank of Korea

DISCLAIMER: This presentation represents the views of the author and not necessarily those of the BOK or BOK policy. The views expressed herein should be attributed to the author and not to the BOK, its management or its Monetary Policy Committee.

DISCLAIMERDISCLAIMER

The views expressed in this presentationThe views expressed in this presentation

DISCLAIMERDISCLAIMER

The views expressed in this presentation The views expressed in this presentation represent those of the presenter and do not represent those of the presenter and do not necessarily represent those of the Bank ofnecessarily represent those of the Bank ofnecessarily represent those of the Bank of necessarily represent those of the Bank of Korea. Korea.

1

OutlineOutlineOutlineOutlineI.I. Potential Systemic Risks Unique to Korea Potential Systemic Risks Unique to Korea

II.II. MacroprudentialMacroprudential Measures DeployedMeasures Deployed1)1) M iM i d d thd d th1)1) Main Main rreasons we advanced these measureseasons we advanced these measures

2)2) Impacts of these measures Impacts of these measures

III.III. Possible Obstacles to ImplementationPossible Obstacles to Implementation-- Asymmetric impacts in addressingAsymmetric impacts in addressing procyclicalityprocyclicalityAsymmetric impacts in addressing Asymmetric impacts in addressing procyclicalityprocyclicality

I.I. Potential Systemic Risks Unique to KoreaPotential Systemic Risks Unique to Koreay qy q

C it l Fl V l tilitC it l Fl V l tilit1 Capital Flow Volatility Capital Flow Volatility

2 Household DebtHousehold Debt

Both factors affect systemic risk in terms of procyclicality. Implies Korean economy exposed more to systemic

risk in the time-varying dimension, than in the cross-sectional dimension. (B. Aydin, M. Kim and H. Moon: “Financial Linkages across Korean Banks”

1/14

( y gIMF ,WP/11/201, 2011)

In particular, strong procyclicality of capital flowsp , g p y y pamplifying business cycle fluctuation is a systemic risk factor common to emerging Asian countries

Capital Inflows to Asia & GDP Growth Capital Inflows to Korea & GDP Growth

35.0

40.0

12.0

14.0

Capital inflows/GDP(LHS)

(%) (%)

5.0

10.0

2 0

3.0

4.0

10 0

15.0

20.0

25.0

30.0

6.0

8.0

10.0 GDP growth (RHS)

10 0

-5.0

0.0

-2.0

-1.0

0.0

1.0

2.0

GDP Growth (RHS)

-5.0

0.0

5.0

10.0

0.0

2.0

4.0

01 02 03 04 05 06 07 08 09 10 11-20.0

-15.0

-10.0

-6.0

-5.0

-4.0

-3.0

00 01 02 03 04 05 06 07 08 09 10 11

Net Capital Flow/GDP (LHS)

Source: BOK staff calculation

(conjecture) Emerging Asian Economies may have high reliance for credit supply on capital inflows in the form of externalfor credit supply on capital inflows in the form of external liabilities, rather than on funding by domestic bank deposits.

2/14

1 High Capital Flow VolatilityHigh Capital Flow Volatility1 High Capital Flow Volatility High Capital Flow Volatility

Capital Flows Financial Market Volatilities (std. dev*)250

Short-term debt(billion dollars)

221.9 0 35140

A B150

200

Short term debtBondEquity

.9

101.60.25

0.30

0.35

100

120

140 Won/Dollar FX rate (LHS)KOSPI (LHS)Treasury Bond Yield (3Y, RHS)

C

0

50

100

97 11~98 3 98 4~08 8 08 9~08 12 09 1~11 6 11 7~11 12 0.10

0.15

0.20

40

60

80

A B-100

-50

97.11~98.3 98.4~08.8 08.9~08.12 09.1~11.6 11.7~11.12-21.4

-69.6

-12.6

0.00

0.05

0

20

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12C

(Asian Crisis)B

(Lehman Crisis) * 3-month moving averages


(EU Debt Crisis)

3/14

2 Rapid Increase in Household DebtRapid Increase in Household Debt2 Rapid Increase in Household DebtRapid Increase in Household Debt

