This document discusses various time series econometric models and methods for analyzing the relationship between variables, including: 1) Vector AutoRegressive (VAR) and Vector Error Correction (VECM) models treat all variables symmetrically without distinguishing between independent and dependent variables. 2) Unit root tests, cointegration tests, and checking for stationarity are important prerequisites for time series econometric models. 3) The steps of Vector Error Correction modeling include testing for stationarity, cointegration, selecting the optimal lag length, and estimating the VECM.

1. Vector Error
Correction Model

2. Model VAR/VECM
Model VAR/VECM
memperlakukan seluruh
variabel secara simetris
tanpa mempersalahkan
variabel independen dan
dependen (Gujarati:
2003); atau dengan kata
lain model ini
memperlakukan seluruh
variabel sebagai variabel
endogen.

3. Uji Akar Unit
• Stasioneritas merupakan salah
satu prasyarat penting dalam
model ekonometrika untuk data
runtut waktu (time series).
• Data stasioner adalah data yang
menunjukkan mean, varians dan
autovarians (pada variasi lag)
tetap sama pada waktu kapan
saja data itu dibentuk atau
dipakai, artinya dengan data
yang stasioner model time series
dapat dikatakan lebih stabil.
• Apabila data yang digunakan
dalam model ada yang tidak
stasioner, maka data tersebut
dipertimbangkan kembali
validitas dan kestabilannya.

4. Uji Kointegrasi
• Uji kointegrasi perlu
dilakukan untuk mengetahui
apakah data mempunyai
hubungan jangka panjang
(terkointegrasi).
• Hubungan saling
mempengaruhi juga dapat
dilihat dari kointegritas yang
terjadi antar variabel itu
sendiri dan menentukan
model yang akan diestimasi,
apakah menggunakan VAR
biasa atau VAR – Vector
Error Correction Model
(VAR-VECM).

5. VAR
• Penelitian dilakukan dengan metode
deskriptif kuantitatif menggunakan Regresi
Vector Autoregression (VAR) untuk
mengetahui keterkaitan antar variabel dan
kontribusi masing-masing variabel terhadap
perubahan variabel lainnya.
• Walaupun ada metode lain yang lebih
sederhana untuk mengetahui keterkaitan
antar variabel, misalnya dengan Ordinary
Least Squares (OLS) namun tidak seperti
dengan VAR.
• VAR selain dapat digunakan untuk analisis
keterkaitan antar variabel, VAR juga dapat
melihat pergerakan respon dan variabilitas
seluruh variabel selama periode penelitian,
yaitu melalui hasil impulse response dan
variance decomposition baik dengan grafik
maupun tabel.

6. VECM
• Vector Error Correction Model
(VECM) adalah VAR terestriksi yang
digunakan untuk variabel yang non-
stasioner tetapi memiliki potensi
untuk terkointegrasi.
• Setelah dilakukan pengujian
kointegrasi pada model yang
digunakan maka dianjurkan untuk
memasukkan persamaan kointegrasi
ke dalam model yang digunakan.
• Pada data time series kebanyakan
memiliki tingkat stasioneritas pada
first difference atau I(1).
• VECM sering disebut sebagai desain
VAR bagi series non-stasioner yang
memiliki hubungan kointegrasi.
Dengan demikian, dalam VECM
terdapat speed of adjustment dari
jangka pendek ke jangka panjang

7. Analisis Impulse
Response
• Analisis Impulse Response dilakukan
untuk melihat respon suatu variabel
ketika terjadi kejutan/ goncangan pada
variabel lainnya.
• Secara individual koefisien di dalam
model VAR/VECM sulit diinterpretasikan
maka para ahli ekonometrika
menggunakan analisis Impulse
Response.
• Analisis Impulse Response ini melacak
respon dari variabel endogen di dalam
sistem VAR karena goncangan (shock)
atau perubahan di dalam variabel
gangguan (e).
• Impulse Response merupakan hasil
estimasi VAR/VECM yang dapat
digambarkan dengan grafik (graph) atau
tabel, dengan melihat graph atau tabel
impulse response kita dapat melihat
seberapa besar respon variabel terhadap
kejutan/ goncangan sebesar satu standar
deviasi (S.D) dari variabel - variabel di

8. Analisis variance
decomposition
• Analisis variance decomposition
dilakukan untuk mengetahui
variabel - variabel mana yang
mempunyai peran yang relatif
penting dalam perubahan
variabel itu sendiri maupun
variabel lainnya.
• Sedangkan analisis variance
decomposition ini
menggambarkan relatif
pentingnya setiap variabel di
dalam kontribusi persentase
varian setiap variabel karena
adanya perubahan variabel
tertentu di dalam sistem
VAR/VECM.

