Discrete Economic Dynamics
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Transcript of Discrete Economic Dynamics
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Dynamic Macroeconomic Theory
Thomas LuxUniversity of Kiel
Prof. Dr. Thomas Lux, [email protected]
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In this lecture: Focus is mainly a deterministic dynamic system without stochasticshocks
However: Adding small amounts of noise does mostly not change the qualitativeoutcome of the dynamics so that in theoretical purpose the analysis of the deterministicanalogue is appropriate.
Prof. Dr. Thomas Lux, [email protected]
Dynamic Macroeconomic Theory
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Variants of dynamic equations:
1) difference equation:
equivalently:
(2) differential equation:
but there might be also higher derivatives:
(3) mixed difference differential equations:
higher derivatives, more lags are possible
nonlinear equations:
Prof. Dr. Thomas Lux, [email protected]
( )tgyayay ttt +++= ...2211
( ) ( )tgyayay ttyy
t
tt
...1 2211
1
++=
=
( )tyyf tt ,...,, 21 =
( )tyhdt
dyt
t ,=
( ) ( ) ( )tgyayayaya nnnn =++++
1
1
10 ...
( ) ( ) ( ) ( ) ( )tgwtybtybwtyatya =+++ 1010
( ) = nttt yyyg ,...,, 1
Dynamic Macroeconomic Theory
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1.1.1. Mathematical Background
First-order linear difference equation:
with time-dependent function this is called a non homogenous equation
Homogeneous equation :
or:
Solution via iteration:
Prof. Dr. Thomas Lux, [email protected]
( )tgycyc tt =+ 101
( )tg
0
0
1
101
=+
=+
tt
tt
byy
ycyc
1
0,c
cb=
( ) etc.02
01
0
byby
bAbyy
Ay
=
==
= ( )
( ) Ab
yby
t
t
t
=
=
0
1.1 First and Second Order DifferenceEquation
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is a general solution as it satisfies
irrespective of A
to fix A, any known function value could be used, e.g.
types of dynamic behavior:
monotonic convergence
oscillatory convergence
monotonic divergence
oscillatory divergence
( )Aby tt =
( )
( ) 01
1=+
tt y
tt
y
AbbAb
t*
t
(-b)
y* AAbyty == *)(**)*,(
:1
:1
:01
:10
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Gandolfo,1997. Fig.3.1
1.1 First and Second Order DifferenceEquation
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( )tgAbycAbyc tt =+++ 101 )()(
Solution of the non-homogeneous equation:
General principle: Solution of non-homogeneous equation consists of solution of
homogeneous equation plus so-called particular solution
Hence: solution for
Particular solution can often be interpreted as a steady state equilibrium in economicmodels
It can be easily checked: if
is also a solution!
( ) =+ tgycyc tt 101 yAby t
t += )(
( )tgycyc =+ 01
1.1 First and Second Order DifferenceEquation
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Determination of particular solutions:
Try a function with the same form of g(t) but with undetermined constants
Substitute into non-homogeneous equation and determine the coefficients
Examples:
General solution:
Prof. Dr. Thomas Lux, [email protected]
( )
01
01
)1(
cc
ayacc
yatg
+===+
==
:try
101
0 )(cc
aA
c
cy
t
t ++=
1.1 First and Second Order DifferenceEquation
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Prof. Dr. Thomas Lux, [email protected]
( )
t
t
ttt
tt
dcdc
Bdy
cdc
BdC
BdCcCdcd
BdCdcCdc
CdydBtg
0101
01
1
101
,
0)(
: try)2(
+=
+=
=+
=+
==
1.1 First and Second Order DifferenceEquation
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yAyty +== 00 )0,(
Determination of the constant A:
for example, for:
Knowledge of leads to:
Prof. Dr. Thomas Lux, [email protected]
( )....
sincos: trysincos)3( 21 ttytBtBtg +=+=
yAccy
t
t += )(1
0
yyyc
cyyyA
t
t +== )()( 01
00
1.1 First and Second Order DifferenceEquation
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Second-Order Linear Difference Equations
General form:
Homogeneous equation:
or:
)(c 20112 tgyycyc ttt =++
2
)4(
0)(
0
2/1
2
2
12,1
2
1
22-t
2-t
2
1-t
1
t
1aaa
aa
aa
=
=++
=++
In analogy to first-order equations: try a function like:t
ty
2
0
2
1
c
c2c
c
12211
20112
a,a,0a0c
===++=++
ttt
ttt
yyayyycyc
characteristic equation
two solutions
1.1 First and Second Order DifferenceEquation
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Cases:
(1) real-valued solutions:
Combine both solution into:
two constants, because two initial conditions are needed to solve a second-orderequation
Convergence requires:
(2) identical solutions:
Since one only has one solution, one tests as a second solution
Second-Order Linear Difference Equations
04- 22
1>= aa
ttt AAy 2211 +=
1,1 21
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Prof. Dr. Thomas Lux, [email protected]
(3) complex numbers with imaginary part:< 0
Try a solution:
would be real-value if A, A were complex conjugate!
