Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) -...
Transcript of Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) -...
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Solving DSGE models: an example.Hansens Real Business Cycle Model
IAMA, Lecture 5
Prof. H. Uhlig1
1Humboldt Universität zu [email protected]
Winter 2006/07
Prof. H. Uhlig IAMA: Lecture 5
![Page 2: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/2.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
![Page 3: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/3.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Overview
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
![Page 4: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/4.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Overview
The solution strategy
The solution strategy for a model works as follows:
1. Find the first order necessary conditions2. Calculate the steady state3. Loglinearize around the steady state4. Solve for the recursive law of motion5. Calculate impulse responses and
(HP-filtered) moments
We will execute this strategy, using Hansens real businesscycle model as particular example.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
The modelRational expectationsLabor supply
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
![Page 6: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/6.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
The modelRational expectationsLabor supply
Hansens benchmark Real Business Cycle Model
max E
[
∞∑
t=0
βt(log ct − Ant)
]
s.t.ct + kt = γezt kθ
t−1n1−θt + (1 − δ)kt−1
andzt = ρzt−1 + ǫt , ǫt ∼ N(0, σ2) i .i .d .
where ct is consumption , nt is labor , kt is capital , γt = γezt istotal factor productivity (TFP) .
Prof. H. Uhlig IAMA: Lecture 5
![Page 7: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/7.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
The modelRational expectationsLabor supply
Hansens benchmark Real Business Cycle Model
Define, for convenience;
output: yt = γezt kθt−1n1−θ
t
return: Rt = θyt
kt−1+ 1 − δ
See:1 Hansen, G., “Indivisible Labor and the Business Cycle,”
Journal of Monetary Economics, 1985, 16, 309-27.2 Cooley, editor, Frontiers of Business Cycle Research,
Princeton University Press, 1995.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
The modelRational expectationsLabor supply
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
![Page 9: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/9.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
The modelRational expectationsLabor supply
Rational expectations
We assume that the social planner chooses ct , kt , nt etc.,using all available information at date t , and formingrational expectations about the future.
Rational expectations are the mathematicalexpectations, using all available information
Rational expectations only ”live in” a model, in which thestochastic nature of all variables is clearly spelled out.
Prof. H. Uhlig IAMA: Lecture 5
![Page 10: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/10.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
The modelRational expectationsLabor supply
Rational expectations
Example: dice role.
Dice 1, date t : Xt . Dice 2, date t + 1: Yt+1. Sum:St+1 = Xt + Yt+1.
Et−1[St+1] = 7. Et [St+1] = 3.5 + Xt .Et+1[St+1] = Xt + Yt+1.
E.g. Xt = 2, Yt+1 = 1. Then Et−1[St+1] = 7, Et [St+1] = 5.5,Et+1[St+1] = 3.
Example: AR(1)
zt+1 = ρzt + ǫt+1, Et [ǫt+1] = 0.
Then: Et [zt+1] = ρzt .
Prof. H. Uhlig IAMA: Lecture 5
![Page 11: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/11.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
The modelRational expectationsLabor supply
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
![Page 12: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/12.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
The modelRational expectationsLabor supply
Labor lotteries and labor supply
We assume a very elastic labor supply for aggregate labornt ,
ut = log(ct) − Ant
... which turns out to be needed in order to quantitativelyexplain observed employment fluctuations.
However, we typically imagine individual labor elasticity tobe small.
This can be true simultaneously by considering laborlotteries .
Source: Richard Rogerson, ”Indivisible Labor, Lotteriesand Equilibrium,” Journal of Monetary Economics; 21(1),January 1988, 3-16.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
The modelRational expectationsLabor supply
Labor lotteries and labor supply
Individual labor supply nt may be based on some utilityfunction u(ct) + v(nt).Suppose that
labor is indivisible : agents either have a job or do not,nt = 0 or nt = n∗.Agents are assigned to jobs according to a lottery, withprobability πt .Shirking, moral hazard etc. are not possible.Unemployment insurance is perfect, and consumption ct isindependent of job status.Total labor supplied: nt = πtn∗
Normalization: v(0) = 0, v(n∗)/n∗ =: −A < 0.Expected utility:
E [u(ct) + v(nt)] = u(ct) + πtv(n∗) = u(ct) − Ant
Prof. H. Uhlig IAMA: Lecture 5
![Page 14: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/14.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
![Page 15: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/15.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Step 1:Find the first-order necessary conditions (FONCS)
Form the Lagrangian
L = max E
[
∞∑
t=0
βt((log ct − Ant)
−λt
(
ct + kt − γezt kθt−1n1−θ
t − (1 − δ)kt−1
)
)]
Prof. H. Uhlig IAMA: Lecture 5
![Page 16: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/16.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Find the first-order necessary conditions...
