Financial Stability Review (FSR) - Bank Indonesia … preparation of the Financial Stability Review (FSR) is one of the avenues through which Bank Indonesia achieves its mission “to

The preparation of the Financial Stability Review (FSR) is one of the avenues

through which Bank Indonesia achieves its mission “to safeguard the stability of the Indonesian

Rupiah by maintaining monetary and financial system stability for sustainable national

economic development”.

Publisher:

Bank Indonesia

Information and Orders:

This edition is published in March 2012 and is based on data and information available as of September 2011,unless stated otherwise.

Source: Bank Indonesia, unless stated otherwise.

The PDF format is downloadable from: http://www.bi.go.id

For inquiries, comments and feedback please contact:

Bank Indonesia

Department of Banking Research and Regulation

Financial System Stability Group

Jl.MH Thamrin No.2, Jakarta, Indonesia

Phone: (+62-21) 381 8902, 381 8075

Fax: (+62-21) 351 8629

Email: [email protected]

FSR is published biannually with the objectives:

To improve public insight in terms of understanding financial system stability.

To evaluate potential risks to financial system stability.

To analyze the developments of and issues within the financial system.

To offer policy recommendations to promote and maintain financial system stability.

Financial Stability Review

( No. 18, March 2012)

Directorate of Banking Research and Regulation

Financial System Stability Bureau

ii

iii

Table of Contents ......................................................................................................................................... ........... iii

Foreword .............. .................................................................................................................................................... vii

Overview ......... ......................................................................................................................................................... 3

Chapter 1. External and Internal Conditions .............................................................................................................. 5

1.1. Potential External Vulnerabilities ............................................................................................................... 7

1.2. Potential Internal Vulnerabilities ................................................................................................................ 8

Box 1.1. Household Behaviour ......................................................................................................................... 14

Chapter 2. Financial System Resilience ....................................................................................................................... 17

2.1. Structure and Resilience of the Financial System ....................................................................................... 19

2.2. Risk in the Banking System ....................................................................................................................... 20

2.3. Potential Financial Market Risk and Financing Risk .................................................................................... 29

Box 2.1 An Upgraded Sovereign Rating and Financial System Stability ............................................................. 38

Chapter 3. Challenges and Prospects of Financial System Stability .............................................................................. 41

3.1. Threat of Global Economic Slowdown on Indonesian Economy ................................................................ 43

3.2. Impact on the Indonesian Financial System ............................................................................................... 47

3.3. Impact on the Banking Sector .................................................................................................................. 48

3.4. The Outlook of the Financial System Stability ............................................................................................ 49

Chapter 4. Topical Issues............................................................................................................................................ 51

4.1. Stress Testing the Impact of International Trade and Foreign Loans of the Corporation on Banks ................. 53

4.2. Strengthening Bank Capital as Part of the Efforts to Maintain Financial System Stability ........................... 56

4.3. Broadening Public Access to Financial Services through Bank Network Expansion ..................................... 58

4.4. European Crisis ........................................................................................................................................ 63

Article ................ ...................................................................................................................................................... 67

Article 1 External Shocks, Macroeconomic Stability, and Monetary Regimes in the Small-open New Keynesian

Model of the Indonesian Economy .................................................................................................... 69

Article 2 Macroprudential and Microprudential Surveillance and Policies .......................................................... 79

Article 3 Determinants of the Household Liquidity Requirement in Indonesia: an Empirical Study with

Data from the Household Balance Sheet Survey ................................................................................ 95

Table of Contents

iv

1.1 Total Indonesian Exports and Imports .............. 71.2 International Commodity Prices (USD) ............. 71.3 Transition in the Share of Indonesia Exports ... 81.4 Confidence Index ........................................... 81.5 Inflation in several ASEAN Countries .............. 81.6 Composition of Direct Investment and Portfolio Investment to Indonesia ................... 91.7 Indonesia Balance of Payments ....................... 91.8 Rupiah Exchange Rate .................................... 91.9 Rupiah Exchange Rate Volatility ...................... 101.10 ROA and ROE of Non-Financial Public Listed Companies ..................................................... 111.11 DER and TL/TA of Non-Financial Public Listed Companies ..................................................... 111.12 Key Corporate Financial Indicators .................. 111.13 Credit and NPL to the Household Sector ......... 121.14 Composition of Credit to the Household Sector by Type (per December 2011) .............. 131.15 Performance of Credit to the Household Sector by Type ............................................... 131.16 NPL in Household Sector by Type ................... 13Figure Box 1.1.1 Composition of Total Household Spending 2009-2011 ..................................... 14Figure Box 1.1.2 Changes in Price (ytd) ..................... 14Figure Box 1.1.3 Sources of Household Debt ............. 15Figure Box 1.1.4 Composition of Household Assets ... 16

2.1 Asset Composition of Financial Institutions ..... 192.2 Financial Stability Index 1996-2011 ................ 202.3 Share of Bank Funding and Financing ............. 202.4 Growth in Deposits by Semester ..................... 202.5 Deposit Growth based on Ownership ............. 212.6 Composition of Bank Liquid Assets ................. 212.7 Share of Bank Placements at Bank Indonesia .. 212.8 Share of Liquid Assets .................................... 222.9 Credit Growth by Currency ............................ 222.10 Credit Funding by Currency ............................ 222.11 Credit Growth by Type ................................... 232.12 Credit Growth by Economic Sector ................. 232.13 Growth and Share of Property Credit ............. 232.14 Non-Performing Loans (NPL) ........................... 232.15 NPL Growth by Currency ................................ 242.16 NPL Ratio by Currency .................................... 24

List of Tables and Figures

Figures

1.1 Government Foreign Debt .............................. 101.2 Government Debt Service Ratio ...................... 101.3 Probability of Default using the Contingent Claims Analysis Method ................................. 12

2.1 Number of Financial Institutions ..................... 212.2 Liquid Assets Growth ..................................... 212.3 Profit/Loss of Banking Industry ....................... 262.4 Profitability and Credit by Bank Group ........... 262.5 Performance of the Prime Lending Rate ............ 282.6 SBN Ownership .............................................. 322.7 Financing sourced from Credit, Shares and Bonds ............................................................ 342.8 Financial Indicators of Finance Companies ...... 362.9 NPL by Type of Finance .................................. 362.10 Insurance Company Investment ...................... 37

3.1 Global Economic Growth Projections .............. 443.2 Simulation of Easing Fuel Subsidies ................ 463.3 Projected GDP and Inflation ........................... 463.4 Stock Exchange Correlations .......................... 48

4.1 Summary of Results for Stress Test 1: Impact on Bank Liquidity ................................ 554.2 Summary of Results for Stress Test 2: Impact on Bank CAR and NPL ........................ 554.3 A Capital Comparison between Prevailing Regulations and the Requirements according to Basel III ...................................................... 574.4 Adoption of Financial Services ........................ 584.5 Access to Financial Services ............................ 59

Tables

v

2.17 NPL Growth by Credit Type ............................ 242.18 NPL Ratio by Credit Type ................................ 252.19 NPL Ratio by Economic Sector ........................ 252.20 NPL Ratio of Property Credit ........................... 252.21 Composition of Bank Profit/Loss ..................... 262.22 Composition of Interest Income for the Banking Industry (%) ...................................... 272.23 Rupiah Interest Rate Spread (%) ..................... 272.24 Bank ROA and BOPO (%) ............................... 272.25 Capital, the Minimum Statutory Reserve and Bank CAR ...................................................... 282.26 CAR by Bank Group (%) ................................ 282.27 MSM Credit Growth (yoy) .............................. 292.28 Non-Performing MSM Bank Loans (%) ........... 292.29 A Map of Financial System Stability ................ 302.30 Non-resident Flows of Shares, Government

Securities (SBN) and Bank Indonesia Certificates (SBI) ............................................. 302.31 SBN Prices by Tenor ........................................ 312.32 FR Benchmark Series SBN Prices ..................... 312.33 SBN VaR by Tenor .......................................... 312.34 SBN Price Volatility ......................................... 312.35 SBN Maturity Profile ....................................... 322.36 The JSX Composite and other Global Price Indices ............................................................ 322.37 The JSX Composite by Sector ......................... 322.38 Share Prices in the Banking Sector .................. 332.39 Stock Market Volatility in the Region .............. 332.40 Volatility on Regional Bourse .......................... 332.41 Mutual Fund by Type ..................................... 332.42 Issuers and Stock Issuances ............................ 342.43 Issuers and Corporate Bond Issuances ............ 342.44 Finance Company Performance ...................... 352.45 Share of Finance Company Financing ............. 352.46 Sources of Funds for Finance Companies ........ 352.47 Market Share of 11 Insurance Companies ...... 38Figure Box 2.1.1 Share of Foreign Ownership in January

2012 .............................................................. 39Figure Box 2.1.2 Inflows of Foreign Ownership to the

Indonesian Financial Market ........................... 393.1 Flows of Private Direct Investment (Net) .......... 443.2 Flows of Private Portfolio Investment (Net) ...... 44

3.3 Composition of Foreign Capital Inflows to Indonesia ....................................................... 453.4 Composition of Foreign Capital Inflows to Indonesia ....................................................... 453.5 Ratio of Credit to GDP in Indonesia, Malaysia, the Philippines and Thailand ............................ 463.6 Long-Term Trend of Credit to GDP ................. 463.7 SUN Price Volatility ......................................... 473.8 Performance of the JSX Composite and other Global-Regional Indices .................................. 473.9 Projected Credit Growth ................................ 493.10 Projected Growth in Deposits (% yoy) ............ 503.11 Financial Stability Index .................................. 50

4.1 Average projected Contraction on European Banks’ Balance Sheets .................... 644.1 European Bank Lending to Emerging Economies (in trillions of US$) ........................ 64

Figures Figures

vi

List of Abbreviations

ADB Asian Development BankAPBN Anggaran Pendapatan dan Belanja NegaraAS Amerika SerikatASEAN Association of Southeast Asian NationsATMR Aktiva Tertimbang Menurut RisikoBapepam- LK Badan Pengawas Pasar Modal dan Lembaga

KeuanganBCBS Basel Committee on Banking SupervisoryBIS Bank for International SettlementBNM Bank Negara MalaysiaBOPO Rasio Biaya Operasional terhadap

Pendapatan OperasionalBPD Bank Pembangunan DaerahBPR Bank Perkreditan RakyatBPRS Bank Perkreditan Rakyat Syariahbps basis pointBRC BPD Regional ChampionBRIC Brazil, Rusia, India, dan ChinaBUS Bank Umum SyariahCAR Capital Adequacy RatioCC Code of ConductCCP Central Counter PartiesCDS Credit Default SwapCRA Credit Rating AgencyCRBC China Banking Regulations CommissionsDER Debt to Equity RatioDPK Dana Pihak KetigaDSM Direktorat Statistik Ekonomi dan MoneterEFSF European Financial Stability FacilityETF Exchange-Traded FundEU European UnionFASB Financial Accounting Standard BoardFDI Foreign Direct InvestmentFSA Financial Service AuthorityFSAP Financial Sector Assessment ProgramFSB Financial Supervisory BoardFSI Financial Stability IndexG20 The Group of TwentyGDP Gross Domestic ProductGIM Gerakan Indonesia MenabungG-SIFI Global Systemically Important Financial

InstitutionsGWM Giro Wajib MinimumIAIS International Association of Insurance

SupervisorIASB International Accounting Standard BoardIDMA Inter-dealer Market AssociationIHK Indeks Harga KonsumenIHSG Indeks Harga Saham Gabungan

IMF International Monetary FundIOSCO International Organization of Securities

CommissionsJCI Jakarta Composite IndexJPSK Jaring Pengaman Sistem KeuanganKCBA Kantor Cabang Bank AsingKI Kredit InvestasiKK Kredit KonsumsiKMK Kredit Modal KerjaKPR Kredit Pemilikan RumahLBU Laporan Bulanan Bank UmumLC Letter of CreditLDR Loan to Deposit RatioL/R Laba RugiMEA Masyarakat Ekonomi ASEANMKM Mikro, Kecil, dan MenengahNAB Nilai Aktiva BersihNII Net Interest IncomeNIM Net Interest MarginNPF Non Performing FinancingNPI Neraca Pembayaran IndonesiaNPL Non Performing LoanOPEC Organization of the Petroleum Exporting

CountriesOTC Over the CounterPD Probability of DefaultPDB Produk Domestik BrutoPDN Posisi Devisa NetoPIIGS Portugal, Ireland, Italy, Greece and SpainPLN Pinjaman Luar NegeriPMA Penanaman Modal AsingPMDN Penanaman Modal Dalam NegeriPMK Peraturan Menteri KeuanganPMK BI Protokol Manajemen Krisis Bank IndonesiaPNS Pegawai Negeri SipilPP Perusahaan PembiayaanRBB Rencana Bisnis BankROA Return on Asset ROE Return on EquitySBDK Suku Bunga Dasar KreditSBI Sertifikat Bank IndonesiaSBN Surat Berharga NegaraSIFI Systemically Important Financial InstitutionsSUN Surat Utang NegaraTKI Tenaga Kerja IndonesiaTL/TA Rasio total kewajiban terhadap total aset TPI Tim Pengendalian InflasiTPID Tim Pengendalian Inflasi DaerahUMP Upah Minimum Provinsi

List of Abbreviations

ADB Asian Development BankAEC Asean Economic CommunityASEAN Association of Southeast Asian NationsBapepam- LK Capital market and Financial Institution

Supervisory BoardBCBS Basel Committee on Banking Supervisory

BIS Bank for International SettlementBEI Indonesia Stock Exchange

BNM Bank Negara MalaysiaBPD Regional Banksbps basis pointsBRC BPD Regional ChampionBRIC Brazil, Rusia, India, dan ChinaCAR Capital Adequacy RatioCC Code of ConductCCP Central Counter PartiesCDS Credit Default SwapCPI Consumer Price IndexCRA Credit Rating AgencyCRBC China Banking Regulations CommissionsDER Debt to Equity RatioEFSF European Financial Stability FacilityETF Exchange-Traded FundEU European UnionFASB Financial Accounting Standard BoardFDI Foreign Direct InvestmentFSA Financial Service AuthorityFSAP Financial Sector Assessment ProgramFSB Financial Supervisory BoardFSI Financial Stability IndexG20 The Group of TwentyGDP Gross Domestic ProductGIM Indonesian Saving MovementG-SIFI Global Systemically Important Financial

InstitutionsIAIS International Association of Insurance

SupervisorIASB International Accounting Standard BoardIDMA Inter-dealer Market AssociationIMF International Monetary FundIOSCO International Organization of Securities

CommissionsIHSG/JSXComposite

Jakarta Stock Exchange Index

JPSK Financial System Safety NetLBU Commercial Bank ReportLC Letter of CreditLDR Loan to Deposit RatioMSM Micro Small and Medium Credit

NII Net Interest IncomeNIM Net Interest MarginNOP Net Open PositionNPF Non Performing FinancingNPL Non Performing LoanOPEC Organization of the Petroleum Exporting

CountriesOTC Over the CounterPBI Bank Indonesia RegulationPD Probability of DefaultPIIGS Portugal, Ireland, Italy, Greece and SpainPMK BI Bank Indonesia’s Crisis Management

Protocol

ROA Return on Asset PUAB Interbank Money Market

ROE Return on EquitySBI Bank Indonesia CertificatesSBN Government SecuritiesSIFI Systemically Important Financial Institutions

SUN Government BondsSSB Securities

TL/TA Total Loss to Total Asset RatioUS United States of America UU Act

vii

Bank Indonesia publishes this 18th Edition of the Financial Stability Review (FSR), March 2012, as a form of

accountability and transparency regarding the task and function of Bank Indonesia in terms of maintaining financial

system stability. The publication is expected to assist stakeholders, particularly financial market players and policymakers,

monitor risk in the financial system at an early stage, while simultaneously helping to mitigate the risk.

This edition of the FSR contains information on financial system stability in Indonesia during the second half of

2011 and how the domestic financial system flourished despite the financial crisis in Europe. Financial system stability

bolstered national economic performance, thus prompting several international rating agencies to upgrade Indonesia’s

sovereign rating to investment grade.

The global economic slowdown and uncertainty surrounding crisis resolution in Europe had the potential to escalate

risk in the banking sector. Notwithstanding, the impact on the banking industry in Indonesia remained relatively limited

due to low exports from Indonesia to Europe as well as low domestic bank exposure to Europe. Meanwhile, banking sector

performance was positive, as reflected by adequate capital and stable profitability. Likewise, the performance of finance

companies also improved dramatically on the back of solid credit growth and the downward interest rate trend.

Nevertheless, vigilance and caution are still required looking forward considering that the direction of the global

economy can change in an instant, thereby exacerbating pressures on financial system stability. The impact of deleveraging

in the European banking sector, the efficacy of risk management and the possibility of mounting volatility on the stock

and bond markets all require closer attention, in addition to debtor performance and potential credit risk as well as an

increase in the intermediation function in productive sectors.

God willing the publication of FSR will always provide useful information to Bank Indonesia’s stakeholders, in particular

that regarding the results of research and monitoring conducted at Bank Indonesia pertinent to financial system stability.

We remain open to comments, recommendations and criticisms from any party in order to improve future editions of

the Financial Stability Review.

Jakarta, March 2012

GOVERNOR OF BANK INDONESIA

Darmin Nasution

Foreword

This page intentionally blank

Overview

1

Overview

2

Overview


Overview

3

Financial system resilience and stability were well

preserved in Semester II 2011 despite encountering

pressure in the middle of the semester. The financial

crisis in Europe continued to overshadow risk in Indonesia

and globally, however, domestic markets and financial

institutions successfully absorbed the risk emanating from

global and domestic shocks. The success of Indonesia in

terms of maintaining financial system stability was clearly

appreciated by a couple of rating agencies, namely Fitch

and Moody’s, who upgraded Indonesia’s sovereign rating

to investment grade. This upgrade will surely translate into

capital for Indonesia in the face of potential risk looking

ahead.

Externally, a slowdown in the global economy

and uncertainty surrounding crisis resolution in

Europe had the potential to amplify risk in the

banking sector. Europe slipping into a moderate recession

as a result of fiscal consolidation, bank deleveraging and

the sovereign debt crisis prompted the IMF and World Bank

to revise down their global economic growth projections

from 4% and 3.6% to 3.25% and 2.8% respectively. Such

conditions undermined global demand and precipitated

a decline in exports from developing countries, including

Indonesia. Notwithstanding, the impact on the domestic

banking industry was limited because Indonesian exports

and exposure to Europe were relatively small. Concerning

foreign capital inflows, investment portfolio to Indonesia

experienced a decline but Foreign Direct Investment (FDI)

surged in line with solid domestic economic prospects.

Domestically, real sector performance was

steady. Global economic shocks had no significant

impact on the corporate sector in Indonesia. The corporate

probability of default indeed increased compared to the

same position in the preceding year with profitability

placed under increasing pressure. Nonetheless, the level of

corporate debt also tended to decline; hence, as a whole,

risk in the corporate sector was well managed. Meanwhile,

public confidence in the economy and the downward

interest rate trend encouraged the household sector

to increase its level of debt and consumption. This was

demonstrated by robust credit growth to the household

sector for mortgages and automotive loans compared to

other types of loan. Although credit performed well in the

reporting period, concerns emerged over the rapid pace

of consumption loans, which has the potential to create

problems at a later date.

The domestic financial market responded well

to pressures in Semester II 2011, fully recovering by

the close of the year. Greater risk aversion from global

investors had an impact on the domestic financial market.

The price of government securities (SBN) experienced

a significant decline before rebounding and stabilising

with monetary operations that concomitantly maintained

stability on the rupiah interbank money market (PUAB).

On the capital market, the JSX Composite and net asset

value (NAV) of mutual funds came under pressure but

market confidence was fully restored by the end of the

year. Financing through the capital market, primarily

Bab 1 Overview

4

Overview

shares, slumped due to the wait-and-see attitude of

potential issuers.

The banking industry and finance companies

performed steadily. Bank capital remained at a level

considered adequate to absorb risk as the global crisis

unfolded. Profitability was stable supported by a decline

in the cost of loan loss provisions as well as a wider net

interest margin for the banks. Meanwhile, rupiah and

foreign exchange credit grew rapidly in nearly all economic

sectors. The performance of finance companies also

improved significantly, the majority of which stemmed

from consumer financing for the purchase of motor

vehicles. This was buttressed by solid credit performance

as well as the downward interest rate trend.

RISK OUTLOOK

The outlook for the financial system in Indonesia

up to Semester I 2012 is more stable compared to

Semester II 2011. If they materialise, the impact of oil

price hikes in semester I 2012 will be felt in the subsequent

semester, while foreign capital flows are expected to

stabilise thus alleviating volatility on the financial market. In

addition, measures to improve prudence are also expected

to ease bank credit risk.

Nevertheless, global economic and political dynamics,

which can change in the blink of an eye, demand greater

prudence. Consequently, the banking sector and financial

market players are expected to:

• Remain alert to the deleveraging process of banks in

Europe, which has the potential to undermine credit

lines as well as USD interbank lending.

• Conduct stress tests and review liquidity contingency

plans in order to mitigate liquidity risk, in particular

for banks that depend heavily on global wholesale

funding.

• Augment risk management and stay alert to the

possibility of mounting volatility on the stock and

bond markets.

• Monitor the performance of borrowers who depend

heavily on trade with countries that are currently

experiencing difficulties.

• Remain alert to the possibility of escalating

consumption credit risk in the household sector and

enhance the intermediation function in productive

sectors.

Caution is advised in terms of maintaining adequate

liquidity amid the apparent trend of slower growth in

deposits and accelerated credit growth.

5

Chapter 1. External and Internal Conditions

Chapter 1External and Internal Conditions

6



7


1.1 POTENTIAL EXTERNAL VULNERABILITIES

Mounting risk from the crisis in Europe has left

future domestic economic growth uncertain. External

risk factors, such as the sovereign debt crisis in the euro zone

and economic slowdowns in developed countries, sparked

risk in the domestic economy. Recent developments in the

euro area have indicated signs of contagion to surrounding

and trade partner countries, primarily through banks and

the economy. Consequently, the IMF revised down its

global economic growth projection from 4% to 3.25%.

The economy of Indonesia responds to changes in external

conditions, therefore, domestic economic activity could

also have experienced a slight contraction.

The economic slowdown was also attributable

to specific problems affecting certain countries.

Japan, for instance, contracted from positive 4% growth

to minus 0.9%, principally as a result of the earthquake in

March 2011. The disaster destroyed physical infrastructure,

thereby disrupting production activity, knocked out

electricity supply from the stricken nuclear power plant

and undermined consumption. Brazil, which had posted

impressive 7.5% growth in 2010, only achieved 2.9% in

2011 due to an array of structural problems that forced

the adoption of a tight monetary policy stance, prudential

policy that curbed credit growth and fiscal policy that failed

to provide economic stimuli.

This turmoil, which shows no signs of abating,

persisted in the form of fiscal policy in the US, while Europe

consistently failed to agree how to overcome the fiscal and

financial problems in financial crisis struck PIIGS countries,

as well as the second bailout for Greece that has still not

been approved by the Greek Parliament. By yearend 2011

several rating agencies downgraded the sovereign ratings

of the US and nine European countries, which spurred

increasingly risk averse sentiment from global investors.

Chapter 1 External and Internal Conditions

Source: Indonesian Financial Statistics, Bank Indonesia


Figure 1.1Total Indonesian Exports and Imports

Figure 1.2International Commodity Prices (USD)

Million USD

-

4.000

2.000

8.000

6.000

12.000

10.000

16.000

14.000

18.000

20.000

Total Export Total Import

Feb-

07A

pr-0

7Ju

n-07

Aug

-07

Oct

-07

Dec

-07

Feb-

08A

pr-0

8Ju

n-08

Aug

-08

Oct

-08

Dec

-08

Feb-

09A

pr-0

9Ju

n-09

Aug

-09

Oct

-09

Dec

-09

Feb-

10A

pr-1

0Ju

n-10

Aug

-10

Oct

-10

Dec

-10

Feb-

11A

pr-1

1Ju

n-11

Aug

-11

Oct

-11

Dec

-11

0

200

400

600

800

1000

1200

1400

Dec-

06M

ar-0

7Ju

n-07

Sep-

07De

c-07

Mar

-08

Jun-

08Se

p-08

Dec-

08M

ar-0

9Ju

n-09

Sep-

09De

c-09

Mar

-10

Jun-

10Se

p-10

Dec-

10M

ar-1

1Ju

n-11

Sep-

11De

c-11

0

50

100

150

200

250

Natural Gas Palm Oil Coal (right) Crude Oil (right)

8


Source: Survey conducted by the Directorate of Economic and Monetary Statistics, Bank Indonesia


Source: Bloomberg

6.10% posted in 2010, on the back of public confidence

and business player confidence. This was further

corroborated by the increase in the consumer confidence

index1 in December 2011, which peaked at its highest level

in three years, namely 116.6 (Figure 1.4).

Figure 1.5Inflation in several ASEAN Countries

Figure 1.4Confidence Index

Figure 1.3Transition in the Share of Indonesia Exports

0%

5%

10%

15%

20%

25%

Japan China India ASEAN US Europe Others

2000 2005 2011

Consumer Confidence IndexCurrent Economic Conditions IndexConsumer Expectations Index

(Index)140

130

120

110

100

90

80

70

60 1 2 3 4 5 6 7 8 9 10 11 12

2009

1 2 3 4 5 6 7 8 9 10 11 12

2010

1 2 3 4 5 6 7 8 9 10 11 12

2011

Average weightedfor 18 cities

-6

-2

-4

2

0

4

6

10

8

14

yoy (%)

12

Jan

- 07

Apr -

07

Jun

- 07

Oct -

07

Jan

- 08

Apr -

08

Jun

- 08

Oct -

08

Jan

- 09

Apr -

09

Jun

- 09

Oct -

09

Jan

- 10

Apr -

10

Jun

- 10

Oct -

10

Jan

- 11

Apr -

11

Jun

- 11

Oct -

11

Philippines Malaysia Thailand Indonesia

1 Based on the results of the 2011 BI Consumer Survey.

1.2 POTENTIAL INTERNAL VULNERABILITIES

1.2.1 Macroeconomic Conditions and the Real Sector

Although not as high as the preceding year, the

performance of exports from Indonesia remained

positive. Based on Bank Indonesia data, during Semester

II 2011 exports from Indonesia grew by 6%, totalling

USD 201.5 billion for the year, which is up by 27.5% on

the previous year. Imports in Semester II 2011 also grew

more slowly compared to the previous semester at 10%,

achieving USD 166.1 billion (fob) for the year, which is

an increase of 30% over the preceding year. The decline

in exports was chiefly due to a slump in the commodity

prices of mainstay exports from Indonesia like palm oil,

crude oil and coal.

Slower export growth has already begun to

affect Indonesia but on a relatively small scale. The

rise in imports exceeded the rise in exports, thereby eroding

the current account surplus at the end of Semester II 2011

compared to the previous semester (Figure 1.1 and Figure

1.2). Posting a surplus amid the recession in Europe was

possible by increasingly diversified export destinations from

Indonesia, with the current trend of favouring emerging

market countries (Figure 1.3).

Low inflation helped catalyse business activity. In

terms of prices, headline inflation in Semester II 2011

tended to ease well below the inflation target of 5%

±1. Headline inflation was 3.79% (yoy) at the end of

the semester (Figure). A downward inflation trend was

reported in many countries; however, Indonesia remained

as the country with the highest level of inflation in

ASEAN-5.

Solid international trade and strong domestic

consumption buoyed economic growth. Six point five

percentgrowth was achievedin 2011, which exceeded the

9


in Indonesia increased on the previous year from 47% to

76%, while the portion of portfolio investment contracted

from 53% to 24% (Figure 1.6). The sectors that enjoyed

the most additional direct investment in Semester II 2011

were the manufacturing sector totalling USD 529 million,

real estate, leasing and business services with USD 369

million and the agricultural sector amounting to USD 92

million.

The balance of payments recorded a surplus of

US$11.9 billion overall for the year despite relatively

intense pressures in Semester II. Foreign exchange reserves

in Indonesia at the end of Semester II 2011 amounted to

USD 110.12 billion, which is equivalent to 6.4 months of

imports and government foreign debt repayments. This

figure is smaller than the position recorded at the end of

Semester I 2011, namely USD 119.7 billion but larger than

yearend 2010 at USD 96.2 billion.

Market risk had the potential to escalate due to

the weak rupiah coupled with mounting exchange rate

volatility. In harmony with the balance of payments, the

rupiah exchange rate depreciated by around 114 points

compared to the previous semester to a level of Rp8,825

per USD (Figure 1.8) at the end of 2011. Furthermore,

average exchange rate volatility was also more pronounced

compared to the previous semester, increasing from 0.18%

(Figure 1.9) to 0.25%.

1.2.2 Investment and the Balance of Payments

The impact of a decline in portfolio investment

growth on the financial market required close monitoring.

Investment flows into Indonesia in Semester II 2011 were

negative, indicating investment outflow totalling USD 5.4

billion. The torrent of investment outflow was due to risk

averse global investors appearing in the second half of

2011 following prolonged and widespread uncertainty

surrounding the fiscal problems in Greece and the languid

recovery in the US. Notwithstanding, overall in 2011

investment flowing into Indonesia remained positive

amounting to USD 14 billion; down 47.2% on the previous

year.


