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Stability, Multiplicity, and Sun Spots(Blanchard-Kahn conditions)
Wouter J. Den HaanLondon School of Economics
c© 2011 by Wouter J. Den Haan
August 29, 2011
Multiplicity Getting started General Derivation Examples
Introduction
• What do we mean with non-unique solutions?• multiple solution versus multiple steady states
• What are sun spots?• Are models with sun spots scientific?
Multiplicity Getting started General Derivation Examples
Terminology
• Definitions are very clear• (use in practice can be sloppy)
Model:
H(p+1, p) = 0
Solution:p+1 = f (p)
Multiplicity Getting started General Derivation Examples
Unique solution & multiple steady states
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.60
0.5
1
1.5
2
p
p+1
45o
Multiplicity Getting started General Derivation Examples
Multiple solutions & unique (non-zero) steady state
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
p
p +1
45o
Multiplicity Getting started General Derivation Examples
Multiple steady states & sometimes multiple solutions
34
“Traditional” Pic
ut
ut+1
45o
positive expectations
negative expectations
From Den Haan (2007)
Multiplicity Getting started General Derivation Examples
Large sun spots (around 2000 at the peak)
Multiplicity Getting started General Derivation Examples
Sun spot cycle (almost at peak again)
Multiplicity Getting started General Derivation Examples
Sun spots in economics
• Definition: a solution is a sun spot solution if it depends on astochastic variable from outside system
• Model:
0 = EH(pt+1, pt, dt+1, dt)
dt : exogenous random variable
Multiplicity Getting started General Derivation Examples
Sun spots in economics
• Non-sun-spot solution:
pt = f (pt−1, pt−2, · · · , dt, dt−1, · · · )
• Sun spot:
pt = f (pt−1, pt−2, · · · , dt, dt−1, · · · , st)
st : random variable with E [st+1] = 0
Multiplicity Getting started General Derivation Examples
Sun spots and science
Why are sun spots attractive
• sun spots: st matters, just because agents believe this
• self-fulfilling expectations don’t seem that unreasonable
• sun spots provide many sources of shocks• number of sizable fundamental shocks small
Multiplicity Getting started General Derivation Examples
Sun spots and science
Why are sun spots not so attractive
• Purpose of science is to come up with predictions• If there is one sun spot solution, there are zillion others as well
• Support for the conditions that make them happen notoverwhelming
• you need suffi ciently large increasing returns to scale orexternality
Multiplicity Getting started General Derivation Examples
Overview
1 Getting started
• simple examples
2 General derivation of Blanchard-Kahn solution
• When unique solution?• When multiple solution?• When no (stable) solution?
3 When do sun spots occur?
4 Numerical algorithms and sun spots
Multiplicity Getting started General Derivation Examples
Getting started
•Model: yt = ρyt−1
• infinite number of solutions, independent of the value of ρ
Multiplicity Getting started General Derivation Examples
Getting started
•Model: yt = ρyt−1
• infinite number of solutions, independent of the value of ρ
Multiplicity Getting started General Derivation Examples
Getting started
•Model: yt+1 = ρyt
y0 is given
• unique solution, independent of the value of ρ
Multiplicity Getting started General Derivation Examples
Getting started
•Model: yt+1 = ρyt
y0 is given
• unique solution, independent of the value of ρ
Multiplicity Getting started General Derivation Examples
Getting started
• Blanchard-Kahn conditions apply to models that add as arequirement that the series do not explode
yt+1 = ρytModel:
yt cannot explode
• ρ > 1: nique solution, namely yt = 0 for all t• ρ < 1: many solutions• ρ = 1: many solutions
• be careful with ρ = 1, uncertainty matters
Multiplicity Getting started General Derivation Examples
State-space representation
Ayt+1 + Byt = εt+1
E [εt+1|It] = 0
yt : is an n× 1 vectorm ≤ n elements are not determined
some elements of εt+1 are not exogenous shocks but prediction errors
Multiplicity Getting started General Derivation Examples
Neoclassical growth model and state space representation
(exp(zt)kα
t−1 + (1− δ)kt−1 − kt)−γ
=
E
[β (exp(zt+1)kα
t + (1− δ)kt − kt+1)−γ
×(
α exp (zt+1) kα−1t + 1− δ
) ∣∣∣∣∣ It
]
or equivalently without E[·](exp(zt)kα
t−1 + (1− δ)kt−1 − kt)−γ
=
β (exp(zt+1)kαt + (1− δ)kt − kt+1)
−γ
×(
α exp (zt+1) kα−1t + 1− δ
)+eE,t+1
Multiplicity Getting started General Derivation Examples
Neoclassical growth model and state space representation
Linearized model:
kt+1 = a1kt + a2kt−1 + a3zt+1 + a4zt + eE,t+1
zt+1 = ρzt + ez,t+1
k0 is given
• kt is end-of-period t capital• =⇒ kt is chosen in t
Multiplicity Getting started General Derivation Examples
Neoclassical growth model and state space representation
1 0 a30 1 00 0 1
kt+1kt
zt+1
+ a1 a2 a4−1 0 00 0 −ρ
ktkt−1
zt
= eE,t+1
0ez,t+1
Multiplicity Getting started General Derivation Examples
Dynamics of the state-space system
Ayt+1 + Byt = εt+1
yt+1 = −A−1Byt +A−1εt+1
= Dyt +A−1εt+1
Thus
yt+1 = Dty1 +t+1
∑l=1
Dt+1−lA−1εl
Multiplicity Getting started General Derivation Examples
Jordan matrix decomposition
D = PΛP−1
• Λ is a diagonal matrix with the eigen values of D• without loss of generality assume that |λ1| ≥ |λ2| ≥ · · · |λn|
Let
P−1 =
p̃1...