Differentiate:
∂L∂ct
:1ct
= λt
∂L∂nt
: A = λt(1 − θ)yt
nt
∂L∂λt
: ct + kt = γezt kθt−1n1−θ
t + (1 − δ)kt−1
∂L∂kt
: λt = βEt [λt+1Rt+1]
The last equation needs explanation.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Differentiating with respect to kt
Write out the objective at date t : for the future, one canonly form conditional expectations Et [·]. ”Telescope” outthe Lagrangian:
L = . . . + βt((log ct − Ant)
−λt
(
ct + kt − γezt kθt−1n1−θ
t − (1 − δ)kt−1
))
+Et
[
βt+1((log ct+1 − Ant+1)
−λt+1
(
ct+1 + kt+1 − γezt+1kθt n1−θ
t+1 − (1 − δ)kt
))]
+ . . .
Differentiate with respect to kt :
0 = βtλt − Et
[
βt+1λt+1
(
θyt+1
kt+ 1 − δ
)]
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Differentiating with respect to kt
Sort terms and use
Rt+1 = θyt+1
kt+ 1 − δ
to find
λt = βEt [λt+1Rt+1]
This equation is called an Euler equation and also theLucas asset pricing equation .
Prof. H. Uhlig IAMA: Lecture 5
![Page 19: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/19.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Collecting equations1 First order conditions and a definition:
1ct
= λt
A = λt(1 − θ)yt
nt
Rt = θyt
kt−1+ 1 − δ
λt = βEt [λt+1Rt+1]
2 Technology and Feasibility constraints:
yt = γezt kθt−1n1−θ
t
ct + kt = yt + (1 − δ)kt−1
zt = ρzt−1 + ǫt , ǫt ∼ N(0, σ2) i .i .d .
Prof. H. Uhlig IAMA: Lecture 5
![Page 20: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/20.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
![Page 21: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/21.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Step 2: Calculate the steady state
At the steady state, all variables are constant.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Take all equations ...1 First order conditions and a definition:
1ct
= λt
A = λt(1 − θ)yt
nt
Rt = θyt
kt−1+ 1 − δ
λt = βEt [λt+1Rt+1]
2 Technology and Feasibility constraints:
yt = γezt kθt−1n1−θ
t
ct + kt = yt + (1 − δ)kt−1
zt = ρzt−1 + ǫt , ǫt ∼ N(0, σ2) i .i .d .
Prof. H. Uhlig IAMA: Lecture 5
![Page 23: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/23.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
... and drop the time subscripts.1 First order conditions and a definition:
1c
= λ
A = λ(1 − θ)yn
R = θyk
+ 1 − δ
λ = βλR
2 Technology and Feasibility constraints:
y = γez kθn1−θ
c + k = y + (1 − δ)k
z = ρz
Prof. H. Uhlig IAMA: Lecture 5
![Page 24: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/24.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Parameters
1 Calibration: θ = 0.4, δ = 0.012, ρ = 0.95, σǫ = 0.007,β = 0.987, γ = 1, A so that n = 1/3 (see Cooley,Frontiers...).
2 Estimation:1 GMM: mimics calibration, see Christiano and Eichenbaum,
“Current Real-Business Cycle Theories and AggregateLabor Market Fluctuations,” American Economic Review,vol 82, no. 3, 430 - 450.
2 Maximum Likelihood: see e.g. Leeper and Sims, “Toward aModern Macroeconomic Model Usable for Policy Analysis,”NBER Macroeconomics Annual, 1994, 81 - 177.
With numbers for the parameters, the steady state can becalculated explicitely.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Explicit calculation
From the production function,
y = γez kθn1−θ
we get
y =
(
γez(
yk
)
−θ) 1
1−θ
n
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Explicit calculation: n given, solve for A.
1. R = 1β
5. c = y − δk
2. yk
= R−1+δθ
6. λ = 1c
3. y =(
γez(
yk
)
−θ) 1
1−θ
n 7. A = λ(1 − θ) yn
4. k =(
yk
)
−1y
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Explicit calculation alternative: A given, solve for n.