9. Tahapan Vector Error
Correction Model

10. Uji Stasioneritas Data GDP
Menggunakan Derajad Fist
Different
Null Hypothesis: D(GDP) has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic - based on SIC, maxlag=5)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -5.800745 0.0005
Test critical values: 1% level -4.416345
5% level -3.622033
10% level -3.248592
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(GDP,2)
Method: Least Squares
Date: 12/26/16 Time: 16:26
Sample (adjusted): 1988 2010
Included observations: 23 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
D(GDP(-1)) -1.256134 0.216547 -5.800745 0.0000
C -0.128365 2.342936 -0.054788 0.9569
@TREND("1986") 0.011725 0.160532 0.073036 0.9425
R-squared 0.627234 Mean dependent var 0.097000
Adjusted R-squared 0.589957 S.D. dependent var 7.975109
S.E. of regression 5.106830 Akaike info criterion 6.220142
Sum squared resid 521.5943 Schwarzcriterion 6.368250
Log likelihood -68.53164 Hannan-Quinn criter. 6.257391
F-statistic 16.82645 Durbin-Watson stat 2.148797
Prob(F-statistic) 0.000052

11. Uji Stasioneritas Data Inflasi
Menggunakan Derajad Fist
Different
Null Hypothesis: D(INF) has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 1 (Automatic - based on SIC, maxlag=5)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -5.634037 0.0008
Test critical values: 1% level -4.440739
5% level -3.632896
10% level -3.254671
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(INF,2)
Method: Least Squares
Date: 12/26/16 Time: 16:29
Sample (adjusted): 1989 2010
Included observations: 22 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
D(INF(-1)) -1.953261 0.346689 -5.634037 0.0000
D(INF(-1),2) 0.446797 0.211076 2.116758 0.0485
C 2.560159 6.762509 0.378581 0.7094
@TREND("1986") -0.201108 0.453594 -0.443366 0.6628
R-squared 0.739927 Mean dependent var 0.070525
Adjusted R-squared 0.696582 S.D. dependent var 24.44025
S.E. of regression 13.46253 Akaike info criterion 8.200663
Sum squared resid 3262.315 Schwarz criterion 8.399035
Log likelihood -86.20730 Hannan-Quinn criter. 8.247394
F-statistic 17.07045 Durbin-Watson stat 2.208962
Prob(F-statistic) 0.000017

12. Uji Stasioneritas Data
Pemberian Kredit
Menggunakan Derajad Fist
Different
Null Hypothesis: D(PK) has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic - based on SIC, maxlag=5)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -3.894911 0.0292
Test critical values: 1% level -4.416345
5% level -3.622033
10% level -3.248592
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(PK,2)
Method: Least Squares
Date: 12/26/16 Time: 16:32
Sample (adjusted): 1988 2010
Included observations: 23 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
D(PK(-1)) -0.885081 0.227240 -3.894911 0.0009
C 4.832443 1.951936 2.475718 0.0224
@TREND("1986") -0.337412 0.133173 -2.533636 0.0198
R-squared 0.431936 Mean dependent var -0.168830
Adjusted R-squared 0.375130 S.D. dependent var 3.897393
S.E. of regression 3.080839 Akaike info criterion 5.209389
Sum squared resid 189.8314 Schwarzcriterion 5.357497
Log likelihood -56.90797 Hannan-Quinn criter. 5.246637
F-statistic 7.603663 Durbin-Watson stat 1.938351
Prob(F-statistic) 0.003499

