harga saham negara importir minyak di kawasan Asia Tenggara yakni indeks JKSE di Indonesia, variabel makroekonomi tidak dominan mempengaruhi
pergerakan JKSE, namun diantara ketiga variabel makroekonomi yang diuji, peran inflasi lebih dominan. Pergerakan Strait Times di Singapura didominasi
oleh nilai tukar, hal ini mengindikasikan bahwa arus modal yang berada di Singapura memiliki peran dalam menggerakan indeks STI. Sedangkan pergerakan
SET di Thailand didominasi oleh inflasi. Perubahan harga minyak dunia kemungkinan tidak menjadi salah satu sebab dominannya inflasi dalam
pergerakan SET karena peran harga minyak dunia sendiri tidak terlalu besar. Untuk indeks harga saham negara importir minyak di kawasan Asia Timur yakni
BSE di India, variabel makroekonomi tidak terlalu dominan mempengaruhi pergerakan indeks BSE. Sementara untuk indeks Nikkei di Jepang dan indeks
KOSPI di Korea Selatan, variabel makroekonomi yang cukup dominan mempengaruhi indeks Nikkei adalah inflasi. Untuk indeks harga saham negara
importir minyak di kawasan Eropa yakni FTSE di Inggris, DAX di Jerman, CAC di Perancis, dan SMI di Swiss menunjukan bahwa peran variabel makroekonomi
tidak terlalu dominan. Untuk indeks harga saham negara eksportir minyak di kawasan Amerika yakni pergerakan indeks GSPT di Kanada sangat didominasi
oleh variabel suku bunga. Sedangkan pergerakan indeks Mexican Bolsa tidak terlalu dominasi oleh variabel makroekonomi. Untuk indeks harga saham negara
importir minyak lainnya di kawasan Amerika yakni indeks Bovespa di Brasil, pergerakan indeks harga saham ini sangat didominasi oleh suku bunga dan nilai
tukar. Sedangkan indeks SP 500 di Amerika Serikat didominasi oleh variabel inflasi.
5.2 Saran
Dalam kaitannya dengan penelitian mengenai pengaruh harga minyak dunia dan variabel makroekonomi terhadap indeks harga saham maka saran-saran
yang dapat diberikan adalah: 1.
Otoritas bursa saham, baik pada negara eksportir dan importir minyak di kawasan Asia Tenggara, Asia Timur, Eropa, dan Amerika, dapat menjadikan
pergerakan harga minyak mentah dunia sebagai indikator kondisi perekonomian global.
2. Para investor pasar modal, khususnya investor pasar saham perlu
mempertimbangkan faktor eksternal yang cukup berpengaruh terhadap pergerakan indeks harga saham. karena hal tersebut akan berpengaruh pada
kinerja perusahaan yang pada akhirnya akan mempengaruhi harga saham perusahaan.
5.3. Keterbatasan Penelitian
Beberapa keterbatasan penelitian ini diantaranya adalah : 1.
Variabel makroekonomi yang digunakan dalam penelitian ini belum sepenuhnya menunjukan kondisi perekonomian secara makro di suatu negara.
2. Penggunaan indeks harga saham utama sebagai indikator pasar saham di
suatu negara yang dipengaruhi harga minyak dunia belum mencerminkan kondisi pasar saham yang sebenarnya.
5.4. Saran Penelitian Lanjutan
Bagi penelitian
selanjutnya, penelitian
berikutnya dapat
mempertimbangkan beberapa saran berikut : 1.
Penelitian berikutnya perlu menambahkan variabel lain agar hasil analisis lebih memperlihatkan pengaruh harga minyak dunia terhadap ekonomi suatu
negara. 2.
Komponen-komponen indeks harga saham berdasarkan sektor dan bidang yang terkait dengan energi minyak dunia karena pergerakan indeks harga
saham utama di suatu negara tidak selalu dapat dijadikan indikator pengaruh harga minyak dunia terhadap ekonomi negara bersangkutan, khususnya
sektor industri yang terkait dengan minyak mentah. Selain itu, tidak semua perusahaan yang terdaftar di bursa saham merupakan perusahaan yang terkait
langsung dengan komoditas seperti minyak mentah dunia. Dua sektor yang dapat menjadi pertimbangan untuk penelitian selanjutnya adalah sektor
manufaktur dan sektor pertambangan.