High Level Household leverage at historic peak

Floating Rates Almost 90% of mortgage loansg g g

Household Debt-to-Disposable Income Mortgage Loans, by Interest Rate Type1)

155%Fixed Rate

10.1%

129%

Floating Rate 89.9%

2005 2006 2007 2008 2009 2010

Source : Bank of Korea

Sources : Bank of Korea, 9 major domestic banksNote: 1) As of end-2011 4/14

II.II. MacroprudentialMacroprudential Measures DeployedMeasures Deployedpp p yp y

1 Responses to Capital Flow Volatility Responses to Capital Flow Volatility

Capital Inflows Capital Outflows

International Cooperation

Ai d t t bili i h t t it l fl d t bli hi Aimed at stabilizing short-term capital flows and establishing backstop (safeguard) against sudden capital outflows

5/14

1) Main reasons we advanced these measures In open emerging markets, non-core liabilities take form of short-term

FX liabilities, increasing vulnerability to outbreak of crisis High capital flow volatility also causes interest and FX rate deviation

1) Main reasons we advanced these measures

High capital flow volatility also causes interest and FX rate deviation from economic fundamentals, thereby weakening monetary policy transmission channel

Non-core Liabilities of Korean Banks

Net FX Liabilities

(billion dollars) (%p)

Foreign Portfolio Investment and Term Spread

(trillion won) (billion dollars)

1 0

2.0

3.0

7.0

12.0Bond InvestmentEquity InvestmentTerm Spread

(billion dollars) (%p)

A B

400

500

600 FX borrowingDebt SecuritiesOthers

(trillion won)

A 150

200

250

short-term liabiliieslong-term liabiliies

(billion dollars)

A B

-1.0

0.0

1.0

-3.0

2.0

A B

100

200

300

A: Lehman CrisisB: EU Debt Crisis

B

50

100

150

Source: Shin & Shin (2010), updated by BOK staff

-2.0 -8.008.1 08.7 09.1 09.7 10.1 10.7 11.1 11.7 12.1

0

100

05 06 07 08 09 10 11

6/14

005 06 07 08 09 10 11

2) Impacts of these measures (in response to capital inflows)

Effective so far Short-term External Debt Decreased Arbitrage Incentive Reduced Arbitrage Incentive Reduced Terms of Foreigners’ Bond Investment Lengthened

Foreign Bank Branches’Changes in External Debt before Foreigners’ BondForeign Bank Branches Arbitrage Incentive

Changes in External Debt, before and after ceilings

Foreigners Bond Investment, before and after

taxation

1.5 Arbitrage incentivesLevy rate(short-term)Moving Avg. of net arbitrage incentive

(%)

67 1100

150

200 (billion dollars)

7

9 short-term bond investment

long-term bond investment

(billion dollars)

Implementation(Jan. 11)

0.5

1.0

g g g

Arbitrage incentive Arbitrage incentive

60.4

171.8 67.1

-156.6 -100

-50

0

50

100

short-term external debtlong-term external debt

1

3

5

0.0 Jan-11 Apr-11 Jul-11 Oct-11

before levy Arbitrage incentiveafter levy

-200

-150

Before Ceiling(Apr. 09~Dec. 10)

After Ceiling (Jan. 11~Nov.11)

-3

-1

09.1Q 3Q 10.1Q 3Q 11.1Q 3Q

Announcement(Oct. 10)

Source: Bank of Korea 7/14

2 Responses to Household DebtResponses to Household DebtCaveat: more work needed to establish how much of changes in house price and loan growth attributable to macroprudential policy

Housing indicators (Seoul area) before and after loan regulation tightening1)

tightening

Mortgage loans2) House prices3) Housing transactions4)

1) Comparison between six-month periods before and after strengthening of loan regulations 2) In trillions of won 3) Apartment basis 4) In units of 10,000 * Source: Bank of Korea 8/14

III.III. Possible Obstacles Possible Obstacles to to ImplementationImplementation