Figure 1.6Composition of Direct Investment and Portfolio

Investment to Indonesia

Figure 1.7Indonesia Balance of Payments

0%

20%

30%

10%

40%

50%

70%

60%

90%

80%

2005 2006

Direct Investment Portfolio Investment

2007 2008 2009 2010 2011

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1*Q2*Q3*Q4*

2006 2007 2008 2009 2010 2011

-10000

-5000

0

5000

10000

15000

FDI PI Other Investment Financial Account

Direct investment is expected to drive economic

activity and the financial market. Based on share, the

share of direct investment (FDI) against total investment Source: Bloomberg, processed

Figure 1.8Rupiah Exchange Rate

0

2.000

4.000

6.000

8.000

10.000

12.000

14.000

0

2.000

4.000

6.000

8.000

10.000

12.000

14.000

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12

2008 2009 2010 2011

Monthly Average Quarterly Average Semesterly Average

10


The government debt to service ratio increased

slightly but the government implemented measures

to gradually reduce its debt while simultaneously

seeking low-risk sources of finance. Pressures from a

slowdown in exports also undermined the debt to service

ratio of Indonesia from 22.5% to 27.3% (Table 1.2). The

upgraded rating affirmed for Indonesia at the end of 2011

is expected to encourage the return of investment flows,

thereby meeting the domestic requirement for foreign

exchange. The ratio of debt to GDP dropped to 25% in

2011 and is scheduled to slide further to 22% in 2014.

Source: Bloomberg, processed


Figure 1.9Rupiah Exchange Rate Volatility

1.2.3 Condition of the Public Sector

The budget deficit remained below the safe

threshold of 3% of GDP. The state budget (APBN) for

Semester II 2011 posted a deficit of Rp88.3 trillion (2.1%

of GDP), far below the target deficit of Rp150.8 trillion.

A reduction in the budget deficit was possible through

the higher-than-expected collection of non-tax revenues,

while central government spending in 2011 only reached

96.7% of the 2011 APBN-P.

The smaller deficit provided the government

leeway to reduce domestic and foreign debt, thereby

reinforcing fiscal posture in terms of stimulating

development. At the end of Quarter III 2011 government

foreign debt had reached USD 112.96 billion; equivalent

to Rp1,002 trillion at a rate of Rp8,875/1USD.

Amid ubiquitous uncertainty surrounding global

economic conditions, the government needs to create

- 1,5

- 1

- 0,5

0

0.5

1

1.5

Volatility

Lower Limit

1 31 61 91 121 151 181 211 241 271

Upper Limit Actual

253 days Period

Table 1.1Government Foreign Debt

Dec-09 Nov-11Jun-10 Dec-10 Jun-11

Central

Government 90.853 97.571 106.860 114.887 112.962

Monetary

Authority 8.412 8.126 11.764 13.222 10.272

Total 99.265 105.697 118.624 128.109 123.234

millions of USD

Table 1.2Government Debt Service Ratio

Q-I Q-I

2010 2011

Q-II Q-IIQ-III Q-IIIQ-IV Q-IV

Foreign Exchange Reserves 71.823 76.321 86.551 96.207 105.709 119.655 114.503 110.123

In months of imports and foreign

debt repayments 6,7 6,0 6,9 7,2 7,4 7,2 7,1 6,4

Debt Service Ratio (%) 21,2% 23,2% 20,3% 23,7% 18,0% 22,5% 21,2% 27,3%

a more enabling environment for domestic economic

growth, which can be achieved through greater

government spending, particularly that which enhances

the investment climate and boosts the income of the

general public.

11


1.2.4 Risk in the Corporate Sector

Entrepreneurs remained optimistic amid

uncertain product sales. Controlled inflationary

pressures and maintained exchange rate stability raised

the optimism of business players regarding the upcoming

six months as reflected by the Business Activity Survey

(Quarter IV 2011). Nonetheless, the global economic crisis

and the slowdown in international trade activity did have

an adverse impact on the performance of non-financial

public listed companies, as evidenced by the declines in

ROA and ROE in Quarter III 2011 when compared to the

same period in the previous year. In comparison to Quarter

III 2010, ROA decreased from 2.23% to 2.15% in Quarter

III 2011, representing a 3.31% (yoy) decline. Meanwhile,

ROE dropped from 4.54% in Quarter III 2010 to 4.12%

in Quarter III 2011 (Figure 1.10).

Concerning financing, the corporate sector

chose to rely more on internal funding sources, while

tending to shy away from bank loans and issuing

securities. This is observable from the downward trends

in the Debt to Equity Ratio (DER) from 1.04 (Quarter III

2010) to 0.91 (Quarter III 2011) and total liabilities to total

assets (TL/TA) in Quarter III 2011 compared to Quarter III

2010 (Figure 1.11).

Corporate profitability decreased but liquidity

remained adequate. Several operational indicators also

displayed signs of weaker profitability. For instance, the

collection period increased moderately from 0.36 (Quarter

III 2010) to 0.38 (Quarter III 2011) indicating that the

receipt of cash took slightly longer and the inventory turn

over ratio decreased to 1.81 (Quarter III 2011) denoting

a drop in sales figures. Corporate liquidity, however,

improved with an increase in the current ratio from 149%

(Quarter III 2010) to 153% (Quarter III 2011).

Source: Bloomberg

Figure 1.10ROA and ROE of Non-Financial Public Listed

Companies

-200

-100

0

100

200

300

400

- 0

-200

-100

100

200

300

400

Q I

Q II

Q II

IQ

IV Q I

Q II

Q II

IQ

IV Q I

Q II

Q II

IQ

IV Q I

Q II

Q II

IQ

IV Q I

Q II

Q II

IQ

IV Q I

Q II

Q II

I

Q II

Q II

I

Q IV Q

I

2005 2006 2007 2008 2009 2010 2011

% yoy% yoy

ROA(left scale)ROE (right scale)

Source: Bloomberg

Figure 1.11DER and TL/TA of Non-Financial Public Listed

Companies

0,60

0,00

0,20

0,40

0,80

1,00

1,20

1,40

Q I

Q II

Q II

IQ

IV Q I

Q II

Q II

IQ

IV Q I

Q II

Q II

IQ

IV Q I

Q II

Q II

IQ

IV Q I

Q II

Q II

IQ

IV Q I

Q II

Q II

I

Q II

Q II

I

Q IV Q

I

2005 2006 2007 2008 2009 2010 2011

DER TL/TA

Figure 1.12Key Corporate Financial Indicators

0123456

ROA

ROE

Inventory Turn Over

DER

2010:Q

2011:Q


12


Looking ahead, the performance of the

corporate sector is expected to grow positively on

the back of robust purchasing power and strong

domestic demand. The most salient vulnerabilities

that require anticipatory measures from the corporate

sector are, among others, credit risk and exchange rate

risk. The expected probability of default in one year for

non-financial public listed companies in Quarter III 2011

was 2.44%,which is higher than that posted in the same

quarter of the previous year at 2.31% (Table 1.3).

The impact of global economic uncertainty on

international trade and corporate offshore loans on the

banking sector remained relatively insignificant (Box

1.1). However, close monitoring is required of corporate

vulnerability considering that conditions change in real

time and often without warning making them difficult

to predict.

1.2.5 Conditions in the Household Sector

Consumer optimism concerning current

economic conditions helped spur an increase in the

consumer confidence index. The Consumer Confidence

Index (CCI) followed an upward trend throughout Semester

II 2011, peaking at its highest point since 2009 and driven

by consumer optimism in current economic conditions. Up

until the time of writing, CCI had rallied by 2.6 points to

119.2 in January 2012.

Household credit growth with lower NPL.

Bank loans to the household sector continued to follow

an acclivitous trend, achieving 33.23% (yoy) growth

in December 2011 amounting to Rp422.9 trillion.

Concomitantly, non-performing loans (NPL) mirrored a

downward trend with a relatively low ratio of 1.42% in

December 2011.

Table 1.3Probability of Default using the Contingent Claims Analysis Method

2009Q3

Sector 2009Q4

2010Q1

2011Q1

2010Q2

2011Q2

2010Q3

2011Q3

2010Q4

Agriculture 5,43% 2,51% 1,77% 1,16% 0,92% 0,72% 2,37% 2,01% 0,00%

Basic Industry 5,30% 3,48% 3,23% 2,91% 2,40% 2,62% 1,70% 0,89% 2,49%

Consumer Goods Industry 2,93% 2,95% 1,50% 1,45% 0,39% 0,85% 1,15% 0,62% 0,89%

Infrastructure 5,23% 3,09% 1,73% 0,90% 0,99% 1,01% 0,96% 0,79% 0,25%

Miscellaneous Industry 5,74% 5,23% 3,09% 3,88% 3,49% 1,63% 2,18% 6,23% 6,63%

Mining 3,42% 2,98% 1,75% 1,70% 2,14% 2,11% 1,72% 0,77% 1,38%

Property 5,35% 3,09% 2,29% 2,20% 1,79% 1,62% 1,70% 0,88% 0,00%

Trade 7,83% 7,23% 3,96% 4,71% 4,82% 4,69% 4,88% 2,84% 2,78%

Agregate

(total corporation) 5,25% 3,70% 2,52% 2,48% 2,31% 2,25% 2,38% 1,78% 2,44%

*) The Contingent Claims Analysis method is used to calculate the probability of defaultSource: Bloomberg

Source: Periodic commercial bank reports

Figure 1.13Credit and NPL to the Household Sector

0,00%

0,50%

1,00%

1,50%

2,00%

2,50%

3,00%

3,50%

4,00%

50

100

150

200

250

300

350

400

450

Jan

10Fe

b10

Mar

10A

pr10

May

10Ju

n10

Jul1

0A

ug10

Sep

10O

ct10

Nop

10De

c10

Jan

11Fe

b11

Mar

11A

pr11

May

11Ju

n11

Jul1

1A

ug11

Sep

11O

ct11

Nop

11De

c11

% NPLTrillion

Credit RT (left scale) NPL (right scale)

Greater consumer confidence and additional

rupiah liquidity from capital outflows fostered solid

credit growth, especially in the consumption sector.

13


Based on type, most credit to the household sector

(46.68%) was in the form of mortgages, followed by

motor vehicle loans (24.99%), multipurpose loans (24.9%)

and others. The upward growth trend for mortgages and

motor vehicle loans outpaced that of bank loans in general.

Referring to the position in December 2011 for instance,

mortgages grew by 34% (yoy), while bank loans only

achieved 23% (yoy). In fact, motor vehicle loans grew by

an impressive 62.2% on the previous year. Although the

NPL ratio for mortgages and motor vehicle loans remained

relatively low, more specifically at 0.9% and 0.8%

respectively in December 2011, the current downward

interest rate trend together with more widespread public

optimism regarding economic conditions have led to

concerns over excessive public euphoria when applying

for consumption loans. This is possible due to pragmatic

bank behaviour in favouring the allocation of consumption

credit. Countercyclical measurement should be considered

to prevent this, which can curb excessively rapid growth

in mortgages and motor vehicle loans.


Figure 1.14Composition of Credit to the Household Sector by

Type (per December 2011)

Housing46,68%

motor vehicle24,99%

household appliances0,58%

Multipurpose24,90%

Others2,86%


Figure 1.15Performance of Credit to the Household Sector

by Type

-

50

100

150

200

250

Jan

10Fe

b10

Mar

10A

pr10

May

10Ju

n10

Jul1

0A

ug10

Sep

10O

ct10

Nop

10De

c10

Jan

11Fe

b11

Mar

11A

pr11

May

11Ju

n11

Jul1

1A

ug11

Sep

11O

ct11

Nop

11De

c11

Trillion Rupiah

Housing Motor vehicle Household appliances Multipurpose Others

Sumber: LBU

Grafik 1.16NPL in Household Sector by Type

10 10 10 10 10 10 10 10 10 10 10 10 11 11 11 11 11 11 11 11 11 11 11 11

Percent

0,0%

1,0%

2,0%

3,0%

4,0%

5,0%

6,0%

7,0%

8,0%

9,0%

Jan

Feb

Mar

Apr

May Jun Jul

Aug Se

pO

ctNo

pDe

cJa

nFe

bM

arA

prM

ay Jun Jul

Aug Se

pO

ctNo

pDe

c

Housing Motor vehicle Household appliances Multipurpose Others

14


Household Behaviour

Since 2007, Bank Indonesia has routinely

conducted an annual survey of household balance

sheets (Survei NRT). The survey is performed because

economic dynamics and financial system stability in a

country are not merely influenced by macroeconomic

variables but also by specific household factors like

spending, debt and assets.

1. Spending

prices of basic necessities increased, households tended

to allocate spending to basic needs while reducing

spending on non-essential items2. Conversely, in the

event of lower prices the household sector tended to

spend more on non-essential items. This trend can

be observed from a couple of surveys conducted by

Bank Indonesia. In 2010 when food prices soared,

the portion of spending on staple foods increased

from 30% to 33% while non-essential consumption

declined.

In 2011, the share of spending allocated

to basic necessities, in particular food staples

and transportation, declined again. An increase

in spending on basic necessitieswas only reported for

clothing and fashion, as a result of a significant hike

in the price of clothing from 1.85% (2010) to 3.63%

(2011).

Figure Box 1.1.1Composition of Total Household Spending

2009-2011

Food

2009

Wealth accumulation

Transportation, vehiclemaintenance, fuelDebt repaymentsEducationOthers

Food

2010

Debt repayments

Transportation, vehiclemaintenance, fuelElectricity, water,communicationsEducationOthers

Food

2011

Debt repayments

EducationClothing and FashionElectricity, waterOthers

The household sector remained sufficiently

flexible in terms of adjusting its composition of

spending when faced with price hikes. When the

Figure Box 1.1.2 Changes in Price (ytd)

Source: Survey of Household Balance Sheets

Percent

-6,00

-4,00

-2,00

0,00

2,00

4,00

6,00

8,00

2009 2010 2011

Foodstuffs Processed foodsHouses, electricity, water, gas ClothingHealth Education and recreation

Transportation andcommunications

2 Basic Necessities: Clothing, food, housing, transportation, electricity and water. Everything else is considered a non-essential item.

15


More moderate food price hikescompared to

2010 as well as easing inflationary pressures in Semester

II 2011 were addressed by the household sector with

increased spending on non-essential items. Most

growth in spending on non-essential items affected

the celebration of religious festivities and vacations,

which increased by 25.85%, followed by the purchase

of motor vehicles (17%) and the purchase of durable

household goods that could be resold(14%).

The increase in spending on clothing and fashion,

motor vehicles and durable household appliances is

thought to be the result of lower interest rates as well

as increased public optimism regarding the domestic

economy. This is congruous with the results of the

consumer confidence index (CCI) survey, which showed

that in December 2011 CCI peaked at 116.6, its highest

level for the past three years.

2. Debt

The level of household debt increased, which

necessitated close monitoring of corresponding

potential credit risk. Greater consumption was

overshadowed by a larger debt burden, hence spending

on debt repayments increased from 8% in 2009 and

2010 to 10% in 2011. Based on consumption, debt

from financial institutions, mainly banks, increased

significantly from 33.4% (2010) to 41% (2011). Debt

from bon-bank financial institutions remained relatively

stable at around 32.3%. However, debt from non-

financial institutions declined most significantly from

49.2% (2009) to 33.9% (2010) and then to 26.7% in

2011. This shows that the level of financial inclusion

attributable to banks is increasing.

Figure Box 1.1.3 Sources of Household Debt


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

30,9% 33,4%41,0%

19,9%32,7%

32,3%

49,2%33,9% 26,7%

NLK LKNB LKB

Persen

2009 2010 2011

3. Assets

Household assets were still dominated by

fixed assets but with a declining ratio. Based on

composition, the majority of household assets are fixed

assets3, although the share did decline from 88.79%

(2009) to 84.74% in 2011. This was primarily the result

of growth in current assets, including cash, savings,

checking accounts, term deposits, gold, jewellery,

receivables, household nondurablesand livestock. The

composition of current assets has increased since 2009,

namely from 9.55% in 2009 to 14.04% in 2011.

Household debt repayment capacity remained

within the safe threshold. Holistically, the increase

in household debt was accompanied by significant

growth in assets; therefore the debt to assets ratio

(DAR) decreased from 3.78% (2010) to 3.68% (2011).

Nonetheless, as the increase in debt was not offset by an

increase in income, the debt service ratio (DSR) jumped

from 9.29% (2010) to 14.05% (2011). Hitherto, no

specific threshold values for DAR and DSR have been

given that are deemed safe. Canada uses a threshold

3 Fixed assets include houses, land, motor vehicles and durable household appliances, including clothing /fashion.

16


of 80% for DAR, which is categorised as high, while

Davaney (1994) used a benchmark DSR of 30%.

The current persistent downward interest rate

trend has stimulated public consumption as reflected

by an increase in certain types of consumption credit

that far outpaced that of credit growth in general.

Accordingly, appropriate macroprudential policy

is required to ease the rate of consumption credit

growth.

Figure Box 1.1.4 Composition of Household Assets


Percent

2009 2010 2011

9,55% 10,86% 13,38%0,11% 0,41%0,34%1,09% 0,24%0,25%

88,79% 88,27% 85,46%

0,47% 0,22% 0,60%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Other Assets Fixed assetsInvestment

Restricted assets, Current assets

17

Chapter 2. Financial System Resilience

Chapter 2Financial System Resilience

18



19


The escalating business activity of other financial

institutions and banks as well as their interconnectedness

required monitoring in the context of systemic risk. The

total number of banks remained few but their assets large

and their relationship with other financial institutions, like

finance companies, was based on prudence.

Financial sector resilience was well maintained

during Semester II 2011, as reflected by the Financial

Stability Index (FSI), which dropped from 1.65 (June 2011)

to 1.63 (December 2011), which was below the projected

level of 1.68. The decline in FSI was due to relatively strong

bank resilience and less bank risk as well as an easing of

pressures on the stock and capital markets.

76.90

1.17

9.41

2.75 6.13

0.06 0.65

3.43 0.06

0.43 Commercial Banks

Rural Banks

Insurance

Pension Funds

Finance Companies

Capital Venture Firms

Securities

Mutual Funds

Credit Guarantee Company

Pawn Broker

Financial System Resilience

2.1 STRUCTURE AND RESILIENCE OF THE

FINANCIAL SYSTEM

With a share accounting for 78.07%, the banking

industry continued to dominate the financial system in

Indonesia. Compared to the share in Semester I 2011

amounting to 78.15%, the contraction was due ostensibly

to asset growth by finance companies, mutual funds and

pension funds. The expanding share of finance companies,

among others, was due to strong public demand for

motor vehicle loans submitted through finance companies.

Looking ahead, the role of non-bank financial institutions

in Indonesia is expected to expand through financial

deepening.

Sumber: Bank Indonesia, Kementerian Keuangan

Figure 2.1Asset Composition of Financial Institutions

Institutions Number

Tabel 2.1Number of Financial Institutions

Commercial Banks 120

Rural Banks 1.669

Insurance 141

Pension Funds 272

Finance Companies 194

Capital Venture Firms 71

Securities 147

Mutual Funds 647

Credit Guarantee Company 4

Pawn Broker 1

1) per Q1 2011 2) per Dec 2010 3) 25 Nov 2011 4) July 2011

20


2.2. RISK IN THE BANKING SYSTEM

2.2.1. Funding and Liquidity Risk

Deposits

Deposits continued to dominate the funding

structure of banks. Up to Semester II 2011, the share

of deposits continued to dominate the banks’ sources of

funds, accounting for 94.27% compared to 87.99% in

the previous semester. Interbank funds only contributed

2.76% (down on the preceding semester at 5.84%),

while the other components contributed little amounting

to 1.10% from loans, 0.79% from SSB, other liabilities

with 0.74% and liabilities to Bank Indonesia and security

deposits accounting for 0.17% each. Solid growth in

deposits had a favourable impact on bank liquidity.

Deposits recorded solid growth in line with

that posted over the past few years. Deposits grew

to Rp346.90 trillion or by 14.23% in Semester II 2011,

which is a three-fold increase on the position in Semester

I 2011 at Rp99.19 trillion or 4.24%. This increase is in

harmony with the trend over the past few years, namely

an acceleration in deposit growth at the end of the year

due mainly to the realisation of the state budget by the

government.

Figure 2.2Financial Stability Index 1996-2011

94,27%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Funding Placements

DPK

Antar Bank 2,76%

Credit64,12%

SSB 6,91%

BI6,91%

0

100

50

250

200

150

300

350

400

0

6%

4%

2%

12%

10%

8%

14%

16%

Sem II - 08 sem I - 09 Sem II - 09 Sem I - 10 Sem II - 10 Sem I - 11

Rp T

growth in nominal - left scale growth in % - right scale

Figure 2.3Share of Bank Funding and Financing

Figure 2.4Growth in Deposits by Semester

From ownership standpoint, growth in deposits

relied more on stable individuals. Strongest growth

was reported for private individuals with Rp224.08 trillion

or 16.11% followed by private companies amounting to

Rp100.15 trillion or 18.70%. Conversely, local government

experienced a 41.29% decline subsequent to posting

120.67% growth.

Based on component, all components of deposits

increased with savings and term deposits performing

best at Rp144.62 trillion (19.19%) and Rp126.63 trillion

(11.44%) respectively. Checking accounts and term

deposits had been the most dominant in the previous

semester with 7.68% and 3.51% respectively. The increase

in savings and term deposits indicated the proclivity of

the general public to favour investments with an assured

yield, as well as the high level of public confidence in the

stability of the Indonesian economy.

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

1996

M01

1996

M07

1997

M01

1997

M07

1998

M01

1998

M07

1999

M01

1999

M07

2000

M01

2000

M07

2001

M01

2001

M07

2002

M01

2002

M07

2003

M01

2003

M07

2004

M01

2004

M07

2005

M01

2005

M07

2006

M01

2006

M07

2007

M01

2007

M07

2008

M01

2008

M07

2009

M01

2009

M07

2010

M01

2010

M07

2011

M01

2011

M07

Des 2011 : 1,65

Asia Financial Crisis

1997/1998: 3,23

Mini Crisis Global Crisis (Nov 2008): 2,432005: 2,33

FSI 1996 - 2011

21


0

250

200

150

100

50

-50

-100

Centr

al Go

vernm

ent

Local

Gov

ernme

ntPri

vate i

ndivid

uals

Privat

e - Fin

ancia

l Instit

ution

sPri

vate C

ompa

nies

Othe

r priv

ate

Non-r

eside

nts

Rp T

semester I 2011 semester II 2010

Figure 2.5Deposit Growth based on Ownership

Primary ReservesTertiary Reserve

Secondary ReserveLiquid Assets (right)

0

600

Rp T Rp T

400

200

1,100

1,000

900

800

700

600

Dec

- 1

0

Jan -

11

Feb -

11

Mar

- 1

1

Apr

- 11

Mey

- 1

1

Jun -

11

Aug -

11

Sep -

11

Oct

- 1

1

Nov

- 11

Dec

- 1

1

Jul -

11

Figure 2.6Composition of Bank Liquid Assets

Table 2.2Total Number of Financial Institutions

Growth ytdDec

2011(Rp T)

Nominal(Rp T)

Nominal(Rp T)

% %

Growth yoy

Primary Reserves 314.09 37.78 13.67 87.55 38.65

Secondary Reserves 663.41 114.67 20.90 96.80 17.08

Tertiary Reserves 69.24 (3.12) (4.32) (4.76) (6.43)

Total 1,046.74 149.32 16.64 179.59 20.71

* The components of liquid assets above has not exclude primary reserve obligation

Based on currency, growth in deposits was

contributed by those denominated in rupiah as well as

foreign currency. Rupiah deposits grew during the reporting

semester to Rp305.50 trillion or 88.06% of total growth

in deposits, while dollar deposits accounted for Rp41.40

trillion or 11.94% of the total. This increase in dollar deposits

exceeded the Rp3.26 trillion contraction experienced in the

previous semester.

Liquidity Risk

The growth in liquid assets (16.64%) outpaced

that of deposits (14.23%). Total bank liquid assets

increased by 16.64% in Semester II 2011 to Rp1,046.74

trillion. The growth in liquid assets stemmed primarily from

the increase in secondary reserves consisting of SBI, other

placements at Bank Indonesia, Trading SUN and available-

for-sale SUN making up 20.90% and an increase in primary

reserves comprising of cash and checking accounts held

at Bank Indonesia amounting to 13,67%. Meanwhile,

the banks’ tertiary reserves declined in Semester II 2011

by 4.32%.

The increase in bank secondary reserves was

principally due to an increase in other placements at

Bank Indonesia (consisting of the Deposit Facility and Call

Money) and increases in Trading SUN.

BI Checking Account Placements in other BI instrumentsSBI

0%

100%

Rp T

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

Dec-1

0

Jan-1

1

Feb-

11

Mar-

11

Apr-1

1

May

-11

Jun-

11

Jul-1

1

Aug-1

1

Sep-

11

Oct-11

Nov-1

1

Dec-1

1

Figure 2.7Share of Bank Placements at Bank Indonesia

22


Bank liquidity remained adequate to meet the

corresponding liabilities. The AL/NCD ratio increased

from 182.34% to 184.70% compared to the position

at the end of Semester I 2011. This was due chiefly to

a significant increase in liquid assets in Semester II 2011

despite an uneven spread of liquidity and funds. The

majority of liquid assets and deposits were held by 14 large

banks with a share accounting for more than 70%, while

116 other banks shared less than 30% between them.

In terms of liquidity risk, the level of liquid

assets held to anticipate deposit withdrawals was

adequate. Based on the results of stress tests, no individual

bank had the potential to experience liquidity shortfalls

under a scenario of a 5% decline in deposits (during the

2008 crisis average deposit withdrawals reached 5%).

Meanwhile, when compared to conditions at the end of

December 2008, the position of individual banks in terms

of covering the withdrawal of non-core deposits continued

to improve. In this context, there remained many banks

with a ratio of liquid assets to non-core deposits in excess

of 100% and not one bank had a ratio below 50%.

2.2.2. Credit Risk and Performance

Credit Performance

Bank loans to productive sectors increased.

Credit grew by 12.78% in the second semester of 2011 or

24.59% for the year (yoy), which exceeded that recorded

in the same semester of the preceding year at 11.3%.

The acceleration in credit growth in Semester II 2011 was

linked to increasingly conducive economic conditions that

allowed the banks to allocate more credit, especially to

productive sectors.

Foreign exchange denominated credit grew

rapidly by 16.2%, up on the previous semester.

Rapid forex credit growth has endured since Semester II

2010, which seemed inextricably linked to the trend of

rupiah appreciation. Consequently, banks are urged to

remain cautious of risks stemming from a weaker rupiah

that could undermine the debt repayment capacity of

borrowers and eventually lead to non-performing loans.

Forex credit was financed in Semester II 2011 by liquidating

86%

7%

4% 3%1%

1_mo

1_3_mo

3_6_mo

6_12_mo

12_mo

50,5

(29,7)

8,3

Loans

Interbank (Net)

Placement at BI

(3,6)

(5,5)

41,4

(40)(20) 0 20 40 60

Other Liabilities

Borrowing

Total Deposits

Rp T

Figure 2.10Credit Funding by Currency

Figure 2.9Credit Growth by Currency

9.7%

21.0%

11.3%9.9%

13.6%

10.5%12.1%

16.2%

12.8%

0%

5%

10%

15%

20%

25%

Rupiah FX Total

sem II/10 sem I/11 sem II/11

Liquid Assetsof 14 Large Bank

73%

Other BankLiquid Unit

27%

Deposits of14 Large Bank72%

Other BankDeposits

28%

Share of liquid assetsin the banking industry

Share of Funds inthe banking industry

Figure 2.8Share of Liquid Assets

23


interbank foreign exchange funds that tended to be short

term in nature, while foreign exchange deposits actually

experienced positive growth. Unstable global economic

conditions stemming from the protracted debt crisis in

Europe and the slowdown in the US encouraged bankers to

opt for foreign exchange funds to finance domestic credit

allocation. Therefore, the banking sector must remain

vigilant of such funding sources due to the possibility of

a mismatch, which has the potential to trigger additional

losses in the exchange rate.

The role of credit to productive sectors was

relatively dominant during Semester II 2011.

Compared to the prior semester, investment credit grew

by 14.1% to Rp464.3 trillion, working capital credit grew

by 13.6% to Rp1,068.7 trillion, and consumption credit

by 10.6% to Rp667.12 trillion. Solid investment credit

growth is expected to benefit the real sector and contribute

to national economic growth. Nevertheless, the banking

15.8%

6.8%

13.6%

3.5%

16.8%

14.1%

9.7%

12.3%

10.6%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%


Working capital credit Investment credit Consumption credit

Figure 2.11Credit Growth by Type

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Agric

ultu

re

Min

ing

Man

ufac

turin

gIn

dust

ry

Elec

tric

ity

Cons

truc

tion

Trad

e

Tran

spor

tatio

n

Buss

ines

sSe

rvic

e

Soci

al S

ervi

ce

Oth

ers

sem II/10 semI/11 semII/11

Figure 2.12Credit Growth by Economic Sector

0

10

20

30

40

50

60

0

1

2

3

4

5

6

2007 2008 2009 2010 2011

RpT%Loan Loss Provisions

(right-hand scale)

Nominal NPL (right-hand scale)

Gross NPL(left-hand scale)Net NPL

(left-hand scale)

0%

2%

4%

6%

8%

10%

12%

14%

16%

0%

10%

20%

30%

40%

50%

60%

70%

80%

2004 2005 2006 2007 2008 2009 2010 2011

Share of property credit against total credit (right-hand scale)

Property credit growth (yoy) (left-hand scale)

Figure 2.13Growth and Share of Property Credit

Figure 2.14Non-Performing Loans (NPL)

sector must continue to closely monitor investment credit

risk, particularly in terms of bank funding sources that

tend to be short term while the majority of investment

credit tends to be longer term. Meanwhile, based on

sector, all productive sectors grew positively compared

to June 2011.