3. Penelitian selanjutnya perlu mencari model penelitian yang lebih tepat untuk
menggambarkan pengaruh harga minyak dunia terhadap indeks harga saham pada suatu negara.
Halaman ini sengaja dikosongkan
DAFTAR PUSTAKA
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Research Paper , pp 1 – 27, School of Accounting Finance and
Management, University of Essex, Colchester. Adebiyi, M.A., Adenuga, A.O., Abeng, M.O. dan Omanukwue, P.N. 2009. ’Oil
Price Shocks, Exchange Rate and Stock Market Behaviour: Empirical Evidence from Nigeria’. Research Paper, pp 1 – 41, Central Bank of
Nigeria.
Amisano, G., dan Giannini. 1997. ‘Topics in Structural VAR Econometrics’. Springer-Verlag Berlin. Heidelberg. Germany.
Apergis, N., dan Miller, S.M. 2008. ‘Do Structural Oil Market Shocks Affect Stock Prices?’, Research Paper, pp 1 – 26, Department of Financial
Banking Management, University of Piraeus, Greece. Arsana, I Gede Putra. 2005. VAR Vector Autoragressive. Lab Komputasi
Universitas Indonesia. Basher, S.A., dan Sadorsky, P. 2006. ‘Oil price risk and emerging stock markets’,
Global Finance Journal, vol. 172, pp 224-251.
Basher, S.A., Haug, A.A., dan Perry Sadorsky. 2010. ‘Oil Prices, Exchange Rate and Emerging Markets’, Research Paper, pp 1 – 32, Munich University
Library. Bjornland, H.C. 2008. ‘Oil Price Shocks and Stock Market Booms in an Oil
Exporting Country’, Research Paper, pp 1 – 37, Department of Economics, Norwegian School Management.
Blanchard, O. 2006. ‘Macroeconomics 4
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edition’ , Pearson Prentice Hall, New
Jersey. Bohi, D.R. 1989. ‘Energy Price Shocks and Macroeconomic Performance’.
Resources for the Future , Washington.
British Petroleum. 2010. Statistical Review of World Energy Market. BP Statistical Review of World Energy.
Coudert, V., Mignon, V., dan Penot, A. 2008. ‘Oil Price and the Dollar’, Energy Studies Review, vol. 15:2
, pp 1-20. Dimitrova, D. 2005. ’The Relationship between Exchange Rates and Stock Prices:
Studied in a Multivariate Model’, Issues in Political Economy, vol.14, pp 1 – 25, The College of Wooster.
Enders, W. 2004. ‘Applied Econometric Time Series’, John Wiley Son Inc., New York.
Energy Information Administration. 2004. The International Crude Oil Market Handbook
. Engle, R.F. dan C.W.J. Granger .1987. ‘Cointegration and Error-Correction:
Representation, Estimation, and Testing ’, Econometrica 55, pp. 251-276
Gujarati, D. 2004. ‘Basic Econometrics fourth edition’, McGraw Hill, New York. Haldane, A.G. 1997. ‘The Monetary Framework in Norway, in A.B. Christiansen
and J.F. Qvigstad eds., Choosing a Monetary Policy Target’ ,
Scandinavian University Press 67-108, Oslo. Handa, J. 2009. ‘Monetary Economics 2
nd
edition’ , Routledge Taylor Francis
Group, New York. Hildebrand, P.M. 2006. ’Monetary Policy and Financial Markets’, Swiss National
Bank, Zurich. Husnan, S. dan Pudjiastuti. 1994. ‘Dasar Manajemen Keuangan, edisi 1’, Unit
Penerbit dan Percetakan AMP YKPN, Yogyakarta. International Monetary Fund. 2010. World Economic Outlook: Recovering, Risk,
and Balancing .