Asymmetric impacts in addressing procyclicalityCountercyclical Buffers/ Dynamic Provisioning

pp

1 Countercyclical Buffers/ Dynamic ProvisioningCeilings on LTD/DTIAdjustments of Risk Weights on Specific Exposures

1

2

3 j g p p

More effective BoomMore effective during Boom

Boom DownturnLess effective during Bust

Countercyclical policy Credit cycle before MAPPActual credit cycle after MAPP

9/14

1 Countercyclical Buffer (CCB)Countercyclical Buffer (CCB)

Boom: E+w A?D bt b t ff ti i dit t l

1 Countercyclical Buffer (CCB)Countercyclical Buffer (CCB)K: capital ratioE: equity

• Doubts about effectiveness in credit control • Despite regulators’ deployment of CCB,

banks still have incentive to increase more profitable loans.

w: risk weightA: asset value

• Impacts may be offset by time lag, or less effective in periods of rapid credit expansion, since banks given transition period up to 12 months to meet CCB targets.

?

Boom DownturnB

Bust: E+ w A?• Doubts about effectiveness in mitigating

deleveraging (slowing decrease in A) Boom

• Under uncertainties about duration of financial crisis, banks likely to opt to maintain their capital buffer targets set during boom, out of concerns that declines in their capital ratios

?

Countercyclical policy Credit cyclemight be interpreted as aggravated financial soundness

10/14

2 Ceilings on DTI/LTVCeilings on DTI/LTV2 Ceilings on DTI/LTVCeilings on DTI/LTV

BOOM BUST

?

Effective in limitingexcessive credit provision by banks during economic

May be less effective in improving liquidity conditions or supply of credit Despite eased LTV/DTI limits, banks

upturns likely to focus on cash hoarding rather than lending

4,000

5,000

6,000

Tightening of LTV

Introduction of DTI (Aug. 05)

Tightening of DTI (Feb. 07)

Tightening of DTI (Sep. 09)

(billion won )

Loosening of DTI (Nov 08)

Loosening of DTI (Aug. 10)

Mortgage Loan Fluctuations1)

1,000

2,000

3,000

4,000 g g(Oct. 03)

(Nov. 08)

0

1,000

Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Jul-09 Jan-10 Jul-10

Source: Bank of Korea 11/14

Empirical Test on Determinants of Loan SizeEmpirical Test on Determinants of Loan Size

Dependent Variable: Household Loans (with income information)2006

(Tighter DTI)2007

(Tighter DTI)2008

(Eased DTI)2009

(Tighter DTI)2010

(Eased DTI)2011

(Tighter DTI)

Financial VariablesLog (collateral value) 0.705*** 0.622*** 0.653*** 0.782*** 0.687*** 0.621***Income of Borrower 0.009*** 0.022*** -0.003*** 0.010*** 0.014*** 0.011***co e o o o e 0.009 0.022 0.003 0.010 0.014 0.011Interest Rate (CD yield)1) -0.072*** -0.029*** -0.095*** -0.136*** -0.043*** 0.072***High Credit2) dummy 0.082*** 0.038*** -0.059*** 0.089*** 0.046*** 0.048***Gangnam3) dummy 0.045*** 0.075*** 0.171*** 0.003*** 0.088*** 0.111***

Non-financial VariablesInterest Only Payment4) dummy -0.164*** -0.043*** 0.059*** 0.118*** 0.101*** 0.006***Group Loan dummy 0 019*** 0 017*** 0 035*** 0 089*** 0 083*** 0 007***Group Loan dummy -0.019 0.017 0.035 0.089 0.083 -0.007Business Owner5) dummy 0.023*** 0.024*** 0.026*** 0.042*** 0.034*** 0.029***Maturity 0.025*** 0.021*** 0.015*** 0.015*** 0.020*** 0.023***

Regulatory VariablesLTV dummy -0.093*** -0.046*** 0.004*** -0.102*** -0.031*** -0.116***DTI dummy -0.051*** -0.096*** -0.066*** -0.046*** -0.008*** -0.019***

CConstant 2.431*** 2.858*** 3.110*** 1.230*** 1.963*** 2.583***Adj. R2 : 0.364Obs. : 48,016

Adj. R2 : 0.308Obs. : 35,530

Adj. R2 : 0.295Obs. : 55,698

Adj. R2 : 0.332Obs. : 71,545

Adj. R2 : 0.292Obs. : 72,481

Adj. R2 : 0.282Obs. : 40,985

Analysis shows LTV/DTI to have asymmetric policy impacts: regulation tightening more effective than regulation easing