Growth in property credit, which collapsed in

2009, rebounded in the middle of 2010. Property credit

growth in Semester II 2011 increased by 12.4% or 23.8%

(yoy), which exceeded that posted in Semester I 2011 at

just 10.1% or 17.8% (yoy) as well as that reported for

the same position a year earlier at 7% or 15.5% (yoy).

The share of property credit in total bank credit remained

relatively small at 13.1% of the total. However, with a

large unmet requirement from residents for housing,

property credit and especially mortgages will have further

opportunity to flourish.

24


Credit Risk4

Bank credit risk eased slightly in Semester II

2011 compared to Semester I-2011. The gross NPL ratio

was just 2.17% at the end of Semester II 2011, down

from 2.74% in June 2011 and 2.56% in December 2010.

Total non-performing loans decreased to Rp5.7 trillion in

Semester II 2011 or around 2.3% of the total increase in

bank credit for the period. In addition to strong bank credit

growth, writing off around Rp6 trillion in credit by several

banks in December 2011 contributed to the significant

decline in the gross NPL ratio.

Banks confronted a potential increase in risk on

foreign currency denominated loans. Historically, the

ratio of non-performing foreign currency loans peaked

in 2000 at over 30% as fallout from the 1997/1998

crisis; well above the NPL ratio for rupiah denominated

loans. Nonetheless, the performance of foreign currency

credit has improved significantly in the past few periods.

The NPL ratio of foreign currency credit since January

2011 has remained below that of rupiah based loans,

reaching 2.03% and 2.19% respectively in December

2011. According to the ratio, non-performing loans have

declined, however, nominally NPL for foreign currency

denominated credit increased by 8.9% compared to the

previous semester when a 10% drop was recorded.

6,4%

-17,3% -17,4%

15,4%19,1%

25,5%

-10,72% -11,26% -10,53%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

KKKIKMK


Figure 2.17NPL Growth by Credit Type

0

1

2

3

4

5

6

7

8

9

2007 2008 2009 2010 2011

%

Rp NPL Ratio FX NPL Ratio NPL Total

-4,8%-2,3%

-4,4%

23,8%

-10,0%

18,2%

-13,7%

8,9%

-10,8%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

Rupiah Valas Total


Figure 2.15NPL Growth by Currency

Figure 2.16NPL Ratio by Currency

When observed according to the type of loan,

a decline in total NPL was reported for all three

types of loans in Semester II 2011, with the biggest

decrease affecting investment credit. This decline in

NPL for investment credit, among others, was thanks to

improvements in the quality of middle segment investment

credit at several large banks. In line with the decline in

non-performing loans, the gross NPL ratio for working

capital credit, investment credit and consumption credit

decreased on the preceding semester from 3.37%, 2.47%

and 1.95% to 2.65%, 1.92% and 1.57%.

Considering its longer time frame compared

to the other types of loan, investment credit has

inherently more credit risk. Historical data indicates

that investment credit has maintained a higher gross

4 Excluding channelling unless otherwise stated.

25


0

3

6

9

12

2007 2008 2009 2010 2011

%

consumptioncredit

Investmentcredit

workingcapital credit

Figure 2.18NPL Ratio by Credit Type

Figure 2.19NPL Ratio by Economic Sector

0

2

4

6

8

10

2007 2008 2009 2010 2011

%

Agriculture Mining Manufacturing Industry Electricity Construction

0

2

4

6

8

10

2007 2008 2009 2010 2011

%

Trade Transportation Business Services Social Services Others

NPL ratio than the other two types of loan since the year

2000. However, since 2009 the NPL ratio of investment

credit has remained below that of working capital credit.

In Semester II 2011, nominal NPL for investment credit

dropped by 11.26%, leading to a decline in the gross

NPL ratio to 1.92% compared to the 2.4% posted at

year end 2010. Looking ahead, investment credit risk can

be controlled if credit allocation continues to adhere to

prudential principles.

0%

2%

4%

6%

8%

10%

12%

14%

16%

Mortgages Real Estate Construction Total Property

By sector, nearly all sectors experienced a

decline in non-performing loans in Semester II 2011,

with the largest declines affecting the mining sector

(72%), followed by transportation (35.2%), social services

(26.2%), business services (24.4%), others (12.5%), trade

(9.8%) and construction (3.1%). Notwithstanding, the

electricity and agricultural sectors experienced an increase

in non-performing loans amounting to 41.2% and 5.6%

respectively. This increase in NPL was attributable to more

loans being classified as doubtful and loss in the agricultural

and utilities (electricity, gas and water) sectors. In terms

of credit risk stemming from other sectors, the nascent

emergence of rising NPL in the trade and manufacturing

sectors requires closer monitoring.

Property credit risk in Semester II 2011 was well

controlled, with a decline in the NPL ratio for property

credit from 3.0% (June 2011) to 2.4% in December

2011. Although the ratio was slightly above that for

total credit (2.17% in December 2011%), the trend was

downward. This decline NPL for property credit in Semester

II 2011 was primarily contributed by improvements in the

collectability of mortgages. The NPL ratio of mortgages

dropped to 1.8% compared to the position in June 2011

at 2.5% in line with enhancements to loan management

at commercial banks.

Figure 2.20NPL Ratio of Property Credit

26


2.2.3. Profitability and Capital

Profitability

The profitability of the banking industry

increased on the strength of improved domestic

economic conditions. Banks posted a net profit of Rp75

trillion, which exceeded that posted in Semester I 2011 and

Semester II 2010 at just Rp37.1 trillion and Rp57.3 trillion

respectively. The jump in profit was driven by, among

others, growth in loan interest income, which accounts

for 82.66% of total interest income, linked to the 24.59%

(yoy) level of credit growth at the end of the reporting

period. Solid profits were reflected by the 3.03% return

on assets posted by the banks in December 2011.

When observed by bank group (data for December

2011 compared to December 2010), all bank groups

experienced an increase in their net profits due to credit

growth. The strongest growth in profit was recorded by

state-owned banks, achieving 43.5% growth on net profit

in 2010, followed by foreign bank branch offices with

35.4%, foreign exchange banks with 27%, joint venture

banks with 18% and regional banks with 5.9%.

Up to the end of Semester II 2011, the

composition of bank profit was still dominated by

operational profit. In December 2011, bank operational

profit was recorded at Rp56.4 trillion or 58.16% of total

profit, which is a two-fold increase over that posted in

June 2011 at Rp26 trillion.

The dominance of operational profit stems from

increased Net Interest Income (NII). Average monthly NII

in Semester II 2011 was Rp13.93 trillion, which surpassed

that reported in Semester I 2010 (Rp12.18 trillion) and

0

10

20

30

40

50

60

70

80

0

10

20

30

40

50

60

%T Rp

Operational Profit/Loss(left-hand scale)Non-Operational Profit/Loss (left-hand scale)Share of Profit/Loss (right-hand scale)

Figure 2.21Composition of Bank Profit/Loss

Table 2.3Profit/Loss of Banking Industry

Source: Periodic commercial bank reports, Bank Indonesia

Rp T Dec 2010 Jun 2011 Dec 2011

Operational profit/loss 48,3 26,1 56,4

Non-operational profit/loss 27,7 20,5 40,7

Before taxes profit/loss 76,1 46,6 97,1

After taxes profit/loss 57,3 37,1 75,0


Dec-10

L/R After Taxes(T Rp)

NIM (%)Growth Credit

(% YOY)

Dec-10Dec-10Dec-11 Dec-11Dec-11Jun-11 Jun-11

Bank Group

1. State-owned 22,77 16,62 32,66 18,0% 20,9% 6,11 6,30 6,55

2, Private 21,06 13,14 26,74 29,8% 29,1% 5,69 5,58 5,65

3, Regional 7,51 4,14 7,95 19,0% 22,3% 8,74 8,14 8,10

4, Joint venture 2,06 1,12 2,43 22,3% 21,6% 3,83 4,02 3,91

5, Foreign branch office 3,91 2,07 5,29 13,0% 20,8% 3,54 3,59 3,62

Industry total 57,31 37,10 75,08 22,8% 24,6% 5,73 5,79 5,91

Table 2.4Profitability and Credit by Bank Group

27


Figure 2.22Composition of Interest Income for the

Banking Industry (%)

0%

20%

40%

60%

80%

100%

Dec'09 Dec'10 Jun11 Dec11

Placements at Bank Indonesia Interbank Credit SSB Others

7,75 6,75 8,15 8,063,46 2,52 3,02 2,53

75,16 81,10 81,02 82,42

12,73 8,88 7,14 6,32

Semester II 2010 (Rp12.79 trillion). This reflects greater

bank efficiency in reducing its interest burden, while

concomitantly increasing interest income as a result of

solid credit growth.

In terms of the sources of interest income, during

the second half of 2011 interest income from loans was

still the largest contributor to interest income with a share

accounting for 82.66% of the total. However, this share

tended to shrink when compared to the three previous

semesters, namely 81.06% in June 2010, 81.03% in

December 2010 and 80.95% in June 2011. Strong credit

growth is cited as the principal determinant for the

dominance of interest income from loans.

The interest rate spread tended to narrow but

the share of interest income from loans to total interest

income increased from 81.02% in Semester I 2011 to

82.42%. This reflects that when endeavouring to boost

their income, banks tend to increase credit volume rather

than broadening their spread. Consequently, the narrower

spread accompanied by an increase in credit volume raised

the Net Interest Margin (NIM) of banks in December 2011

by 32 bps to 6.11% compared to the position in Semester

I 2011 at 5.79%; or an increase of 38 bps on the position

in December 2010 at 5.73%.

The narrower interest rate spread is in line

with Bank Indonesia policy to catalyse the banking

industry so that the intermediation function operates

Figure 2.23Rupiah Interest Rate Spread (%)

8.0

7.57.0

6.5

6.0

5.5

5.0

4.5

4.0 Jan-06M

ar-06M

ey-06Jul-06Sep-06N

ov-06Jan-06M

ar-07M

ey-07Jul-07Sep-07N

ov-07Jan-08M

ar-08M

ey-08Jul-08Sep-08N

ov-08Jan-09M

ar-09M

ey-09Jul-09Sep-09N

ov-09Jan-10M

ar-10M

ey-10Jul-10Sep-10N

ov-10Jan-11M

ar-11M

ey-11Jul-11Sep-11N

ov-11

83,0

84,0

85,0

86,0

87,0

88,0

89,0

1,0

1,5

2,0

2,5

3,0

3,5

2007 2008 2009 2010 Jun'11 Dec'11

%%

ROA (left scale) BOPO (right scale)

efficiently and transparently. Since its inaugural

publication in March 2011, the prime lending rate has

trended downwards in all credit segments as a result of

a decline in all three components of the prime lending

rate, namely the cost of funds, overhead costs and profit

margin. Compared to the position in March 2011, the

prime lending rate in December 2011 was 45 bps lower

for mortgages, 33 bps lower for the corporate segment, 19

bps lower for retail and 5 bps lower for non-mortgages.

The Return on Assets (ROA) was relatively stable,

declining 4 bps in December 2011 from 3.07% to 3.03%.

Annually, however, ROA in December 2011 increased from

2.86% in December 2010 to 3.03%. The decline in ROA

during Semester II 2011 occurred due to a significant increase

in credit allocation, which affected the magnitude of total

assets in the banking industry. On the other hand, robust

credit growth was accompanied by greater bank efficiency,

Figure 2.24Bank ROA and BOPO (%)

28


as denoted by the decline in the BOPO efficiency ratio in

semester II 2011 to 85.42% from 90.47% in June 2011,

86.14% in December 2010 and 85.92% in June 2011.

Capital

The average capital adequacy ratio (CAR) of the

banking industry dropped to 16.82% compared to

17.53% in the prior semester. Over the past three years,

average bank CAR dipped to lowest level in semester II-2010

(16.79%). Meanwhile, based on its position at the end of

Semester II 2011, CAR had recorded a new low of 16.07%.

Nevertheless, this level of bank CAR is still relatively high

compared to the minimum capital requirement stipulated in

Basel II. The low average level of CAR at the end of Semester

II 2011 compared to Semester I 2011 was primarily caused

by a hike in the minimum statutory reserve that exceeded

the average increase in capital. In Semester II 2011, the

average minimum statutory reserve for banks increased

by Rp244.59 trillion or 11.46% while average capital only

increased by Rp25.97 trillion or 6.94%.

Based on bank group, the downward trend in

average CAR stemmed from a decline in average CAR

for all bank groups, excluding foreign bank branch

offices. The average CAR of foreign bank branch offices

rebounded to its highest level at 25.71% with the support

of a significant increase in average capital during Semester

II 2011, more specifically Rp6.47 trillion (13.45%), and a

10

12

11

13

14

15

16

17

18

19

0,00Dec’08 Dec’09 Jun’10 Dec’10 Jun’11 Dec’11

0,50

1,00

1,50

2,00

2,50

3,00

%Rp T

CAR (right scale)Risk-WeightedAssets (left scale)

Capital (left scale)

Figure 2.25Capital, the Minimum Statutory

Reserve and Bank CAR

Figure 2.26CAR by Bank Group (%)

35.00 %

30.00

State-owned Private Regional Joint venture Foreign

25.00

20.00

15.00

10.00

5.00

0.00

Dec’08 Dec’09 Jan’10 Dec’10 Jan’11 Dec’11

decline in average statutory reserves of Rp17.82 trillion

(9.16%). The average CAR of joint venture banks remained

relatively high at a level of 20.58%. On the other hand,

average CAR for the largest extenders of credit, namely

regional banks, private banks and state-owned banks,

trended downwards compared to the previous period.

Average CAR for regional banks was 14.55%, private banks

was 15.51% and stsate-owned banks was 16.06%.

Table 2.5Performance of the Prime Lending Rate

Note: data excludes outliers and calculated by weighted average

SamplesCredit

Segment March April May June July Augt Sept Oct Nov Dec

Corporate 10,51 10,58 10,64 10,72 10,54 10,55 10,51 10,50 10,36 10,18

Retail 11,80 12,21 11,84 11,91 12,00 12,08 12,04 11,98 11,78 11,61

Mortgages 11,16 11,25 11,35 11,38 11,03 11,03 11,04 10,98 10,82 10,71

Non-Mortgages 11,56 11,70 11,76 11,86 11,86 11,96 11,88 11,83 11,68 11,51

29


Figure 2.27MSM Credit Growth (yoy)

50

40

30

20

10

-

(10)2007 2008 2009

MSM (total) Non MSM

2010 2011

Credit

Although bank CAR remained well above the

threshold level, it must still be maintained and

strengthened. Banks that extend the most credit must

continue to mitigate potential weaknesses in terms of bank

resilience to credit risk and market risk amid unsettled

global financial market conditions. Furthermore, capital

should be strengthened in order to anticipate meeting the

capital regulations and requirements pursuant to Basel III,

in partuclar for banks classified as systemic.

Micro, Small and Medium (MSM) Credit

MSM credit slowed down slightly but still

contributed the most to total bank credit. In December

2011, the share of MSM credit amounted to 51.95%,

lower than that in December 2010 (52.48%) and June

2011 (53.06%). This decline in share was due to a larger

increase in non-MSM credit compared to MSM credit

growth. During Semester II 2011, MSM credit grew by

11.23% or 24.24% (yoy), clearly outpaced by non-MSM

credit growth at 16.33% or 26.94% (yoy). MSM credit

growth in Semester II 2011 was relatively slow compared

to growth posted in Semester I 2011; however, non-MSM

credit growth in Semester II 2011 was far in excess of that

in Semester I 2011 at just 9.12%. Overall, annual credit

growth for MSM and non-MSM in 2011 was lower than

that in 2010.

MSM credit risk was relatively low. Despite solid

MSM credit growth the gross NPL ratio was maintained at

a low level of 2.27% in December 2011, far lower than the

position in June 2011 (2.87%) and December 2010 (2.60%).

This is one determinant that encourages banks to supplement

their allocation of MSM credit, as well as the sheer number of

banks now entering the MSM sector. MSM credit data does

not include credit cards or (Islamic) rural banks but does include

Islamic commercial banks (BUS).

Figure 2.28Non-Performing MSM Bank Loans (%)

9.08.07.06.05.04.03.02.0

1.0

2007 2008 2009 2010 2011MSM

-

Non MSM

2.3 POTENTIAL FINANCIAL MARKET RISK AND

FINANCING RISK

2.3.1 Potential Financial Market Risk

The domestic financial market experienced pressures

in Semester II-2011 stemming from mounting external

shocks due to the deteriorating debt crisis in Europe and

economic slowdown in the US. Accordingly, such market

dynamics led to an escalation in risk to financial system

stability, in particular the stock market, government

securities (SBN) and the exchange rate.

Nevertheless, a timely policy response from Bank

Indonesia and the Government helped ensure that the

financial market could absorb global shocks. The financial

market began to show signs of recovery at the end of

2011 with stability and the recovery enduring into the

beginning of 2012.

30


net outflows totalling Rp61.2 trillion in semester II-2011

compared to net inflows of Rp64 trillion in the previous

semester. The outflows consisted of Rp53.8 trillion from SBI

and Rp14.5 trillion from SBN, while a net inflow of Rp7.1

trillion was recorded for shares. The outflow of capital amid

solid domestic economic growth drove strong demand

for foreign exchange, thereby leading to depreciatory

pressures on the exchange rate in the second semester of

2011 followed by increased volatility.

Money Market Risk

Interbank money market stability (in rupiah and

foreign exchange) was well maintained during the

reporting period. Risk on the rupiah interbank money

market eased compared to the preceding semester in line

with excess liquidity in the banking system. Furthermore,

Bank Indonesia strived to preserve interest rate stability

on the interbank money market by maintaining a (rupiah)

liquidity balance through foreign exchange monetary

operations to accrue SBN as a monetary instrument, which

also served to stabilise the SBN market.

SBN Market Risk

The government bond (SBN) market experienced

significant pressures in semester II-2011 compared to

the previous semester, however, Bank Indonesia

and the Government were able to restore stability

through an array of policy measures. External shocks

abated the rising tide of SBN prices in September 2011,

with short-tenor prices actually in decline up to yearend

2011 (Figure 2.31). Price pressures were also noted on the

FR benchmark series, which began to slide in September-

October 2011 before recovering at the end of the year and

persisting into the new year (Figure 2.32).

-50

-40

-30

-20

-10

0

10

20

30

40

50

Jan-11 Feb-11 Mar-11Apr-11 Mei-11Juni-11 Juli-11 Ags-11 Sept-11Okt-11 Nov-11 Des-11 Jan-12

Bank Indonesia Certificates (SBI) Government Securities (SBN) Stock

Figure 2.30Non-resident Flows of Shares, Government Securities

(SBN) and Bank Indonesia Certificates (SBI)

The domestic financial market experienced expanding

pressures in semester II-2011 as external shocks intensified

(Figure 2.29). Shocks were triggered by a protracted

deterioration in the euro zone debt crisis coupled with

an economic slowdown in the US, which threatened

to undermine global economic growth. Consequently,

investors on the financial market rebalanced their portfolios

and deleveraged by shifting placements from financial

assets in emerging market countries, including Indonesia,

to safe-haven assets denominated in US dollars.

Non-resident investors withdrew placements

primarily from tradable government securities

(SBN) (capital outflows), while capital also flowed

away from Bank Indonesia Certificates (SBI) as they

reached maturity (Figure 2.30). Non-residents recorded

Figure 2.29A Map of Financial System Stability

PUAB VolatilityRupiah

20151050-5

Jun -11 Dec -11

Exchange Rate VolatilityUSD/IDR

IHSG VolatilitySUN Volatility (%)

Foreign Debt/GDP(%)

31


80

85

90

95

100

105

110

115

120

125

130

Jan-11

Feb-1

1

Mar-1

1

Apr-1

1

May-1

1

Jun-11

Jul-11

Aug-1

1

Sep-1

1

Oct-1

1

Nov-1

1

Dec-1

1

FR0055 FR0053 FR0056 FR0054 IDMA

Figure 2.32FR Benchmark Series SBN Prices

0,4

0,6

0,8

1,0

1,2

1,4

1,6

Dec10 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec11

Short-Term Medium-Term Long-Term

Figure 2.33SBN VaR by Tenor

Figure 2.34SBN Price Volatility

0%

10%

20%

30%

40%

50%

60%

70%

80%

Jan-

11

Feb-

11

Mar

-11

Apr-1

1

May

-11

Jun-

11

Jul-1

1

Aug-

11

Sep-

11

Oct-1

1

Nov-

11

Dec-

11

1 year 5 years 10 years

Figure 2.31SBN Prices by Tenor

100

105

110

115

120

125

130

135De

c'10 Jan Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec'1

1

Short-Term Medium-Term Long-Term

SBN risk, which intensified in February 2011,

escalated again in September 2011 before easing

in November 2011 and thereafter. The indicator of

SBN risk to bank performance is measured using Value at

Risk (VaR) for SBN held by the banks according to tenor

(Figure 2.33). In general, VaR followed a downward trend

with a significant drop in risk on short-tenor SBN, which

was linked to excess liquidity. Excess liquidity stemmed

from the macroprudential policy to extend the minimum

holding period of Bank Indonesia certificates from one to

six months, which precipitated a shift, primarily in non-

resident investments, from SBI to SBN.

Another risk indicator, namely SBN yield

volatility, further corroborated the increase in risk

in February 2011 for 1-year, 5-year and 10-year tenors.

Volatility also increased in semester II-2011, initially on

short-tenor SBI due to the new six-month minimum holding

period but subsequently also on longer tenor SBI of 5 and

10 years in September 2011 as a result of external shocks

(Figure 2.34).

The number of government bonds (SBN)

increased in harmony with the fiscal financing

requirement. Notwithstanding, non-resident

ownership of SBN actually declined due to less risk-

appetite from investors as a result of global economic

shocks. Total SBN increased by Rp32.59 trillion, while

foreign/non-resident ownership declined by Rp12.13 trillion

in semester II-2011. The decline in foreign ownership was

ostensibly caused by absorption into the banking sector,

while the maturity profile remained relatively the same as

the preceding semester, namely that the VR series was

dominated by tenors of less than 10 years. The distribution

of SBN maturity was comparatively even, thereby ensuring

control over maturity risk.

32


70

90

110

130

150

170

190

210

230

250

Jan-

10Fe

b-10

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10Ap

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ar-11

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ay-1

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Jul-1

1Au

g-11

Sep-

11Oc

t-11

Nov-1

1De

c-11

FinancialConsumptionInfrastructure

AgriculturePropertyTrade

JSX CompositeBasic IndustryMiningMiscellaneous Industry

Figure 2.37The JSX Composite by Sector

Figure 2.36The JSX Composite and other Global Price Indices

60

80

100

120

140

160

180

Jan-

10Fe

b-10

Mar

-10

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ay-1

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-11

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11Ju

l-11

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p-11

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-11

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-11

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-11

IHSG FSSTI NKY Hang Seng KOSPI DJIA

-

5

10

15

20

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30

35

40

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50

2012

2013

2014

2015

2016

2017

2018

2019

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2022

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2028

2030

2031

2032

2037

2038

2041

2042

Fixed Rate Variable Rate

Figure 2.35SBN Maturity Profile

By sector, financial sector shares continued to

outperform the market overall (Figure 2.36). This was

due to stable conditions in the banking sector with an

expanding intermediation function and improved quality,

hence maintaining bank profitability. Meanwhile, the

shares of several large banks nearly all performed better

in semester I-2011 compared to the declines reported in

semester II as a result of concerns over external shocks

on the domestic banking sector (2.38). Congruent with

the limited exposure of domestic banks to foreign banks,

the impact of external shocks had minimal effect on the

performance of individual shares.

Stock Market Risk

Similar to the SBN market, the stock market was

also beset with external pressures in semester II-2011,

followed by a subsequent recovery emerging at the

beginning of 2012. The dynamics of the domestic bourse

were subjected to a battle between bullish sentiment

domestically and in the US and bearish sentiment

stemming from the euro zone debt crisis and its impact on

economies in Asia. The JSX composite index experienced

pressures in August 2011, sliding from 3,888 points at the

end of June 2011 to dip below the psychological barrier

of 3,000 points in December 2011 before rebounding

strongly to 3,821.99 points.

Table 2.6SBN Ownership

SBN Ownership (trillions of rupiah)

Jun’11 Dec’11 ChangesBanks 226,54 265,03 38,49

Bank Indonesia 3,12 7,84 4,72

Mutual Funds 48,76 47,22 -1,54

Insurance 93,42 93,09 -0,33

Foreign 234,99 222,86 -12,13

Pension Funds 36,69 34,39 -2,3

Securities 0,07 0,14 0,07

Others 47,44 53,05 5,61

Total 691,03 723,62 32,59

33


0

10

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40

50

60

Dec1

0

Jan

11

Mar

11

Apr1

1

May

11

Jun

11

Jul1

1

Aug1

1

Sep

11

Oct1

1

Nov1

1

Dec1

1

Jan

12

Indonesia Malaysia JapanSingapore Thailand Hong kong

%

0,01

-0,04

-0,05

0,18

0,01

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0,00

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-10,00% -5,00% 0,00% 5,00% 10,00% 15,00% 20,00%

BCA

Niaga

Permata

Panin

BII

Mandiri

Bukopin

BRI

Danamon

BNI

January December

Figure 2.38Share Prices in the Banking Sector

Figure 2.39Stock Market Volatility in the Region

020406080

100120140160180200

Jan

11

Feb

11

Mar

11

Apr1

1

May

11

Jun

11

Jul1

1

Aug1

1

Sept

11

Oct1

1

Nov1

1

Dec1

1

Rp T

Equity funds Money market funds Discretionary fundsFixed-income funds Protected funds Indexed fundsETF equity funds ETF fixed-income funds Sharia compliant funds

Figure 2.41Mutual Fund by Type

Figure 2.40 Volatility on Regional Bourse

540

560

580

600

620

640

660

680

50

70

90

110

130

150

170

Jan

11

Feb

11

Mar

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11

Jun

11

Jul1

1

Aug

11

Sep

11

Oct

11

Nov

11

Dec

11

NAV (Rp T) Number of Shares/Units of Billion Number of Mutual Fund

Stock market risk escalated but has since

subsided. JSX composite risk, measured by the level of

volatility, was well controlled in semester I-2011 despite

intense risk from Japan due to the natural disasters

that befell the country in March 2011 (Figure 2.40).

Deteriorating conditions on global financial markets in

September 2011 prompted concerns over weaker global

demand and economic performance in Asia, thus stock

market risk escalated in the region. JSX composite risk

was the highest in the region but returned to normal at

yearend with volatility actually lower than that reported

at the beginning of the same year. A pre-emptive

government and Bank Indonesia policy response instituted

to minimise the impact of externalities coupled with the

positive response of market players to less concern over

an economic slowdown in the US helped ease volatility

significantly, which tended to flatten/stabilise.

Mutual Funds

The performance of mutual funds continued to

improve in semester I and II despite a stutter in the growth

rate in September 2011, as reflected by the correction in

Net Asset Value (NAV) subsequent to significant growth

in the preceding month. The NAV correction largely

affected discretionary funds, fixed-income funds and

equity funds in line with their underlying investments, for

which the indicators of risk or volatility spiked in August

and September 2011.

Several indicators of mutual fund performance

followed an upward trend during the reporting

period. The number of mutual funds available in semester

II-2011 expanded slightly from 632 (June 2011) to 646

(December 2011). The NAV of mutual funds increased

by 5.34% to Rp157 trillion in semester I-2011 and by

34


7.11% to Rp168 trillion in semester II of the same year.

The largest increase recorded in 2011 was contributed

by equity funds. The rise in net asset value (NAV) of such

companies was primarily supported by an upturn in the

value of investment as well as a greater number of units in

circulation, increasing from 83.32 billion at the beginning

of the year to 85.41 billion in December 2011.

2.3.2. Financing through the Capital Market and

Finance Companies

Stock and Corporate Bond Issuances

Financing through the capital market continued

in 2011 but not as vigorously as in the preceding year.

Capital market financing from stock and bond issuances

reached Rp100 trillion in 2011, a slight decrease on the

previous year at Rp115 trillion (Table 2.7). The slowdown

was primarily attributable to a decline in the number of

stock issuers, while bond issuances surged by 25% from

Rp35 trillion to Rp46 trillion. The decline in stock issuances

was due to the wait-and-see attitude of potential issuers

due to mounting share price volatility in 2011. Meanwhile,

as of the first week of February 2012, bond issuances

continued, reaching Rp690 billion.

By semester in 2011, more shares were issued

in semester I than semester II, with a value of Rp35.7

trillion and Rp23.8 trillion respectively. The share price

index was corrected in semester II-2011, affecting the

capitalisation value, which began to recover but has yet to

reach the levels posted in July 2011. The number of issuers

issuing also declined slightly from 13 in semester I-2011

to 11 in semester II, hence bringing the total number of

issuers to 546.