Kilian, L. dan Park, C. 2007. ’The Impact of Oil Price Shocks on the U.S. Stock Market’, Research Paper, Department of Economics, University of
Michigan. Kilian, L. 2009. ‘Oil Price Volatility: Origins and Effects’, Working Paper ERSD-
2010-02 , WTO Economic Research and Statistic Division, Geneva,
Switzerland. Krugman, P.R. dan Obstfeld, M. 2003. ‘International Economics: Theory and
Policy, sixth edition’ , Pearson Education, Inc., Boston.
Maghyereh, A. 2004. ‘Oil Price Shocks and Emerging Stock Markets: a Generalized VAR Approach’, International Journal of Applied
Econometrics and Quantitative Studies. Vol.1-2 , pp 27 – 40.
Mankiw, G. 2007. ‘Macroeconomics, sixth edition’, Worth Publishers. Masih, R., Peters, S., dan De Mello, L. 2010. ‘Oil Price Volatility and Stock Price
Fluctuations in an Emerging Market: Evidence from South Korea’, Research Paper
, pp 1 – 32. McCoy, D. 1997. ‘How Useful is Structural VAR Analysis for Irish Economics’.
Technical Paper no. 2RT97 . Ireland.
Mishkin, Frederick S. 2001. ’The Transmission Mechanism and the Role of Asset Prices in Monetary Policy’, NBER Working Paper Series, Massachusetts.
------------------------. 2001. The Economics of Money, Banking and Financial Market. Sixth Edition
. Columbia: Columbia University. Puspopranoto, S. 2004. ‘Keuangan Perbankan dan Pasar Keuangan, Konsep,
Teori, dan Realita ’, LP3ES, Jakarta.
Sims, C. A., 1980. ‘Macroeconomics and reality’, Econometrica, 48, pp 1-48.
Halaman ini sengaja dikosongkan
LAMPIRAN
Lampiran 1 Hasil Analisis VECM, IRF, dan FEVD Amerika Serikat
Vector Error Correction Model
Vector Error Correction Estimates Date: 071711 Time: 09:48
Sample adjusted: 2000M04 2010M10 Included observations: 127 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 LNSP-1
1.000000 I-1
-0.134856 0.02190
[-6.15712] LNINF-1
22.17652 4.81896
[ 4.60193] LNER-1
-1.142977 0.45035
[-2.53799] LNOIL-1
0.067384 0.24947
[ 0.27011] TREND00M01
-0.048701 0.00896
[-5.43831] C
-105.6476 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
-0.104680 -0.167502
-0.003938 -0.038402
-0.102797 0.01849
0.06494 0.00152
0.01388 0.03776
[-5.66066] [-2.57934]
[-2.59924] [-2.76658]
[-2.72262] DLNSP-1
0.049150 0.321713
0.010396 -0.064996
0.294911 0.08336
0.29272 0.00683
0.06257 0.17019
[ 0.58965] [ 1.09906]
[ 1.52215] [-1.03881]
[ 1.73285] DLNSP-2
-0.124143 0.500965
-0.000760 -0.032060
0.325588 0.08467
0.29734 0.00694
0.06355 0.17287
[-1.46620] [ 1.68485]
[-0.10949] [-0.50446]
[ 1.88339] DI-1
-0.003486 0.583930
0.002374 -0.009955
0.044024 0.02676
0.09396 0.00219
0.02008 0.05463
[-0.13029] [ 6.21464]
[ 1.08294] [-0.49567]
[ 0.80587] DI-2
-0.038520 -0.036060
-0.005593 -0.028184
-0.077136 0.02641
0.09273 0.00216
0.01982 0.05392
[-1.45872] [-0.38886]
[-2.58480] [-1.42188]
[-1.43067]
DLNINF-1 -0.893545
-4.131668 0.405695
-2.894644 -0.034866
1.32104 4.63909
0.10824 0.99159
2.69721 [-0.67639]