12/14

3 Adjustment of Risk Weights on Specific Exposures (ARW)Adjustment of Risk Weights on Specific Exposures (ARW)3 Adjustment of Risk Weights on Specific Exposures (ARW)Adjustment of Risk Weights on Specific Exposures (ARW)

<Operating Mechanism of ARW>

Increase in credit risk in a particular asset, AiIncrease in credit risk in a particular asset, Ai

Operating Mechanism of ARW

Upward adjustment of risk weights for loans to the asset (wi)Upward adjustment of risk weights for loans to the asset (wi)

Increase in capital requirements (K)Increase in capital requirements (K)

Incentive to reduce exposure to the asset (Ai)Incentive to reduce exposure to the asset (Ai)

13/14

<Banks’ Responses in Unintended Direction>p: Regulator’s action and intended

direction of banks’ response: Banks’ responses in reality

Excessive concentration on a particular asset, AiExcessive concentration on a particular asset, Ai

: Banks responses in reality

Upward adjustment of risk weights for loans to the asset (wi), and resultant tightened capital requirement (K) Upward adjustment of risk weights for loans to the asset (wi), and resultant tightened capital requirement (K) g p q ( )g p q ( )

Banks’ ReponsesR it li i (E )

Banks’ ReponsesR it li i (E )1 Recapitalizing (E )Reducing other assets(Aj ) with lower risk weights and returnsRecapitalizing (E )Reducing other assets(Aj ) with lower risk weights and returns

According to UK FSA (2009),

1

2

According to UK FSA (2009), ARW (wi) E 50%, exposure to other assets 25%

exposure to targeted asset 25% 14/14





https://www.imf.org/external/np/seminars/eng/2012/macro/pdf/kang.pdf

http://www.bcu.gub.uy/Paginas/Default.aspx

Macroprudential Policy Framework:

The Case of Korea

Tae Soo Kang Financial Stability Department

Bank of Korea

High-Level Seminar on Macroprudential

Policies to Achieve Financial Stability

Held by Banco Central Del Uruguay and IMF

(Punta del Este, Uruguay, March 1–2, 2012)

IMF Stylized 3 Types of Models for MPF: Full Integration, Partial Integration and Separation

No Single Universal Solution:

No sole “Best Practice” for addressing Unique

Systemic Risks in all Countries

“A cat’s color (MPF) does not matter, black or white,

as long as it can catch mice (Systemic Risk).” (Deng

Xiaoping, 1978)

Outline

I. What are the Potential Systemic Risks

Unique to Korea?

II. Macroprudential Policy Responses

III. Macroprudential Policy Framework in Korea:

Institutional Arrangements

1/23

I. What are the Potential Systemic

Risks Unique to Korea?

129

%

More exposed to Systemic Risk in a Time-varying

Dimension, entailed by Procyclicality, than in a Cross-

sectional Dimension

• Empirical Evidence: “Financial Linkages across Korean Banks,”

IMF-BOK Joint Research, 2011. WP/11/201)

Procyclicaity emanating from Volatile Capital Flows

and Build-up of Household Debt may result in

heightened Systemic Risk in Korea.

2/23

129

%

3/23

In particular, Strong Procyclicality of Capital

Flows Amplifies Business Cycle Fluctuation

Capital Inflows to Asia & GDP Growth

Source: BOK staff Calculation

Capital Inflows to Korea & GDP Growth

-5.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

01 02 03 04 05 06 07 08 09 10 11

Capital inflows/GDP(LHS)

GDP growth (RHS)

(%) (%)

-20.0

-15.0

-10.0

-5.0

0.0

5.0

10.0

-6.0

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

00 01 02 03 04 05 06 07 08 09 10 11

GDP Growth (RHS)

Net Capital Flow/GDP (LHS)

A

(Asian Crisis)

B

(Lehman Crisis)

Capital Flows

A B

Financial Market Volatilities (std. dev*)

* 3-month moving averages

1 High Capital Flow Volatility

4/23

-100

-50

0

50

100

150

200

250

97.11~98.3 98.4~08.8 08.9~08.12 09.1~11.6 11.7~11.12

Short-term debt

Bond

Equity

(Billion dollars)

-21.4

-69.6

221.9

101.6

-12.6

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0

20

40

60

80

100

120

140

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12

Won/Dollar FX rate (LHS)

KOSPI (LHS)

Treasury Bond Yield (3Y, RHS)


C

(EU Debt Crisis)

C

Speculators’ Arbitrage-Seeking Behavior in

Volatile Markets may Aggravate Volatility.