13. Uji Stasioneritas Data Suku
Bunga Deposito
Menggunakan Derajad Fist
Different
Null Hypothesis: D(SBD) has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 1 (Automatic - based on SIC, maxlag=5)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -5.103868 0.0025
Test critical values: 1% level -4.440739
5% level -3.632896
10% level -3.254671
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(SBD,2)
Method: Least Squares
Date: 12/26/16 Time: 16:37
Sample (adjusted): 1989 2010
Included observations: 22 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
D(SBD(-1)) -1.574804 0.308551 -5.103868 0.0001
D(SBD(-1),2) 0.457196 0.210278 2.174248 0.0433
C 1.203804 3.141517 0.383192 0.7061
@TREND("1986") -0.138791 0.211667 -0.655703 0.5203
R-squared 0.636147 Mean dependent var -0.145227
Adjusted R-squared 0.575505 S.D. dependent var 9.578100
S.E. of regression 6.240446 Akaike info criterion 6.662946
Sum squared resid 700.9770 Schwarzcriterion 6.861317
Log likelihood -69.29241 Hannan-Quinn criter. 6.709676
F-statistic 10.49019 Durbin-Watson stat 1.958128
Prob(F-statistic) 0.000323

14. Uji Stasioneritas Data Suku Bunga
Pinjaman
Menggunakan Derajad Fist
Different
Null Hypothesis: D(SBP) has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 1 (Automatic - based on SIC, maxlag=5)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -4.962859 0.0034
Test critical values: 1% level -4.440739
5% level -3.632896
10% level -3.254671
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(SBP,2)
Method: Least Squares
Date: 12/26/16 Time: 16:39
Sample (adjusted): 1989 2010
Included observations: 22 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
D(SBP(-1)) -1.394343 0.280956 -4.962859 0.0001
D(SBP(-1),2) 0.494682 0.206535 2.395153 0.0277
C 0.400430 1.729565 0.231521 0.8195
@TREND("1986") -0.070171 0.116703 -0.601276 0.5552
R-squared 0.595673 Mean dependent var -0.076250
Adjusted R-squared 0.528285 S.D. dependent var 5.013330
S.E. of regression 3.443230 Akaike info criterion 5.473663
Sum squared resid 213.4050 Schwarz criterion 5.672034
Log likelihood -56.21029 Hannan-Quinn criter. 5.520393
F-statistic 8.839476 Durbin-Watson stat 1.958988
Prob(F-statistic) 0.000811

15. Penentuan Lag Lenght
VAR Lag Order Selection Criteria
Endogenous variables: GDP INF PK SBD SBP
Exogenous variables: C
Date: 12/26/16 Time: 18:09
Sample: 1986 2010
Included observations: 24
Lag LogL LR FPE AIC SC HQ
0 -324.9631 NA 601861.9 27.49693 27.74236 27.56204
1 -249.3639 113.3988* 9368.133* 23.28033* 24.75289* 23.67100*
* indicates lag order selected by the criterion
LR: sequential modified LR test statistic (each test at 5% level)
FPE: Final prediction error
AIC: Akaike information criterion
SC: Schwarz information criterion
HQ: Hannan-Quinn information criterion

16. Uji Kausalitas
Granger
Pairwise Granger Causality Tests
Date: 12/26/16 Time: 18:11
Sample: 1986 2010
Lags: 1
Null Hypothesis: Obs F-Statistic Prob.
INF does not Granger Cause GDP 24 4.10796 0.0556
GDP does not Granger Cause INF 1.98216 0.1738
PK does not Granger Cause GDP 24 2.55440 0.1249
GDP does not Granger Cause PK 0.01453 0.9052
SBD does not Granger Cause GDP 24 0.00150 0.9694
GDP does not Granger Cause SBD 2.68521 0.1162
SBP does not Granger Cause GDP 24 0.03127 0.8613
GDP does not Granger Cause SBP 1.25153 0.2759
PK does not Granger Cause INF 24 2.36590 0.1389
INF does not Granger Cause PK 1.15411 0.2949
SBD does not Granger Cause INF 24 1.36402 0.2559
INF does not Granger Cause SBD 5.05910 0.0354
SBP does not Granger Cause INF 24 0.49128 0.4910
INF does not Granger Cause SBP 1.44262 0.2431
SBD does not Granger Cause PK 24 9.96131 0.0048
PK does not Granger Cause SBD 0.06407 0.8026
SBP does not Granger Cause PK 24 8.46963 0.0084
PK does not Granger Cause SBP 0.01032 0.9201
SBP does not Granger Cause SBD 24 0.12975 0.7223
SBD does not Granger Cause SBP 0.85364 0.3660