Similar to the pattern of stock issuances, the

issuance of corporate bonds declined in the second

semester of 2011 compared to the first. In semester

I-2011, bond issuances reached Rp27 trillion from six

issuers compared to Rp18.7 trillion by five issuers, with the

Table 2.7Financing sourced from Credit, Shares and Bonds

2010 % 2011 % Pertum- 2012 F

T Rp T Rp buhan

Credit 1.766,00 94% 2.199,00 96% 24,52%

IPO 29,56 2% 19,60 1% -33,69% 25 emisi

Rights issue 48,67 3% 34,80 2% -28,50% 40 emisi

Bonds Issuance 36,6 2% 45,70 2% 24,86% 40

Total 1.880,83 100% 2.299,10 100% 22,24%

0

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3000

3500

4000

4500

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500

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Dec

10

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11

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1

May

11

Jun

11

Jul1

1

Aug

11

Sep

11

Oct

11

Nov

11

Dec

11

(Rp Trillion)

Capitalization Value (BEI) Issuance Value IHSG (RHS)

Figure 2.42Issuers and Stock Issuances

182

184

186

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194

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198

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0

50

100

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10

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11

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11

Nov

11

Dec

11Issuer ValueRp Billion

Issuance (LHS) Issuer (RHS)

Figure 2.43Issuers and Corporate Bond Issuances

total number of issuers standing at 199. Stagnant growth

in bond issuances was mainly affected by externalities,

while domestic fundamentals remained solid with robust

economic growth and low inflation.

35


Finance Company Performance and Risk

The performance of finance companies improved

significantly in 2011 (data up to November 2011)

compared to 2010, with finance companies playing

an active role in financing economic development.

Strong performance was achieved due to buoyant

economic growth that required financial support from the

banking sector and finance companies. Business volume,

as reflected by the assets of finance companies, increased

by Rp55.9 trillion in 11 months during 2011 to Rp286.2

trillion, with an increase in assets in semester II amounting

to Rp29.2 trillion, which is larger that that posted in

semester I at Rp26.7 trillion.

350

Trillion Rp

Assets Financing Fundingn Capital

300

250

200

150

100

50

0

Jun-2010 Dec-2010 Jun-2011 Nov-2011

Figure 2.44Finance Company Performance

Figure 2.45Share of Finance Company Financing

80

70

60

50

40

30

20

10

Leasing Factoring Credit Cards ConsumerFinancing

0

Jun-2010 Dec-2010 Jun-2011 Nov-2011

200

Trillion Rp

150

100

0

Offshore LoansDomestic loans Loans ReceivedSecurities Issued

Jun-2010 Dec-2010 Jun-2011 Nov-2011

Figure 2.46Sources of Funds for Finance Companies

Rp26 trillion in semester I and by Rp29.5 trillion in semester

II, to reach Rp241.9 trillion in November. The majority of

consumer financing was used for motor vehicle loans, the

rapid growth of which was in line with domestic economic

expansion as well as the relatively less stringent credit

terms, especially for motorcycle loans, associated with

finance companies compared to banks and indications of

the continued requirement for better public transportation

infrastructure.

From a funding perspective, the increase in

business volume was funded by loans received

domestically and from abroad, as well as the issuance

of securities. Funding for finance companies increased by

Rp21.3 trillion in semester I and Rp19.1 trillion in semester

II for a combined increase of Rp36.9 trillion on the previous

year, amounting to Rp185.2 trillion in total. Funds sourced

from domestic loans experienced the most growth at

Rp21.3 trillion (Rp11.8 and Rp9.5 trillion in semester I

and II respectively), to reach Rp106.3 trillion. Funds from

offshore loans accounted for the second largest growth,

achieving Rp78.9 trillion in November 2011. The increases

during semester I and II for offshore loans amounted to

Rp7.3 trillion and Rp11.8 trillion respectively, combining

for a total increase in offshore loans of Rp19.1 trillion,

which is far in excess of the growth posted in the previous

year at Rp12 trillion.

Most financing from finance companies was

used for consumer financing and leasing. Financing

increased in 2011 by Rp55.5 trillion, more specifically by

36


Table 2.8Financial Indicators of Finance Companies

Billion Rp Dec-10 June-11 Nov-11

Assets 230.301 259.548 286.226Liabilities 182.470 211.019 231.888 o/w Debt 163.701 192.183 213.899Capital 47.831 48.529 51.162Profit Before Tax 11.563 5.932 10.812Profit After Tax 8.929 4.727 8.491

%

ROA 0,05 0,02 0,04ROE 0,24 0,12 0,21BOPO 0,74 0,79 0,78Debt/Equity 3,42 4,35 4,53Obligations/Equity 3,81 4,35 4,53

Table 2.9NPL by Type of Finance

NPL (Billion Rp) Dec-10 Jun-11 Nov-11

Leasing 351 261 297Factoring 73 78 119Credit Cards 44 38 0Consumer Financing 2.189 2.469 2.701Total Financing 2.658 2.846 3.117

% NPL Dec-10 Jun-11 Nov-11

Leasing 0,63% 0,43% 0,38%Factoring 3,07% 2,51% 3,37%Credit Cards 4,62% 4,06% 3,03%Consumer Financing 1,63% 1,59% 1,61%Total Financing 1,37% 1,29% 1,25%

Insurance Company Performance and Risk

Robust expansion in 2009 endured into 2010.

In harmony with ongoing economic expansion and

the development of financial services, 138 insurance

companies operated specialising in life insurance (46

companies), general insurance (87) and social insurance

(5) in December 2010. Of those 138 insurance companies,

11 were public listed with assets topping Rp21.65 trillion,

which is up 18 % on the position in December of the

previous year at Rp18.27 trillion. Two large insurance

companies dominated the 11 public listed companies with

an 81% market share.

Investment risk from the assets of the 11 public

listed companies was linked to share and bond price

volatility. The investment asset composition of insurance

companies was dominated by shares (54%), term deposits

(18%) and bonds (14%). The impact on insurance

company investment of share price volatility risk must be

monitored due to the large portion of investment assets

as well as unstable financial markets due to the unresolved

debt crisis in the euro zone.

The inherent risks associated with finance company

financing were controlled at a low level, as reflected by a

low NPL ratio and relatively stable financial indicators. Non-

performing loans from finance companies were maintained

below 1.4%, although the method used to calculate NPL

is different to that used for banks. The low NPL ratio was

also attributable to the increased level of collateral held by

finance companies, the majority of which was consumer

financing, in particular motor vehicle loans that are easy

to seek approval for and liquidate if the loan becomes

doubtful or a loss. In terms of the type of finance, the NPL

ratio for factoring and credit cards was above average.

Meanwhile, amid persistent business expansion, financial

indicators for finance companies remained sound.

37


PNIN43%

PNLF38%

ABDA4%

AHAP1%

AMAG3%

ASBI1%

ASDM1%

ASRM2%

ASJT1%

LPGI4% MREI

2%

Figure 2.47Market Share of 11 Insurance Companies

Table 2.10Insurance Company Investment

2010 2009

Billion % Billion %

Investment Assets 20.170 93 16.989 92

Term Deposits 3.925 18 2.592 14

Bonds 1.141 5 689 4

Shares 13.739 63 11.906 65

Mutual Funds 1.179 5 1.490 8

Non Investment Assets 1.480 7 1.285 8

Total Assets 21.650 100 18.273 100

38


Firmly positioned as an emerging market

country in Asia, the role of the Indonesian economy

started to become significant in the region with

Indonesia one of the few countries that maintained

stable economic growth amid the global economic

downturn. Improvements in a number of national

economic indicators demonstrated that the condition

of the domestic financial system was resilient enough

to absorb the economic turbulence in Europe and the

US over the past several years. Despite a minor spillover

effect from the global turmoil on domestic financial

markets, particularly the stock and bond markets, the

effect on the real sector was minimal.

The prospects of the Indonesian economy and

its ability to absorb global pressures led to an upgrade

in Indonesia’s sovereign rating. Two international

rating agencies, namely Fitch and Moody’s, affirmed

Indonesia’s Investment Grade status and upgraded

their corresponding sovereign rating. The upgraded

rating provides Indonesia with greater momentum to

attract foreign investment into the country and also

strengthens the monitoring mechanisms for capital

and foreign investment flowing in and out of the

economy.

Domestically, economic resilience accompanied

by stable public purchasing power due to rising

incomes and a demographic dominated by productive-

aged citizens, helped ensure the sustainability of retail

production in line with growing public consumption.

This paints a sound picture for potential investors that

the domestic economy will continue to expand even in

the midst of a global economic slowdown.

Impact of upgraded Sovereign Rating on

Financial Market

An upgraded credit rating certainly affects the

perception of investment risk as well as the magnitude

of risk premium when conducting international financial

transactions. As the rating improves it indirectly lowers

the risk premium on financial transactions. Consequently,

the cost of international financial transactions to Indonesia

becomes more efficient and simpler to process. In addition,

assuming that other economic fundamentals also improve

and infrastructure is conducive, then the potential for a

deluge of short, medium and long-term foreign investment

increases. The process of foreign funds gradually flowing into

the country through financial market instruments improves

with financial product diversification of various tenors.

The flow of foreign funds to Indonesia is linked to

the regional flow of capital, which itself is the result of

global investment flowing around pressures emanating

from the protracted debt crisis in Europe. Flows of foreign

funds to Indonesia began to evaporate in the middle of

2011, which also affected financial markets in the region.

Notwithstanding, the domestic policy mix applied to manage

foreign capital flows and bank liquidity through a measured

exchange rate and interest rate policy response, coupled

with macroprudential policy and enhanced infrastructure for

domestic financial transactions provoked a positive response

from domestic investors. The diverse array of policy measures

instituted by domestic authorities was effective in providing

ample room to reinforce the money market and capital

market in order to dampen external economic pressures.

An Upgraded Sovereign Rating and Financial System Stability

39


into the economy, including foreign direct investment

(FDI). Furthermore, long-term investment flowing into

Indonesia is expected to reduce the potential for a

sudden capital reversal while indirectly helping maintain

domestic financial system stability.

Risk Prudence

Other aspects of risk required close monitoring to

ensure comparative advantage in terms of investment

transaction efficiency. The potential for criminality in

financial transactions as well as moral hazard required

special attention. To this end, intermediation and

arbitration was prioritised along with strengthening

legal aspects in order to ensure the ease of investing

in Indonesia, which will stimulate positive sentiment

regarding longer-term portfolio investment in the

domestic economy. In addition, market risk, liquidity

risk and credit risk are all used as the basis for

calculating risk, without ignoring other forms of risk.

Therefore, a broad source of capital flows through a

diverse investor base is expected to catalyse the real

sector and stimulate domestic GDP growth.

Building on what has already been discussed, an

improvement in the investment rating not only lowers

the cost of investment but also minimises the potential

risk linked to investments in speculative financial

instruments. Furthermore, a diverse investor base will

raise market expectations, thereby augmenting the

quality of capital inflows.

Coordination and cooperation between the

respective financial authorities is a prerequisite to

investment-based policy synchronisation and an

integrated potential risk mitigation process, which

aims to buoy the national economy and exploit the

momentum gained from the upgraded sovereign rating

in order to create a better investment regime.

An easing of sovereign risk as a result of an

upgraded rating is further evidenced by the narrower

spread on several financial instruments, including a

number of derivatives. Taking into consideration the

natural market forces of supply and demand, a lower

perception of sovereign risk will encourage a narrower

pricing interval/spread on financial instruments. In

addition, a simpler transaction process together with

a simpler fund transfer procedure from the financial

market in one country to that in another country,

including a shift in capital flows on financial markets

all serve to reduce the cost of investment. Therefore,

it is expected that the growing ease of investing

in Indonesia will act as an additional incentive for

foreign investors to broaden the types of investment

-60,00

-50,00

-40,00

-30,00

-20,00

-10,00

0,00

10,00

20,00

30,00

40,00

Semester 12011 Semester 2 2011 Jan-12

SBI SBN Stock

Figure Box 2.1.2Inflows of Foreign Ownership to the Indonesian

Financial Market

SBI SBN Stock

Figure Box 2.1.1Share of Foreign Ownership in January 2012


41

Chapter 3. Challenges and Prospects of Financial System Stability

Chapter 3Challenges and Prospects ofFinancial System Stability

42



43


3.1 THREAT OF GLOBAL ECONOMIC SLOWDOWN

ON INDONESIAN ECONOMY

The global economy has been confronting

numerous challenges especially relating to large

public debt, significant budget deficits and interest

rates that are trending towards zero. In its latest

edition, the World Economic Outlook (WEO) was most

critical of the deteriorating conditions in the euro zone.

Furthermore, through its WEO published on 24th January

2012, the IMF announced that in order to overcome the

issues in Europe there are thee recovery requirements

as follows: more gradual and therefore sustainable

adjustments; providing adequate liquidity and easy

monetary policy; and enhancing policymaking credibility.

The policy measures taken to overcome

the crisis in the euro area remained suboptimal.

Multilateral institutions like the IMF revised down their

initial predictions of global economic growth to 3.3%,

down by 0.75% from the estimate published in September

2011. The revisions to previous growth projections were

triggered by an increase in the yield on government

bonds, the impact of bank deleveraging on the economy

as well as fiscal consolidation by governments in the euro

zone. Meanwhile, economic growth in other developed

countries was also predicted to slow as a result of spillover

from neighbouring countries through the trade sector and

financial sector, which will continue to deteriorate.

In addition to developed countries, the IMF also

predicts a slowdown in emerging market countries like

China and India. A downturn in these two powerhouses

would be the result of a decline in exports to Japan, the

United States and Europe. On the other hand, economic

growth projections for ASEAN-5 member countries are

optimistic with higher growth projected compared to

2011. Despite a decline in exports from these developing

countries, an influx of foreign capital in the form of

foreign direct investment coupled with strong domestic

consumption will drive economic growth to a more

optimistic level. Widespread global optimism surrounding

the economy of Indonesia is illustrated by such growth

predictions, where the domestic economy is projected to

expand by 6.6%, which is even higher that that projected

for Thailand and the Philippines.

Positive expectations for the Indonesian

economy have the potential to provoke a torrent

of foreign capital in the form of direct and indirect

investment. This is even more likely when considering the

conditions in other countries still struggling to overcome

the crises. Figure 3.1 illustrates private direct foreign capital

flows into developing countries, which have surged in

recent years since 2003 despite a brief decline in 2007 but

then rebounding post-crisis in 2009. Private capital flows

followed a similar trend with a significant upswing after

the global crisis in 2008.

Chapter 3 Challenges and Prospects of Financial

System Stability

44


Source: World Economic Output, IMF, 2012

Figure 3.1Flows of Private Direct Investment (Net)

Source: World Economic Output, IMF, 2012

Figure 3.2Flows of Private Portfolio Investment (Net)

*) IMF : China, India, Malaysia, Thailand, Philipina, IndonesiaSource: IMF, ADB and World Bank, processed

ADBWEO-IMF

2010 2010 20102011 2011 20112012 2012 2012

Asia Pacific Consensus Forecast

Table 3.1Global Economic Growth Projections

World Output 5,2 3,8 3,3

Advanced Economies 1,6 1,2 1,9

United States of America 1,8 1,8 2,2 3,0 1,7 2,3

Japan -0,9 1,7 1,6 4,4 -0,8 1,7

Euro 1,6 -0,5 0,8 1,9 1,5 -0,5

Developing Asia * 7,9 7,3 7,8 8,6 7,5 7,7 7,3 6,0 5,4

China 10,4 9,2 8,2 10,3 9,3 9,1 10,4 9,2 8,5

India 9,9 7,4 7 8,5 7,9 8,3 8,7 7,2 7,0

ASEAN 5 6,9 4,8 5,2 7,1 5,2 5,6

Indonesia 6,1 6,6 6,8 6,1 6,5 6,2

Malaysia 7,2 4,8 5,1 7,2 4,7 4,9

Philipina 7,6 4,7 5,1 7,7 3,7 4,7

Thailand 7,8 4 4,5 7,8 2,5 4,5

Vietnam 6,8 5,8 6,5

Latin America and the

Caribbean 4,6 3,6 3,9

Middle East and North Africa 3,1 3,2 3,6

Sub-Saharan Africa 4,9 5,5 5,3

Billion US $

0

100

200

300

400

500

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Emerging and Developing Economies Central and Eastern EuropeCommonwealth of Independent States Developing AsiaLatin America and the Caribbean Middle East and North AfricaSub Saharan Africa

Billion US $

Emerging and Developing Economies Central and Eastern EuropeCommonwealth of Independent States Developing AsiaLatin America and the Caribbean Middle East and North AfricaSub Saharan Africa

-100

-50

0

50

100

150

200

250

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

The potential inflow of foreign capital, particularly

portfolio investment remains high, which is congruous

to the pattern of foreign portfolio investment illustrated

in Figure 3.2. Solid domestic economic fundamentals in

Indonesia and favourable investment prospects, especially

after investment grade status was affirmed, led to 30.1%

(yoy) growth in FDI.

45


In addition is the threat of a soaring oil price

that continues to trend in excess of USD 100/

barrel and which is currently USD 118/barrel. The

skyrocketing price of oil directly affects the burden of

fuel subsidies borne by the government and has the

potential to raise domestic fuel prices. Past experience

has provided a number of valuable lessons, including that

soaring international oil pricesinfluence inflation and in

turn affect the NPL ratio of bank loans. Any deterioration

in NPL requires vigilance because it can undermine overall

financial system stability.

A number of threats from the domestic

economy remained on top on the external challenges

faced. Internal sources of vulnerability loomed until the

end of 2011, including short-term capital flow volatility,

corporate and household debt pressures, rapid credit

growth, particularly consumption credit and inefficient

banking conditions. However, the range of policy measures

and efforts taken by Bank Indonesia and the banking

community were successful in supressing credit risk and

market risk in the financial system.

Another vulnerability with the potential

to exacerbate credit risk was fuel price hikes.

Implementation of Government Regulation No. 15, 2012,

which controls retail prices and private consumption of

certain types of fuel, will affect credit growth targets

and compound bank credit risk. Research conducted

by Bank Indonesia showed that if fuel prices are raised,

then economic growth targets will face corrections and

credit growth will drop by 0.46% within three quarters

(predominantly investment credit) and NPL will increase by

0.14% in one quarter, with the largest increase affecting

working capital credit.

Source: Indonesian Financial Statistics, Bank Indonesia, processed

Figure 3.3Composition of Foreign Capital Inflows to Indonesia

Source: Indonesian Financial Statistics, Bank Indonesia, processed

Figure 3.4Composition of Foreign Capital Inflows to Indonesia

From the perspective of portfolio investment,

uncertainty over resolution of the euro debt crisis along

with a slowdown in the US recovery process precipitated

a USD 4.3 billion deficit in public portfolio investment up

to quarter III-2011. The deficit was principally blamed

on foreign capital outflow from the SUN market and

widespread non-resident ownership of SBI reaching

maturity. Such conditions confirmed the very real threat

of a sudden capital reversal. In just a brief moment of

around three months the surplus capital flows evaporated

to become a deficit. Therefore, policy measures to balance

macroeconomic conditions are vital in the upcoming

periods.

0

25

50

75

100Percent

Q1

Q2

Q3

Q4

Q1

Q2

Q3

Q4

Q1

Q2

Q3

Q4

Q1

Q2

Q3

Q4

Q1

Q2

Q3

Q4

Q1*

Q2*

Q3*

Q4*

*

2006 2007 2008 2009 2010 2011

FDI PI OI

(10,000)

(5,000)

-

5,000

10,000

15,000

6000

4000

-

-

-2000

0

2000

4000

6000

8000

Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1* Q3*2006 2007 2008 2009 2010 2011

FDI PI Other Investment Financial Account

46


Despite the range of internal and external pressures,

the economy of Indonesia is still expected to expand at

a level of 6.63% with the possibility of a correction in

accordance with policy relating to fuel prices.

an assessment in to the long-term trend of credit growth

showed that credit would continue to grow exponentially,

even exceeding actual conditions. Credit growth that has

already surpassed its historical average requires vigilance

in order to avoid another crisis.

2012*2010 2011

GDP (%, yoy) 6.1% 6.3% 6.32% (baseline)

Adjustment:

6.26% (Fuel limitation)

6.09% (Fuel price increase)

Inflation

(%, end period) 6.96% 3.9% 4.33%

Adjustment:

5.08% (Fuel limitation)

6.32% (Fuel price increase)

Table 3.3Projected GDP and Inflation

*) Bank Indonesia projected values

Type

Lag LagDec 2011 Dec 2011Scenario: Decline in GDP from 6.5% to 6.3%

Fuel Price Increases Fuel Price Increases

% Credit (Y-o-Y) % NPL

Table 3.2Simulation of Easing Fuel Subsidies

Investment Credit 3 33,20 -0,46 1 2,17 0,06

Working Capital Credit 1 21,38 -0,27 1 2,65 0,14

Consumption Credit 3 24,07 -0,20 1 1,52 0,04

Total Credit 4 24,53 -0,42 1 2,17 0,08

*) Assume there are increasing price in Electricity Tariff and Fuel (rise for Rp1.500/liter and Rp2.000/liter)

Source: World Bank, 2011

Figure 3.5Ratio of Credit to GDP in Indonesia, Malaysia, the

Philippines and Thailand

-

50.00

100.00

150.00

200.00

250.00

300.00

350.00

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Indonesia Malaysia Philippines Thailand

Source: Monthly bank reports

Figure 3.6Long-Term Trend of Credit to GDP

-20

-10

0

10

20

30

40

2001

M09

2002

M02

2002

M07

2002

M12

2003

M05

2003

M10

2004

M03

2004

M08

2005

M01

2005

M06

2005

M11

2006

M04

2006

M09

2007

M02

2007

M07

2007

M12

2008

M05

2008

M10

2009

M03

2009

M08

2010

M01

2010

M06

2010

M11

2011

M04

2011

M09

Credit Growth Credit Cycle Trend

Another challenge is to raise credit quality

under a framework of bank intermediation. The role

of the banking sector in the national economy is already

optimal despite a lower ratio of credit to GDP than that

found in other ASEAN member countries. The low ratio of

credit to GDP indicates that the business sector in Indonesia

does not merely rely on funds sourced from banks alone,

but also from other sources like bonds, internal funds and

so forth. In addition, greater flows of FDI are also a source

of funds for investment and a source of funds for domestic

entrepreneurs in the production process. The results of

47


3.2 IMPACT ON THE INDONESIAN FINANCIAL

SYSTEM

The impact of the crisis in Europe began to

appear on the bond market in Indonesia at the end

of the third quarter in 2011. Mounting SUN price

volatility compared to the preceding quarter provided

strong indications of such conditions. Pressures of a sudden

capital reversal were closely monitored considering that

the impact of the debt crisis in Europe, which has already

spread to peripheral countries, encouraged investors to

withdraw their investments. This flight to safety appeared

in the form of SUN price volatility at the end of the third

quarter and throughout the fourth quarter.

The balance of payments further confirmed

capital outflows in the third quarter to the tune of

USD 4.9 billion. However, macroeconomic conditions

were then much better than during the global crisis

in 2008, when the rupiah succumbed to depreciatory

pressures and slumped to Rp13,000 per US$, a 50%

correction undermined the stock market, SUN prices

suffered a 30% correction and the policy rate shot up

to 9.5%. In contrast, the impact of the ongoing crisis

in Europe has not spurred rupiah depreciation, with the

rupiah averaging around Rp9,000 per US$.

Mounting volatility, which peaked in January at 6%,

marred capital flows during the past year of 2011. Intense

SUN price volatility at the time was caused by a dramatic

rise in the trade of long-term SUN, in particular 10-year,

amounting to 31.1% (mtm). However, after May 2011

SUN price volatility stabilised at an average level of less

than 1%. Bond market conditions slipped backwards as the

Greek crisis peaked in September 2011. A lack of clarity in

terms of resolving the debt crisis in Greece and peripheral

European countries also ratcheted up the volatility on SUN

prices up to the end of semester II-2011.

Figure 3.7SUN Price Volatility

-6%

-4%

-2%

0%

2%

4%

6%

Mar

-10

Mei

-10

Jul-1

0

Sep-

10

Nov-

10

Jan-

11

Mar

-11

Mei

-11

Jul-1

1

Sep-

11

Nov-

11

Jan-

12

Note: Indexed against those on 31st December 2005

Figure 3.8Performance of the JSX Composite and other

Global-Regional Indices

0.20

0.70

1.20

1.70

2.20

2.70

3.20

07/08/1107/13/1107/18/1107/23/1107/28/1108/02/1108/07/1108/12/1108/17/1108/22/1108/27/1109/01/1109/06/1109/11/1109/16/1109/21/1109/26/11

10/31/11

10/01/1110/06/1110/11/1110/16/1110/21/1110/26/11

11/05/1111/10/1111/15/1111/20/1111/25/1111/30/1112/05/1112/10/1112/15/1112/20/1112/25/1112/30/11

IHSGPOOMP

FSSTI

UKXNKY

DJIANYA

KLCIKOSPI

SETHang Seng

48


3.3 IMPACT ON THE BANKING SECTOR

The banking sector continued to dominate

the financial system in Indonesia. In general, bank

resilience was reflected by changes in CAR to absorb

exposure to the external sector in the form of

foreign banks. Low bank exposure, with a contribution

of just 3.56% of total bank assets at the end of semester

I-2012, ensured that the impact of shocks overseas did

not significantly affect bank capital domestically. In broad

terms, direct exposure to foreign banks was found in the

form of securities, placements at other banks, acceptances,

bank guarantees and irrevocable L/C. At the end of 2011,

direct exposure to foreign banks was valued at Rp129.95

trillion, representing an increase of 24.16%.

According to the results of stress tests, bank resilience

was more than adequate, with merely a small decline in the

level of CAR, to absorb market risk stemming from a drop

in SUN prices, rupiah depreciation and rising interest rates.

Meanwhile, bank resilience to domestic pressures like fuel

price hikes, which have ramifications for economic growth

and will indeed intensify bank credit risk, is sufficient

according to stress tests. Domestic economic growth is

suspected of having a significant influence over bank credit

risk. The results of simulated fuel price hikes amounting to

Rp1,500 per litre would raise credit risk as evidenced by

the 0.25% increase in non-performing loans.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

1, Indonesia 1,00 0,59 0,45 0,47 0,48 0,38 0,26 0,45 0,47 0,13 0,15 0,31 0,47 0,28 0,57 0,31 0,27 0,29 0,30 0,27 0,32 0,31

2. Singapore 1,00 0,55 0,50 0,52 0,36 0,28 0,56 0,58 0,20 0,23 0,43 0,59 0,41 0,70 0,41 0,39 0,43 0,41 0,39 0,45 0,41

3. Taiwan 1,00 0,38 0,45 0,37 0,30 0,56 0,64 0,12 0,15 0,27 0,55 0,26 0,58 0,27 0,23 0,27 0,28 0,23 0,28 0,27

4. Thailand 1,00 0,41 0,32 0,21 0,37 0,40 0,14 0,16 0,31 0,38 0,30 0,48 0,27 0,28 0,31 0,32 0,30 0,32 0,30

5. Malaysia 1,00 0,41 0,26 0,42 0,44 0,11 0,12 0,28 0,44 0,26 0,48 0,26 0,28 0,28 0,31 0,26 0,29 0,28

6. Philippines 1,00 0,18 0,38 0,36 0,03 0,06 0,13 0,42 0,14 0,39 0,17 0,13 0,15 0,16 0,15 0,17 0,21

7. China 1,00 0,26 0,30 0,07 0,08 0,15 0,27 0,15 0,43 0,10 0,12 0,15 0,15 0,15 0,16 0,16

8. Japan 1,00 0,65 0,12 0,13 0,30 0,65 0,30 0,59 0,29 0,26 0,32 0,28 0,27 0,33 0,29

9. Korea 1,00 0,17 0,19 0,31 0,60 0,31 0,63 0,30 0,26 0,31 0,30 0,28 0,33 0,32

10. Dow Jones 1,00 0,90 0,58 0,13 0,61 0,17 0,44 0,56 0,61 0,40 0,57 0,55 0,29

11. Nasdaq 1,00 0,54 0,15 0,58 0,19 0,44 0,53 0,58 0,38 0,54 0,52 0,27

12. UK 1,00 0,33 0,86 0,38 0,70 0,82 0,89 0,66 0,82 0,81 0,50

13. Australia 1,00 0,30 0,63 0,31 0,29 0,32 0,32 0,29 0,33 0,32

14. German 1,00 0,35 0,69 0,86 0,94 0,66 0,87 0,83 0,51

15.Hongkong 1,00 0,34 0,33 0,37 0,36 0,33 0,39 0,38

16. Ireland 1,00 0,67 0,72 0,58 0,67 0,69 0,49

17. Spain 1,00 0,88 0,70 0,86 0,80 0,54

18. French 1,00 0,69 0,90 0,88 0,54

19. Portugal 1,00 0,68 0,68 0,51

20. Italy 1,00 0,82 0,54

21. Belgium 1,00 0,54

22. Greece 1,00

Table 3.4Stock Exchange Correlations

49


Although this volatility is expected to persist into

the first half of the first semester of 2012, existing

policy measures like reducing the benchmark policy

rate and amending the minimum statutory reserve

for foreign exchange will help alleviate the pressure.

Holistically, financial system conditions will be

maintained during the first semester of 2012.

4. Improvements to risk-based bank supervision

will ease bank credit risk. In addition, efforts

to reinforce bank capital in anticipation of credit

risk through the promulgation of a new regulation

pertaining to risk-weighted assets, to be used as the

basis for calculating the minimum capital requirement

and which becomes effective as of January 2012,

will help reduce bank credit risk. Furthermore, the

potential for credit risk to emerge from the financial

subsidiaries of bank conglomerates also requires

close attention. However, the development of bank

conglomerates remains in its infancy, thereby not

aggravating credit risk any further.