“Most traders…don’t really care that much how they [world

leaders] are going to fix the economy, how they are going to fix

the whole situation – our job is to make money from it….

Personally I’ve been dreaming of this moment for three years. I

have a confession, which is I go to bed every night and I dream

of another recession.” (Interview with 34-year-old Trader, AFP,

September 29, 2011)

5/23

Interaction between Global (push) Factors

and Regional (pull) Factors

Source: IMF(2011)

Cyclical Factors Structural Factors

Push

Factors

Global liquidity

Global risk appetite

Slowing growth of AEs

Diversified capital flows

Advanced countries’

weakened fiscal structures

Pull Factors Interest rate

differentials

Fast recovery of EMEs

High potential growth

Fiscal soundness

Capital market development

6/23

High level⇒ Household Leverage at historic peak

2 Build-up of Household Debt: Fault Lines

Variable Rate⇒ More than 92% of Mortgage Loans

Household debt-to-

disposable income

2005 2006 2007 2008 2009 2010

155%

129%

Interest only paid, No Principal (78.4%)


Mortgage Loans,

by Interest Rate Type1)

Note: 1) As of end-June 2011

Mortgage Loans, by

Repayment Type

Source: Seoul metropolitan

area home mortgage loan

data of 4 major banks

Installment Repayment

Loans on which principal

currently being repaid, Installment

Repayment

Loans currently

in grace period,

41.1% Bullet Repayment

Loans, 37.3%


Mixed Rate

2.4%

Fixed Rate

4.9%

Floating

Rate

92.7%

7/23

Background of Household Debt Increase since 2002

• Housing Price Bubble

• Banks seeking alternative customers, i.e. Households,

in response to decline in demand from Corporate

Sector

• Competition among Banks

• Most recently, increase in household loans for other

purposes (e.g. securing living expenses, funding SOHO

business, smoothing consumption, etc.) rather than home

purchases

• Low interest rates since recent global financial crisis

8/23

129

%

1 High Capital Flow Volatility

-3.0

-1.0

1.0

3.0

5.0

7.0

9.0short-term bond investment

long-term bond investment

(Billion dollars)

Implementation (Jan. 11)

Announcement (Oct. 10)

0

10

20

30

40

50

60

70

80

90

09.1Q 3Q

domestic banks

foreign bank branches

(Billion dollars)

Announcement (Jun. 10) Ceiling cut (Jul.11)

Implementation (Oct. 10)

Foreign Bank Branches’

Arbitrage Incentives Currency Mismatches of FX Banks Foreigners’ Investment in

Bonds

II. Macroprudential Policy Responses

( Policy Responses for Capital Inflows )

9/23

0.0

0.5

1.0

1.5

Jan-11 Apr-11 Jul-11 Oct-11

Arbitrage incentives

Levy rate(short-term)

Moving Avg. of net arbitrage incentive

(%)

Arbitrage incentives before levy Arbitrage incentives

after levy

( Policy Responses for Capital Outflows )

Strengthening of Financial Cooperation:

Backstop against sudden Capital Flow Reversal

• Expansion of Currency Swaps with other central banks (FRB, BOJ, PBC)

• BOK initiated international discussion on G20 Global Financial

Safety Net (GFSN) in 2010, and contributed to launch of CMIM in March 2010

Korea’s Policy Responses to Capital Flow Volatility

10/23

Period of capital inflows (Q2 2009~Q2 2011)

Periods of capital outflows (Q4 2008~Q1 2009, Q3 2011~Q4 2011)

Conventional Currency appreciation

Increases in foreign reserves

Currency depreciation

Decreases in foreign reserves

Unconventional Macroprudential Policy

- Ceilings on FX derivative positions

- Macroprudential Stability Levy

Currency Swaps (FRB in 2008, BOJ

and PBC in 2008 and 2011)

Strengthening of GFSN

These policies differ from Capital Controls, which

differentiate between Residents and Non-residents.