17. Uji Kointegrasi
Tes
Date: 12/26/16 Time: 18:15
Sample (adjusted): 1988 2010
Included observations: 23 after adjustments
Trend assumption: Linear deterministic trend
Series: GDP INF PK SBD SBP
Lags interval (in first differences): 1 to 1
Unrestricted Cointegration Rank Test (Trace)
Hypothesized Trace 0.05
No. of CE(s) Eigenvalue Statistic Critical Value Prob.**
None * 0.864315 104.8951 69.81889 0.0000
At most 1 * 0.746364 58.95450 47.85613 0.0032
At most 2 0.470084 27.40179 29.79707 0.0922
At most 3 0.343245 12.79595 15.49471 0.1225
At most 4 0.127071 3.125717 3.841466 0.0771
Trace test indicates 2 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized Max-Eigen 0.05
No. of CE(s) Eigenvalue Statistic Critical Value Prob.**
None * 0.864315 45.94065 33.87687 0.0012
At most 1 * 0.746364 31.55270 27.58434 0.0146
At most 2 0.470084 14.60584 21.13162 0.3175
At most 3 0.343245 9.670233 14.26460 0.2345
At most 4 0.127071 3.125717 3.841466 0.0771
Max-eigenvalue test indicates 2 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Cointegrating Coefficients (normalized by b'*S11*b=I):
GDP INF PK SBD SBP
0.101859 0.347800 0.036104 -1.405789 1.650881
0.655306 0.330585 -0.057797 0.529281 -0.681051
-0.259037 -0.164216 -0.143548 0.616334 -0.568446
0.182782 0.003653 0.032160 -0.432349 0.851341
-0.438174 -0.190382 0.032276 0.293175 -0.219863
Unrestricted Adjustment Coefficients (alpha):
D(GDP) 1.727485 1.603654 1.351409 -0.633808 0.520434
D(INF) -2.897671 -6.690577 -3.098971 1.788917 -0.990416
D(PK) -0.412772 0.500306 1.481133 0.753633 -0.497229
D(SBD) -1.235379 -2.402961 -1.605837 -0.170230 -0.704008
D(SBP) -1.062763 -1.199451 -0.929479 -0.302824 -0.317417
1 Cointegrating Equation(s): Log likelihood -215.4924
Normalized cointegrating coefficients (standard error in parentheses)
GDP INF PK SBD SBP
1.000000 3.414535 0.354452 -13.80136 16.20756
(0.30389) (0.16064) (1.64820) (2.00843)
Adjustment coefficients (standard error in parentheses)
D(GDP) 0.175959

18. CARA INTEPRETASI
KOINTEGRASI
1. ketika nilai Trace dan nilai
maximum Eigunvalue > Critical
Value dapat disimpulkan bahwa
semua variabel memiliki
hubungan kointegrasi jangka
panjang
2. Dari hasil analisis di atas dapat
dilihat bahwa nilai Trace dan
nilai maximum Eigunvalue >
Critical Value, sehingga dapat
disimpulkan bahwa semua
variabel memiliki hubungan
kointegrasi jangka panjang

