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A Panel Discussion on DSGE Modelling at Central Banks: Country Practices and How It Is Used in Policy Making by Surach Tanboon Monetary Policy Department Bank of Thailand - PowerPoint PPT PresentationTRANSCRIPT
A Panel Discussion onDSGE Modelling at Central
Banks:Country Practices and How It Is
Used in Policy Making by
Surach TanboonMonetary Policy Department
Bank of Thailand
Presented at the SEACEN-CCBS/BOE-BSP Workshop on
Dynamic Stochastic General Equilibrium Modeling and Econometric Techniques
November 23–27, 2009Manila, Philippines
2222Macro Modeling at Bank of Thailand
Bank of Thailand Macroeconometric Model (BOTMM)– Principal model for forecasting
and policy analysis Small New-Keynesian Model
– Used in policy analysis DSGE Model
– Work in progress, currently used to study special issues
– Aimed to complement BOTMM in MPC process
Households
Domestic Firms
Consume
Hire inputs and produce
AGENT
FUNCTIONS
FEATURES
Export Firms
BanksTake deposits from households;lend to firms
GovernmentCentral
Bank
Supply labor to firms and set wage
Deposit funds with banks;trade foreign bonds
Consumption habit persistence
Monopolistic competitive labor market; wage rigidities
Monopolistic competitive local market; price rigidity
Competitive export market
External finance premium
Spend according to fiscal rule
Set interest rate according to monetary policy rule
Fixed proportion of nominal GDPInflation targeting
External finance premium
3
Capital Producer
Invest and supply capital to firms
Investment adjustment costs
Model Environment
Debt-contingent premium on foreign borrowing
44444
Firms
Retailers
labor
Households
Capital produce
r
capital
wholesale good
final good(for
investment)
final good(for consumption)
No Financial Accelerator
Firms Households
capital
Banks
EXTERNAL FINANCE: loans
BALANCESHEET
BALANCESHEET
Capital produce
r
Macro-financial linkage
With Financial Accelerator
4
labor
Key MechanismInverse relationship between
borrower’s balance sheetconditions and premium for
external finance
EXTERNAL FINANCE: deposits
5555
Determination of RD Case 1 QKD < ND
N o need to seek externa l finance;E xternal finance premiu
m is zero
Case 2 ND < QKD < ND + NBD
Firm needs to borrow & bank can cover firm’s demand with its own internal funds
Case 3 QKD > ND + NBD
Bank cannot cover firm’s demand;pays premium when raise external funds; in
turn passes this premiu m onto firms
Model Highlight 1: Double financial accelerator
Source: Sunirand (2002)
6666Model Highlight 2: Euler rate puzzle
Canzoneri, Cumby, and Diba (2007) and Reynard and Schabert (2009)– Euler rate is empirically not related
to observed policy rates Here, bank’s external finance premium acts as wedge between policy rate and deposit rate–Hence interest rate at which
households use for discountingis different from Euler rate
0 5 10 15 20
-10
-5
0
Equity/Assets
0 5 10 15 20
0
0.2
0.4
0.6
Premium
0 5 10 15 20
-10
-5
0
Investment
0 5 10 15 20
-0.4
-0.2
0
0.2Policy interest rate
Without AcceleratorWith AcceleratorWith Accelerator - higher premium sensitivity
7777
Eq
uit
y
sh
ock
0 5 10 15 20
-10
-5
0
Equity/Assets
0 5 10 15 20
0
0.2
0.4
0.6
Premium
0 5 10 15 20
-10
-5
0
Investment
0 5 10 15 20
-0.4
-0.2
0
0.2Policy interest rate
Without AcceleratorWith AcceleratorWith Accelerator - higher premium sensitivity
Financial accelerator intensified: external finance premium becomes more sensitive to balance sheet conditions
0 5 10 15 20
-10
-5
0
Equity/Assets
0 5 10 15 20
0
0.2
0.4
0.6
Premium
0 5 10 15 20
-10
-5
0
Investment
0 5 10 15 20
-0.4
-0.2
0
0.2Policy interest rate
Without AcceleratorWith AcceleratorWith Accelerator - higher premium sensitivity
Model insight: Higher degree of monetary policy accommodation
during crisis times
8888
Plan Ahead
Start inducting DSGE model in MPC process–Policy analysis– Forecasting
Issues to work out– Estimating the model– Striking balance between simplicity
and complexity•Communication between modelers and policymakers/sector specialists
–Dealing with nonmodeled variables– Incorporating off-model information
•Large cross-section data, high-frequency indicators, judgment
– Introducing risks and uncertainty in model