• Price regulations : Macroprudential Stability Levy, imposition of reserve

requirements on foreign currency deposits, etc.

• Quantitative regulations : ceilings on FX position and investment in foreign

currency-denominated assets, regulation of foreign currency loans, etc.

Some Asian EMEs used Capital Controls.

e.g. Prohibition of investment in time deposits with maturities less than 1-year*

(Taiwan, Nov 2009); Restrictions on investment in government bonds and

MMFs* (Taiwan, Nov 2010); Hike in ratio of reserve requirements on non-

residents’ deposits* (Taiwan, Nov 2010)

11/23

Housing indicators (Seoul area) before and after loan regulation tightening1)

1) Comparison between six-month periods before and after strengthening of loan regulations

2) In trillions of won 3) Apartment basis 4) In units of 10,000 * Source: Bank of Korea

Seemingly effective, but more work needed to

establish how much of changes in house price

and loan growth attributable to macroprudential

policy tightening

Mortgage loans2) House prices3) Housing transactions4)

12/26

2 Build-up of Household Debt

Effective

Institutional

Arrangements

for

MPF

13/26

III. Macroprudential Policy Framework (MPF)

in Korea: Institutional Arrangements

Successful Systemic Risk Identification

Timely Use of

Policy Tools

Coordination + Autonomy across Policy Functions

1

2

3

14/26

Financial Stability Policy Framework in Korea

Ex-ante

Macroprudential Policy

Microprudential Policy

Crisis Management

Financial Services Commission (FSC)

Financial Supervisory Service (FSS)

Bank of Korea

Financial Services Commission (FSC)

Financial Supervisory Service (FSS)

BOK: Lender of Last Resort

Korea Deposit Insurance

Corp. (KDIC): Deposit

Insurance and Resolution of FIs

Ministry of Strategy &

Finance (MOSF): FX Policies

and Bail-out

Ex-post

129

%

Policy Coordination among Separate Authorities

“There is no「e pluribus unum」.”

• No formal Organization/Committee dedicated to

Macroprudential Policy

Some Policy Coordination Channels

• Policy Coordination through FSC Meetings:

High-level officials of relevant authorities (BOK, FSS, MOSF and

KDIC) participating as ex officio members

• Various Channels for Information Sharing and

Policy Coordination: e.g. FX Market Stabilization Council, Economic and Financial

Advisory Council, National Economic Advisory Council, etc.

MPF in Korea: Separation (Model 6)

15/26

129

%

16/26

Limitations of Informal Policy Coordination

No Binding Effects of Agreement on Policy

Difficult to identify Agency Accountable for Policy

Responses to Common Systemic Risk

Rivalry or Turf Issues impeding Free Flow of

Information

MPF in Korea: Separation (Model 6)

• Central Bank raises Policy Rate (July 2010)

• Supervisor eases DTI regulation (August 2010)

Counteractive Outcome

1 Counteractive or Push-Me, Pull-You Outcomes

Push-me, pull-you outcome

Lack of Policy Coordination

• Supervisor deploys 「Countercyclical Capital Buffer」

• Central Bank raises Policy Rate

17/26

Cycle Boom Downturn

Macro-

Authority

Credit expansion

⇒ Systemic risk

⇒ Buffer deployed

Credit contraction

⇒ Systemic risk

⇒ Buffer released

Micro-

Authority

-No worry (no mandate for

systemic risk)

-Concern about lowering of FI profitability

by limiting of asset allocation

-Unease. (Why? Lowering of capital

when most needed)

-Concern about negative signaling

effect

Boom Downturn Boom

Countercyclical policy Credit cycle

2 Potential Tensions Between

Micro- and Macroprudential Supervisors

18/26

Build-up of

Common Risks

(Interconnectivity)

Need to Respond

with Macroprudential Policy Tools?