19. Hasil Analisis VECM
Vector Error Correction Estimates
Date: 12/26/16 Time: 19:06
Sample (adjusted): 1989 2010
Included observations: 22 after adjustments
Standard errors in ( ) & t-statistics in [ ]
Cointegrating Eq: CointEq1
DGDP(-1) 1.000000
DINF(-1) 1.726313
(0.14202)
[ 12.1555]
DPK(-1) 0.122653
(0.07408)
[ 1.65564]
DSBD(-1) -5.539141
(0.74085)
[-7.47677]
DSBP(-1) 6.573644
(0.90069)
[ 7.29847]
C -71.98294
Error Correction: D(DGDP) D(DINF) D(DPK) D(DSBD) D(DSBP)
CointEq1 0.404776 -0.824167 -0.066054 -0.345918 -0.276314
(0.16569) (0.53005) (0.17911) (0.22097) (0.11687)
[ 2.44301] [-1.55490] [-0.36879] [-1.56547] [-2.36431]
D(DGDP(-1)) 1.027857 -4.261042 0.602650 -1.582277 -0.621243
(0.73862) (2.36289) (0.79845) (0.98505) (0.52099)
[ 1.39159] [-1.80332] [ 0.75477] [-1.60628] [-1.19243]
D(DINF(-1)) 0.412387 -1.780447 0.207964 -0.675103 -0.166434
(0.43806) (1.40139) (0.47355) (0.58422) (0.30899)
[ 0.94139] [-1.27049] [ 0.43916] [-1.15557] [-0.53864]
D(DPK(-1)) 0.032857 0.275773 0.499861 0.346944 0.194447
(0.18931) (0.60562) (0.20465) (0.25248) (0.13353)
[ 0.17356] [ 0.45535] [ 2.44252] [ 1.37416] [ 1.45617]
D(DSBD(-1)) 0.131888 1.502783 0.100656 1.695484 0.522519
(1.06282) (3.40004) (1.14892) (1.41742) (0.74967)
[ 0.12409] [ 0.44199] [ 0.08761] [ 1.19617] [ 0.69700]
D(DSBP(-1)) -0.197371 -2.383589 0.121075 -2.671894 -0.923470
(1.16759) (3.73519) (1.26218) (1.55715) (0.82357)
[-0.16904] [-0.63814] [ 0.09593] [-1.71589] [-1.12131]
C -0.159871 -0.455559 0.250795 -0.892418 -0.601574
(0.74990) (2.39898) (0.81065) (1.00010) (0.52895)
[-0.21319] [-0.18990] [ 0.30938] [-0.89233] [-1.13731]
R-squared 0.691188 0.622731 0.410246 0.658962 0.699478
Adj. R-squared 0.567664 0.471824 0.174345 0.522547 0.579269
Sum sq. resids 171.6296 1756.460 200.5631 305.2608 85.39055
S.E. equation 3.382599 10.82115 3.656621 4.511177 2.385939
F-statistic 5.595551 4.126576 1.739057 4.830560 5.818852
Log likelihood -53.81391 -79.39680 -55.52760 -60.14801 -46.13477
Akaike AIC 5.528537 7.854254 5.684327 6.104365 4.830434
Schwarz SC 5.875687 8.201404 6.031477 6.451515 5.177584
Mean dependent -0.030506 -0.202817 0.573087 -0.341174 -0.325833
S.D. dependent 5.144459 14.88964 4.024209 6.528666 3.678383
Determinant resid covariance (dof adj.) 554.6528
Determinant resid covariance 81.72673
Log likelihood -204.5204
Akaike information criterion 22.22913
Schwarz criterion 24.21284

20. Impuls Respon
Function
-2
-1
0
1
2
3
4
1 2 3 4 5 6 7 8 9 10
DGDP DINF DPK
DSBD DSBP
Response of DGDP to Cholesky
One S.D. Innovations
-12
-8
-4
0
4
8
1 2 3 4 5 6 7 8 9 10
DGDP DINF DPK
DSBD DSBP
Response of DINF to Cholesky
One S.D. Innovations
-2
0
2
4
6
8
10
1 2 3 4 5 6 7 8 9 10
DGDP DINF DPK
DSBD DSBP
Response of DPK to Cholesky
One S.D. Innovations
-6
-4
-2
0
2
4
1 2 3 4 5 6 7 8 9 10
DGDP DINF DPK
DSBD DSBP
Response of DSBD to Cholesky
One S.D. Innovations
-3
-2
-1
0
1
2
3
1 2 3 4 5 6 7 8 9 10
DGDP DINF DPK
DSBD DSBP
Response of DSBP to Cholesky
One S.D. Innovations

