building and utilizing macroeconomic modeling for policy purposes: an overview by atchana waiquamdee...
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Building and Utilizing Macroeconomic Modelingfor Policy Purposes: An
Overviewby
Atchana WaiquamdeeDeputy GovernorBank of Thailand
Presented at the SEACEN-CCBS/BOE-BSP Workshop on
Dynamic Stochastic General Equilibrium Modeling and Econometric Techniques
November 23–27, 2009Manila, Philippines
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1.Introduction2.Macro models and DSGE
model3.Building DSGE model4.Challenges in macro
modeling 5.Conclusion
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Outline of Presentation
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1. Introduction3
4The Long History of Economic Models
Analogies – clear your thinking– Adam Smith’s pin factory
Early analytical tools – simplify the issues– Alfred Marshall’s demand/supply,
Edgeworth’s box,Cournot’s model of competition, Hicks’ IS-LM analysis
Formal use of mathematics – retain the coherence– Micro: Game theory, General equilibrium – Macro: Dynamic models with optimizing and
rational agents– Empirical: Econometrics, Time-series
5Two macro revolutions
(1) Lucas critique
Role of monetary policy: anchoring inflation expectations
Expectations in previous macro models– Purely adaptive: based on what happened in the
past Rational expectations Agents do not make
systematic errorswhen predicting the future– Model parameters in fact depend on agents’
expectations of policy– Would be naive to evaluate policies based on past
aggregate data– To predict effects of policy experiment, we must
modeldeep parameters that govern individual behavior
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Nevertheless, even in model with rational agents, role of monetary policy is limited– In reality, we do observe impacts of monetary
policy in short run Hence, emerging role of market
imperfections– Imperfect competition– Nominal frictions: price and wage rigidities
Rational expectations and New Keynesian framework– Give rise to crucial role of macroeconomic
stabilization policies– Form the basis for modern macroeconomic
models
Two macro revolutions(2) New Keynesian macroeconomics
777772. An overview of macro models
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Generic uses of macro models
Examination of dynamics of macro variables– Output and its components,
employment, prices Macro models:
– Articulate and expound theoretical ideas
– Test different theories– Construct “what if” scenarios – Produce forecasts
9Using macro models in policymaking process
Policymaker must base decisions on limited understanding ofthe economy, a large and complex system
Models aim to simplify complex system but keep all salient features– Deep parameters capturing preferences, technology,
and institution factors
Good models, for policy making, should…– Be backed by a coherent and logical theory – Replicate the statistical properties of the actual time
series
Both criteria are necessary– Lack of a coherent theory leads to ‘Lucas critique’,
spurious relationships, data mining, over-fitting, and model misspecification for example
– Lack of statistical congruence leads to poor forecasting
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Driven by theory
Driven by data
Portfolio of macro models in most central banks
DSGE model
Macroecono-metric model
VAR
Adapted from Pagan (2003), “Report on Modeling and Forecasting at the Bank of England,” Bank of England Quarterl
y Bulletin , (Spring), 60-88
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Small New-Keynesian model■
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Different models have different comparative advantage inwhat is required by policymakers•Those mainly
driven by data: forecasting
•Those mainly driven by theory: policy analysis
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VAR
Use econometric procedures to obtain model parameters
Emphasize fitting historical data Rely very little on theory
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Macroeconometric Model
Fit data to equations that are loosely based on theory
Typically use error correction mechanism, specifying– Long-run relationship: based on
theory– Short-run relationship: guided by
factors driving short-run dynamics While linked to theory, long-run
values– Do not depend on supply side– May not satisfy stock-flow consistency
Furthermore, model does not emphasize microeconomic agents and their expectations– Susceptible to Lucas critique
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Small New-Keynesian Model
This model borrows key results from New Keynesian economics that emphasizes market imperfections, especially, price rigidities
Model usually specified in terms of gaps—how much each variable is deviated from its long-run, equilibrium value
While model focuses on key aggregate relationships–IS relation, Phillips curve, Taylor rule, UIP condition
they lack structural features that underline aggregate dynamics
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DSGE Model
Neoclassical RBC models
New Keynesian imperfections
Optimizing agents
Perfect competition
Monopolistic competition
No rigidities Real and nominal rigidities
New Neoclassical Synthesis
DSGE Model = Sticky-Price RBC Model
Long runDriving forces = real factors
(e.g., technology shocks)
Short runMonetary policy does have real effects
because of price rigidities
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DSGE models characterize the workings of the economyRational expected utility-maximizing agentsand forward-looking central bankBoth demand and supply sides of the economyStock-flows consistency between various variablesin order to explainShort-run business cycle fluctuationsLong-run growth path of the economy
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Why DSGE Models?