Microprudential

Supervisor

Everything OK

in terms of Individual FI

Health


Micro- and Macroprudential Supervisors

Macroprudential

Supervisor

Concerned about

Interconnectivity

19/23

Coordination Failure

CCB Deployed?

Who should own the Tool?

Central Bank More Focus on Business

Cycle/GDP

Coordination Failure

Microprudential Supervisor may mechanically deploy CCB when credit-to-

GDP ratio rises above its long-term average.

However, Central Bank may tolerate build-up of credit exposures stemming

from increase in money demand for investment entailed by improved

productivity.

Microprudential

Supervisor

More Focus on Credit Cycle

and Individual FI Health


Microprudential Supervisors and Central Bank

Build-up of

Credit Exposures

20/23

0

1,000

2,000

3,000

4,000

5,000

6,000

Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Jul-09 Jan-10 Jul-10

Tightening of LTV

(Oct. 03)

Introduction of DTI

(Aug. 05)

Tightening of DTI

(Feb. 07) Tightening of DTI

(Sep. 09)

( Billion Korean won )

5 Macroprudential Policy Effect Offset: Bounce Back

Mortgage Loan Fluctuations1)

Importance of Communication between Supervisory and Monetary

Authorities

Is Regulation effective under Low Interest Rates + Ample Liquidity?

⇒ Continued risk-taking (returning to mortgage loans)

⇒ Macroprudential policy effects possibly offset, due to monetary

policy stance in opposite direction, and vice versa

21/23

Failure of policy

coordination (Jul. 10)

Central Bank

Government

Supervisors

Application of

Macroprudential

Tools

Application of

Microprudential Tools No Blessing

Systemic Risk?

Shock

Consultation

Way Forward for Separate Framework:

Policy Coordination

22/23

Blessing

Rebuilding Financial Stability Framework:

Amendment of BOK Act (31 Aug, 2011)

23/23

Greater Role in Responding to Systemic Risk

Greater Accountability for Financial Stability

Semiannual Report on Financial Stability (FSR) to National Assembly

Enhanced Access to Microprudential Data Amended Act mandates BOK Access to B/S

info of both Banks and Non-Bank FIs MOU with FSS allowing BOK to Access Wider Range of Microprudential Data

Financial Stability Mandate Re-introduced

Assessment of Systemic Risk a starting point of Financial Stability Policy Framework

Bibliography Angelini, Paolo, Stefano Neri and Fabio Panetta (2011): “ Monetary and macroprudential

policies,” Banca d’Italia working paper.

Bini Smaghi, Lorenzo. (2011): “Macro-prudential supervision and monetary policy—

linkages and demarcation lines” Speech at OeNB annual economic conference, May.

Borio, C. and M. Drehmann (2009): “Towards an operational framework for financial

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Caruana, J. (2010): “Macroprudential policy: working towards a new consensus”,

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Kang, Taesoo and Guonan Ma (2009): “ Credit Card Lending Distress in Korea in 2003”,

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https://www.imf.org/external/np/seminars/eng/2012/macro/pdf/agenda.pdf


http://www.rba.gov.au/publications/confs/2012/bios-2012.html

http://www.kdi.re.kr/upload/7808/a2_3_2.pdf

SOURCE URLs

• http://www.riksbank.se/en/Financial-stability/Macroprudential-Policy-Conference-November-2014/

• http://www.riksbank.se/en/Financial-stability/Macroprudential-Policy-Conference-November-2014/Tae-Soo-Kang/

• http://www.paris-europlace.net/ny2014/RT3_Tae_Soo_Kang.pdf

• https://www.imf.org/external/oap/np/seminars/2012/macroprudential/pdf/IV2Kang.pdf & http://www.imf.org/external/oap/np/seminars/2012/macroprudential/

• https://www.imf.org/external/np/seminars/eng/2012/macro/pdf/kang.pdf

• http://www.koreatimes.co.kr/www/news/biz/2014/03/488_152948.html


http://www.riksbank.se/en/Financial-stability/Macroprudential-Policy-Conference-November-2014/Tae-Soo-Kang/

Economy & Finance

Kang Tae Soo -- Riksbank Macroprudential Conference Stockholm, Sweden, November 2014