Credit is projected to grow in 2012 by around 26%

compared to the 18% predicted for deposits. Meanwhile,

assuming economic growth of 6.32% (yoy) and inflation

at 4.33% (yoy), credit growth in the first semester of 2012

will reach around 27.12% (yoy).

3.4 THE OUTLOOK OF THE FINANCIAL SYSTEM

STABILITY

Financial system stability in Indonesia will

be maintained. Taking into account the various

considerations already elaborated above, the financial

stability index (FSI) is projected in the range of 1.40-1.71

with a baseline of 1.56. This projection demonstrates the

ongoing improvements in the financial system compared

to the second semester of 2011 when FSI was 1.63. The

predicted improvements in the financial system stem from

several salient factors as follows:

1. Macroeconomic conditions were maintained

amid the planned implementation of government

regulation no 15, 2012, which legislates retail

prices and consumption of specific types of

fuel. This regulation is merely one step in the plan

to gradually curtail fuel consumption. The Minister

of Energy and Mineral Resources will handle the

next phase of restrictions based on the results of

coordinated meetings led by the Minister of the

Economy. Considering that the restrictions on certain

types of fuel are ongoing, there is not expected to

be any fallout from this policy on the general public

during the first semester of 2012, hence, concerns

over bank credit risk can be minimised.

2. Pressures from foreign capital flows will stabilise

as portfolio investment is offset by longer-term direct

investment that tends to endure. The surge in FDI will

catalyseGDP growth and ultimately stimulate credit

growth.

3. Less volatile government bonds price. Net selling

by foreign investors as a result of selling government

bonds in Europe will affect investor perception of

markets in Asia. Capital outflows totalling Rp21.93

trillion occurred up to quarter III and IV-2011, with

the majority of investors selling government SUN. Sumber:

Figure 3.9Projected Credit Growth

30%

35%(% YoY)

25%

20%

15%

10%

5%

50


Financial system resilience in Indonesia was

relatively well preserved, which is evidenced by the

decline in the Financial Stability Index (FSI) from

1.65 in June 2011 to 1.63 in December 2011. The

value of FSI in December 2011 was below the projected

figure of 1.68. Banking sector resilience and an easing of

pressures on the capital market are in harmony with solid

economic resilience overall in Indonesia. Such conditions

were corroborated by two international rating agencies

when Moody’s and Fitch upgraded Indonesia’s rating and

affirmed investment grade status amid widespread global

economic uncertainty.

Financial system stability will be maintained

throughout semester II-2012. FSI is projected in the

range of 1.40-1.71 with a baseline of 1.56. Conducive

macroeconomic conditions, denoted by controlled inflation

and relatively robust economic growth looking ahead, will

drive positive performance in the banking sector and on

the capital market. Indonesia’s upgraded sovereign rating

to investment grade status will contribute to an influx of

foreign funds in the form of foreign direct investment

and portfolio investment. Nonetheless, vigilance and

monitoring is required from Bank Indonesia and the

Government concerning a potential sudden capital reversal

and policy measures must be put in place to anticipate as

well as minimise potential instability risk in the future.

Vigilance is also required over a number of

externalities that could potentially undermine

financial system resilience, for instance the prolonged

global economic crisis could spillover to the Indonesian

economy, in particular through a direct impact on the

balance of payments that would ultimately aggravate

domestic economic growth and inflation. Within the

country itself, unpopular fuel price hikes and restrictions

on fuel consumption, planned for semester I-2012, will

also affect inflation and economic growth. Figure 3.11Financial Stability Index

Figure 3.10Projected Growth in Deposits (% yoy)

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

1996

M01

1996

M07

1997

M01

1997

M07

1998

M01

1998

M07

1999

M01

1999

M07

2000

M01

2000

M07

2001

M01

2001

M07

2002

M01

2002

M07

2003

M01

2003

M07

2004

M01

2004

M07

2005

M01

2005

M07

2006

M01

2006

M07

2007

M01

2007

M07

2008

M01

2008

M07

2009

M01

2009

M07

2010

M01

2010

M07

2011

M01

2011

M07

2012

M01

FSI 1996 - 2012

Global Crisis (Nov 2008): 2.43

1.71

1.40

Asia Financial Crisis1997/1998: 3.23

Mini Crisis 2005: 2.33

Des 2011: 1.63 Jun 2012 : 1.

(% YoY)

10

12

14

16

18

20

22

24

2009

Q2

2009

Q3

2009

Q4

2010

Q1

2010

Q2

2010

Q3

2010

Q4

2011

Q1

2011

Q2

2011

Q3

2011

Q4

2012

Q1

2012

Q2

2012

Q3

2012

Q4

2013

Q1

2013

Q2

2013

Q3

2013

Q4

51

Chapter 4. Topical Issues

Chapter 4Topical Issues

52



53


Chapter 4 Topical Issues

4.1 STRESS TESTING THE IMPACT OF INTERNATIONAL

TRADE AND FOREIGN LOANS OF THE CORPORATION

ON BANKS

Stress Test 1: the impact of a decline in exports/

imports with PIIGS countries on the banking sector

in Indonesia

One mechanism that facilitates spillover from

the global crisis to the banking sector is through the

international trade channel (exports/imports), which can

also undermine the financial position of the corporate

sector as borrowers from the banks.

In relation to the ongoing crises in PIIGS countries

and the USA, the share of Indonesia’s trade with PIIGS is

relatively small at less than 5% of total domestic exports

and imports. The share of trade with the USA is relatively

larger at 10% of the total but this trend is in decline,

substituted by emerging market countries.

A serious problem could emerge if large domestic

conglomerates were reliant on PIIGS countries and the

USA for trade. Stress testing is performed involving lending

banks that transact (import/export) with PIIGS countries

and the USA in order to investigate the direct impact of

disruptions to trade with these countries on the banking

sector in Indonesia.

Exporters

Based on data from November 2011, there are 205

corporate exporters currently operating with loans from

domestic banks. The total amount of credit extended

to the 205 firms is Rp27 trillion, allocated by 75 banks.

Assuming that the majority of exports from these firms are

destined for the USA and PIIGS, it is fair to acknowledge

the dependence of such firms on these countries.

Using a scenario of deteriorating economic conditions

in the USA and PIIGS, the domestic corporate sector suffers

financial difficulties with 50% of the loans written off as a

loss. Based on stress tests, the aggregate average NPL of

the 75 banks exposed to the 205 exporters would increase

from 2.7% to 3.4%, while CAR would decline from 16.5%

to 15.9%. In addition, 11 smaller banks would see their

non-performing loans skyrocket to over 5% with one

bank experiencing a significant decline in CAR to below

the threshold of 8%.

Importers

Also based on data from November 2011, 40

importers are operating with loans from 35 domestic banks

for a total of Rp 38.9 trillion. Assuming that the importers

produce and trade goods, the majority of which have been

imported from the USA or PIIGS countries, there is a clear

dependence by importers on such countries.

Using a scenario of deteriorating economic conditions

in the USA and PIIGS, the domestic corporate sector suffers

financial difficulties with 50% of the loans written off as

a loss. According to stress tests, the average NPL ratio

would increase form 2.7% to 3.9%, while CAR would

drop from 16.4% to 15.4%. A further 11 banks, one of

which being a large bank, would experience an increase

in NPL to above 5% but no banks would suffer a decline

in CAR to below 8%.

54


Stress Test 2: the impact of corporate offshore

bank loans from PIIGS countries on the banking

sector in Indonesia

Spillover form the global crisis can also be transmitted

through the offshore loans channel. Although the

monitoring of private offshore loans has been an area of

focus for improvement since the onset of the modern era

of Bank Indonesia by overseeing flows of foreign exchange,

assessments into the possibility of a worst-case scenario are

continuously required through stress testing as no other

mechanism can gauge the depth of crisis conditions.

Consequently, stress testing is conducted to measure

the magnitude of the impact on the banking sector in

terms of liquidity, capital and non-performing loans if a

borrower (bank) is overly dependent on the USA and PIIGS

countries. A scenario of domestic banks with offshore loans

from the USA and PIIGS is used assuming that conditions

in the lending countries deteriorate with all loans written

off as loss (sudden death).

Two Scenarios of the Stress Tests

The first scenario measures the impact on domestic

bank liquidity if the corporate sector requests that the

banks convert the foreign debt into domestic loans. This

implies that domestic banks allocate additional credit to

such firms in order to service their foreign loans. In this

context the banking sector is confronted by a dilemma,

where in the event that the request to convert the loans

is not met, the corporate sector would have to resort to

using its own business funds to repay the outstanding

offshore loans, which would undermine business activity

and ultimately limit the affected firms’ domestic debt

repayment capacity.

On the other hand, the banking sector must also

maintain adequate liquidity (calculated by dividing liquid

assets by non-core deposits), for which the ideal value

is 100%. Ideally, banks would therefore only need to

use their excess liquidity when accepting the transfer.

Accordingly, banks would only be able to convert the

foreign debt if the process did not bring the ratio down

to below 100%.

The second scenario measures the impact on capital

and non-performing loans if domestic banks are unable

to convert the foreign debt into domestic bank loans and

bank credit to the corporate sector simultaneously matures.

Consequently, the corporate sector would have to utilise

internal funds to first repay its outstanding offshore loans

before subsequently paying off its domestic loans.

Based on the position in August 2011, as many

as 74 firms had outstanding foreign debt from the USA

and PIIGS countries totalling Rp29.3 trillion, with the US

accounting for 99.4% of the total. Furthermore, the 74

corporations were also indebted to domestic banks to the

tune of Rp12.03 trillion.

Results of the first Scenario – Impact on Bank

Liquidity

According to the first scenario 14 domestic banks

would not have sufficient liquidity to convert 50% of

the foreign debt into domestic loans. Similar results

are obtained when the worst-case scenario of 100% is

converted, only the magnitude is more severe. Under the

most probable scenario, namely that only loans maturing

in 2012 would be converted, all banks would be able

to absorb the foreign debt and convert it into domestic

loans.

Results of the Second Scenario – Impact on Bank

NPL and CAR

A second series of stress tests was conducted on

between 40 and 74 corporations, for whom financial

statements could be acquired. The assumption is that

the corporate sector would repay 50% and 100% of

its foreign debt and domestic loans respectively, where

55


the foreign debt is repaid prior to settling the domestic

loans. If after the foreign debt has been repaid the level of

corporate funds is below the level of outstanding domestic

loans, then the firm will default and the domestic loan is

written off.

Based on the data, the foreign debt of the 40

corporations totals Rp 23.9 trillion, while domestic loans

total Rp7.1 trillion. Assuming that the 40 firms have to

PIIGS country+USA

liquidity needed globally

Foreign Debts Pay off/payment

from PIIGS country

74 corporation 1

)

Foreign Debts amount: Rp29,3 T

Domestic Debts amount = Rp12,03T

40 Corporation 2

)

Foreign Debts amount: Rp23,9 T

Domestic Debts amount = Rp7,1T

Source

of fund ?

Yes No

Turned Foreign Debts into

Domestic Debts

How does the impact on

domestic banks liquidity? 2

)

Pay off Foreign Debts and Domestik Debts

thats due. If the funds are not enough, hows

the impact to banks NPL and CAR

Were net excess liquidity able to

cover additional new credit?

49 Banks

- Initial liquid Rp350,8T becomes Rp333,29T

after deducted by 50% Foreign Debts

- There are 14 banks that has not enough

excess

50% Foreign Debts and Domestik Debts pay off scenario results

NPL of 49 banks rose from 2,8% to 4,2%

Bank with NPL above 5%, increasing from 4 banks to 25 banks

CAR of 49 banks down from 17,25% to 16,05%

There are 10 banks with CAR under 8%

Note:

1) 74 corporations that has Foreign Debts from PIIGS country +USA, Domestic Debts

2) 40 corporations that has Foreign Debts from PIIGS country +USA, Domestic Debts

and Balance Sheet

3) 50% scenario from Foreign Debts +Domestic Debts paid off by company’s net profit

4) Liquid Assets after deducted by Committees Loan

1

2

Picture 4.1Stress Test: the impact of corporate offshore loans from the US and

PIIGS on the banking sector in Indonesia

repay 50% of their foreign debt and domestic loans

respectively, then 25 banks will see their NPL exceed

5% and 10 banks will experience a decline in CAR to

below 8%. Similar results are obtained when 100% of

the foreign debt and domestic loans are repaid although

the respective capital ratios are smaller and the NPL ratios

increase further.

Total 74 39

Total Liquid Assets 351 333 316

Total Foreign Debt 29,3

Total Domestic Bank Loans 12,03

Number Of Banks With Insufficient Liquidity

Corporate BankScenario

Debt Convertion 50% Debt Convertion 100%

Table 4.1Summary of Results for Stress Test 1: Impact on Bank Liquidity

in trillion rupiah

56


4.2 STRENGTHENING BANK CAPITAL AS PART OF

THE EFFORTS TO MAINTAIN FINANCIAL SYSTEM

STABILITY

A valuable lesson to come out of the global crisis was

the ease at which the impacts spread from one economy

to the next. This was linked to the increasingly integrated

nature of global financial markets and institutions. Banks,

as a financial institution with a significant role, are the

focus of attention considering their vital function as

intermediation institutions, where nearly all economic

activities involve a bank in some way. However, in reality

there are numerous banks operating globally that do not

maintain an adequate capital buffer to absorb potential

losses. One reason for this is the weak capital regulatory

regime that tends to amplify procyclicality. In addition to

capital, liquidity shortfalls are one problem that surface

during crisis periods.

The G-20 initiated global financial sector reforms in

response to the global financial crisis. The most important

elements of the reforms include reforming the capital and

liquidity regulatory regime globally as well as mitigating

procyclicality, commonly referred to as Basel III. The

new regulations are not merely microprudential but

also macroprudential due to their interconnectedness.

Accordingly, the resilience of an individual bank will

contribute to reduce the risk of shocks in the banking

system overall.

One of the new microprudential regulations relates

to efforts to augment bank capital in terms of quality

and quantity. One way to enhance the quality of capital

is through predominant common equity on tier 1 capital,

simplifying tier 2 capital as well as eliminating tier 3 and

innovative tier 1 capital. Meanwhile, in order to increase

the quantity of capital, minimum common equity should

be raised from 2% to 4.5% of risk-weighted assets and

the tier 1 minimum should be raised from 4% to 6%.

Therefore, after factoring in the conservation buffer of

2.5%, the common equity ratio, tier 1 and CAR to risk-

weighted assets are 7%, 8.5% and 10.5% respectively. An

increase in capital, which is the primary buffer to absorb

losses, is expected to ensure banks are more resilient when

facing crisis conditions.

From a macroprudential standpoint, efforts were

introduced to mitigate procyclicality through formulation

of a countercyclical capital framework, which requires a

capital conservation buffer (2.5%) and countercyclical

capital buffer (0 - 2.5%). Under the prevailing concept,

as business or economic conditions improve, banks tend

to utilise their capital to conduct business activities, for

instance by allocating credit, which can be excessive.

However, during crisis conditions banks are forced to

maintain additional capital in order to absorb any losses

that are incurred. Clearly this will exacerbate the situation

of the banks, which are already in a difficult position.

According to the new concept, banks are required to raise

their levels of capital during economic boom conditions

Table 4.2Summary of Results for Stress Test 2: Impact on Bank CAR and NPL

Average NPL of 39 banks 2,8% 4,19% 4,24%

Number of banks with NPL > 5% 5 25

Average CAR of 39 banks 17,25% 16,05% 16%

Number of banks with CAR < 8% 0 10

Before Stress TestScenario

Debt Convertion 50% Debt Convertion 100%

in trillion rupiah

57


through a conservation buffer that can be utilised during

the subsequent downturn. This is expected to alleviate

some of the burden borne by the banks during crisis

conditions.

Meanwhile, the countercyclical capital buffer was

put in place in order to avoid excessive credit growth. This

was motivated by the experience that credit bubbles often

precede banking crises. Of course, the implementation

of this policy must be performed prudentially in order

to avoid restricting much needed credit growth to boost

activity in the business community, which in turn catalyses

the economy as a whole. Therefore, the application of

a countercyclical capital buffer ranges from 0 – 2.5%

according to policy in each respective jurisdiction.

A combination of the policies mentioned, coupled

with the application of international liquidity standards

known as the liquidity coverage ratio (LCR) and net stable

funding ratio (NSFR), is expected to reduce the frequency

and depth of future banking crises. Such policies can

clearly not be implemented immediately; therefore

they will be phased in gradually starting in 2013 with

full implementation planned for 2019. Consequently,

the banking sector has sufficient time to adjust to the

new policies and meet the new requirements through a

predetermined transitional period.

The Basel Committee on Banking Supervision

(BCBS) conducted a quantitative impact study (QIS) in

order to investigate the impact of the new regulations.

Two banks from Indonesia were included in the sample

for the study, which revealed that the level of capital at

these two respondent banks was actually higher than the

level of capital based on prevailing regulations. Moreover,

internally Bank Indonesia has also conducted studies on

the application of Basel III on all banks in Indonesia using

data from monthly bank reports. In general, the results are

consistent with the QIS undertaken by BCBS, namely that

the average CAR of banks is higher based on the new Basel

III requirements compared to current regulations. Bank

CAR according to Basel III shows that the aggregate capital

value of banks remains above the minimum requirement

of 8% and 10.5% with the additional conservation buffer.

In terms of individual banks, nearly all of the banks were

able to meet the new requirements.

Prevailing Basel III RegulationsCommon Equity/Total Modal 98.5%* 88.7%

Tier 1/Total Modal 89.9% 88.4%

Common Equity/ATMR 16.0% 15.3%

Tier 1/ATMR 14.6% 15.3%

CAR 16.1% 17.3%

*) common equity prior to adjustment

Table 4.3A Capital Comparison between Prevailing Regulations

and the Requirements according to Basel III

Bank CAR according to Basel III is higher than

prevailing regulations because bank capital in Indonesia is

in the form of common equity and the majority regulatory

adjustment required by Basel III represents a regulatory

adjustment to current Bank Indonesia regulations. A

number of current regulatory adjustments are relatively

conservative; hence the application of Basel III will have a

favourable impact of bank capital. Although the share of

common equity and tier 1 to total bank capital in Basel III

is lower compared to prevailing regulations, this is more to

do with conceptual differences. For instance, according to

prevailing regulations, regulatory adjustments can be made

to tier 1 and tier 2 capital, while under Basel III all regulatory

adjustments focus on tier 1 capital. In general, tier 1 bank

capital is dominated by common equity, which is evidence

that banks in Indonesia have a solid capital structure that

is permanent and tailored to absorbing losses. In addition,

the magnitude of bank capital in Indonesia indicates that

domestic banks will comfortably meet the two new BCBS

requirements, set at a minimum of 4.5% (LCR) and 6%

(NSFR) respectively.

58


In general, banks in Indonesia will be able to meet

the capital requirements associated with Basel III, however,

a number of borderline banks require special attention.

Furthermore, many banks allocated a lot of credit

throughout the past year of 2011. Such banks will need

to start formulating ways to increase their capital. As the

dominant force in the financial system of Indonesia, sound

banks are the key to maintaining overall financial system

stability. One way that this can be achieved is through

strengthening bank capital. An adequate capital buffer

can boost domestic bank resilience to potential shocks

stemming from within the country or from overseas,

while also simultaneously enhancing the resilience of

the financial system as a whole. Crises can often not be

avoided, however, if an adequate system is set in place

then the adverse impacts should be minimised.

4.3 BROADENING PUBLIC ACCESS TO FINANCIAL

SERVICES THROUGH BANK NETWORK EXPANSION

Background

A World Bank survey conducted in 2007 found

that around 48% of all households in Indonesia did not

have access to formal financial institutions. In addition,

financial institutions in Indonesia were only serving 31%

of the general public, while 17% lived without any form

of financial services. This reality reflects the suboptimal

financial system in Indonesia. If the financial system could

reach all strata of society then the benefits of financial

services would be felt throughout the community. This in

turn would buoy the national economy considering that

the contribution from the financial sector is an important

element of economic growth.

A comparison between several countries performed

by the World Bank and IMF in 2010 revealed that use

of financial services remains relatively low in Indonesia.

This is reflected by the ratio of outstanding bank credit

(as a percentage of GDP), MSME credit (as a percentage

of GDP), total bank depositors per 1,000 adults, and

outstanding deposits (as a percentage of GDP), all of which

are relatively low as presented in Table 4.4.

One determinant of the high number of citizens with

no access to financial services in Indonesia is geographical.

Limited infrastructure and the natural conditions of the

Indonesian archipelago are two of the constraints banks

must fight to overcome when providing public services in

remote and rural areas. The problem of limited banking

services in such outlying areas is also linked to the bank’s

economies of scale in each respective area of operation.

This pattern can be observed from the distribution of

banking services, like branch offices and ATM per 1,000

km2, as well as the ratio of banking services to service area

as presented in Table 4.4.

Table 4.4Adoption of Financial Services

Indicator Indonesia Malaysia Thailand Philippines Brazil

Adoption of Financial Services Number of bank borrowers per 1,000 adults 274,80 284,06 236,98 n.a 193,96

(unit: persons)

Outstanding bank credit (% of GDP) 27,49 93,59 85,18 27,57 29,04

MSME credit (% of GDP) 0,67 17,43 30,67 n.a 3,77

% of MSME credit/total bank credit 21,6 39 35 n.a n.a

Number of depositors per 1,000 adults 504,74 1.619,94 1.119,94 487,76 n.a

(unit: persons))

Outstanding deposits (% of GDP) 36,41 117,17 74,04 53,02 47,51

59


Data on the ease of access to the financial sector in

Indonesia, when observed for each respective province,

illustrates a variety of conditions. In West Irian Jaya and

Papua, financial services have to cover an area of more than

1,000 km2. The hostile terrain that must be covered and the

lack of infrastructure available exacerbate the exhausting

distances that must be traversed by those wishing to

engage in financial services. Java is the best-served island

by banking services, while Sumatera, Kalimantan and

Sulawesi continue to suffer from a dearth of banking

services in the form of branch offices and ATMs.

When the number of adults served by each outlet

is taken into consideration, it can be seen that areas

in Eastern Indonesia, like East Nusa Tenggara, Papua

and Maluku require better financial services with each

outlet currently serving more than 20,000 of the adult

population.

Branchless Banking

In response, a breakthrough is required in order to

broaden public access to financial services, in particular

banking services. The concept of branchless banking is

one solution to reaching the unbanked in remote areas.

Branchless banking is a distribution strategy to provide

financial services without depending on the presence of a

traditional or ‘brick-and-mortar’ branch office. One aspect

is to exploit information, communications and technology,

namely cellular telephones (mobile banking), point of sale

systems connected to terminals, GPRS and others. Another

aspect is the current outsourcing trend, involving grocery

Table 4.5Access to Financial Services

Indicator Indonesia Malaysia Thailand Philippines Brazil

Level of Access to Financial Services Number of branch offices per 1,000 km2 7,71 6,18 11,59 15,69 2,33

Number of branch offices per 100,000 adults 8,32 10,48 11,16 7,69 13,76

Number of ATMs per 1,000 km2 12,39 33,12 80,68 30,35 20,46

Number of ATMs per 100,000 adults. 13,37 56,18 77,69 14,88 120,62

Figure 4.2Number of Banking Services per km2

60


Figure 4.3Number of Adults per Financial Service Outlet

stores, counters selling mobile phone credits and petrol

stations (agent banking).

Over the past decade, branchless banking using

cellular telecommunication technology (and agents selling

credits) has become a hot topic due its compatibility with

conditions for people at the bottom of the proverbial

pyramid. One form of branchless banking that has gained

popularity in many developing countries in recent years

is mobile money. Under this scheme, end users can save

their money using a cellular phone and then actually

deposit or withdraw the money through agents working

in cooperation with the bank. Mobile money has already

been implemented in Kenya and the Philippines.

Globally there are two types of branchless banking

as follows:

1. Telco-led model: telecommunications companies are

the initiators due to their technological competence

and existing network of credit top-up retailers as

well as penetration and reach to remote areas.

The banks play a supporting role and even without

bank involvement telecommunications companies

can still provide financial services, similar to the

case of Kenya. Safaricom is a telco company that

launched the MPesa product. The services offered

by MPesa (a telephone and 35,000 agents) include

cash-in/out, transfers, purchases of goods, shopping,

government financial aid programs, insurance,

remittances from 52 countries, prepaid cooperation

with Visa, payment of bills, school fees, allocation of

credit, salary disbursements and dividend payments.

Indirectly, Safaricom has become the largest retail

bank in Kenya, with which the banking sector cannot

compete despite a focus on the payment system

(money velocity).

A weakness in this approach is that the customers’

money does not accrue interest, nor does a deposit

insurance corporation guarantee it. Customers are

also not given the opportunity to apply for loans

through this system as they would with conventional

banks.

2. Bank-led model: in this case the bank is the pioneer,

serving the general public relying on support from

a telecommunications company and agents as well

as other merchants. This form of synergy not only

61


accelerates money velocity, however, customer

protection and the possibility of obtaining credit that

suits the needs of the customer are also important.

Using this approach, Brazil successfully added 19

million new bank accounts in four years circulating

more than USD 100 billion. There is now no district

in Brazil that does not benefit from banking products

and services.

In general, the application of branchless banking

requires a number of important elements as follows:

1. Information, communications and technology.

This includes the technology provided by

telecommunications companies, interoperability

among the payment systems like ATMs, as well as

retail clearing available to all providers and banks/

institutions involved.

2. Reliable and trusted agents that can open accounts for

new customers and handle cash-in/out and transfers.

Agents must be furnished with additional technology

like EDC, POS and/or cellular telephones.

3. Supporting polices/regulations. Neither of the first

two points will materialise without support from

appropriate policies and regulations.

Branchless banking “extends the reach and depth

of financial services” and greatly benefits the general

public at the bottom of the pyramid, who are generally

found in rural areas, well out of the reach of traditional

banking services.

Application Constraints

1. Documents. It would be wrong if, because of limited

valid documents, a lack of technology and low

incomes, the people at the bottom of the pyramid

were unable to connect to the banking sector, could

not save or could not transfer money or apply for

credit congruent to their conditions and requirements.

Proportional regulations supplemented with other

mitigating tools are one possible solution. Looking

ahead, the general public is believed will favour

financial transactions with non-bank providers,

namely in the form of branchless banking and this

trend has already persisted for the past decade in

many emerging market countries.

2. Knowledge and culture. The understanding of people

at the grass roots level concerning banking products

and services remains low; therefore, it is necessary to

improve financial literacy. This is compounded further

by an untrusting culture in terms of entrusting money

to someone else or through the use of technology.

3. Suitable products. For grass roots members of the

general public, administrative fees are a consideration

because they can erode their level of savings. Small

loans repaid on a daily or weekly basis are most

appropriate but rarely offered by conventional

commercial banks.

4. Know your customer principles, which require each

new account to be opened with a valid document

that the customer must sign directly, face-to-face

with the bank employee, can help the bank ensure

the validity of the prospective customer.

Practices in other Countries

1. In Kenya prior to 2007 only 7.5% of the population

had a bank account, however, fast-forward to 2011

and as many as 40% of the adult population owned

a bank account with 83% of the population owning

a mobile telephone. Accordingly, Safaricom, which

is the largest telecommunications operator in Kenya

with an 89% market share, became known as one

of the most successful companies through its mobile

money financial service and the associated product

called MPesa. MPesa experienced growth in excess of

250% from April 2007 to November 2011. Using the

62


MPesa product citizens can transfer money, initiate

payments as well as deposit and withdraw money

through the biggest agent network in Kenya.

2. Public access to banks in South Africa is relatively

good with 63% of the adult population having

a bank account. The high pick-up rate for bank

accounts in SA is due to a government program

known as ‘Mzansi Initiatives’ operated from 2004-

08 that invited the unbanked community to open

bank accounts in the form of a magnetic debit card.

There are over 10,000 ATMs and 100,000 POS in

the country so South Africans were already used to

making card-based payments. This mobile banking

product was offered by nearly all banks in SA as an

additional service for their customers.

3. In the Philippines the first SMS financial service

using mobile phones was offered by SMART (a

telecommunications company), where the general

public could access services like deposits and

withdrawals without visiting a bank. Over time,

SMART extended its network through cooperation

with merchants and public service companies as well

as the banking sector in order to enhance its service.

The development of mobile money in the Philippines

was possible due to deep mobile phone penetration,

with mobile phone subscribers skyrocketing from

5 million in 2000 to more than 81 million in 2010.

Growth in mobile phone usage was bolstered by the

availability of mobile payments through handsets in

2009, by which time 57% of the adult population

in the Philippines had a bank account.

Practices in Indonesia

From observations in Indonesia, branchless banking

has already begun domestically (in addition to ATMs and

the Internet) but products remain thin on the ground as

follows:

1. Telkomsel launched its product known as T-Cash.

2. Telkom has a product known as Delima.

3. Satelindo launched DompetKu (MyWallet).

4. BPR-KS has EDC.

5. Bank Sinarmas serves the Sinarmas Group through

cooperation with Smart.

6. Bank Sinar Harapan Bali is conducting trials regarding

cooperation with Axis.