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Why DSGE Models?
DSGE models provide coherent framework
for policy analysis and forecastingProvide counterfactual experiments/simulationsAnswer questions relating to structural changesIdentify sources of shocks in the economyForecast and predict the effects of policy changesEvaluate alternative policies
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17What can DSGE offer the policymaker?
It aims at ‘understanding’ rather than just ‘forecasting’– A rigorous structural model is required to uncover
the underlying driving forces of economic development
It imposes logical discipline on the policymaker– Effects of monetary policy works in complex ways
especially for small open economies; Interdependence of economic variables must be acknowledged
It is conceptually a natural tool for policy experiments– The framework is free from ‘Lucas critique’, and is
therefore more stable for alternative policy experiments
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Traditional process
Policymaking process
Assumptions &risk assessment
Standard Macro-
econometric model
Inputs
Balance of risk &policy decision
Tunings Forecasts
Judgments
With DSGE
Assumptions &risk assessment
DSGE model
Inputs
Balance of risk & optimal policy
Tunings Forecasts
Judgments
Priors
Scenarios evaluation
Policy experiments
Transmissionlinkages
1919191919DSGE models at policy institutions
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Institution/Model
Key applications
Federal Reserve Board SIGMA
Increased government spending, rising home consumption demand, falling currency risk premiums, changes in foreign demand, permanent productivity growth, reductions in labor and capital tax rates
IMFGEM & GIMF
Multi-country open economy;Fiscal analysis (GIMF)
Central Bank of ChileMAS
Contribution of shocks to business cycle,Effects of copper price shocks under different fiscal rules
RiksbankRAMSES
Scenario analysisgiven alternative interest rate paths
Bank of ThailandBOTDSGE
Macro-financial linkage:financial accelerators
2020202020Applications of DSGE Models at policy institutions
Examples of policy analysisA.E ffectiveness of alternative
monetary policy rules (Laxto n and Pesenti, 2 0 0 3 )
B.E ffects of structural reform p olicies
(Bayoumi, Laxton, and Pesenti, 2 0 04 )
C.Natural rates of output and interest(Edge, Kiley, and Laforte, 2008)
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Two-country DSGE model used to assess effectiveness
of Taylor rules in Czech Republic Key findingsRules that perform well in closed economy also perform well in another closed economy
Yet, maybe inefficient when applied to small open economies
Such rules respond too weakly to forecasts of inflation andtoo strongly to movements in output gapIn small, open, emerging economies, a modified rule that responds strongly to inflation produces better macroeconomic performance
21A. E ffectiveness of A lternativeM onetary P olicy Rules
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Two-country DSGE model where price and wage markup parameters of euro
area are lowered to U.S. levelsto simulate impact of increasing
product & labor market competition
Key findingsEuro area output and welfare rises significantlyThere are positive spillovers to the rest of the worldStructural reforms ease the task of monetary policymakers in euro area
Increased competition reduces nominal rigidities in euro area
Costs of stabilizing output reduced, thereby making it easierto use monetary policy in a counter-cyclical manner
22B. E ffects of structural reformpolicies
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A disaggregated DSGE model for U.S. economy studying
historical evolution of natural rates of output and interest
Potential output Output that would prevail absent wage and price rigidities and abstracting from shocks to markups
– Different from a more traditional view of potential outputas a smoothly evolving series
23C. Natural rates of output and interest
2424242424In short, DSGE models facilitate assessing how structural
features of the economy affect its responses to shocks
Reduced-form models If someone disagrees with predicted dynamics, it may be difficult to discuss why VARs impose very little restrictions
(just regressing on past data), making it difficult to identify what is behind model dynamics
Structural models are superior as they offer precise and coherent framework of where restrictions come from If policymakers disagree with the
results, it is possible for staffto identify what is behind them and fix them
Two-way interaction between policymakers and staff
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3. Building models for policy purposes
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2626262626General Approach and Objective
Identify key features/stylized facts of economy Balanced growth path, steady-state
ratios Slow adjustments in prices and
wages Slow adjustments in GDP
components, e.g. consumption, investment
Mimic those features by incorporating in models: Calibrate key stylized facts, e.g. C/Y
= 0.60 Nominal rigidities: contractual
price/wage setting processes Real rigidities: habit persistence,
investment adjustment costs