21. Variance
Decomposition
Variance Decomposition of DGDP:
Perio... S.E. DGDP DINF DPK DSBD DSBP
1 3.382599 100.0000 0.000000 0.000000 0.000000 0.000000
2 5.086207 46.74317 46.08823 0.000515 5.596292 1.571791
3 5.947351 34.20393 47.88769 0.509096 13.73104 3.668243
4 6.580950 30.49343 46.70161 1.469278 15.40282 5.932853
5 7.060662 29.47668 47.24860 2.160413 14.76346 6.350834
6 7.406299 32.57496 45.55352 1.976335 13.88307 6.012118
7 7.830543 33.56492 45.75772 1.788670 13.24133 5.647367
8 8.314425 31.06764 47.79236 1.646447 13.84160 5.651946
9 8.760986 28.84915 48.72701 1.487031 14.84437 6.092435
10 9.140411 27.81536 49.03225 1.510797 15.16212 6.479480
Variance Decomposition of DINF:
Perio... S.E. DGDP DINF DPK DSBD DSBP
1 10.82115 86.26126 13.73874 0.000000 0.000000 0.000000
2 13.78525 62.35443 29.43091 2.380177 3.688641 2.145839
3 15.06228 53.33882 29.01183 2.120276 11.09538 4.433697
4 16.69003 52.83647 23.96661 5.443203 11.57934 6.174383
5 18.09412 53.35852 21.61486 8.138057 10.55210 6.336469
6 19.22892 57.32572 19.19901 7.978658 9.641232 5.855380
7 20.34079 59.70302 17.83113 7.658575 9.227567 5.579710
8 21.28296 58.38833 18.21680 7.468313 10.07020 5.856360
9 22.19160 57.00621 17.86609 7.701174 11.01484 6.411692
10 23.14154 56.63786 17.05918 8.429563 11.12903 6.744361
Variance Decomposition of DPK:
Perio... S.E. DGDP DINF DPK DSBD DSBP
1 3.656621 3.939550 2.062750 93.99770 0.000000 0.000000
2 6.380594 2.512207 0.730875 96.05586 0.684916 0.016138
3 9.456593 1.670075 0.683661 96.14433 1.262049 0.239886
4 12.42399 1.590326 0.761834 95.66609 1.574294 0.407460
5 15.07797 1.230612 0.544792 96.32542 1.474409 0.424764
6 17.46758 0.936049 0.418438 96.98181 1.280718 0.382989
7 19.55142 0.765614 0.356074 97.35894 1.178059 0.341317
8 21.45120 0.668938 0.331337 97.50501 1.170100 0.324615
9 23.27048 0.627130 0.336703 97.48846 1.213598 0.334106
10 25.01078 0.596170 0.327674 97.48810 1.240163 0.347894
Variance Decomposition of DSBD:
Perio... S.E. DGDP DINF DPK DSBD DSBP
1 4.511177 76.21048 2.349035 3.857802 17.58268 0.000000
2 6.983478 43.51717 20.37206 5.389668 27.36048 3.360622
3 8.783112 28.29588 22.28578 6.935118 36.74410 5.739125
4 10.14616 27.91946 17.35175 12.42840 35.82480 6.475589
5 11.39042 30.70307 14.72813 16.77355 31.89041 5.904843
6 12.29242 33.84679 13.24312 17.35829 30.26059 5.291209
7 13.17452 34.82415 12.76302 17.27361 30.16709 4.972129
8 14.11875 32.77809 13.36564 17.45285 31.30412 5.099300
9 15.03072 30.99502 13.17132 18.33490 32.11995 5.378809
10 15.88477 30.67312 12.48708 19.66901 31.73534 5.435441
Variance Decomposition of DSBP:
Perio... S.E. DGDP DINF DPK DSBD DSBP
1 2.385939 61.91827 0.719314 13.67798 22.50746 1.176971
2 3.716272 37.23092 18.77930 6.227571 35.80848 1.953726
3 5.089295 19.85201 25.45993 5.315334 45.26054 4.112184
4 5.912345 16.48280 21.04111 9.619308 47.52002 5.336758
5 6.611213 18.12687 18.11677 14.86228 43.81684 5.077237
6 7.111373 21.03349 16.47314 16.20891 41.77168 4.512782
7 7.587358 22.47066 15.86722 16.13581 41.42105 4.105267
8 8.145596 20.91232 16.65045 15.93297 42.45603 4.048229
9 8.720197 19.03802 16.77169 16.41686 43.49800 4.275420
10 9.232627 18.31227 16.14664 17.75491 43.38891 4.397272
Cholesky Ordering: DGDP DINF DPK DSBD DSBP