p̃n
where p̃i is a (1× n) vector
Multiplicity Getting started General Derivation Examples
Dynamics of the state-space system
yt+1 = Dty1 +t+1
∑l=1
Dt+1−lA−1εl
= PΛtP−1y1 +t+1
∑l=1
PΛt+1−lP−1A−1εl
Multiplicity Getting started General Derivation Examples
Dynamics of the state-space system
multiplying dynamic state-space system with P−1 gives
P−1yt+1 = ΛtP−1y1 +t+1
∑l=1
Λt+1−lP−1A−1εl
or
p̃iyt+1 = λti p̃iy1 +
t+1
∑l=1
λt+1−li p̃iA−1εl
recall that yt is n× 1 and p̃i is 1× n. Thus, p̃iyt is a scalar
Multiplicity Getting started General Derivation Examples
Model
1 p̃iyt+1 = λti p̃iy1 +∑t+1
l=1 λt+1−li p̃iA−1εl
2 E[εt+1|It] = 03 m elements of y1 are not determined
4 yt cannot explode
Multiplicity Getting started General Derivation Examples
Reasons for multiplicity
1 There are free elements in y1
2 The only constraint on eE,t+1 is that it is a prediction error.
• This leaves lots of freedom
Multiplicity Getting started General Derivation Examples
Eigen values and multiplicity
• Suppose that |λ1| > 1• To avoid explosive behavior it must be the case that
1 p̃1y1 = 0 and
2 p̃1A−1εl = 0 ∀l
Multiplicity Getting started General Derivation Examples
How to think about #1?
p̃1y1 = 0
• Simply an additional equation to pin down some of the freeelements
• Much better: This is the policy rule in the first period
Multiplicity Getting started General Derivation Examples
How to think about #1?
p̃1y1 = 0
Neoclassical growth model:
• y1 = [k1, k0, z1]T
• |λ1| > 1, |λ2| < 1, λ3 = ρ < 1• p̃1y1 pins down k1 as a function of k0 and z1
• this is the policy function in the first period
Multiplicity Getting started General Derivation Examples
How to think about #2?
p̃1A−1εl = 0 ∀l
• This pins down eE,t as a function of εz,t
• That is, the prediction error must be a function of thestructural shock, εz,t, and cannot be a function of other shocks,
• i.e., there are no sunspots
Multiplicity Getting started General Derivation Examples
How to think about #2?
p̃1A−1εl = 0 ∀l
Neoclassical growth model:
• p̃1A−1εt says that the prediction error eE,t of period t is a fixedfunction of the innovation in period t of the exogenous process,ez,t
Multiplicity Getting started General Derivation Examples
How to think about #1 combined with #2?
p̃1yt = 0 ∀t
• Without sun spots• i.e. with p̃1A−1εt = 0 ∀t
• kt is pinned down by kt−1 and zt in every period.
Multiplicity Getting started General Derivation Examples
Blanchard-Kahn conditions
• Uniqueness: For every free element in y1, you need one λi > 1• Multiplicity: Not enough eigenvalues larger than one• No stable solution: Too many eigenvalues larger than one
Multiplicity Getting started General Derivation Examples
How come this is so simple?• In practice, it is easy to get
Ayt+1 + Byt = εt+1
• How about the next step?
yt+1 = −A−1Byt +A−1εt+1
• Bad news: A is often not invertible• Good news: Same set of results can be derived
• Schur decomposition (See Klein 2000)
Multiplicity Getting started General Derivation Examples
How to check in Dynare
Use the following command after the model & initial conditions part
check;
Multiplicity Getting started General Derivation Examples
Example - x predetermined - 1st order
xt−1 = Et [φxt + zt+1]
zt = 0.9zt−1 + εt
• |φ| > 1 : Unique stable fixed point• |φ| < 1 : No stable solutions; too many eigenvalues > 1
Multiplicity Getting started General Derivation Examples
Example - x predetermined - 2nd order
φ2xt−1 = Et [φ1xt + xt+1 + zt+1]
zt = 0.9zt−1 + εt
• φ1 = −2.25, φ2 = −0.5 : Unique stable fixed point(1+ φ1L− φ2L2)x = (1− 2L)(1− 1
4L)• φ1 = −3.5, φ2 = −3 : No stable solution; too manyeigenvalues > 1(1+ φ1L− φ2L2)x = (1− 2L)(1− 1.5L)
• φ1 = −1, φ2 = −0.25 : Multiple stable solutions; too feweigenvalues > 1(1+ φ1L− φ2L2)x = (1− 0.5L)(1− 0.5L)
Multiplicity Getting started General Derivation Examples
Example - x not predetermined - 1st order
xt = Et [φxt+1 + zt+1]
zt = 0.9zt−1 + εt
• |φ| < 1 : Unique stable fixed point• |φ| > 1 : Multiple stable solutions; too few eigenvalues > 1
Multiplicity Getting started General Derivation Examples
References• Blanchard, Olivier and Charles M. Kahn, 1980,The Solution ofLinear Difference Models under Rational Expectations,Econometrica, 1305-1313.
• Den Haan, Wouter J., 2007, Shocks and the Unavoidable Road toHigher Taxes and Higher Unemployment, Review of EconomicDynamics, 348-366.• simple model in which the size of the shocks has long-termconsequences
• Farmer, Roger, 1993, The Macroeconomics of Self-FulfillingProphecies, The MIT Press.• textbook by the pioneer
• Klein, Paul, 2000, Using the Generalized Schur form to Solve aMultivariate Linear Rational Expectations Model• in case you want to do the analysis without the simplifyingassumption that A is invertible