[-0.89062] [ 3.74817]
[-2.91920] [-0.01293]
DLNINF-2 4.004969
6.925749 -0.076978
2.145997 3.268665
1.25901 4.42124
0.10316 0.94502
2.57055 [ 3.18105]
[ 1.56647] [-0.74623]
[ 2.27084] [ 1.27158]
DLNER-1 0.022913
-0.418252 0.005460
-0.016306 0.233147
0.12910 0.45335
0.01058 0.09690
0.26358 [ 0.17749]
[-0.92258] [ 0.51617]
[-0.16827] [ 0.88453]
DLNER-2 -0.211457
-0.656227 0.001626
-0.055732 -0.098172
0.12661 0.44462
0.01037 0.09504
0.25851 [-1.67012]
[-1.47593] [ 0.15677]
[-0.58643] [-0.37977]
DLNOIL-1 0.077166
0.182364 0.011987
0.110601 0.140949
0.05552 0.19497
0.00455 0.04167
0.11336 [ 1.38988]
[ 0.93536] [ 2.63508]
[ 2.65399] [ 1.24342]
DLNOIL-2 0.067320
0.023311 0.000116
0.036562 0.057424
0.05656 0.19860
0.00463 0.04245
0.11547 [ 1.19034]
[ 0.11737] [ 0.02493]
[ 0.86127] [ 0.49731]
C -0.006236
-0.006111 0.001409
0.005205 0.000636
0.00551 0.01936
0.00045 0.00414
0.01126 [-1.13109]
[-0.31562] [ 3.11969]
[ 1.25775] [ 0.05650]
DUMMY -0.014828
-0.056597 -0.001117
-0.011505 -0.004121
0.00873 0.03067
0.00072 0.00656
0.01783 [-1.69759]
[-1.84513] [-1.56019]
[-1.75478] [-0.23110]
R-squared 0.314907
0.578390 0.424028
0.157045 0.237666
Adj. R-squared 0.242792
0.534010 0.363400
0.068313 0.157420
Sum sq. resids 0.196452
2.422634 0.001319
0.110684 0.818937
S.E. equation 0.041512
0.145778 0.003401
0.031159 0.084756
F-statistic 4.366733
13.03268 6.993863
1.769881 2.961725
Log likelihood 230.7365
71.21238 548.4708
267.1691 140.0847
Akaike AIC -3.428922
-0.916730 -8.432611
-4.002663 -2.001334
Schwarz SC -3.137785
-0.625593 -8.141473
-3.711525 -1.710197
Mean dependent -0.001860
-0.044567 0.001929
0.002914 0.007949
S.D. dependent 0.047705
0.213552 0.004263
0.032282 0.092335
Determinant resid covariance dof adj. 1.70E-15
Determinant resid covariance 9.89E-16
Log likelihood 1292.909
Akaike information criterion -19.24266
Schwarz criterion -17.65260
Impulse Response Function
Period 1
0.000000 2
0.004701 3
0.007738 4
0.005894 5
0.004390 6
0.002355 7
-0.000570 8
-0.003037 9
-0.004706 10
-0.005935 11
-0.006781 12
-0.007253 13
-0.007517 14
-0.007714 15
-0.007901 16
-0.008108 17
-0.008344 18
-0.008601 19
-0.008859 20
-0.009101 21
-0.009316 22
-0.009498 23
-0.009648 24
-0.009768 25
-0.009865 26
-0.009945 27
-0.010011 28
-0.010070 29
-0.010122 30
-0.010169 31
-0.010211 32
-0.010250 33
-0.010284 34
-0.010314 35
-0.010340 36
-0.010363 37
-0.010382 38
-0.010398 39
-0.010413 40
-0.010425 41
-0.010435 42
-0.010445 43
-0.010453 44
-0.010460 45
-0.010466 46
-0.010472 47
-0.010477 48
-0.010481 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.041512 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.059617
97.16104 0.117052
1.349300 0.750886
0.621724 3
0.067697 95.81783
0.143424 1.533019
0.716989 1.788734
4 0.074666
94.68306 0.118097
2.117889 0.987439
2.093518 5
0.083292 89.53940
0.206691 6.455893
1.837881 1.960133
6 0.093372
80.53672 0.351833
15.08019 2.407881