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Households
Consume and invest
Hire inputs and produce
Model environment of a baseline DSGE model
Agents
What they do
Features
Firms
GovernmentCentral
Bank
Supply labor to firms and set wage
Consumption habit persistence;
Monopolistic competitive labor market; wage rigidities
Monopolistic competitive market
Spend according to fiscal rule
Set interest rate according to monetary policy rule
Fixed proportion of nominal GDPInflation targeting
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Invest Investment adjustment costs
price rigidity
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Model consists ofa)First-order conditions
and policy rulesb)Exogenous processesc)Market clearing conditionsd)Steady-state conditions
TransitiondynamicsN equationsin N unknowns
Transitiondynamics &terminalconditions
Fully/partially micro-founded behavior
Dynamic path ofmodel variablescan be solved (Think of solving a system of differential equations)
3.1. Model structure28
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1. Firm’s input demand problem
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Optimal inputs demanded
a) First-order conditions
micro-founded behavior
3.1. Model structure
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2. Firm’s pricing problem
Optimal price setting micro-founded behavior
Price rigidity parameterMarkup
parameter
characterize underlyingstructure of economy
Price in long run = markup over marginal cost
Price in short run depends on how difficult it is for firms to change prices
3.1. Model structure
32323232323.2. Model parameterization
Two broad methods Calibration Select parameters based
on empirical findingsthat result in model that best characterizes Thai economy
Estimation Potential difficulties with likelihood– limited data– structural breaks– multiple local maxima
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33333333334. Challenges and New Directions
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Reliance on individual rationality Near-absence of heterogeneity Simplifying assumptions:
– Assuming perfect financial market: missing macro-financial linkage
– Assuming Ricardian equivalence: no role of fiscal policy
Approximate model solution– Missing nonlinearities originally built
in model
Potential weaknesses in DSGE models
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Not enough emphasis on financial market imperfections – Standard models focus on real
economy exclusively– Probably missing real-financial
linkage in the economy While some models study liquidity
problems in financial markets– They do not explain why some
assets that previouslywere very liquid suddenly stop being traded
Possible improvement Integrate financial imperfections in
addition to standard nominal and real rigidities in macro models—recent study by Bank of Thailand
More on last day of Workshop
4.1. Models need to strike balancebetween simplicity and complexity
36363636364.2. Model solutions need to incorporate
risks and uncertainty
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Although DSGE models themselves admit nonlinearities,model solution relies on linearizing the model– We focus on small shocks in the neig
bourhood of steady state– Buiter (2009): We took these
models “into the basement and beat them with a rubber hose until they behaved”
In such linear quadratic framework equations describing economy are linear and objective function specifying policy goals is quadratic– Minimizing inflation and output
volatility subject to linear model
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Under these assumptions, monetary policy is certainty equivalent
– Policy responses do not depend on variances or any other aspect of probability distribution of shocks
– Mishkin (2008): In such an environment, monetary policy “does not focus on risk management”
Possible improvement Solving model using higher-order
approximation methods that retain information discarded by linearization (first-order approximation)
4.2. Model solutions need to incorporate
risks and uncertainty
38383838384.3. DSGE models need to have
good forecast performance
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It was only until recently that DSGE models can
Track/forecast time series as well as VAR (Smets and Wouters, 2003)
Incorporate extraneous predictions and judgments consistent with underlying structure of the model (Benes et al., 2009)
Predict future path of nonmodeled variables (Schorfheide and Sills, 2009)
These improvements will help Utilize information on high-frequency
(monthly) indicators in (quarterly) DSGE models
Gain more accuracy of initial condition of forecast
More on last day of Workshop
393939393939We need macro models for policymaking process
Success of central banks rests in appropriate and timely response of monetary policy to disturbances to anchor inflation expectation
Role of modelers and forecasters is to provide clear framework of the working of economy and monetary policy transmission
Models help policymakers take appropriate action and communicate their decisions to public– Provide consistent framework to
think about forecast andto evaluate alternative monetary policy