Future Application

The best application of branchless banking in

Indonesia would come in the form of a hybrid model,

namely one that is led by the banks but supported through

cooperation with telecommunications companies and

agents (bank-led model). Implementation also involves

rural banks and microfinance institutions (LKPD, LPN, BKD,

etc.). The involvement of rural banks and microfinance

institutions is crucial to create synergy among those

involved.

In its preliminary stage, the application of branchless

banking enables customers access to services like cash-in/

out, money transfers and payment of bills as a pilot project.

All mobile phone subscribers have the mobile banking

application pre-installed on their SIM cards. In order to

succeed, the existing constraints must be overcome,

including revisions to KYC principles, massive financial

education programs, availability of suitable products, as

well as supporting infrastructure.

Bank Indonesia is continuing its financial inclusion

program in collaboration with the Government in order

to broaden public access to banking services by negating

existing price and non-price constraints. The financial

inclusion program is supported by five pillars, one of

which is distribution that aims to expand the reach of

formal financial services to residents in remote and rural

areas. One activity conducted was a study into branchless

banking, which covered the possibility of applying mobile

63


banking in Indonesia. Through this concept it is hoped

that unbanked citizens in remote and rural areas will have

access to banking services. (*)

4.4 EUROPEAN CRISIS

The turmoil in Europe remained at a critical stage

with vulnerability rife in the banking sector. Deleveraging

by banks in the euro zone continued, which led to a scarcity

of global financing. The effect of contagion was visible

through the financial and trade channels. Consequently,

effective coordination is required in terms of compiling a

sound contingency plan.

The impact of the crisis in Europe on the performance

and resilience of the global financial sector, including

Indonesia, requires close observation. Up to yearend

2011 the performance of financial markets and banking

sectors in the Asia/Pacific region, including Indonesia, were

affected by the sovereign debt crisis in the euro zone as

well as the downturn in global economic growth and less

international trade. In Asia/Pacific, contagion from the

crisis in Europe was transmitted through the trade and

financial channels. Regarding the financial channel, banks

in Europe experienced funding shortfalls in US dollars,

which went on to affect other banks with the exception

of those not yet active internationally, including banks in

Indonesia. Nonetheless, action from the ECB and other

central banks through multi-currency swap lines has

alleviated tight dollar liquidity for the time being. Referring

to the trade channel, weak exports are being reported as

reflected by languid trade growth in a number of countries

that depend heavily on exports. Although the financial

sector in Indonesia was stable up to yearend 2011, the

Government and Bank Indonesia remained vigilant over

the transmission of contagion through the financial and

trade channels. Preparations in Indonesia took the form of

a Crisis Management Protocol (CMP) formulated by Bank

Indonesia with the Government.

Shocks in the Euro Area

The sovereign debt crisis in Europe remained at a

critical stage. Although agreement was reached to save

Greece, market players remained relatively pessimistic

considering that the decision undermined the already bleak

global economic growth outlook for 2012. Risk aversion

continued globally, despite previous endeavours to

supplement market liquidity by the ECB and other specific

central banks5, among others, through multi-currency

swap lines. Such circumstances illustrated the relative

scepticism of market players concerning the policies taken.

In addition, credit rating agencies signalled their intent to

downgrade the ratings of all euro zone member countries,

which reinforced the lost perception of risk-free status for

financial instruments categorised as sovereign.

The deleveraging process of banks in Europe began

amid a scarcity in sources of funds and capital. More

deleveraging is expected in 2012, with banks cutting

back their credit lines and trade finance or withdrawing

dollars from other jurisdictions. This is reflected by a

significant potential contraction on the banks’ balance

sheet (refer to Figure 4.1), which creates feedback loops

between pressures on the sovereign and the banking

system and undermines economic prospects. Spillover

pressures emerged outside of the euro zone, which

dented global economic prospects over the past few

months. Furthermore, in the midst of lacklustre market

confidence investors tended to seek safe havens. Under

serious conditions, potential deleveraging in emerging

market countries is significant.

The relevant authorities instituted a policy response

to the sovereign debt crisis and slow growth in the US.

The policy response taken comprised of low interest rates,

the purchase of assets and the provision of liquidity by the

central bank as lender of last resort. Consequently, the

5 ECB bekerjasama dengan Federal Reserves, Bank of Japan, dan Swiss National Bank.

64


balance sheets of central banks experienced a significant

expansion. There are two issues relating to this expansion

that require close monitoring as follows: 1) mounting

credit risk faced by the corresponding central banks; and

2) the adjustment process, borne by public funding, will

ultimately undermine the credibility of the central bank

and place additional pressures on the exchange rates in

affected countries. It is feared that this process will trigger

new shocks on global financial markets.

Stressed financial market conditions in Europe

coupled with unpropitious economic prospects could raise

the risk of contagion at the international level through:

a. Risk-averse market players. The evaporation

of capital flows and increased integration among

financial markets escalated risk aversion and

deleveraging by creditors in Europe.

b. Interconnection and exposure to banks in

Europe. Losses stemming from exposure to banks

in Europe can be transmitted to other banks and

financial institutions globally. As is the case with

losses from exposure to sovereign bonds.

c. The trade channel. Trade financing is becoming

scarce due in part to limited asset growth by banks

in Europe as a result of deleveraging.

d. Safe havens. Untargeted shifts in the exchange

rate due to investors seeking safe havens. The most

favoured currencies include US dollars, Swiss francs

and Australian dollars.

On the other hand, the banking sector in the euro

area continued to face a number of arduous challenges.

Widespread deleveraging was attributable to, among

others, suboptimal sequencing processes. The European

Banking Authority (EBA) requested banks to raise their

minimum capital, while the capacity of banks to actually

raise capital is currently low and capital is expensive amid

uncertain and unpredictable market conditions. In addition,

a protracted transmission process has encouraged banks

to favour balance sheet downsizing in order to meet

prevailing capital requirements. There are concerns

that this policy will compound procyclicality during the

ongoing crisis. Two other significant challenges include

the dollar liquidity funding gaps and the sluggish domestic

economies of Europe. Consequently, the deleveraging

process by banks in Europe is expected to expand.

Such unsettling conditions require comprehensive

policy to restore market confidence. Policy failures in

the euro area will spread globally through the trade and

financial channels. Consequently, it is currently accepted

that the rescue policy needs to be massive and flexible with

front-loaded measures. The policies that should currently

be considered as priorities for authorities in Europe include,

Spain France Germany

20132012

12%

10%

8%

6%

4%

2%

0%

UK Switzerland Average

Figure 4.1Average projected Contraction onEuropean Banks’ Balance Sheets

Source: BIS, processed

Asia Latin America Eropa

2010 Jun-112007 2008 2009

1.6

1.4

1.2

1

0.8

0.6

0.4

0.2

0

Figure 4.2European Bank Lending to Emerging Economies

(in trillions of US$)

Source: BIS, processed

65


among others: a) bank recapitalisation and restructuring

as conducted in Indonesia during the crisis in 1997-98; b)

a term-funding backstop; and c) application of a blanket

guarantee or explicit deposit insurance.

To this end and in anticipation of more severe

fallout to come, the role of the Financial Stability Board is

becoming increasingly important, where inter-authority

coordination is urgently required, among others, to

undertake contingency planning as follows:

a. Intensive cooperation among all FSB members to

minimise the potential risk of deleveraging and the

possibility of worse to come.

b. Home supervisors must ensure that the deleveraging

process is orderly and various options are attempted

to strengthen capital.

c. Clear communications between home and host

authorities to ensure joint implementation of the

contingency plan, particularly in countries most

affected by the crisis.

Liquidity support on primary markets for each

currency is required to reduce funding stress. Under the

worst-case scenario, it is crucial to guarantee the smooth

operation of financial infrastructure and identify ways to

overcome big bank defaults.

Impact on and Mitigation of Risk in Indonesia

For Indonesia, one impact of the low interest rate

policy and weak global economic prospects that requires

tight vigilance is capital inflows. This is due to favourable

growth prospects in Indonesia, which boosts market

confidence. In addition, the improvement in Indonesia’s

rating to investment grade status also spurred market

confidence. In this respect, the return of potential carry

trades on currencies with a relatively high interest rate

must also be monitored. A deluge of capital inflows will

catalyse credit growth but there remains the threat of asset

price bubbles if credit growth exceeds its corresponding

prudential corridor.

Nevertheless, amid global financial market shocks,

the banking sector in Indonesia maintained positive

performance and solid resilience. The capital adequacy ratio

(CAR) reached 16.6% with net NPL at 0.8% (November

2011), which demonstrated the high level of solvency and

resilience to credit risk as the main risk faced by the banking

industry in Indonesia. The results of stress tests indicated

that the domestic banking sector would dampen any

increases in credit risk, market risk and liquidity risk. On the

other hand, the minimum statutory reserve requirement

based on the loan to deposit ratio has helped balance

intermediation with policy to avoid systemic liquidity risk.

In addition, the Government and Bank Indonesia have

prepared a crisis management protocol, which is expected

to bolster coordination and facilitate a quick authority

response in order to prevent systemic risk.


67

Article 1. External Shocks, Macroeconomic Stability, and Monetary Regimes in the Small open

New Keynesian Model of the Indonesian Economy

Article

68




69



I. INTRODUCTION

To stimulate the US economy which was hardly affected

by the US financial crisis 2008, the Federal Reserve pumped

billion dollars to the economy in the effort searching the light of

recovery. This action is well-known as quantitative easing (QE)

program. In Europe, similar problem exists. Some European Union

(EU) members like Greece and Ireland have very serious public

debt problem and current deficit. To avoid being default, they

seek liquidities assistance from European central bank. Greece

has received the second bailout within 1 year.

Large-scale monetary stimuli in the US and Europe precipitated a surge in liquidity that ultimately

lowered the level of yield on global financial markets. Furthermore, bleak economic prospects

stemming from excessive government debt, acute budget deficits and shortfalls in the current

accounts of numerous advanced countries undermined investor confidence. Consequently, investors

diverted their funds away from developed countries in favour of emerging market countries that

performed better economically and could offer higher yields. The influx of short-term capital flows

to developing countries became known as hot money. In this paper the small-open new Keynesian

model is used to model the determinants of hot money flows to Indonesia and their impact on

economic stability in terms of monetary policy (domestic inflation targeting, (CPI) inflation targeting,

exchange rate targeting and Taylor Rule implicit policy targeting). Simulations revealed that domestic

inflation targeting leads to the smallest welfare losses while exchange rate targeting leads to the

largest compared to other elements of monetary policy.

Keywords: new Keynesian, small open economy, external shocks, monetary regimes, Indonesia.

JEL Classification Number: E52, E32, F41

The Fed and European central bank printed new money

to conduct the QE programs or bailouts. As the result, the US

and European financial markets have excess liquidities which

push down the returns in their financial markets. These excess

liquidities which flow to emerging markets are regarded as

“hot money”. They have a short investment horizon and can

be pulled out any time without any exit constraints. Financial

markets in EM become bullish. As the result, cost of borrowing

is decreasing. However, there is concern about negative effects

of hot money inflows. First, sudden reversal of hot money flows

1 flexible CPI inflation targeting in Svenson (2000) is close to the definition of “Taylor rule” implicit policy targeting in this paper.

External Shocks, Macroeconomic Stability, and

Monetary Regimes in the Small-open New Keynesian Model

of the Indonesian Economy

Article 1

Bayu Kariastanto1

70



can affect the stability of emerging market economies. Second,

hot money inflows will cause currency appreciated over its real

value. It may affect competitiveness of domestic products in the

international markets. Currency appreciations also make foreign

products cheaper. It can lead to the deterioration of current

account surplus in the country’s balance of payment.

There are debates about effective policies to deal with the

above conditions. Some economists argued that government

should limit the flow of short term liquidity because they just

cause instability in the domestic economy and their benefits are

not proven yet. Other economists argue that government should

intervene the market to keep exchange rates at designed rate

or at least reduce the exchange rate volatilities. The rest argued

that government should only care to the inflation stability which

indirectly stabilizes other economic indicators.

To join discussion above, in this paper, I develop small open

Keynesian model of Indonesian economy to mitigate the effect of

hot money inflows (which can be caused by real shocks in global

economy and/or by shocks in international financial market). I

also simulate the best monetary policy to deal with hot money. I

found that domestic price targeting is the best policy to minimize

the welfare losses.

II. LITERATURE REVIEW

New Keynesian model is currently regarded as the most

sophisticated model and employed by almost all central banks in

the world. This model dominates articles in the leading monetary

and business cycle journals. Unfortunately, new Keynesian model

researches on Indonesian economy are still few. Consequently,

supporting researches such us experimental research on

consumer preference are not well-developed.

There are some studies to find optimal monetary policy

using new Keynesian model of the small-open economy. Svenson

(2000) found that flexible CPI inflation targeting is the most

effective policy rule in dealing with various shocks. Gali and

Monaceli (2005) develop new Keynesian model of the small-open

economy and calibrate the model with Canadian data. They find

that domestic inflation targeting is the optimal monetary policy

to deal with home and foreign technology shocks. In spirit of

Gali and Monacelli (2005), Liu (2006) develop model for the

New Zealand economy and find that model can replicate well

fluctuation in the New Zealand economy, even though this

paper didn’t explicitly state the best monetary policies. Korinek

(2010) find that excessive foreign borrowing which partly caused

by hot money flow can increase the risk of the occurrences of

financial crisis. He argued the best policy response to deal with

hot money is to impose reserve requirement on foreign debts.

Gertler, Gilchrist, and Natalucci (2003) study Korean experience

in Asian financial crisis (sudden reversal of liquidity or massive

liquidity outflow). They argued that flexible exchange rate (Taylor

policy rule) will produce smallest welfare loss in Korea.

As described above, the previous studies conclusion about

the best monetary policies to deal with hot money and other

shocks are still mixed. This paper contribution is to formulate

the best monetary policies for Indonesia to deal with hot money

inflow caused by external shocks.

III. THE MODEL

The core framework is a small open economy with nominal

price rigidities base on work of Gali and Monacelli (2005). The

key modification is introduction of exogenous shocks on global

economy and global financial markets to capture the causes of

capital inflows to emerging markets. Consequently, the reverse

shocks can also trigger sudden reversal of capital flows.

Within this model there exist households and firms. There is

also government and foreign sectors. Households work, save, and

consume tradable goods which are produced both domestically

(D) and abroad (F). Domestically and foreign-made goods are

not perfectly substitutes.

Within the home country, there are two types of producers:

good producers and retailers. Good producers consist of many

identical firms that produce final good for both domestic

consumptions and exports. Retailers sell the final goods to

the costumers. They are monopolistically competitive and set

71



nominal price on a staggered basis. The role of retailers in this

model is to provide nominal price rigidities as common in the

new Keynesian model.

III.1. Households

IIII.1.1.Consumption Composites

Let Ct be a composite of tradable consumption goods.

Households preference over home consumption, , and foreign

consumption, , is expressed by CES index:

(1)

The corresponding consumer price index (CPI), Pt , is

expressed by:

(2)

The static optimization the above problems yield the

optimal allocation between domestic and foreign goods at

any given expenditure which can be expressed by the isoelastic

consumption demands:

(3)

III.1.2.Household’s Decision Problem

Let N denotes household labor, then for each period,

household maximizes his utilities which are represented by:

(4)

Subject to sequent of budget constraint:

(5)

where Wt denotes nominal wages, TRt government

transfer, Tt lump sum tax, Bt nominal bond in domestic currency,

and it nominal interest rate.

The optimality condition for household problem can be

written as:

(6)

(7)

III.2. Firms

III.2.1.Production

A typical firm in the home economy produces a

differentiated good with linear technology, A, represented by

the production function:

(8)

The real marginal cost, MC, will be common across

domestic firm and expressed by:

(9)

In the equilibrium, the domestic production should be equal

with domestic good consumptions and exports. Mathematically,

it can be expressed with:

(10)

III.2.2.Price Setting

Following Calvo (1983) and Yun (1996), each firm may

reset its price with probability 1- ø at any given period. This

implies that domestic firm will choose to maximize:

Subject to sequent budget constraints:

where is the stochastic discount factor for nominal payoffs,

ø_t (.) is the cost function, and is output in period t+k for

a firm which reset its price at period t.

The first order condition (FOC) of this optimization problem is

written as follow:

(11)

where denotes the nominal marginal cost and M=

denotes desired mark up.

Given the pricing rule above, the domestic aggregate price index

evolve as follow:

(12)

III.3. Government

Each period government imposes a lump sum tax on

household income and spends tax revenue on welfare program

which directly enjoyed by household. Government maintains

balance budget such as Tt= TRt at all t.

Government also conducts monetary policy to stabilize

the economy. There are four policy rules which can be chosen:

�

.

72



domestic inflation targeting (DIT), strict (CPI) inflation targeting

(CIT), exchange rate targeting (PEG), and “Taylor rule” implicit

policy targeting (IPT).

Policy rule for DIT, CIT, PEG, and IPT consecutively can be written

as2:

(13)

(14)

(15)

(16)

where denotes nominal exchange rate and denote natural

rate of capital returns.

III.4. Foreign Sectors

III.4.1.Term of Trade, Exchange Rate, and Risk

Sharing

Terms of trade, S, are defined as the price of imported

good relative to price of domestic good than can be expressed

as follow:

(17)

Hence, real exchange rate is defined as:

(18)

Under the assumption of complete international financial

market and homogenous preferences across the countries, we can

derive uncovered interest parity (UIP) condition from household’s

Euler equation (equation 7) which can be written as:

(19)

III.4.2. Philips Curve and Economic Dynamics in

the Rest of the World

Since the small open economy cannot affect the equilibrium

in the rest of the world, the Philips curve in the rest of the world’s

economy corresponds to the Philips curve in the closed economy

which can be expressed in the log-linearized form as:

(20)

where and marginal cost is given by:

(21)

I shock technology to capture exogenous shocks in the rest of

the world’s economy. The dynamic of technology is represented

by AR(1) process as follow:

(22)

As discussed in Gali and Monacelli (2002), monetary

authority in the rest of world economy can conduct monetary

policy base on a policy rule. I assume that monetary authority

conducted monetary policy base on standard Taylor rule which

is not necessary to be the best policy in this model. The rule is

as follow:

(23)

Where is exogenous monetary policy shock to capture

sudden increase (decrease) premium that should be paid by small

open economy when borrow from financial market. Current hot

money inflow to the emerging market in this model is regarded as

a shock to which decreases rate of return in the international

market. Consequently, sudden reversal should be regarded as a

big shock in the international financial markets. The evolves

as AR(1) process expressed by:

(24)

III.5. Calibration

For calibration, quarterly Indonesian and US data from

1990 to 2010 is obtained from International Monetary Fund’s

International Finance Statistic (IMF’s IFS). US economy is used to

represent the rest of world’s economy described in the model.

I fix the quarterly discount factor at 0.97, which implies

a riskless annual return of about 14% as the average central

bank rate in the data. A baseline value of is set to be 0.7 to

match average consumption to GDP ratio in Indonesia from

1990 to 2010. It implies that degree of openness to be 0.3.

To reach balance trade in the steady state, I set inter temporal

consumption elasticity and elasticity of substitution between

home and foreign good to be 1. Since I cannot find experimental

study about preference parameters in Indonesia, I follow Gali

and Monacelli (2005) in choosing parameters value in the labor

preference. Hence, labor disutility parameter set to be 3. As 2 The first three equations follow Gali and monacelli (2005).

73



is common in the literature, I set the probability of the price

not adjusting on Carlvo pricing, θ to be 0.75. The elasticity of

substitution between differentiated goods from the same origin,

θ set to be 6 which implies a steady state of mark up of 20%.

To calibrate parameters in monetary rule, I follow original

Taylor rule. Hence, I set , , and to be 1.5, 0.5, and 0.5

respectively. Natural rate of capital returns τ set to be 0 to make

the equilibrium closer to equilibrium in competitive economy.

I went to the data set to calibrate premium shock. Table 1

shows the regression result. The result implies that the average

Indonesian premium rate is about 2%. Foreign technology shock

is calibrated using US data following Gali (2008). The exogenous

stochastic processes finally can be approximated by following

equations:

(24)

(25)

IV. RESULT

IV.1. Impulse Responses

Figure 1 shows evolutions of foreign GDP and nominal

interest rate under technology shock and monetary shock.3

Technology shock is a standard deviation of foreign technology

shock which leads to temporary increase in foreign productivity.

Technology shock will increase GDP and decrease price level

in foreign countries. Inflation has more weight than GDP in

determination of nominal interest rate. Consequently, nominal

interest rate will decrease by 0.4 of standard deviation of

technology shock. Since home interest rate is still higher than

foreign interest rate, demand on domestic bond will increase

and domestic interest rate will decrease until UIP condition is

satisfied.4

A standard deviation monetary shock can cause decrease

both foreign GDP and nominal interest rate. As discussed in

Gali (2008), monetary shocks will correlate positively with real

interest rate. Since the real interest rate increase, foreign GDP will

decrease. GDP decrease will be responded by decrease nominal

interest rate to stimulate the economy. Because at that moment

home interest rate is still higher than foreign interest rate,

demand on domestic bond will increase and domestic interest

rate will decrease until UIP condition is satisfied.

Finally, conclusion can be made that a positive technology

shock and monetary shocks in foreign countries will lead to

the capital inflow to home economy (a small open economy).

Phenomenon of current hot money inflow to Indonesia and other

emerging markets could be explained by technology shock or

monetary shock in global economy. To be more precise, it caused

by technology or monetary shocks in the US and Europe.5

Figure 2 shows the evolution of domestic variables

under foreign technology shocks. As discussed above, foreign

technology shock increases foreign GDP, decreases foreign

price level and foreign interest rate. It is difficult to intuitively

determine overall effects of foreign technology shock on various

domestic variables because the effect’s directions are mixed.

The summarized effects are as follow: increase foreign GDP

stimulate increase domestic export, foreign deflation decreases

CPI/domestic price level and then decreases home GDP, decrease

foreign interest rates will depreciate domestic currency and/or

decrease domestic interest rate to satisfy UIP condition. Overall

effects will depend on monetary policies and parameters in the

model.

Output is reduced under all monetary policies. CIT brings

the lowest drop in output. Meanwhile, DIT almost replicates CIT

result and IPT causes the biggest output volatility. Regarding

response on inflations, both CPI and domestic inflation decrease

under all monetary policies. DIT brings the lowest inflations

volatility, followed by CIT, IPT, and PEG.

From the figure 2 we can also see that PEG brings no

volatility in exchange rate. Meanwhile, the other monetary

regimes bring permanent depreciation on exchange rate. DIT

causes the biggest depreciation, followed by CIT and IPT. The

3 Note that all variables are in log deviation or in deviation from competitive equilibrium.

4 See equation 16.

5 The US and Europe can represent foreign economy in this model since their GDP is big enough and shocks in Indonesia (home economy) cannot affect their economy.

74



effect on term of trade is also negative under all monetary

regimes. The order from the most efficient monetary regimes

in minimizing volatility of term of trade is as follow: CIT, DIT,

PEG, and IPT.

Figure 3 shows the evolution of domestic variables under

foreign monetary shocks. In the foreign country, foreign monetary

shock will decreases foreign GDP, increase foreign price level, and

decrease interest rate. It is also difficult to intuitively determine

overall effects of monetary shock on various domestic variables

because the effect’s directions are mixed. The summarized effects

are as follow: decrease foreign GDP will decrease domestic

export, foreign inflation will increase CPI/domestic price level and

then increases home GDP, and decrease foreign interest rates will

depreciate domestic currency and/or decrease domestic interest

rate to satisfy UIP condition. Overall effects will also depend on

monetary policies and parameters in the model.

We should note that the current hot money inflow is more

suitable to be modeled as monetary/financial shocks. Monetary

shocks reduce both GDP and interest rates in foreign economy

such us what currently happen in global economy.

Under foreign monetary shocks, domestic output decreases

in the first period, but increases in the following period under IPT

and ICT. Output remains constant under DIT, but decrease under

PEG. If government only cares with benefit of capital inflow and

doesn’t care with the reversal of capital flow, IPT will become

the best monetary policy, followed by CIT.

Nominal interest rate increases under CIT and gradually

reverts back to the steady state value. Under IPT, interest rate

increases in the first period and decreases afterward until revert

back to the steady state value. Meanwhile, interest rate remains

constant under DIT and decrease under PEG. Both domestic and

CPI inflation increase under CIT and IPT, and then gradually revert

back to the steady state value. Under DIT, domestic inflation

remains constant and CPI inflation increases in the first period,

and then decreases afterward. Under IPT, both domestic and

CPI inflation are decreasing until they revert back to the steady

state value.

Regarding exchange rate, PEG brings no volatility in

exchange rate. Meanwhile, the other monetary regimes bring

permanent depreciation. IPT causes the biggest depreciation,

followed by CIT and DIT. The effect on term of trade is neutral

under PEG, but positive under other monetary regimes. The order

from the most efficient monetary regimes in minimizing volatility

of term of trade is as follow: PEG, DIT, CIT, and IPT.

IV.2. Welfare Analysis

Following Gali and Monacelli (2005), we calculate the

expected welfare losses which can be expressed in term of

variance of inflation and the output gap as follow:

(26)

Table 2 shows the welfare losses under various shocks

and monetary policies. The DIT is the most efficient policies,

followed by CIT, and IPT. PEG is the most inefficient policies

since it produces the biggest welfare lost. Therefore, government

should consider deeper if they want to peg exchange rate directly

or indirectly. DIT and CIT produce almost same welfare losses. It

highlights that inflation targeting framework is still considered

as the best policy to deal with hot money.

V. CONCLUSION

Hot money inflow to the emerging market can be regarded

as natural economic process to balance return on global financial

market. There are two external causes of hot money inflow:

technology shocks and monetary shocks in global economy.

However, the current hot money inflow is more suitable to be

modeled as monetary/financial shocks in global economy because

they reduce both GDP and interest rates in foreign economy such

us what currently happen in global economy.

The effects of hot money inflow on macroeconomics in

Indonesia are mixed and depend on what monetary policy will

be employed in Indonesia. From the welfare analysis, domestic

inflation targeting (DIT) is the most efficient policy and exchange

rate peg (PEG) is the most inefficient policy to deal with hot

money inflow.

75



REFERENCES

Calvo, G. (1983). Staggered Prices in a Utility-Maximizing

Framework. Journal of Monetary Economics, 12,

383-398.

Gali, J. (2008). Monetary Policy, Inflation, and the Business

Cycle. New Jersey: Princeton University Press.

Gali, J., and Monacelli, T. (2005). Monetary Policy and

Exchange Rate Volatility in a Small Open Economy.

Review of Economic Studies, 72, 707-734.

Gertler, M., Gilchrist, S., and Natalucci, F. (2003). External

Constraints on Monetary Policy and the Financial

Accelerator. NBER Working Paper No. 10128,

retrieved August 15th, 2011, from http://www.bis.

org/events/conf0303/gertgilc.pdf.

Harmanta, Bathaluddin, M.B., and Waluyo, J. (2010).

Inflation Targeting under Imperfect Credibility based

on ARIMBI; Lesson from Indonesian Experience.

Paper presented at Central Bank Macroeconomic

Modeling Workshop 19 - 20 October 2010 Manila,

Philippines, from: www.bsp.gov.ph/events/2010/

cbmmw/downloads/papers 2010_CBMMW_01_

paper.pdf.

Korinek, A. (2010, September). Excessive Dollar Borrowing

in Emerging Market. Retreived August 15th, 2011,

from http://www.korinek.com/papers.

Liu, P. (2006). A Small New Keynesian Model of the

New Zealand Economy. Retrieved August 15th,

2011, from http://www.rbnz.govt.nz/research/

discusspapers/dp06_03.pdf.

Monacelli, T. (2004). Into the Mussa Puzzle: Monetary

Policy Regimes and the Real Exchange Rate in a Small

Open Economy. Journal of International Economics,

62, 191-217.

Svensson, L. E. (2000). Open-economy Inflation Targeting.

Journal of International Economics, 50, 155-183.

Stéphane, A., Houtan, B., Juillard, M., Mihoubi, F.,

Perendia, G., Ratto, M., and Villemot, S. (2011),

“Dynare: Reference Manual, Version 4”, Dynare

Working Papers, 1, CEPREMAP.

Yun, T. (1996). Nominal Price Rigidity, Money Supply

Endogeneity, and the Business Cycles. Journal of

Monetary Economics, 37, 345-370.

76



APPENDIX

Table 1 AR Regression of Borrowing Premium

Variable Coefficient Std. Error t-Statistic Prob.