1.623376 7
0.104478 70.86932
0.655328 24.60703
2.568751 1.299569
8 0.116759
61.77487 1.314486
33.26776 2.534654
1.108227 9
0.129914 53.88583
2.271753 40.43955
2.376471 1.026400
10 0.143298
47.55361 3.373897
45.90127 2.156090
1.015132 11
0.156521 42.63230
4.539628 49.85556
1.933990 1.038527
12 0.169429
38.79126 5.697911
52.70547 1.735779
1.069579 13
0.181956 35.74507
6.784096 54.80684
1.565966 1.098024
14 0.194105
33.27855 7.766142
56.40969 1.422824
1.122797 15
0.205923 31.23156
8.636882 57.68401
1.302682 1.144858
16 0.217460
29.49228 9.400951
58.73988 1.201289
1.165607 17
0.228758 27.98683
10.06990 59.64210
1.114801 1.186367
18 0.239844
26.66661 10.65836
60.42706 1.040141
1.207829 19
0.250731 25.49895
11.18049 61.11558
0.974934 1.230045
20 0.261421
24.46109 11.64831
61.72049 0.917395
1.252702 21
0.271908 23.53602
12.07137 62.25108
0.866215 1.275319
22 0.282187
22.70984 12.45674
62.71559 0.820428
1.297400 23
0.292254 21.97053
12.80952 63.12210
0.779300 1.318545
24 0.302106
21.30738 13.13337
63.47850 0.742247
1.338498 25
0.311746 20.71076
13.43108 63.79224
0.708782 1.357141
26 0.321178
20.17211 13.70492
64.07002 0.678488
1.374466 27
0.330411 19.68395
13.95688 64.31763
0.650996 1.390538
28 0.339451
19.23982 14.18886
64.53988 0.625980
1.405458 29
0.348308 18.83422
14.40266 64.74063
0.603150 1.419338
30 0.356989
18.46250 14.60001
64.92296 0.582252
1.432284 31
0.365503 18.12073
14.78251 65.08931
0.563065 1.444390
32 0.373856
17.80560 14.95164
65.24164 0.545396
1.455731 33
0.382056 17.51428
15.10873 65.38155
0.529078 1.466372
34 0.390108
17.24433 15.25496
65.51038 0.513968
1.476366 35
0.398018 16.99363
15.39136 65.62931
0.499943 1.485757
36 0.405792
16.76034 15.51883
65.73934 0.486896
1.494588 37
0.413435 16.54281
15.63817 65.84139
0.474731 1.502895
38 0.420953
16.33959 15.75006
65.93626 0.463369
1.510716 39
0.428349 16.14939
15.85514 66.02466
0.452735 1.518085
40 0.435629
15.97104 15.95394
66.10722 0.442767
1.525034 41
0.442798 15.80352
16.04698 66.18450
0.433405 1.531595
42 0.449860
15.64591 16.13470
66.25700 0.424599
1.537796 43
0.456818 15.49738
16.21752 66.32513
0.416302 1.543664
44 0.463677
15.35721 16.29581
66.38928 0.408474
1.549223 45
0.470440 15.22472
16.36992 66.44979
0.401076 1.554495
46 0.477112
15.09932 16.44015
66.50696 0.394076
1.559500 47
0.483695 14.98048
16.50678 66.56104
0.387443 1.564256
48 0.490192
14.86771 16.57008
66.61228 0.381149
1.568780 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 2 Hasil Analisis VECM, IRF, dan FEVD Brasil
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 20:31
Sample adjusted: 2000M04 2010M10 Included observations: 127 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 CointEq2
LNSP-1 1.000000
0.000000 I-1
0.000000 1.000000
LNINF-1 15.04351
-385.1716 3.24676
66.8448 [ 4.63340]
[-5.76218] LNER-1
3.058938 81.18638
0.70928 14.6028
[4.31273] [ 5.55964]
LNOIL-1 -2.367274
