Assinment 3
Q1
a)
Μ π‘ = −0.609 + 0.7851ππ_πππππππ‘ + 0.246ππ_π€ππππ‘βπ‘ + π’1π‘
ππ_πππ
N=263
R2=0.998
adjR2=0.998
Μ π‘ = −2.146 + 0.312ππ_ππππ‘ + 0.877ππ_ππππ‘ − 0.007π‘π3ππ π‘ + π’2π‘
ππ_πππ
N=288
R2=0.9953
adjR2=0.9952
b)
πStat
Variable name
ln_pce
ln_income
ln_wealth
ln_cpi
ln_ppi
ln_gdp
tb3ms
4.800
5.224
3.153
3.292
3.060
5.944
-1.268
5% Critical
-1.950
-1.950
-1.950
-1.950
-1.950
-1.950
-1.950
Unit Root (not
stationary)
Y
Y
Y
Y
Y
Y
Y
c)
πStat
Variable name
βln_pce
βln_income
βln_wealth
βln_cpi
βln_ppi
βln_gdp
βtb3ms
-4.160
-4.574
-5.092
-2.695
-5.295
-4.310
-5.835
5% Critical
-1.950
-1.950
-1.950
-1.950
-1.950
-1.950
-1.950
Unit Root (not
stationary)
N
N
N
N
N
N
N
d)
H0: u has unit root
H1: u has no unit root
Leval of significance = 0.01
T stat is smaller than we reject the null hypothesis an conclude that there is long run
relationship (cointegration)among these variables.
e)
H0: u has unit root
H1: u has no unit root
Leval of significance = 0.01
T stat is bigger than t stat, so we accept the null hypothesis an conclude that there is no
cointegration among these variables.
f)
Μ π‘ = 0.690 − 0.1054βππ_ππππ‘ + 0.3369βππ_ππππ‘ − 0.01578βπ‘π3ππ π‘ + π’2π‘
βππ_πππ
N=287
R2= 0.5403
adjR2= 0.5354
Q2
a)
Μ π‘ = 0.7109 − 0.6992πΈπΆππ‘−1 πππ π’π − 0.1967πΈπΆππ‘−1 πππ − 0.1074βππ_ππππ‘
βππ_πππ
+ 0.3013βππ_ππππ‘ − 0.01808βπ‘π3ππ π‘ + π’2π‘
N=263
R2= 0.5406
adjR2= 0.5317
Q3
In this case they cannot be positive because the model is shoeing that its growing to fast, so in
order to correct for this the y1 and y2 must be negative or else if they were positive it would
just add to the problem. However if a model had the opposite problem than they could be
positive.