1. R = 1β
5. ck
= yk− δ
2. yk
= R−1+δθ
6. c = 1λ
3. yn =
(
γez(
yk
)
−θ) 1
1−θ
7. k = c( c
k )
4. λ = A(1−θ)( y
n )8. y =
(
yk
)
k
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
![Page 29: Solving DSGE models: an example. Hansens Real Business ...web.sgh.waw.pl/~jg23234/do/(didactic) - Solving... · Prof. H. Uhlig1 1Humboldt Universität zu Berlin uhlig@wiwi.hu-berlin.de](https://reader033.fdocuments.us/reader033/viewer/2022050314/5f760dafe09fd107e9321437/html5/thumbnails/29.jpg)
The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Step 3: Loglinearize around the steady state
Replace the dynamic nonlinear equations by dynamiclinear equations.
Interpretation and calculation are made easier, if theequations are linear in percent deviations from the steadystate.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
The Principle of Loglinearization
For x ≈ 0,ex ≈ 1 + x
For xt , let xt = log(xt/x) be the log-deviation of xt from itssteady state. Thus, 100 ∗ xt is (approximately) the percentdeviation of xt from x . Then,
xt = xext ≈ x(1 + xt)
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Application of Loglinearization
Application: The equation
xt + ct = yt
together with its steady state version
x + c = y
deliver the dynamic relationship
x xt + cct = y yt
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Example: RBC
Do it slowly for two equations:
The resource constraint:
ct + kt = yt + (1 − δ)kt−1
cect + kekt = yeyt + (1 − δ)kekt−1
c(1 + ct) + k(1 + kt) ≈ y(1 + yt) + (1 − δ)k(1 + kt−1)
(Note: c + δk = y)
cct + k kt ≈ y yt + (1 − δ)k kt−1
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Example: RBC
The asset pricing equation:
λt = βEt [λt+1Rt+1]
λeλt = βEt
[
λReλt+1+Rt+1
]
1 + λt ≈ βREt
[
1 + λt+1 + Rt+1
]
( Note: 1 = βR)
λt ≈ Et
[
λt+1 + Rt+1
]
On “ignored” Jensen terms: can also assume jointnormality of logdeviations insteady. This changes thesteady state , not the dynamics .
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
All loglinearized equations
# Equation Loglinearized(i) 1
ct= λt 0 = ct + λt
(ii) A = λt(1 − θ) ytnt
0 = λt + yt − nt
(iii) Rt = θ ytkt−1
+ 1 − δ 0 = −RRt + θ yk
(
yt − kt−1
)
(iv) yt = γezt kθ
t−1n1−θ
t 0 = −yt + zt + θkt−1 + (1 − θ)nt
(v) ct + kt = yt + (1 − δ)kt−1 0 = −cct − k kt + y yt + (1 − δ)k kt−1
(vi) λt = βEt [λt+1Rt+1] 0 = −λt + Et [λt+1 + Rt+1]
(vii) zt+1 = ρzt + ǫt+1 zt+1 = ρzt + ǫt+1
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Recursivity
State variables are: kt−1, zt (or, alternatively, kt−1 andzt−1).
The dynamics of the model should be describable by arecursive law of motion (RLOM),
λt = f(λ)(kt−1, zt)
kt = f(k)(kt−1, zt)
yt = f(y)(kt−1, zt)
etc.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Recursivity
Assume that the RLOM is linear in the log-deviations,
λt = ηλk kt−1 + ηλzzt
kt = ηkk kt−1 + ηkzzt
yt = ηyk kt−1 + ηyzzt
etc. for coefficients ηλk , ηλz , etc.
To make life simpler here, we shall try to reduce the systemto only k and λ (one doesn’t have to).
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Simplify:
Note: yt = 1θzt + kt−1 + 1−θ
θλt
Abbreviations:
α1 =yk
+ (1 − δ)
α2 =ck
+1 − θ
θ
yk
α3 =yθk
α4 = 0
α5 = 1 + (1 − θ)y
Rk
α6 =y
Rk
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Obtaining the solution
We obtain the following first-order two-dimensionalstochastic difference equation :
0 = −kt + α1kt−1 + α2λt + α3zt (1)
0 = Et [−λt + α4kt + α5λt+1 + α6zt+1] (2)
zt = ρzt−1 + ǫt (3)
where zt is an exogenous stochastic process.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Obtaining the solution
Compare to the following first-order two-dimensionalstochastic difference equation to be studied in the lectureon difference equations:
0 = −xt + α1xt−1 + α2yt + α3zt (4)
0 = Et [−yt + α4xt + α5yt+1 + α6zt+1] (5)
zt = ρzt−1 + ǫt (6)
They are the same with xt = kt , yt = λt .