46.52118 0.39317
8.09465 [-6.02100]
[ 5.74715] TREND00M01
-0.072796 1.755488
0.01658 0.34141
[-4.38989] [ 5.14194]
C -62.26365
1375.467 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
-0.299962 0.251074
-0.002312 -0.017511
0.070028 0.08701
1.44688 0.00295
0.05470 0.09225
[-3.44738] [ 0.17353]
[-0.78325] [-0.32012]
[ 0.75908] CointEq2
-0.014854 0.021580
0.000101 3.27E-05
-0.000117 0.00422
0.07021 0.00014
0.00265 0.00448
[-3.51801] [ 0.30736]
[ 0.70815] [ 0.01233]
[-0.02623] DLNSP-1
0.232906 -4.633485
0.010732 0.200101
0.211772 0.11766
1.95648 0.00399
0.07397 0.12475
[ 1.97953] [-2.36827]
[ 2.68812] [2.70527]
[ 1.69762] DLNSP-2
-0.098276 -0.307006
0.011765 0.013627
-0.057669 0.12407
2.06315 0.00421
0.07800 0.13155
[-0.79209] [-0.14880]
[ 2.79466] [0.17470]
[-0.43839] DI-1
0.023345 -0.298180
-0.000208 -0.014057
0.000497 0.00710
0.11806 0.00024
0.00446 0.00753
[ 3.28805] [-2.52559]
[-0.86206] [-3.14938]
[ 0.06600] DI-2
0.006131 -0.184614
-9.64E-05 -0.008299
-0.012809
0.00679 0.11296
0.00023 0.00427
0.00720 [ 0.90261]
[-1.63433] [-0.41828]
[-1.94334] [-1.77844]
DLNINF-1 2.513797
69.86232 0.510814
-2.672194 5.012172
2.48551 41.3307
0.08434 1.56256
2.63526 [ 1.01138]
[ 1.69032] [ 6.05686]
[-1.71014] [ 1.90196]
DLNINF-2 -6.481814
12.98273 -0.136472
2.110139 2.555025
2.41178 40.1047
0.08183 1.51620
2.55709 [-2.68756]
[ 0.32372] [-1.66766]
[ 1.39173] [ 0.99919]
DLNER-1 0.096008
-1.893970 -0.006910
-0.195309 0.107101
0.20951 3.48382
0.00711 0.13171
0.22213 [0.45826]
[-0.54365] [-0.97197]
[-1.48287] [ 0.48215]
DLNER-2 0.354290
2.705632 0.021056
0.258850 -0.020601
0.18153 3.01868
0.00616 0.11412
0.19247 [1.95163]
[ 0.89630] [ 3.41834]
[ 2.26813] [-0.10703]
DLNOIL-1 -0.005029
2.347268 0.001014
-0.049998 0.223360
0.08986 1.49433
0.00305 0.05649
0.09528 [-0.05596]
[ 1.57079] [ 0.33242]
[-0.88499] [ 2.34427]
DLNOIL-2 -0.122678
3.244730 0.000876
0.040001 0.178207
0.08458 1.40645
0.00287 0.05317
0.08968 [-1.45044]
[ 2.30704] [ 0.30540]
[ 0.75229] [ 1.98723]
C 0.034087
-0.618704 0.002939
0.002990 -0.035058
0.01521 0.25285
0.00052 0.00956
0.01612 [ 2.24178]
[-2.44695] [ 5.69597]
[ 0.31281] [-2.17459]
DUMMY -0.002841
0.327163 0.000379
0.001783 -0.007505
0.01585 0.26354
0.00054 0.00996
0.01680 [-0.17926]
[ 1.24143] [ 0.70536]
[ 0.17898] [-0.44667]
R-squared 0.195845
0.197259 0.683616
0.278256 0.325985
Adj. R-squared 0.103332
0.104908 0.647218
0.195223 0.248444
Sum sq. resids 0.644108
178.1034 0.000742
0.254564 0.724059
S.E. equation 0.075499
1.255443 0.002562
0.047463 0.080048
F-statistic 2.116942
2.135972 18.78163
3.351163 4.204012
Log likelihood 155.3337
-201.6794 585.0281
214.2815 147.9037
Akaike AIC -2.225727
3.396527 -8.992568
-3.154039 -2.108720
Schwarz SC -1.912195
3.710059 -8.679036
-2.840507 -1.795187
Mean dependent 0.010848
-0.054803 0.005313
-0.000228 0.007949
S.D. dependent 0.079730
1.326976 0.004313
0.052908 0.092335
