BALANCING A PARSIMONIOUS AND COMPLEX MODEL IN ...

BALANCING A PARSIMONIOUS AND COMPLEX MODEL IN EMERGING MARKET ECONOMIES: CASE OF INDONESIA (General Equilibrium Model of Bank Indonesia - GEMBI)

Prepared for Structural Dynamic Macroeconomic Models In Asia-Pacific Economies Workshop Bali, June 3-4,2008 Economic Modeling & Outlook Group, Bureau of Economic Research, Directorate of Economic Research and Monetary Policy BANK INDONESIA

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The increasing needs of DSGE in Emerging Market  Many central banks have increasingly been interested in DSGE model  Many central banks have increasingly been interested in DSGE model to guide their monetary policy formulation for some reasons : ƒ DSGE has strong micro‐foundation Æ all economic agents maximize their  objective function subject to their constraint. ƒ The behavior of economic agents is constructed on the basic of rational  h b h i f i i d h b i f i l expectation Æ monetary policy formulation is influenced by expectation  (forward looking) g p y some variablesof monetary  y ƒ Endogenous policy rule in the DSGE model Æ policy (interest rate) and fiscal policy (tax) are determined with in the   model. ƒ DSGE model is able to generate economic steady state in the long run  owing to dynamic optimization principle of economic agents owing to dynamic optimization principle of economic agents . 

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Issues on DSGE Implementation  in Emerging Market in Emerging Market  • Market imperfection  Æ price and wage rigidity, adjustment cost,  financial market disintermediation and excess liquidity Æ model  financial market disintermediation and excess liquidity  model become more complicated • The credibility of monetary and fiscal authorities are still weak Æ the  standard model based on full credibility has to be adjusted. • Free capital mobility does not fully exist in emerging market due to  F it l bilit d t f ll i ti i k td t numerous types of exchange rate arrangements such as managed floating  and fixed exchange rate system and some degree of capital control. • Different economic structure  Æ economic sector model become more  relevant  to capture the specific and dominant sector Æ the model has to  more disaggregated. • Statistical data required to estimated parameter in emerging market is  less accurate, reliable and availability as compared to developed less accurate, reliable and availability as compared to developed  countries. • Therefore the construction DSGE model  in emerging market should  consider the specific features of emerging market economies .

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Trade off between Parsimonious and Complex Model • The bigger the scale of the model Æ the larger the number b off parameters to be b estimated, d estimation is more complex. •

The bi Th bigger the th scale l off the th model d l Æ transmission t i i mechanism is more complex (black box).

•

The bigger the scale of the model Æ more difficult to communicate the result to the policy makers.

• The bigger the scale of the model Æ more complicated model Æ the result often can not explain real world phenomena.

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Specific Features of Indonesia DSGE Model: GEMBI GEMBI has 6 economic agents: 1. Household Æ Indonesian household is heterogeneous: g Life-time consumers (capitalist) Hands-to-mouths consumers (non capitalist). 2. Firms: Æ agriculture sector is very important in Indonesia Economic sector : Finished g goods non-agriculture g producers p and Agriculture g producers Production process : Finished good, intermediate producers, and Importers 3. Financial Institutions/Banks Æ Indonesian Banks are not fully perfect competition Æ need adjustment/transaction cost. 4 4. Fiscal Authority - Non Ricardian Model (current consumption consider budget deficit) - Government expenditure consider ratio debt to GDP maximum 60% 5. Monetary Authority: - Endogenous policy rule Inflation forecast based output gap Taylor Rule - Stock of SBI (Central Bank Certificate) is endogenous to capture excess liquidity 6. Rest of the World (external sector) - Uncovered interest rate parity is not fully hold (imperfect capital market) - Capital account account, current account and foreign exchange reserve are endogenous endogenous. 5

Emerging Market Imperfection Application in GEMBI model IMPERFECTION OF ECONOMIC AGENTS (ADJUSTMENT COST) • The preference of all economic agent consider opportunity cost • Type of adjustment cost: - Transaction costs (consumption activities) Æcash vs non cash - Adjustment cost (investment activities) Æ time to build - Real cost function (bank activities) Æ cost to manage deposit and credit • Objectives of adding adjustment cost: – Better short-run dynamics – Greater flexibilityy in controlling g speed p of adjustment j – Consistent with long-run equilibrium

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Emerging Market Imperfection Application in GEMBI model IMPERFECTION IN LABOR MARKET ((WAGE RIGIDITY)) • Labour market in Indonesia is not flexible (rigid)Æ the existence of wage rigidity Æ market clearing doesn’t fully work. work • Rigidity in labour market can generate wage inflation that p the dynamics y on labour market. further explain • Due to wage rigidity Æ we can have better short-run output and inflation dynamics.

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Emerging Market Imperfection Application in GEMBI model IMPERFECTION IN EXTERNAL SECTOR 1. Interest Parity is not sufficient to explain the dynamics of exchange rate in Indonesia Æ need to add risk premium variable in the model model. 2. Interest Parity is not sufficient to explain the movement of capital p flows Æ need to add cost of p portfolio.