Constant 2.043667 0.935542 2.184473 0.0319Borrowing Premium(-1) 0.809694 0.066240 12.22360 0.0000

R-squared 0.657017 F-statistic 149.4163Adjusted R-squared 0.652619 Prob(F-statistic) 0.000000

Table 2 Welfare Losses

Monetary Policies Technology Shocks

Monetary Shocks

CPI inflation targeting -0.1101 -0.0109 Domestic inflation targeting -0.1088 0 Exchange rate peg -1.2860 -1.8584 “Taylor Rule” implicit policy targeting -0.2069 -0.0405

Figure 1Evolution of Global GDP and Interest Rate under Various Shocks

-0.4-0.20

0.20.40.60.81

2 4 6 8 10 12 14 16

-0.5-0.4-0.3-0.2-0.10

2 4 6 8 10 12 14 16

GDP Gap Interest Rate

77



Figure 2Domestic Variables under Foreign Technology Shocks

2 4 6 8 10 12 14 16-0.25

-0.2

-0.15

-0.1

-0.05

0

2 4 6 8 10 12 14 16-0.4

-0.3

-0.2

-0.1

0

0.1

2 4 6 8 10 12 14 160

0.5

1

1.5

2

2.5

2 4 6 8 10 12 14 16

-0.2

-0.1

0

0.1

fixed CIT DIT Taylor Rule

2 4 6 8 10 12 14 16

-0.4

-0.3

-0.2

-0.1

0

2 4 6 8 10 12 14 16

-0.4

-0.3

-0.2

-0.1

0

Output Gap Interest Rate

Domestic Inflation CPI Inflation

Exchange Rate Term of Trade

78



Figure 3Domestic Variables under Foreign Monetary Shocks

2 4 6 8 10 12 14 16-0.6

-0.4

-0.2

0

0.2

2 4 6 8 10 12 14 16-0.4

-0.2

0

0.2

2 4 6 8 10 12 14 16-0.8

-0.6

-0.4

-0.2

0

0.2

2 4 6 8 10 12 14 160

1

2

3

4

2 4 6 8 10 12 14 160

0.2

0.4

0.6

fixed CIT DIT Taylor Rule

2 4 6 8 10 12 14 16-0.8

-0.6

-0.4

-0.2

0

0.2

Output Gap Interest Rate

Domestic Inflation CPI Inflation

Exchange Rate Term of Trade

79

Article 2. Macroprudential and Microprudential Surveillance and Policies

Macroprudential and Microprudential

Surveillance and Policies

Article 2

Rapid financial sector development over the past decade in terms of the institutions and their products has

increased the complexity and inter-institutional connectivity of the financial system, thereby exacerbating the

risk and instability faced. Maintaining financial system stability has become an increasingly hot topic in the

post-2008 crisis era, often cited as the priority of central banks in many countries. One way the changing

trend towards anticipating future crises is being realised is through the application of macroprudential policy

by the respective central bank, including Bank Indonesia, namely how to prevent or minimise the extent of

systemic risk.

BACKGROUND

Considering the dynamics of the financial sector,

concerns over financial system stability have become

important to the economy. A number of factors support

this proposition. First is the increasingly integrated

global economy coupled with rapid financial product

development, which could lead to potential financial

instability. Globalisation and economic liberalisation has

led to greater integration and interconnectedness in the

global economy (Article Figure 2.1). Ultimately, problems in

one country can now spread quickly to other countries and

can even trigger a crisis. On the other hand, advancements

in information technology have expedited the financial

transaction process and deregulation has nurtured rapid

financial sector product development (Pereira, 2008).

Second is economic instability, which can trigger a

broad impact across the financial sector. The financial crisis

that befell Indonesia in 1997-98 revealed macroeconomic

imbalances prompted by externalities spreading though

Global Financial Network in 1985

Article Figure 2.1

Global Financial Network in 2005

Source: Financial Stability Review, June 2009, Bank of England

Ricky Satria2, Indri Driawati3, Indrajaya4, Primitiva Febriarti5

2 Assistant Director of Financial Sistem Stability Group, Bank Indonesia. Email: [email protected] Manager of Financial Sistem Stability Group, Bank Indonesia. Email: [email protected] Manager of Financial Sistem Stability Group, Bank Indonesia. Email: [email protected] Assistant Manager of Financial Sistem Stability Group, Bank Indonesia. Email: [email protected]

80


the exchange rate and undermining domestic banking

stability, eventually leading to a multi-dimensional crisis.

Meanwhile, in 2007-08, monetary stability centred on low

interest rates to catalyse economic growth but had the

unintended impact of encouraging risk-taking behaviour

(Hyman Minsky’s, 1992) through product innovation and

an increase in leveraging by financial institutions, which

led to the subprime mortgage debacle. Investors became

a source of procyclicality that resulted in boom and bust

cycles due to their collective behaviour.

Third, the financial crisis incurs large recovery costs.

The financial crisis in Indonesia in 1997-98 cost the country

approximately 50% of GDP in recovery costs. Meanwhile,

the US poured nearly $ 700 billion into the economy to

rescue its financial system from economic crisis in 2008.

The costs borne were not merely incurred by commercial

banks but investment banks and insurance companies too.

Meanwhile, the Bank of England (BoE) spent around £3

billion saving Northern Rock and injecting capital into a

number of large banks.

The 2008 crisis prompted fundamental changes to

several aspects of crisis anticipation around the globe:

1. The crisis was caused by a failure in the banking

sector supervision function. Several countries in

Europe began to reassess their financial sector

supervision structure, particularly for banks, which

had previously separated the supervision function

from the central bank. With a focus on the soundness

of individual banks no longer adequate, systemic

stability became desirable and necessary. The

National Bank of Belgium (NBB) began supervising

systemic financial institutions that had previously

been under the auspices of the Financial Services

Authority (FSA). Meanwhile, the FSA in the UK

will become a subsidiary of the Bank of England in

2015. Similarly, Spain, France and Italy plan to follow

suit.

2. Strengthening the disparate consumer protection

function through microprudential policy, similar to

that implemented in the Netherlands (twin peak) in

2002 and the proposed Vocker Rule in the US as well

as plans in the UK.

3. Mandating the central bank with maintaining financial

system stability (through macroprudential policy and

supervision of systemic financial institutions) by

conducting surveillance on the financial system as a

whole in order to detect potential systemic risk.

4. Bolstering inter-institutional coordination as well as

accountability and governance. This can be achieved

by establishing committees similar to those set up in

the UK (Financial Policy Committee), the US (Financial

Stability Oversight Council), France (Financial

Regulation and Systemic Risk Council) and the ECB

(European Systemic Risk Board).

MACROPRUDENTIAL

Definition of Macroprudential

Experience gleaned form the crisis in 2008 led

to demands to change the views, policies, authority

and responsibility of the government, regulators in the

financial sector and the central bank with a renewed

focus on financial system stability (FSS). The application

of macroprudential policy represents one of the efforts

taken to maintain financial system stability. Use of the term

macroprudential has snowballed since the crisis in 2008,

particularly by regulators, central banks and international

institutions (BIS, IMF and G30). In addition, research by

academics relating to macroprudential policy has also

mushroomed. The term macroprudential first emerged

in the 1970s but was formally coined by Andrew Crocket

(2000), the General Manager of BIS, who postulated

that microprudential policy must be juxtaposed against

macroprudential policy.

81


Borio (2003) opined that macroprudential policy

aims to mitigate risk in the financial system that could

significantly precipitate a decline in the real economy,

reflected by Gross Domestic Product (GDP). Despite no

standard definition of macroprudential, fundamentally

macroprudential policy places a focus on limiting/

mitigating systemic risk. The following definitions have

been put forward for macroprudential policy:

“Macroprudential policy aims to maintain financial

intermediation stability (for instance payment services,

credit intermediation and guarantees for risk) in an

economy.” (Bank of England, 2009).

“Macroprudential policy aims to enhance financial

system resilience and mitigate systemic risk that may

emerge from inter-institutional linkages and the tendency

for financial institutions to follow economic cycles

(procyclical), thereby exacerbating systemic risk.” (G30

WG, 2010).

“Macroprudential policy aims to limit risk and the cost

of systemic crises.” (BIS working papers, 2011).

In addition, macroprudential policy aims to

simultaneously prevent boom and bust cycles in the

economy attributable to the behaviour of financial

institutions. (Article Figure 2.1).

Microprudential and Macroprudential

Fundamentally, financial system stability is predicated

upon the soundness of individual financial institutions.

Maintaining the soundness of individual financial institutions

is achieved through a microprudential approach, namely

through regulations, oversight and inspections of individual

financial institutions. Nonetheless, sound individual

financial institutions do not automatically translate into

a stable financial system. The crisis in 2008 revealed that

sound individual financial institutions operating under

stable economic conditions and low inflation can lead to

joint innovation (herding behaviour) in the financial sector

and provoke an increase in leverage that ultimately spurs a

crisis. Such circumstances raised awareness that soundness

of the entire system is essential.

Solvabilitas

Times

Level solvabilitasnormal Bust

Boom

Signals to activatemacroprudential policy;

Forward-looking indicators.

Downturn (materialisation of systemic risk); phase of decreasing solvency and

increasing pessimism;

Turning point(or onset of a crisis).

Prosperous times (accumulation of systemic risk); phase of increasing solvency and widespread optimism.

Unsustainable change in financial stability marginal risk;

for instance financial market indicators (credit spread, CDS

spread) or market liquidity indicators.

Signals to terminate the policy; current indicators (level of

default, NPL ratio, provisioning rate, borrowing) and financial

market indicators.

Article Figure 2.1Macroprudential Policy Implementation

Source: Frait Czech Republic FSR, 2011

82


increased mortgage allocation and the tendency to

extend credit to certain sectors. Policy response is to

apply the loan to value ratio (LTV).

2. Cross-section risk, is inherent risk at financial

institutions originating from similar portfolios among

individual financial institutions (trend) and the

interconnectedness of individual financial institutions

in a system, like lending and borrowing on the

interbank money market. Policy response is generally

to recalibrate prudential policy to limit potential risk,

for example through the provision of more capital.

Correlation between risk and among institutions

is an important factor to monitor in terms of the

macroprudential approach.

On the other hand, microprudential policy focuses

on risk assessments and the performance of individual

financial institutions and the implications on the affected

financial institution itself, not the financial and economic

system as a whole. The capacity of an individual financial

institution to confront external sources of risk (exogenous)

is also included, for instance macro conditions. The

overarching goal of microprudential monitoring is

consumer protection.

There is a fundamental difference between the two

approaches in terms of the objective, the risks monitored

and the strategy implemented. Borio (2003) summarised

the difference between the two approaches as presented

in the following table:

Operationally, the macroprudential approach is

somewhat similar to the microprudential approach, namely

through regulation, supervision and inspection. Supervision

and inspection centres around potential risk, risk

management, obligations to stakeholders and resilience.

In addition, macroprudential policy also emphasises the

following salient points:

• A focus on systemically important financial institutions

(SIFI), therefore, the macroprudential authority is also

commonly the regulator of systemic institutions.

Source: adjusted from FSAP: Experience and Issuers Going Forward,Stefan Ingves, Economic Forum 16th December 2003

Conversely, maintained financial system stability is

a factor conducive for financial institutions to operate

soundly. Therefore, microprudential and macroprudential

stability is indispensible for maintaining financial system

stability in an economy.

Article Figure 2.3Macroprudential Supervision as a part of Financial

System Stability

Article Figure 2.2Three Pillars of Financial System Stability

macroprudential

supervision

Financial

system

stability

microprudential

supervision

Approach

Monitoring risk utilises a top-down method bearing

in mind the macroprudential approach aims to observe

systemic risk that threatens the financial system as a

whole. The top-down approach focuses on portfolio risk

as follows:

1. Time-varying risk, namely the analysis of risk

that accumulates over time in the financial sector,

commonly stemming from procyclicality. Such

risk is found in the financial sector and economy,

which amplifies the financial cycle and business

fluctuations, creating boom and bust conditions.

This is similar to the trend of increased leverage,

83


Article Table 2.1Macroprudential versus Microprudential Policies

Macroprudential Microprudential

Intermediate objective Monitoring and assessment of the financial system as a whole

Monitoring and assessment of the soundness of individual f inancial institutions

Overarching goal Reducing the cost of the crisis (decline in GDP)

Consumer protection.

Risk Model Partly endogenous Exogenous

Correlation and exposure to cross-border financial institutions (contagion risk)

Important Irrelevant

Prudential policy calibration Focus on systemic risk; top down Focus on the risk faced by individual financial institutions ; bottom up.

Source: Claudio Borio (2003), Towards a Macroprudential Framework for Financial Supervision and Regulation

• Monitoring industrial trends, including small

banks.

• Observing the impact on the financial system and

the economy:

o In the event of problems at a systemic financial

institution.

o Of financial institution trends holistically.

• The soundness group business model is crucial for

holding companies.

These issues are observed collectively as a whole in

relation to prevailing phenomena and macroeconomic

performance domestically and internationally to calculate

the probability of shocks and their impact on the financial

system. Monitoring represents the starting point when

looking for systemic potential. Consequently, stress tests

and simulations of various scenarios are regularly used

as the primary tools. Detailed surveillance is conducted

on individual financial institutions to corroborate the

conclusions drawn and avoid bias in the results or erroneous

signals when applying the top-down, macroprudential

approach.

Another difference is in the indicators used. The

macroprudential approach refers to Financial Soundness

Indicators (IMF) consisting of key indicators and additional

indicators, including aggregated banking, economic and

corporate indicators. An array of additional indicators can

be used depending on the dynamics faced. Meanwhile,

the microprudential approach refers to financial ratios

indicating the soundness level of individual banks,

including aspects of capital, asset quality, management

competence, financial performance, liquidity conditions,

market risk and other supporting indicators.

Macroprudential Policy Instruments

The most common macroprudential policies

introduced to prevent systemic risk stemming from time

varying risk and cross-section risk are presented in the

following table:

From a microprudential perspective, regulations are

instituted to maintain the soundness of individual banks

as follows:

• Relating to capital in order to control minimum

capital.

• Relating to asset quality by determining bank

asset quality, provisions and limitations on credit

allocation.

• Relating to management by reinforcing risk

management, governance, compliance, the

composition of directors and commissioners as well

as fit and proper tests.

• Relating to performance by limiting the disbursement

of dividends to shareholders.

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• Relating to liquidity by regulating the level of liquid

assets that must be maintained.

In addition to the more general regulations

promulgated, close monitoring is also conducted by

preventing certain activities through cease and desist

orders.

Institutions that play a Macroprudential Role

In principle, any authority can issue macroprudential

policy, however, central banks are considered the most

suitable (Nier, 2011). This has been evidenced over

the past decade, particularly during the 2008 crisis, by

central banks adjusting their vision and mission, including

regulations, to include or strengthen the financial system

stability function.

The results of an IMF survey on macroprudential

policy in 2010 revealed that of the 60 respondents globally,

as many as 90% of central banks were mandated with

maintaining financial system stability. Meanwhile, 48% of

those were also mandated with setting macroprudential

policy.

The function to maintain financial system stability

by central banks has also been reflected by an increase

in the publication of Financial Stability Reviews over the

past 15 years.

Central banks are the most appropriate institutions to

implement macroprudential policy based on the following

considerations:

a. Independence. Policy implementation in the

financial sector must be conducted by a fully

independent organisation. Independence helps to

minimise political intervention during disruptions

to the financial system. Independence encourages

central banks to take more rapid and decisive actions

prior to a financial crisis.

b. Comprehensive Instruments. Central banks are

able to rapidly mitigate the impact of financial system

instability on the economy through the existing

Tool Dimension of Risk

Time Varying Cross Section

Category 1. Tools developed specifically to mitigate systemic risk.

• Countercyclical capital buffer• Through-the-cycle valuation of margins or haircuts for repos• Levy on non core liabilities• Countercyclical change in risk weights for exposureto certain sectors• Time varying systemic liquidity surcharges

• Systemic capital surcharges• Systemic liquidity surcharges• Levyon non-core liabilities• Higher capital charges for trades not cleared through CCPs

Category 2. Recalibration tools.

• Time varying LTV, Debt to income and Loan to income caps• Timevarying limits in currency mismatch or exposures (e.g. Real estate)• Time varying limits on loan to deposit ratio• Time varying caps and limits on credit or credit growth• Dynamic provisioning• Stressed VaR• Rescalling risk weights

• Powers to break up financial firms on systemic risk concerns• Capital charge on derivative payable• Deposit insurance risk premiums sensitive to systemic risk• Restrictions on permissible activities

Source: IMF Paper 2011, Macroprudential Policy: An Organising Framework

Article Table 2.2Examples of Macroprudential Tools

85


Source: Costa, Alejo. Macroprudential Policy: Survey 2010, IMFSource: Cihák, Martin, Sònia Muñoz, Shakira Teh Sharifuddin and Kalin Tintchev,

Financial Stability Reports: What Are They Good For? IMF Working Paper WP/12/1, IMF, January 2012.

Article Figure 2.2 The Mandate to Maintain Financial System Stability

and Macroprudential Policy

Article Figure 2.3 Publication of the Financial Stability Review

Central Bank Objective/Task

Bank Negara Malaysia, Malaysia “…to promote monetary stability and financial stability conduducive to the sustainable growth of the Malaysian economy. “

Bank of England, United Kingdom “…an objective of the bank shall be to contribute to protecting and enhancing the stability of the financial system of the United Kingdom”

Bank of Japan, Japan “… to ensure smooth settlement of fund among banks and other financial institutions, thereby contributing to the maintenance of stability of financial system.”

Bank of Thailand, Thailand “…to maintain monetary stability, financial institution system stability and payment system stability.”

Monetary Authority of Singapore, Singapore “…to foster a sound and reputable financial centre”

Reserve Bank of Australia, Australia “…has a number of functions and powers, and undertakes a number of activities, for what are broadly “financial stability” purposes, including : banking system oversight, non-bank deposit takers, insurance sector, payment system oversight, financial stability and market analysis”

Source: official website of the respective central bank

Article Table 2.3Financial System Stability Mandate at several Central Banks

Macroprudential Policy Mandate

Financial System Stability Mandate

0

10

20

30

40

50

60

70

80

90

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

.

Number of Central Banks Publishing a Financial Stability Review

instruments in their arsenal. Liquidity problems can

be overcome through open market operations,

market intervention and liquidity assistance through

LOLR or a discount window, as well as adjusting the

reserve requirement and policy rate. Central Banks

can use macroprudential instruments like dynamic

provisioning, countercyclical capital buffers, LTV and

others to mitigate systemic risk.

c. Policy Response and Synergy. Nurturing

synergy in the formulation of monetary policy,

macroprudential policy or a combination of the

two, primarily to prevent and respond rapidly to a

crisis. This is necessary to ensure the accuracy and

efficacy of the policies issued. This has encouraged

several countries that separated the bank supervision

function (microprudential) from the central bank

to reconsolidate under the auspices of the central

bank (for example Belgium in 2011 and the UK in

2012).

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d. In harmony with function as Lender of Last

Resort (LOLR). Efforts to create and maintain

financial system stability in line with its authority

as lender of last resort, which is required for crisis

prevention and resolution.

e. Comprehensive Resources. In general, central

banks have adequate resources in terms of competent

human resources, infrastructure, budget and

information systems.

Authority

From the existing literature, it can be summarised

that the authority naturally possessed by the institutions

mandated with implementing financial system stability/

macroprudential is as follows:

a. The authority to acquire data and information

concerning financial institutions. Data on individual

financial institutions is crucial in the analysis of

financial system conditions and systemic risk.

Furthermore, on-site examinations can be conducted

as required.

b. Designation powers. The institutions mandated with

implementing macroprudential policy also have the

authority to determine the scope of banks and non-

bank financial institutions that can individually or

jointly trigger systemic risk.

c. The authority to determine and formulate policy. The

macroprudential policy/regulations formulated can

be used to overcome problems in the financial system

according to the source and the level of risk.

d. The authority to use specific and effective instruments

to mitigate systemic risk.

Ultimately, the macroprudential institution chosen

will have a wide and extensive scope of authority, however,

this is necessary considering that the overarching goal

is vital for the economy of a country. Balancing this

broad scope of authority can be achieved through clear

governance and accountability.

Governance

Based on the considerations mentioned, accountability

and governance are prerequisites for the implementation

of macroprudential policy. Furthermore, a transparent

decision-making process is also crucial. In broad terms,

what has happened in other countries is as follows:

• Reporting surveillance activity and the macroprudential

policy taken regularly to the general public through

publications like the Financial Stability Review.

• Establishing internal and external financial stability

committees. Externally, such committees generally

consist of the central bank, the financial sector

regulator and the Ministry of Finance as members.

Under crisis conditions or if a troubled financial

institution is potentially systemic, such committees

decide which policy to take, including the use of

public funds.

Monetary Links

During the period leading up to the crisis in 2008,

success by central banks in terms of creating sound

macroeconomic conditions, as reflected by a low level of

inflation (low interest rates) to stimulate the economy,

was actually responded to very differently by investors.

Stable monetary and economic conditions, in actual fact,

triggered speculative actions by investors chasing higher

returns and led to more leveraging in order to expand their

opportunities. This was primarily attributable to excessively

high future expectations, which resulted in economic

bubbles and a financial crisis. Such conditions opened the

eyes of world to the trade-off between price stability and

financial system stability.

Investors created additional procyclicality (accelerating

economic growth during an expansionary period and

exacerbating the contractionary period) that spurred

fluctuations in economic output. Procyclicality appeared in

the business cycle and affected financial conditions due to

87


the herding behaviour of investors. Consequently, boom

and bust conditions were created, which undermined the

efficacy of monetary policy implementation.

Considering that the natural mandate of a central

bank is in the monetary sector, namely price stability,

an additional macroeconomic mandate would serve to

bolster the effectiveness of monetary policy management.

Furthermore, positive synergy is created through the

implementation of monetary and macroprudential policy

under the auspices of the central bank (Nier, 2011). In

fact, Blachard (2010) also emphasised that the formulation

of monetary policy is improved if macroprudential

policymaking is housed under the same roof.

Accordingly, macroprudential policy formulation

will take into consideration conditions in the financial

sector and vice versa, thereby ensuring that the policies

issued are more effective and accurate. This is because

monetary policy and macroprudential policy directly affect

conditions in the economy and financial sector despite

differing objectives. Both policies are mutually beneficial

but not substitutable. Under crisis conditions the linkages

between monetary and macroprudential policy become

even clearer (Volcker 2010).

Implementation of Micro and Macroprudential

Policy in several Countries

The macro and microprudential approach has

become the focus of authorities in each country to

maintain financial system stability. In practice, macro

and microprudential supervision can be placed under the

umbrella of one authority or separated depending on the

structure and characteristics of the respective financial

system, legal system and culture of inter-institution

coordination. In other words, there is no one-size-fits-all

macroprudential framework.

Inflation expectationsAggregate supply-demand

High measure of debt levels (dangerous)Overvalued asset valueIndicators of excess liquidityIndicators of construction and activity on the property marketIndicators of internal and external economic equilibriumIndicators of the external position financial institutionsLevel of leverage between institutions and capitalRatio of market liquidity and other indicators of liquidityIndicators of asset maturity and liabilitiesIndicators of currency mismatch.

Policy Indicators

Monetary stability Financial sector resilience and capacity to absorb pressuresChanges in the financial cycleAsset price volatilityLevel of uncertainty that relates to the soundness of the financial system under unstable financial conditions

Intermediate Target

Monetary Stability Financial System StabilityUltimate Goal

Instruments Interest rateLiquidity management (OPO, etc)Forex intervention

Reserves (buffer)CAR (countercyclical buffers)Liquidity ratio – to prevent panic sales

Other macroprudential regulatory and supervision instrumentsLTV, etcCommunications

Short-term Interest RatesMoney In CirculationThe Exchange Rate

Capital And Bank Liquidity ChannelsBank Costs Related To Bank Risk Exposure

Price stability defined as low and stable inflation

Financial System Stability, namely preventing the spread of systemic risk

Transmission Mechanism

Sanctions Imposed On Banks And Non-bank Financial Institutions Due To An Increase In The Scale Of Risk

Article Table 2.4Monetary Stability versus Financial System Stability

Source: Bank Indonesia

88


MacroEconomics

HouseholdFinancial

Condition

CorporationFinancial

Performance

Bank

Non-BankFinancialInstitution

Money Market: -Capital Market-Money Market

FinancialSystem

Infrastructure

ProfitabilityCapitalizationEfficiency


IHSGYield CurvePUAB rate

DefaultSettlementRisk

FinancialSystemStability

MonetaryStability Exchange

RateInflation

DomesticDemand

Risk:IndividualLevelSistemic Credit Risk

Liquidity RiskMarket Risk

International andDomestic Market

(contagion)

Cyclicality Management

Sistemic Risk Mitigation

• Funding Function (intermediation) goes well

• Maintained Asset Price

• Controlled Risk

Monetary aggregate creation

(Credit and Money Supply)

well-managedCyclicality Management

Establishment of Expectation


Risk:IndividualLevelSistemic

Article Figure 2.4Financial System Stability Framework

Source: Bank Indonesia

Notwithstanding, changes have occurred in the

regulatory framework for financial institutions since the

2008 crisis, with a number of countries consolidating

macro and microprudential supervision at the central

bank (Article Table 2.5). The reason for this is to enhance

the effectiveness of coordination, monitoring and policy

implementation, including crisis prevention and resolution

(Blanchard 2010).

Future Challenges for the Macroprudential

Authority

Considering that macroprudential is still a relatively

new term, there remain numerous implementation

challenges. There are at least two challenges in the

implementation of macroprudential policy (Nier, 2011).

• The first, financial system development requires a

flexible macroprudential policy response and absolute

authority. According to Nier, there are three areas of

authority that are prerequisite to the implementation

of macroprudential policy as follows:

a) Information collection powers;

b) Designation powers; and

c) Calibration and rulemaking process.

The three areas of authority can give the respective

institution a very broad scope of authority, which will

clearly throw up a number of challenges. Nonetheless,

this is necessary considering the importance of the goal

for the economy of a country.

• Second is bias when taking action. Macroprudential

policy implementation does not produce clear, direct

benefits that can immediately be felt. The benefits

are more medium and long term and cannot be

measured accurately with confidence. Meanwhile,

the costs are real and incurred immediately. For

example, the rescue of Goldman Sachs and AIG by

the Fed, which did not necessarily restore financial

89


the banking sector, gleaned from experience of the crisis

in 1997-98.

The promulgation of Act No 21, 2011 regarding

the Financial Services Authority, legally and formally

transferred the microprudential supervision function of

both institutions to the Financial Services Authority. Act No

21, 2011, was issued due to the mandate contained within

the BI Act 1999 and motivated by the crisis in 1997-98.

Clarification of Article 40 of the FSA Act also mandates

Bank Indonesia with macroprudential supervision, in

particular for inspecting systemic banks. This represents

the legal starting point of the macroprudential function

at Bank Indonesia, which was further bolstered by future

amendments to the BI Act.

Framework

The goal of implementing the macroprudential

function at Bank Indonesia is to prevent the future

occurrence of crises and, in the event of a crisis, strive to

resolve it by incurring as little cost as possible.

In general, there are three lines of defence to the

prevention of crises as follows:

or economic stability. Similarly, the UK government

injected capital into the Royal Bank of Scotland and

rescued Northern Rock.

These two challenges complicate macroprudential

implementation, not only in terms of mandating the central

bank but also in policy implementation, which can be

further undermined by political impartiality.

IMPLEMENTATION IN INDONESIA

Background

Currently, microprudential supervision in the

domestic financial sector is split among several authorities.

Microprudential supervision of the capital market as well

as non-bank financial institutions is the responsibility of

Bapepam-LK (The Capital Market and Financial Institution

Supervisory Board). Microprudential supervision of the

banking sector is the responsibility of Bank Indonesia.

Although microprudential supervision has not been legally

mandated, Bank Indonesia actively preforms this function

through the Financial System Stability Bureau established

in 2003. This was undertaken based on the desire to

investigate early signs of potential risk that could endanger

Type Pre-crisis (prior to 2008) Post-crisis (after 2008)

Integration between prudential supervision and business ethics (one peak)

Austria (2002); Belgium (2004), German (2002); Swiss, Sweden, UK (FSA), Hungary (2000); Poland (2006); Japan, Korea, Singapore, Colombia, Nicaragua.

Finland (2009); German, Swiss, Sweden, Hungary, Poland, Japan, Korea, Singapore, Colombia, Nicaragua.

Sepa ra t ion o f p rudent i a l supervision and business ethics (twin peaks)

Australia (1998), Netherlands (2002). Belgium (2011), Italy (planned), Spain (planned), French (planned), UK (with various aspects of supervision), Australia (1998), Netherlands (2002).

C o n s o l i d a t e d p r u d e n t i a l supervision integrated at the central bank

Netherlands, Hongkong, Singapore, Swiss. Belgium (2011), Italy (planned), Spain (planned), French (planned), UK (planned), Netherlands, Hongkong, Singapore, Swiss.

C o n s o l i d a t e d p r u d e n t i a l supervision separate from the central bank

Australia, Belgium, UK (FSA), Japan, Hungary, German.

Australia, Japan, Canada, Hungary.

Source: IMF, Kingdom of the Netherlands-Netherlands: Publication of FSAP Documentation-Technical Note on Financial Sector Supervision: The Twin Peaks Model, July 2011, IMF Country Report No. 11/208

Article Table 2.5Supervisory Framework in selected Countries

with various aspects of supervision

90


• Eliminate the threat. This is achieved by identifying

sources of risk when economic conditions are normal

and then trying to minimise them. However, this is

not a simple task because potential risk can originate

from anywhere: internally (macroeconomy, financial

institutions) and externally (external macroeconomy,

financial sector). The mitigation options available are

also sometimes outside the remit of the central bank,

thereby necessitating coordination. For example, the

application of LTV when credit growth is excessive.

• Strengthen resilience. Financial system resilience must

be reinforced if the potential threats appear to be

materialising. For example, by increasing bank capital

or restricting certain transactions.

• Crisis management. Crisis management is required

if the potential threats cannot be overcome and

instability is created. In this context, a rapid decision-

making process is crucial, including inter-institution

and cross-border coordination.

of systemic institutions and inspections. Inspections

are conducted through onsite examinations at the

affected banks or other relevant parties to support

surveillance analysis.

2. Macroprudential policy regulation, namely by

promulgating macroprudential policy.