Determinant resid covariance dof adj. 3.71E-13
Determinant resid covariance 2.07E-13
Log likelihood 953.5539
Akaike information criterion -13.72526
Schwarz criterion -11.88885
Impulse Response Function
Period 1
0.000000 2
0.001101 3
-0.001717 4
-7.24E-08 5
-0.003641 6
-0.006138 7
-0.008529 8
-0.009730 9
-0.010280 10
-0.010463 11
-0.010644 12
-0.010699 13
-0.010640 14
-0.010419 15
-0.010090 16
-0.009696 17
-0.009289 18
-0.008884 19
-0.008492 20
-0.008112 21
-0.007751 22
-0.007410 23
-0.007095 24
-0.006807 25
-0.006546 26
-0.006310 27
-0.006099 28
-0.005910 29
-0.005743 30
-0.005594 31
-0.005464 32
-0.005349 33
-0.005249 34
-0.005162 35
-0.005086 36
-0.005020 37
-0.004963 38
-0.004914 39
-0.004872 40
-0.004836 41
-0.004805 42
-0.004778 43
-0.004756 44
-0.004736 45
-0.004720 46
-0.004706 47
-0.004694 48
-0.004684 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.075499 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.112430
97.60060 0.586673
0.442040 1.361098
0.009586 3
0.139547 93.13717
0.492568 0.286937
6.061952 0.021369
4 0.160646
90.25161 0.892608
0.242385 8.597276
0.016125 5
0.181736 86.18863
1.683077 0.193109
11.88246 0.052730
6 0.202098
82.35795 2.736662
0.177057 14.59345
0.134881 7
0.222522 79.00032
3.693486 0.200112
16.84791 0.258175
8 0.242081
76.17830 4.586151
0.248758 18.60710
0.379694 9
0.260825 73.59587
5.502510 0.290705
20.12849 0.482432
10 0.278577
71.27457 6.434752
0.326678 21.40004
0.563966 11
0.295579 69.15080
7.357547 0.360052
22.50097 0.630633
12 0.311875
67.23950 8.245161
0.395347 23.43585
0.684144 13
0.327551 65.53271
9.078244 0.431744
24.23156 0.725747
14 0.342617
64.01586 9.854622
0.468196 24.90552
0.755801 15
0.357113 62.66116
10.57891 0.502951
25.48146 0.775515
16 0.371067
61.44690 11.25587
0.535529 25.97513
0.786569 17
0.384522 60.35360
11.88846 0.565918
26.40118 0.790842
18 0.397517
59.36691 12.47879
0.594434 26.76994
0.789931 19
0.410088 58.47451
13.02876 0.621241
27.09037 0.785120
20 0.422267
57.66564 13.54081
0.646441 27.36972
0.777393 21
0.434082 56.93043
14.01768 0.670063
27.61430 0.767531
22 0.445559
56.26020 14.46214
0.692163 27.82934
0.756158 23
0.456723 55.64738
14.87673 0.712825
28.01928 0.743778
24 0.467596
55.08552 15.26379
0.732151 28.18776
0.730782 25
0.478199 54.56902
15.62541 0.750243
28.33785 0.717471
26 0.488551
54.09305 15.96358
0.767193 28.47211
0.704073 27
0.498668 53.65334
16.28011 0.783084
28.59271 0.690752
28 0.508566
53.24617 16.57672
0.797993 28.70149
0.677633 29
0.518258 52.86823
16.85496 0.811991
28.80002 0.664801
30 0.527758
52.51665 17.11627
0.825147 28.88961
0.652320 31
0.537077 52.18888
17.36196 0.837523
28.97141 0.640229
32 0.546225
51.88267 17.59323
0.849178 29.04636
0.628554 33
0.555213 51.59605
17.81118 0.860165
29.11530 0.617308
34 0.564048
51.32724 18.01681
0.870535 29.17892
0.606495 35
0.572739 51.07468
18.21104 0.880333
29.23783 0.596113
36 0.581293
50.83696 18.39473