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INTERACTIONS AMONG ECONOMIC AGENTS IN COMPLEX GEMBI

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BANKS AS ONE ECONOMIC AGENT IN COMPLEX GEMBI Banks maximizes profit with respect to its asset and liabilities ∞

Max Et ∑ β t , s Π iB, s s =t

Constraint (Bonds, Deposit and Loans) Π tB + BB ,t + Sbit + et BB* ,t + Loant − (1 − α B − α R ) Dt = (1 + it −1 ) BB ,t −1 + (1 + it −1 ) Sbit −1 )(1 + θ t*−1 )et BB* ,t −1 + (1 + ilt −1 ) Loant −1 − (1 − α B − α R + idt −1 ) Dt −1 − Pt At C B ( Loant , Dt ) + ((1 + it*−1 )(

Where  C B ( Loan , D ) is the cost of portfolio adjustment, t t

1 ⎛ Ω L Loant − Ω D Dt ⎞ B C ( Loant , Dt ) = ⎜ ⎟ 2⎝ Pt At ⎠

2

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FISCAL AND MONETARY AUTHORITY IN COMPLEX GEMBI • Constraint for Fiscal Authority (transfer, subsidy, and foreign debt) c d BG ,t + et L*G ,t = PG + s P COM t t t COM , t t + Trf t + (1 + it −1 ) BG , t −1

+ (1 + it*−1 )(1 + θt*−1 )et L*G , t −1 − τ c Pt C Ct − τ wWt Lt − τ Π Π t

• Constraint for Central Bank ( Currency, Reserves and outstanding SBI) Constraint for Central Bank ( Currency Reserves and outstanding SBI)

X t − X t −1 = BCB ,t − (1 + it −1 ) BCB ,t −1 + et Rt* − (1 + it*−1 )et Rt*−1 − Sbit + (1 + it −1 ) Sbit −1 − α R ( Dt − Dt −1 )

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Need for more parsimonious model? p Need for a simplified version, thus SIMPLE GEMBI

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Transmission Mechanism of simple GEMBI p

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GEMBI simulation for monetary policy : Imported p Inflation Shock 1. Measuring g monetaryy p policyy response p to an inflation shock as well as its impact to economic growth and exchange rate. 2 Inflation 2. I fl ti shock h k is i assumed d 3% on ttop off it its steady state value of 6%. 3 In this simulation, 3. simulation BI-rate is an endogenous variable as a function of inflation deviation from its target and output deviation from its potential value (Taylor rule).

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GEMBI simulation for monetary policy : p Imported Inflation Shock 3% inflation shock (from 6% to 9%) 100 bp increase in BI-Rate during 2008

10.0%

8.0% 7.0% 6.0% 5 0% 5.0%

100 bp p response p of BI Rate will bring g inflation rate down to its initial value in a year

4.0% 2 2008-II 20 008-IV 2009-II 2 20 009-IV 2010-II 2 20 010-IV 2011-II 2 20 011-IV 2012-II 2 20 012-IV 2013-II 2 20 013-IV 2014-II 2 20 014-IV 2015-II 2 20 015-IV 2016-II 2 20 016-IV 2017-II 2 20 017-IV

Inflation rate

9.0%

BI rate increase 100bp

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GEMBI simulation for monetary policy : Imported Inflation Shock and interest rate response 3% inflation shock (from 6% to 9%) 100 bp increase in BI-Rate during 2008 9.50%

9% (Q3-08 & Q4-08)

9.25%

8.75% (Q1-09)

8.75%

8.5% (Q2-09)

8 50% 8.50%

8.25% (Q3-09) 8.25%

8% (Q4-09) 8.00% 7.75%

8.75%(Q2-08)

20 017-II 20 017-IV

20 015-IV 20 016-II 20 016-IV

20 015-II

20 014-II 20 014-IV

20 013-II 20 013-IV

20 012-II 20 012-IV

20 011-II 20 011-IV

20 010-IV

20 010-II

20 009-IV

20 009-II

7.50%

20 008-II 20 008-IV

Interest rate

9.00%

BI rate increase 100bp

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GEMBI simulation for monetary policy : Imported Inflation Shock and impact on economic growth 3% inflation shock ((from 6% to 9%)) 100 bp increase in BI-Rate during 2008 6.2 %

6.3% 6 2% 6.2%

6%

6.0% 5.9% 5.8%

100 bp response of BI rate will drive down economy growth to 5.7% (Q2-08) followed by an increase to 6.2% (Q3-09) during one year and eventually back its steady state value l off 6%

5.7% 5.6% 5 5% 5.5%

5.7 %

5.4%

BI rate increase 100bp

2012 2-III 2012 2-IV

201 12-I 2012-II

2011 1-III 2011 1-IV

201 11-I 2011-II

2010 0-III 2010 0-IV

201 10-I 2010-II

2009 9-IV

2009 9-III

200 09-II

200 09-I

2008 8-III 2008 8-IV

5.3% 200 08-II

Economic G Growth

6.1%

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GEMBI simulation for monetary policy : Imported Inflation Shock and impact on exchange rate 3% inflation shock (from 6% to 9%) 100 bp increase in BI-Rate during 2008

9450

9254 Rp/USD

9250 100bp response of BI rate will keep exchange rate relatively stable with small apreciation trend due to huge interest rate differensial

9150

9050

BI rate increase 100bp

201 12-IV

201 12-III

20 012-II

201 11-IV 20 012-I

201 11-III

20 011-II

20 011-I

201 10-IV

201 10-III

20 010-II

20 010-I

200 09-IV

200 09-III

20 009-II

20 009-I

200 08-IV

200 08-III

8950 20 008-II

Exchange Rate

9350

9271 Rp/USD

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Conclusion • Although we moved to simple GEMBI some emerging market features are  still maintained (open economy, production stages, price and wage  ll d( d d rigidity, and import dependant nature of economy) • Simple Simple GEMBI had been used to simulate monetary policy response for  GEMBI had been used to simulate monetary policy response for various shocks such as : exchange rate appreciation, imported inflation  shock and review of medium term inflation target   • H However, some problems are persist, such as : bl i h – Some theoretical‐inconsistent simulation (need for TA) – Unsatisfactory forecast result (need for TA) – Communication to policy makers Communication to policy makers

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THANK YOU TERIMA KASIH

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