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
The Method of Undetermined Coefficients
Postulate the recursive law of motion
λt = ηλk kt−1 + ηλzzt (7)
kt = ηkk kt−1 + ηkzzt (8)
Plug this into equations (1) once and (2) “twice” and exploitEt [zt+1] = ρzt , so that only the date-t-states kt−1 and zt
remain ,
0 = (−ηkk + α1 + α2ηλk ) kt−1
+ (−ηkz + α2ηλz + α3) zt
0 = (−ηλk + α4ηkk + α5ηλkηkk ) kt−1
+ (−ηλz + α4ηkz + α5ηλkηkz + (α5ηλz + α6) ρ) zt
Compare coefficientsProf. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
On plugging in twice...
Plugging
λt = ηλk kt−1 + ηλzzt , kt = ηkk kt−1 + ηkzzt ρzt = Et [zt+1]
twice into
0 = Et [−λt + α4kt + α5λt+1 + α6zt+1]
= Et [−(ηλk kt−1 + ηλzzt) + α4(ηkk kt−1 + ηkzzt)
+α5(ηλk kt + ηλzzt+1) + α6zt+1]
= Et [−ηλk kt−1 − ηλzzt + α4ηkk kt−1 + α4ηkzzt)
+α5ηλk (ηkk kt−1 + ηkzzt) + (α5ηλz + α6)zt+1]
= (−ηλk + α4ηkk + α5ηλkηkk ) kt−1
+ (−ηλz + α4ηkz + α5ηλkηkz + (α5ηλz + α6) ρ) zt
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Comparing coefficients
On kt−1:
0 = −ηkk + α1 + α2ηλk
0 = −ηλk + α4ηkk + α5ηλkηkk
One gets the characteristic quadratic equation
0 = p(ηkk ) = η2kk −
(
α1 −α2
α5α4 +
1α5
)
ηkk +α1
α5(9)
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Solving the characteristic equation
Solutions:
ηkk =12
((
α1 −α2
α5α4 +
1α5
)
(10)
±
√
(
α1 −α2
α5α4 +
1α5
)2
− 4α1
α5
Choose the stable root | ηkk |< 1. There is at most one stableroot, if
| ηkk ,1ηkk ,2 |=|α1
α5|> 1
With ηkk , calculate
ηλk =ηλλ − α1
α2
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Comparing coefficients
On zt :
0 = −ηkz + α2ηλz + α3
0 = −ηλz + α4ηkz + α5ηλkηkz + (α5ηλz + α6) ρ
Solution:
ηλz =α4α3 + α5ηλkα3 + α6ρ
1 − α4α2 − α5ηλkα2 − α5ρηkz = α2ηλz + α3
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Step 5: Calculate impulse responsesand (HP-filtered) moments
Impulse responses: will be explained now.
HP-filtered moments: will be discussed later.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Impulse Response Functions: response to a shock inzt
1 Set z0 = 0, ǫ1 = 1, ǫt = 0, t > 12 Calculate zt = ρt
3 Set k0 = 0.4 Calculate recursively
kt = ηkk kt−1 + ηkzzt
5 With that, calculate
λt = ηλk kt−1 + ηλzzt
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Results: Impulse Responses to shocks
−2 0 2 4 6 8−0.5
0
0.5
1
1.5
2Impulse responses to a shock in technology
Years after shock
Per
cent
dev
iatio
n fr
om s
tead
y st
ate
capital
consumption
output
labor
interest
technology
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Impulse Response Functions: response to an initialdeviation of the state kt from its steady state.