tt
t i(Ai(Ay )) ++=
ty
212
12121 42
11
2
1 /, )aa(-ai ==
Second-Order Linear Difference Equations
S d O d Li Diff E i
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Prof. Dr. Thomas [email protected]
Coordinate transformation to polar coordinates:
modulus or absolute value
we can write:
2122
222
sin,cos
/)(r
rrr
+=
+===
tt
t )ir(rA)ir(rAy sincossincos ++=
Re()
Im()
r
Second-Order Linear Difference Equations
S d O d Li Diff E ti
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Using de Moivres theorem:
assume:
real numbers
Potential for true oscillatory motion already with two lags!period: 2/ , amplitude: depends on r
[ ]
[ ]iAAAAAA
tAtAr
tiAAtAArtitrAt)itrAy
nin)i(
t
t
tt
t
n
)(,
)sin()cos((
)sin()()cos()()sin()(cos()sin()(cos(
)sin()cos(sincos
21
21
=+
+=
++=++=
=
==+
=+=
biAAaAA
ibaAibaA
2)(,2
,
Second-Order Linear Difference Equations
S d O d Li Diff E ti
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Prof. Dr. Thomas Lux, [email protected]
since:
explosive > constant oscillations if = 1
dampened 1 can be excluded by the condition: 1,2< 1
0)1(,0)1(
1)1(,1)1( 2121
>>
+=++=
ff
aafaaf
212)( aaf ++=
f()
1-1
Second-Order Linear Difference Equations
Second Order Linear Difference Equations
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Stability Conditions (sufficient and necessary):
Stability can be checked without explicit solution of difference equation!
Prof. Dr. Thomas Lux, [email protected]
( )
( ) 011)3(
011)2(
011)1(
21
2221
21
>+=
>++=
aaf
aa
aaf
Second-Order Linear Difference Equations
Second Order Linear Difference Equations
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Solution of non-homogeneous equation: add particular solution like before
example:
y
cccgttt
ttt
AAy
gbcbcbcby
gycycyc
2102211
012
20112
:
++
++=
=++=
=++
Second-Order Linear Difference Equations
Determination of constants
via twoinitial conditions
example: lead to
,
21
22111210
10
,
),1(),0(
AA
yAAyyAAy
ytyt
++=++=
==
1 1 2 Economic Application: Multiplier
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If second-order difference equation potentially generates sinusoidal fluctuations
business cycle explanation
Two lagged adjustment are in principle sufficient to generate economicfluctuation
First model of the business cycle: Samuelson, 1939
Prof. Dr. Thomas Lux, [email protected]
1.1.2 Economic Application: MultiplierAccelerator Interaction
:0
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Model structure:
consumption function with time lag, 0 < b< 1(multiplier)
investment
constant part: public expenditures
induce investment: accelerator
goods market equilibrium
1.1.2 Economic Application: MultiplierAccelerator Interaction
ttt
ttt
t
ttt
t-t
IC Y
CCkI
GI
III
bYC
+=
=
=
+=
=
)5(
)()4(
)3(
)2(
)1(
1
1
1.1.2 Economic Application: Multiplier
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0)1(
1
)1(
)1(
)(
)(
""""
2
21
211
11
21
=++
=
++=
=++
++=
=++=
aa
t
t-t-t
t-t-t-
ttt-t
bkkb
b
GY
YbkYkbYYY
GbkYYkbY
GYYkbbY
GCCkbYY
particular solution: try
stability: characteristic equation:
1.1.2 Economic Application: MultiplierAccelerator Interaction
Combine the equations:
1.1.2 Economic Application: Multiplier-
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Stability conditions:o.k.
product of the roots
o.k.