3. Financial sector development, namely by providing

access, products and financial sector infrastructure in

the economy because sources of economic financing

in Indonesia continue to depend on the banking

sector. This is also conducted in order to diversify

risk in the system.

4. Coordination to prevent and resolve a crisis.

In its implementation, there are a number of similar

tools used for macro and microprudential supervision

but their objectives differ. As mentioned previously,

the tools include surveillance and onsite supervision

in order to verify that the data and discussions pertain

to up-to-date conditions.

• Surveillance

Bank Indonesia prioritises the identification

of threats; external and those emanating

from within the financial sector itself. This is

complemented by simulations or stress tests

and early warning signals as the primary

tools.

Surveillance is cyclical, commencing with

the identification of potential threats. In the

identification of potential external threats,

domestic and international macroeconomic

conditions are the main priority. Corporate

and household sector performance is also

subject to surveillance because their behaviour

and conditions affect the banking sector.

Surveillance utilises quantitative indicators

supplemented with qualitative information.

Source: Towards a more stable financial system: Macroprudential supervision at DNB

Article Figure 2.5Three Phases of Maintaining

Financial System Stability

In general, the measures outlined above are

translated at Bank Indonesia into four main functions in

order to maintain financial system stability as follows:

1. Surveillance, namely the process of identifying,

measuring and monitoring conditions in the financial

sector through data analysis, including the supervision

91


contrast, bank inspections by Bank Indonesia

are conducted in order to monitor financial

system stability holistically, among others, to

bolster surveillance and concomitantly obtain

the most up-to-date trends, risk exposure

(market risk, liquidity risk and credit risk),

business strategy and state of resilience. With

differing perspectives, the inspection function

implemented by the two authorities is also

different, namely that Bank Indonesia performs

inspections based on request whereas the FSA

conducts inspections routinely.

• Coordination

Coordination is important for macroprudential

authorities because the role of creating

financial system stability is present among

all parties, not just Bank Indonesia but also

the Government. A coordination committee

was established through a memorandum of

understanding signed on 3rd March 2004

between Bank Indonesia and the Ministry of

Finance to preserve financial system stability.

Subsequently, this was further buttressed by

Act No 21, 2011, regarding the FSA, which

legislated the establishment of the Financial

System Stability Coordination Forum with

members from Bank Indonesia, the Ministry

of Finance, the Deposit Insurance Corporation

and the Financial Services Authority. This

forum, among others, functions to evaluate

regular conditions of financial system stability,

including the determination of crisis conditions

and policymaking to prevent and resolve a

crisis. Each respective institution publishes

up-to-date conditions within their jurisdiction,

including policy recommendations pertaining

to crisis prevention and resolution.

The potential threats identified are measured

using a variety of methods, including stress tests

and simulations, which are used as the basis for

projecting future conditions. This is also used

as the basis for policymaking. Subsequently,

whether the policies are instituted or not they

are new policies and the surveillance function

remains ongoing by monitoring aspects of the

domestic and international macroeconomy,

households, the corporate sector, financial

institutions and financial infrastructure.

Surveillance also includes tighter surveillance of

systemically important financial institutions.

• Inspections

Although Bank Indonesia and the Financial

Services Authority have the authority to

inspect banks; inspections are conducted from

different perspectives. As the microprudential

authority, inspections of financial institutions

by the FSA aim to assess the level of soundness,

risks faced and mitigation efforts undertaken

by an individual financial institution, thereby

ensuring that the general public as end

users of financial services are protected. In

Article Figure 2.6Surveillance Framework

92


Coordination also consists of a sharing

mechanism as well as data and information

exchange.

• Governance

The macroprudential tasks and responsibilities

of Bank Indonesia are set forth in clear work

processes and the outputs are reported publicly

as a form of accountability. The reports can

be in the form of written reports like the

Financial Stability Review or regular reports

to the House of Representatives or seminars

and discussions with various stakeholders.

Meanwhile, internally Bank Indonesia formed

the Financial System Stability Committee.

CONCLUSION

Globalisation, economic l iberal isation and

financial sector deregulation supported by technological

advancements has created economic linkages, integrated

financial sectors and product complexity. This has

exacerbated the impact of contagion and the frequency

of crises. The crisis in 2008 provided an invaluable

lesson for all countries regarding the importance of

maintaining financial system stability through the

application of macroprudential policy. Despite no one-

size-fits-all framework, central banks around the world

have bolstered their function through the application of

macroprudential aspects by revising their respective vision

and mission as well as issuing regulations to broaden

their mandate. Initially, there were conflicts between

the monetary and macroprudential function, however,

the majority of the literature and practical experience

has shown the impact to be positive for the economy

thanks to synergy and the complementary nature. In

fact, the most recent phenomenon is for microprudential

regulators to consolidate under the central bank because

the transmission of monetary and macroprudential policy

of found in the microprudential function. This is meant

to boost the effectiveness of maintaining financial system

stability while supporting sustainable economic growth.

The separation of the microprudential authority

within the FSA, from the macroprudential function

implemented at Bank Indonesia means that effective task

implementation must be maintained at both authorities

through clear coordination. Coordination on crisis

prevention and resolution includes providing access to data

and information that supports task implementation at the

two institutions as well as a joint policy response.

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Article 3. Determinants of the Household Liquidity Requirement in Indonesia:

an Empirical Study with Data from the Household Balance Sheet Survey

Determinants of the Household Liquidity Requirement

in Indonesia: an Empirical Study with Data from the

Household Balance Sheet Survey

Article 3

The household sector has a relatively large impact on financial system stability and the macroeconomy.

A decline in the level of household liquidity can be an early warning indicator of disruptions to financial

stability in a country. Therefore, analyses on the level of liquidity in the household sector have come to

the attention of policymakers. This article attempts to analyse the internal determinants of the level of

household liquidity in Indonesia. Data from the 2010 household balance sheet survey conducted by Bank

Indonesia is used.

Results of the study indicate that a number of internal household factors play an important role in determining

household demand for liquidity. The most salient variables include, among others, household asset value,

household income, the ratio of household income to household assets, the household debt to income

ratio, debt to assets ratio, number of household members, ratio of operational profit to operational cash

in, level of operational cash out, cash out to repay debt, a dummy variable for employment, a dummy for

self-employed and property ownership. The variables for the age of eldest household member, a dummy

for pensioners and cash out for consumption were also significant for a number of estimates. The results of

this research also indicate that households in Indonesia hold liquid assets motivated by transactional motives

and precautionary motives.

Keyword : household liquidity, household behaviour, consumption.

JEL Classification Number : D14, D13, E21

INTRODUCTION

The level of liquidity in an economy affects

macroeconomic and financial stability. Excessive liquidity

can trigger rising inflation (asset price inflation), while a

very low level of liquidity leaves the economy vulnerable

to shocks. A variety of activities across a range of sectors

affects the overall level of liquidity, including real sector

activities (corporate and household) and government

activities.

Households, as a component of the real sector, play

a pivotal role in the economy, observable through three

lenses, namely as providers of production factors, as

consumers and as taxpayers on income earned from the

sale of production factors.

Bagus Santoso6, Pungky P. Wibowo7, Dwityapoetra S. Besar8

6 Faculty of Economics, GadjahMada University. Email [email protected] Deputy Director of the Department of Banking Research and Regulation, Bank Indonesia. Email [email protected] Deputy Director of the Department of Banking Research and Regulation, Bank Indonesia. Email [email protected]

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One concrete measure that can be taken to maintain

financial sector stability is the analysis of credit risk in the

household sector. Financially sound households have

a favourable impact on financial and macroeconomic

stability. Conversely, when the household sector

experiences a shock, financial and macroeconomic stability

is undermined. According to Kask (2003), financially

unsound households are an early warning indicator of

financial instability in a country.

Bank Indonesia, as the monetary authority, is fully

aware of the importance of preserving stability in the

household sector in order to maintain financial stability

overall. One form of surveillance conducted by Bank

Indonesia on the household sector is through a survey of

the household balance sheet (HBS), performed regularly

since 2007. The overarching goal of the survey is to

monitor the financial condition of households in Indonesia

from year to year, gauged using the balance sheet, cash

flow as well as profit or loss of each household.

This research has two main objectives: first is to

analyse the liquidity management behaviour of households

in Indonesia and identify what determines the level of

liquidity in Indonesian households; the second is to assist

policymaking at the monetary authority to preserve

household sector stability in order to buoy sustainable

economic growth.

This paper proceeds with a review of the literature

relating to the level of liquidity in general and specifically

the level in the household sector. The subsequent sections

present the research methodology, the empirical analysis

using 2010 HBS survey data and finally the conclusion and

policy recommendations.

LITERATURE REVIEW

Literature concerning household liquidity is relatively

scarce with not much previous research discussing the topic

comprehensively. Crane (1995) wrote one early research

paper that explored this issue. According to Crane (1995)

household demand for cash is affected by two factors,

namely predictable needs for cash and unpredictable

needs for cash. Crane postulated that households will

hold an amount of cash to accommodate their daily needs,

however households will encounter constraints under

such conditions, with households ultimately losing the

opportunity to accrue a return on that cash. In addition,

households tend to place their funds in current assets.

The results of research conducted by Hubbardet et

al. (1994)demonstrated that low-income households also

generally tend to have a lower level of savings compared

to higher income households. Additionally, Paxton and

Young (2010) as well as Lee and Sawada (2010) concluded

that level of wealth and access to credit has a strong

correlation with precautionary saving. Precautionary

savings are additional savings allocated by a household

from its wealth for use when a shock strikes. The form

of precautionary savings varies, including informal savings

and non-financial savings.

Cunha et al. (2011) found that determinants of

demand for household liquidity are not entirely the same

as factors affecting corporate demand for liquidity. In

determining their level of cash holdings, the household

decision-making process tends to be based on transactional

motives and precautionary motives. The former helps

simplify the household’s daily transactions while the latter

ensures the household holds an amount of cash as a

safety net. Differing from the corporate sector, asymmetric

information tends not to affect household demand for

liquidity.

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Article 3. Determinants of the Household Liquidity Requirement in Indonesia:an Empirical Study with Data from the Household Balance Sheet Survey

Liquidityi= i+ β1Ln_asseti +β2 Ln_disp_inci +β3ras_de_asi +β4 ras_de_inci +β5 ras_inc_asi +β6 Ln_hh_memi +β7 Ln_eldesti +β8 ln_lasti_networth +β9 ras_operationali _profit +β10 ln_consumption credit_operationali +β11Ln_consumption credit_investmenti +β12 Ln_consumption credit_crediti_funding +β13 ln_consumption credit_consumptioni+β14 Ln_working capital credit_operationali +β15 Ln_working capital credit_investmenti +β16 Ln_working capital credit_fundingi+ β17 dum_peni+β18 dum_own_homei+β19 dum_empl β20 dum_selfi

METHODOLOGY

Research Data

This working paper utilises data obtained from the

household balance sheet (HBS) survey in 2010, which can

be constructed to a form and definition similar to that of

the corporate sector, thereby making it easier to apply

corporate concepts to the household sector. In addition

to financial data, the HBS survey also covers demographic

data.

This research uses data from 4,052 households

in Indonesia, equivalent to the size of the valid sample

from the HBS survey. The data is sourced from three

household financial reports, namely the household balance

sheet, household cash flow and household profit or loss,

complemented by demographic information.

Research Model

This study adapts the model developed by Cunha

et al. (2011) in order to analyse the determinants of the

level of liquidity in the household sector in Indonesia. The

research conducted by Cunha et al. (2011) was in fact the

application and development of the model constructed

by Opler et al. (1999) but with a focus on households. A

number of modifications are made in this paper to the

model of Cunha et al. (2011), the objective of which is to

more clearly explain the characteristics of the household

sector in Indonesia.

A number of additional variables are included in this

research in line with the findings of other relevant studies,

for instance Paxton and Young (2010) and Lee and Sawada

(2010), and variables suspected of having a significant

correlation with the household level of liquidity.

The research model of Cunha et al. (2011) was

modified by only using cross-sectional data of all sample

households in each period. In general, the research model

developed in this study can be expressed as follows:

(1)

The model detailed in Equation (1) is estimated using

a number of liquidity measures as follows:

a) Cash logarithm;

b) Cash and savings logarithm;

c) Cash, savings and checking logarithm;

d) Cash, savings, checking and term deposit

logarithm;

e) Savings, checking and term deposit logarithm;

f) Ratio of cash to total assets (in %); and

g) Ratio of current assets to total assets (in %).

A summary of the expected signs of the respective

independent variables is presented in Article Table 3.1 as

follows:

98

Article 3. Determinants of the Household Liquidity Requirement in Indonesia:an Empirical Study with Data from the Household Balance Sheet Survey

Article Table 3.1Definition of Independent Variables used in the Model

Independent Variable Description Expected Sign

ln_asset Total asset logarithm +/-

ln_disp_inc disposable income logarithm +/-

pct_de_as percentage of debt to total assets +/-

pct_de_inc percentage of debt to disposable income +/-

pct_inc_as percentage of disposable income to total assets -

ln_hh_mem number of household members logarithm +/-

ln_eldest_age age of eldest household member logarithm +/-

ln_last_networth household net worth logarithm +

pct_operasional_profit percentage of profit/loss to operational cash in +

ln_consumption credit_operational

operational cash out logarithmhousehold spending on productive processes

+

ln_consumption credit_investment

investment cash out logarithmcash outflow from investment activity

+

ln_consumption credit_credit_funding

funding cash out for debt logarithmhousehold repayments

+

ln_consumption credit_consumption

consumption cash out logarithm +

ln_working capital credit_operational

operational cash in logarithmhousehold income from productive household sectors

+

ln_working capital credit_investment

investment cash in logarithmcash inflow from investment activity

+

ln_working capital credit_funding

funding cash in logarithmreceipt of payments from third parties

+

Dum_pen dummy, if 1: pension and 0: othersfor households with pensioners

+

Dum_own_home dummy, if 1: owns a house and 0: othersfor households that own the property

-

Dum_empl dummy, if 1: employed and 0: othersfor households with working members

+

Dum_self dummy, if 1: self-employed and 0: othersfor households that conduct business activity.

+

Estimation Results

The research model is estimated using the Ordinary

Least Square (OLS) method for each non-independent

variable. Each regression model estimated was confirmed

not to contain independent variables with serious

multicollinearity. The estimation process was performed

using E-Views and Oxmetrics software. The general-to-

specific method model developed by David F. Hendry

(1995) is applied in this research in order to obtain the

best final model from each estimation conducted. The

estimation process begins with a general unrestricted

model (GUM) that is gradually reduced to produce the

best and most robust final model.

99



earning between Rp20,400,000 and Rp65,600,000 were

considered middle income. These categories also formed

the basis of those used in the 2010 HBS survey.

The level of household liquidity is also affected by the

debt repayment capacity of the household sector. Table

3.2 shows that, in general, households that tend to earn

higher incomes also have a higher ratio of total debt to

total assets. One exception was low-income households

in the province of West Sumatra, where households had a

very high ratio of debt to assets. This was due to the small

sample size of respondent households in the province,

leading to outliers that caused inconsistency. Specifically

in the case of West Sumatera, the ratio of debt to assets

for low-income households was higher than the debt

to asset ratio of middle-income households. However,

further analysis of other provinces is presented in Table

3.2, which reveals that higher income households tend to

have a higher debt to asset ratio, which implies that higher

incomes have a positive correlation with greater access to

sources of finance.

ANALYSIS OF HOUSEHOLD LIQUIDITY IN INDONESIA

A preliminary analysis on HBS survey data was

conducted by grouping households according to their

level of net income. Grouping households based on level

of net income is consistent with the HBS survey, where

households are split into three categories based on level on

net income. The three groups are low-income households,

middle-income and high-income households based on a

standard deviation of 0.5 as follows:

1. Lowincome Xi<X-0.5 STDV

2. Middle income: X-0.5 STDV≤Xi≤X+0.5 STDV

3. High income:Xi>X +0.5 STDV

Where: Xi is net income of household i over 12

months, X is the average net income of all households

in the sample over 12 months and STDV is the standard

deviation from household net income.

In the HBS survey, households earning less than

Rp20,400,000 per annum were categorised as low-income,

while high-income households were those that earned

in excess of Rp65,600,000. Consequently, households

Province Household Income Total

North Sumatera 2,87 4,54 6,89 4,49

West Sumatera 24,37 4,47 9,14 6,25

South Sumatera 0,38 0,62 0,77 0,57

DKI Jakarta 2,36 3,23 7,07 4,00

West Java 3,44 5,52 9,04 5,55

Central Java 3,11 5,02 8,26 4,93

East Java 1,56 2,79 7,75 2,75

South Kalimantan 1,09 4,00 5,13 4,21

South Sulawesi 3,25 2,08 3,6 2,42

Bali 3,79 5,02 4,05 4,77

National Average 4,62 3,73 6,17 3,99

Article Table 3.2Ratio of Total Debt to Total Assets based on Income, 2010

Low Middle High

Source: Household Balance Sheet Survey 2010, processed

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One measure of household liquidity is the ratio of

household short-term debt to household current assets.

On average, the value of the short-term debt to current

assets ratio varied across the different provinces, ranging

from 0.58% in South Sumatera to 54.8% in West Java, as

presented in Table 3.3. The table also illustrates a common

pattern, or inverse correlation, between the level of current

assets and the level of income. This denotes that high-

income households tend to have more liquidity compared

to low-income households.

More specifically, we can analyse the ratio of

household debt held at banks to fixed assets. Based on

the results of the 2010 HBS survey as presented in Table

3.4, it can be noted that the ratio of household debt held

at banks to fixed assets is in the range of 0.46% (South

Sumatera) to 4.16% (Bali). In general, Table 3.4 reveals

that high-income households tend to have a relatively

higher portion of debt at banks compared to low-income

households. This indicates that higher incomes positively

correlate to broader household access to bank loans.


North Sumatera 82,43 29,37 5,34 37,3

West Sumatera 0,00 17,87 8,2 14,8

South Sumatera 1,17 0,4 0,06 0,58

DKI Jakarta 30,88 43,16 21,56 36,9

West Java 58,95 59,91 22,99 54,8

Central Java 36,2 25,84 13,18 26,9

East Java 10,49 12,22 28,14 12,7

South Kalimantan 54,8 11,56 4,51 12,7

South Sulawesi 1,95 7,02 3,97 5,97

Bali 9,43 21,82 0,82 17,6


Table Article 3.3Ratio of Short-Term Debt to Current Assets based on Level of Income, 2010

Low Middle High


101




North Sumatera 0,69 2,09 7,91 2,55

West Sumatera 0 2,48 7,36 3,7

South Sumatera 0 0,6 0,87 0,46

DKI Jakarta 0,23 0,98 4,82 1,76

West Java 0,89 3,5 7,7 3,51

Central Java 1,58 3,26 8,37 3,46

East Java 0,35 1,91 7,8 1,83

South Kalimantan 0 1,79 5,42 3,21

South Sulawesi 4,42 1,46 4,08 2,18

Bali 0,14 4,41 5,03 4,16


Table Article 3.4Banks Debts/Fix Assets Ratio by Income Category, 2010

Low Middle High


Table Article 3.5Ratio of Household Debt to Household Assets

Financial Ratio Value

Total Sample 3.355

Liquidity Mismatch Ratios

Bank debt/disposable income 11,02

Principal loan and interest repayments/disposable income

7,74

Consumption spending/disposable income

71,1

Total debt /Disposable Income 16,12

Solvency Ratios

Total debt/Total assets 3,83

Total debt/Current assets 34,8

Total debt/Fixed assets 4,35

Bank debt/Total assets 2,62

Bank debt/Current assets 23,77

Bank debt/Fixed assets 2,97

Total debt/Networth 3,98

Bank debt/Networth 2,72

Note : Processed using a dataset from 2010, which is most comparable to the 2009 dataset. All datasets were calculated using a cash-based approach.

Source: HBS Survey 2010, processed

The financial condition of households in Indonesia

regarding debt remains safe, which is evidenced by the

data presented in Table 3.5. In general, the level of

household debt in Indonesia is well below that of the

conventional safe threshold of 60% of income. This implies

that households in Indonesia managed their debt well in

2010. If the safe threshold is halved to just 30% of income,

there remains a large potential for households to obtain

financial support from the banking sector amounting to

13.88%.

Based on the theory of precautionary savings and

buffer-stock, low-income households are vulnerable to

variability in income and consumption. Therefore, low-

income households tend to hold more cash and cash

equivalents relative to higher income households. The

variables of liquidity contained within cash and cash

equivalents include cash, savings, checking accounts and

term deposits.

Similar to that illustrated in Figure 3.1, the lowest

income households hold the highest level of cash and cash

equivalents. Accordingly, the lowest 20% of low-income

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households have a ratio of cash and cash equivalents to

total assets of around 7.82%. Meanwhile, the highest 20%

of high-income households tend to have a ratio of cash

and cash equivalents to total assets of 5.07%. The results

processed using HBS survey data from 2010 are consistent

with the theory of precautionary savings and buffer-stock

as the basis for households to hold liquid assets (cash and

cash equivalents).

household assets. Households with a higher level of assets

tend to hold a larger amount of cash. Notwithstanding,

when a household increases its asset value, it also reduces

the proportion of current assets to total assets. This is

evidenced by the negative coefficient of asset valuewhen

estimating the ratio of current assets to total assets as

an independent variable. This indicates that the ratio of

current assets to total assets will decline in line with an

increase in household asset value. This implies economies

of scale in the cash holdings used for transactional motives

or precautionary saving motives as corroborated by Paxton

and Young (2010) and Cunha et al. (2011).

The results of this study demonstrate that the level

of household disposable income tends to have a positive

correlation with the level of household liquidity. This

indicates that higher income households also have a

higher level of liquidity. According to Cunha et al. (2011),

a negative correlation would denote that households tend

to utilise additional household income as precautionary

savings.

In addition to using the variable of disposable

income, this research also uses the ratio of disposable

income to total assets as one of the explanatory variables.

The results show that the ratio of disposable income to

total assets has a significant and negative impact on the

level of liquidity, which indicates that households with low

asset productivity tend to require more liquidity.

The type of household debt affects the relationship

between the level of liquidity and level of household debt

(Paxton and Young, 2010). This research uses the ratio of

debt to disposable income as a form of variable for debt.

For the majority of estimations, the ratio of debt to assets

was negative while the ratio of debt to disposable income

was partly negative and partly positive. According to

Paxton and Young (2010), the negative coefficient implies

that households borrow money to meet their emergency

needs due to a lack of liquid assets in the form of savings.

Article Figure 3.1Ratio of Cash and Cash Equivalents to Total Assets

0%

2%

4%

6%

8%

10%

12%

14%

Q1 Q2 Q3 Q4 Q5Quintile

All observations Have debt at bank

In addition, Figure 3.1 also illustrates that households

with bank debt have a higher level of liquidity (have more

cash and cash equivalents) compared to households in

general, particular the lowest 40% (in the Q1 and Q2

categories). This is possibly driven by the requirement

for cash and cash equivalents to repay debt/loans from

a bank.

In broad terms, the variables that affect the level

of liquidity at households in Indonesia are household

asset value, household level of income, the ratio of debt

to income, ratio of debt to assets, number of household

members, ratio of operational profit to operational cash

in, the level of operational cash out, cash out to service

debt, the dummy variable for employed and the dummy

for self-employed as well as household ownership.

When analysed from the level of household cash

holding, Table 3.5 shows that cash holdings for households

in Indonesia have a positive correlation with the level of

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Meanwhile, a positive coefficient indicates that households

have sufficient liquid assets and income but tend to

allocate this to precautionary savings. Therefore, it is most

likely that household debt is used to meet the investment

needs of the household (in the form of financial assets or

fixed assets like property or motor vehicles). In brief, this

indicates that a portion of households in Indonesiautilise

debt to cover their emergency needs yet another portion

uses their debt for investment purposes or the purchase

of assets.

The number of household members had a negative

correlation in all final models, which reveals that as

households expand they tend to require more liquidity to

fund spending on daily household needs. High spending

on household expenses also makes it more difficult for the

households to allocate funds to savings and, hence, such

households tend to have a limited saving portfolio.

The variable net worth had a positive affect on

the level of household liquidity, which indicates that

households with a higher net worth tend to have larger

cash holdings. Moreover, the proportion of current assets

to total assets tended to decline as net worth increases,

similar to that shown by estimations using the ratio of

current assets to total assets as a dependent variable. Such

conditions show that an increase in net worth precipitates

a change in asset portfolio, where households tend to hold

a larger portion of fixed assets.

The level of profitability (ratio of profit or loss to

operational income) produced the expected sign and

significance consistently for each model, which indicates

that highly profitable households tend also to have a higher

level of liquidity.

The variable of cash in/out for operational activity

had a positive coefficient, which reveals that household

demand for liquidity is driven by transactional motives,

where the households tend to use liquid assets for

operational activities.

In contrast, the variable of cash in/out for investment

activity had a negative coefficient, while the coefficient of

cash out for investment was positive. These findings show

that when a household is awash with excess liquidity the

household tends to spend on investment, for instance

through the purchase of financial assets to store wealth.

Conversely, when a liquidity shortfall isexperienced,

households tend to disinvest, for example by liquidating

financial assets or lending household assets.

This research utilisedthe variable of cash out to

service debt as a determinant of household liquidity.

The results show that the coefficient of this variable is

ambiguous. The level of household liquidity measured

using total savings, checking accounts and term deposits

correlates positively to the variable cash out. Nevertheless,

liquidity measured using the amount of cash held had a

negative correlationwith cash out to service debt. This

indicates that the household requirement for liquidity to

repay outstanding liabilities tends to exceed the amount

of cash available, thereby forcing households to dip into

their savings, checking accounts or term deposits to service

the debt.

Estimation results also show that households with

members in employment also have a higher level of

liquidity. This is because those in employment tend to have

a higher level of income compared to the unemployed.

The findings demonstrate that higher levels of income led

to higher levels of liquidity.

Meanwhile, the dummy variable for self-employed

household members had different signs of coefficient for

the different measures of liquidity. Households with self-

employed members tended to hold more cash, however,

their level of liquidity from the perspective of cash and

cash equivalents (cash, savings, checking accounts, term

deposits) was lower. This indicates that households with

a small business or self-employed members tend to make

relatively more cash-based transactions.

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The dummy variable for households that own their

housewas significant in the majority of models with a

negative coefficient. This reveals that households with

property tend to have less liquidity than those not in

possession of property. This can be explained by two

considerations as follows:

1. Households that own their house tend to have more

fixed assets (a change in the asset portfolio).

2. Households that own property tend to have less need

to rent a house compared to households that do not

own property.

The variable for the age of the eldest household

member, the dummy variable for pensions and cash out

for consumption were also significant in a number of

estimations. Similar to the coefficient for total household

members, the variable for the age of the eldest household

member had a negative coefficient. As explained by Paxton

and Young (2010), this negative coefficient is evidence

of a dissaving process by households as the ages of

their members increase. Household members of pension

age experience a decline in income, thereby reducing

household liquidity. Therefore, dissaving is commonplace

in order to meet the spending needs of the household.

The dummy variable of pension in this research

predominantly had a positive coefficient in line with

expectations. This indicates that households with pensioners

tend to have stronger demand for liquidity than households

without members of pension age. This can be explained by

the physical limitations of pensioner households in terms

of liquidating assets as required. According to Cunha et al.

(2011), households with pensioners require more liquidity

due to higher risk aversion.

The variable cash out for consumption spending had

a positive correlation in a number of the models, which

indicates that demand for household liquidity is driven by

transactional motives, where the households tend to utilise

liquid assets to meet the daily needs.

CONCLUSION AND POLICY RECOMMENDATIONS

This research strived to analyse the determinants

of household liquidity in Indonesia. The findings provide

empirical evidence that internal factors play an important

role in determining household demand for liquidity. The

factors include, among others, household asset value, ratio

of household income to household assets, ratio of debt

to income, ratio of debt to assets, number of household

members, ratio of operational profit to operation cash in,

the level of operational cash out, cash out to service debt,

the dummy variables for employed and self-employed as

well as property ownership. The variable for the age of the

eldest household member, the dummy for pensioners and

consumption cash out were also significant for a number

of estimations. The results of this study also showed that

households in Indonesia hold liquid assets motivated by

transactions and precautionary saving.

Disruptions to the financial stability of the household

sector can affect the financial stability of the economy

overall. Therefore, the findings of this research into the

level of household liquidity are expected to assist the

policymaking process in order to formulate appropriate

policies that maintain financial system stability. In particular,

policymakers could formulate strategic measures to

facilitate an increase in liquidity at households experiencing

liquidity shortfalls, for instance through household

financing schemes that do not leave households exposed

and vulnerable to shocks. In addition, policymakers could

also formulate a strategy to help absorb excess liquidity

at households experiencing a liquidity surplus, reallocating

the liquidity to productive activities that are expected to

ultimately raise the welfare and prosperity of households

in Indonesia.

This research focused on internal household factors

like disposable income, assets, net worth and dummy

variables relating to the internal characteristics of the

household. The findings show that internal variables have

105



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DIRECTOR

Wimboh Santoso Suhaedi Linda Maulidina

COORDINATOR & EDITOR

Dwityapoetra S. Besar

COORDINATOR & EDITOR fOR CHAPTER I

Fernando R. Butarbutar

COORDINATOR & EDITOR fOR CHAPTER II

Eva Aderia S., Kurniawan Agung W.

COORDINATOR & EDITOR fOR CHAPTER III

Diana Yumanita

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Financial Stability ReviewNo. 18, march 2012