1 Set zt = 0, t ≥ 12 Set k0 = 1.3 Calculate recursively
kt = ηkk kt−1
4 With that, calculate
λt = ηλk kt−1
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Step 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
Results: Impulse Responses to capital deviations
−2 0 2 4 6 8−0.5
0
0.5
1Impulse responses to a one percent deviation in capital
Years after shock
Per
cent
dev
iatio
n fr
om s
tead
y st
ate
capital
consumption
output
labor
interest
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Alternative representations
Outline1 The solution strategy
Overview2 Hansens benchmark Real Business Cycle Model
The modelRational expectationsLabor supply
3 The solution stepsStep 1: find the FONCsStep 2: Calculate the steady stateStep 3: LoglinearizeStep 4: Solve for the RLOMStep 5: Calculate impulse responses
4 RepresentationsAlternative representations
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Alternative representations
Recall: the loglinearized equations
# Equation Loglinearized(i) 1
ct= λt 0 = ct + λt
(ii) A = λt(1 − θ) ytnt
0 = λt + yt − nt
(iii) Rt = θ ytkt−1
+ 1 − δ 0 = −RRt + θ yk
(
yt − kt−1
)
(iv) yt = γezt kθ
t−1n1−θ
t 0 = −yt + zt + θkt−1 + (1 − θ)nt
(v) ct + kt = yt + (1 − δ)kt−1 0 = −cct − k kt + y yt + (1 − δ)k kt−1
(vi) λt = βEt [λt+1Rt+1] 0 = −λt + Et [λt+1 + Rt+1]
(vii) zt+1 = ρzt + ǫt+1 zt+1 = ρzt + ǫt+1
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Alternative representations
A representation of the problem
There is an endogenous state vector xt , size m × 1, a list ofother endogenous variables yt , size n × 1, and a list ofexogenous stochastic processes zt , size k × 1. The equilibriumrelationships between these variables are
0 = Axt + Bxt−1 + Cyt + Dzt (11)
0 = Et [Fxt+1 + Gxt + Hxt−1 + Jyt+1 + Kyt + Lzt+1 + Mzt ]
zt+1 = Nzt + ǫt+1; Et [ǫt+1] = 0,
where it is assumed that C is of size l × n, l ≥ n and of rank n,that F is of size (m + n − l) × n, and that N has only stableeigenvalues.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Alternative representations
Example: RBC
Variables:
xt = [capital] = [kt ], yt =
Lagrangianconsumption
outputlabor
interest
=
λt
ct
yt
nt
Rt
andzt = [technology] = [zt ]
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Alternative representations
Example: RBC
Matrices:
A =
0000−k
, B =
00
−θ yk
θ(1 − δ)k
, C =
1 1 0 0 01 0 1 −1 00 0 θ y
k0 −R
0 0 −1 (1 − θ) 00 −c y 0 0
andF = [0], G = [0], H = [0], J = [1, 0, 0, 0, 1],
K = [−1, 0, 0, 0, 0], L = [0], M = [0], N = [ρ]
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Alternative representations
Alternative representations 1
Redefine the system as
xt =
[
xt
yt
]
, F =
[
0 0F J
]
, G =
[
A CG K
]
,
H =
[
B 0H 0
]
, L =
[
0L
]
, M =
[
DM
]
,
The system can then be rewritten as a second-orderstochastic matrix difference equation,
0 = Et
[
Fxt+1 + Gxt + Hxt−1 + Lzt+1 + Mzt
]
zt = Nzt−1 + ǫt ; Et−1[ǫt ] = 0 + ǫt
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Alternative representations
Alternative representations 2
Redefine the system as
xt =
xt
yt
zt
, ǫt =
00ǫt
,
F =
0 0 0F J L0 0 0
, G=
A C DG K M0 0 −Ik
, H =
B 0 0H 0 00 0 N
The system can then be rewritten as a second-orderstochastic matrix difference equation,
0 = Et
[
Fxt+1 + Gxt + Hxt−1
]
+ ǫt
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Alternative representations
Alternative Representations 3
E.g. per stacking,
xt =
[
xt
xt−1
]
etc., one can even rewrite the system as a first-orderstochastic matrix difference equation,
0 = Et [Fxt+1 + Gxt ] + ǫt
Here, one needs to keep in mind, that some entries in xt
are predetermined, i.e. already fixed as of t − 1.
This representation is often used, e.g. in Blanchard-Kahn,Farmer, many others.
Prof. H. Uhlig IAMA: Lecture 5
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The solution strategyHansens benchmark Real Business Cycle Model
The solution stepsRepresentations
Alternative representations
Various Representations 4
Various representations appear in the literature.
Which representation is most convenient? That dependson the solution approach.
The “complicated” first representation has the advantageof focussing on a small numer of state variables.
Prof. H. Uhlig IAMA: Lecture 5