Goods market equilibrium is stable, if
Oscillations:
1.1.2 Economic Application: MultiplierAccelerator Interaction
2
22
)1(
4if0
4)1(
/11
0)1(1
(?)01
010)1(1
k
kb
bkkb
kbkb
bkkb
bk
bbkkb
+
>
>++
1.1 First and Second Order Difference
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Gandolfo,1997. Fig.6.1
1.1 First and Second Order DifferenceEquation
Prof. Dr. Thomas Lux, WSP1 Room 507, [email protected], +49 431 880-3661
1.1.2 Economic Application: Multiplier
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[ ]{ }
0)1()1)(1()1(
)1(
0)1()1)(1()1()1(
)1()1()1)(1()1(
)1(
)1(
2
20
20
22
021
0
>+++++
+=
=++++++
+=+++++
+=
+=
t
t
tttt
t
t
gbkgkbg
gGy
gGbkgkbgAg
gGgbkAgkbgA
gAy
gGG
fluctuations around growth path: assume
for particular solution: try
pp pAccelerator Interaction
1.1.3 A First Look at Anticipation:
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One finds that is valid particular solution since
it satisfies the difference equation
Assume g(t) is not a known function, but a sequence of (stochastic) realizations ofexogenous variables
different approach for determination of particular solution: operational method
use lag operator
Application to first-order equation:
pBackward and Forward Solutions
)1(
)1(
1
1
tt
tt
tt-t
xbLy
xybL
xbyy
+=
=+
=+
=
===
0 0
)()(i i
it
i
t
iixbxLby t
1
1
1 ,, +
=== ttnttn
tt yyLyyLyLy
1.1.3 A First Look at Anticipation:
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This holds because:
Operator expansion like Taylor-series expansion about 0!
Note: these sequences converge only if |b| < 1 or || < 1, i.e. if the system is stable
If |b| > 1, consider:
which also fulfills the difference equation and is bounded since |1/b| < 1.
=
=+++=0
221 1)1i
iiL...LLL-(
pBackward and Forward Solutions
it
i
i
bt
i
i
i
bt xxLy +
=
= == 11
1
1
)()(
1.1.3 A First Look at Anticipation:
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Particular solution here = geometrically declining sum of all past or future values of x0depending on whether the equation is stable or unstable
alternative expansion:
Derivation, reformulate and develop the second term in a Taylor series of
Application: forward looking models are typically mathematically unstable, but can berepresented via second type of solution concept for particular solution.
Backward and Forward Solutions
)()11
11
=
=i
ii
LL(
11111 )1()1 =L
LL(
1.1.3 A First Look at Anticipation:
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Illustration: Cobweb model
equilibrium price is particular solution,
since b < 0: improper oscillations
stable if supply should have smaller slope than demand
Backward and Forward Solutions
1
11
1
1
1
111
111
)(
,
bb
aa
b
bAp
b
aap
b
bp
aapbbpSD
pbaSbpaD
t
t
tt
tttt
tttt
+=
=
==
+=+=
11 ++=
=+++
=+++
=+++
==
+
++
xppp
xppp
pppp
tttt
tttt
t
e
tt
e
tin a deterministic context: perfect foresight:
homogeneous part leads to characteristic equation:
Discriminant:
Since a2=1stability conditions are violated; note:one stable, one unstable
Backward and Forward Solutions
1.1.3 A First Look at Anticipation:Backward and Forward Solutions
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Particular solution: Operational method for knownsequence of
for second-order equations:
Denote by F = L-1the forward operator:
with F1, F2roots of the polynomial which coincide with1, 2
)(1
1
1
)1(
))((
21
2
2221
2
21
2
21
2211
21
FFFF
tt
tt
tttt
aFaFLLaLa
XLaLa
y
XyLaLa
Xyayay
=
++=++
++=
=++
=++
Backward and Forward Solutions
1
1
tt xX
1.1.3 A First Look at Anticipation:Backward and Forward Solutions
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it
i
it
i
i
tLtLt
LLLL
XX
XXy
LL
LLFLLF
FFLLaLa
=
=
+=
+=
=
=+=
=
==
==++
0
221
0
11
11
2
111)1)(1(
1
21
21
212
21
,
)1)(1(
))((
))((1
2
2
1
1
21
2
21
1
2
2
1
1
21
Hence:
and
hence:
backward solution
Backward and Forward Solutions
1.1.3 A First Look at Anticipation:Backward and Forward Solutions
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or
In the RE cobweb case: backward solution for stable root, forward solution for unstableroot.
particular solution is geometrically weighted average of all past, present and (known)future shocks.
ttt
t
it
i
iit
i
i
it
i
iit
i
it
it
i
iit
i
it
pAAp
XX
XXp
XXy
i
i
++=