0.889600 29.29256
0.586156 37
0.589718 50.61283
18.56862 0.898374
29.34356 0.576612
38 0.598018
50.40118 18.73345
0.906691 29.39121
0.567468 39
0.606201 50.20101
18.88984 0.914583
29.43586 0.558711
40 0.614271
50.01140 19.03839
0.922080 29.47780
0.550325 41
0.622233 49.83155
19.17965 0.929209
29.51729 0.542294
42 0.630091
49.66072 19.31412
0.935995 29.55456
0.534602 43
0.637851 49.49826
19.44224 0.942461
29.58981 0.527233
44 0.645515
49.34356 19.56444
0.948628 29.62320
0.520171 45
0.653087 49.19607
19.68111 0.954516
29.65490 0.513402
46 0.660571
49.05530 19.79260
0.960142 29.68505
0.506910 47
0.667970 48.92080
19.89924 0.965524
29.71375 0.500681
48 0.675287
48.79215 20.00133
0.970676 29.74113
0.494702 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 3 Hasil Analisis VECM, IRF, dan FEVD India
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 20:43
Sample adjusted: 2000M03 2010M09 Included observations: 127 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 LNSP-1
1.000000 I-1
-0.129350 0.01634
[-7.91854] LNINF-1
-5.795045 3.09117
[-1.87471] LNER-1
4.313763 2.51833
[1.71295] LNOIL-1
-1.897506 0.52692
[-3.60109] TREND00M01
0.032899 C
40.62264 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
0.013267 5.441858
-0.000379 0.001803
0.038714 0.00982
0.87982 0.00094
0.00219 0.01046
[ 1.35126] [ 6.18521]
[-0.40345] [ 0.82304]
[ 3.70214] DLNSP-1
-0.055069 -19.85838
-0.001226 8.29E-05
0.237757 0.10770
9.65065 0.01031
0.02402 0.11470
[-0.51133] [-2.05773]
[-0.11893] [0.00345]
[ 2.07280] DI-1
0.001376 -0.060878
-2.39E-05 -0.000208
0.002598 0.00105
0.09441 0.00010
0.00024 0.00112
[ 1.30624] [-0.64483]
[-0.23733] [-0.88553]
[ 2.31492] DLNINF-1
0.300181 73.87414
0.135633 0.488327
-0.212491 0.95450
85.5316 0.09134
0.21293 1.01659
[ 0.31449] [ 0.86371]
[ 1.48490] [ 2.29341]
[-0.20902] DLNER-1
0.985095 76.05762
0.016224 0.186343
-0.367931 0.46972
42.0914 0.04495
0.10478 0.50028
[2.09718] [ 1.80696]
[ 0.36093] [ 1.77835]
[-0.73545] DLNOIL-1
-0.021172 3.205319
0.013243 -0.002500
0.146176
0.07768 6.96091
0.00743 0.01733
0.08273 [-0.27255]
[ 0.46047] [ 1.78148]
[-0.14425] [ 1.76682]
C -0.021705
-1.268958 0.002368
0.003672 0.007915
0.01671 1.49744
0.00160 0.00373
0.01780 [-1.29884]
[-0.84742] [ 1.48090]
[ 0.98513] [ 0.44472]
TREND00M01 0.000703
0.029003 1.79E-05
-0.000133 -4.15E-05
0.00032 0.02878
3.1E-05 7.2E-05
0.00034 [ 2.18981]
[ 1.00764] [ 0.58125]
[-1.85339] [-0.12125]
DUMMY -0.045435
-2.848201 0.002654
0.008534 5.39E-05
0.02554 2.28842
0.00244 0.00570
0.02720 [-1.77914]
[-1.24462] [ 1.08597]
[ 1.49806] [ 0.00198]
R-squared 0.099590
0.409041 0.118377
0.145063 0.254067
Adj. R-squared 0.038546
0.368976 0.058606
0.087101 0.203496
Sum sq. resids 0.702567
5641.424 0.006434
0.034962 0.796943
S.E. equation 0.077162
6.914382 0.007384
0.017213 0.082181
F-statistic 1.631433
10.20942 1.980516
2.502732 5.023903
Log likelihood 149.8171
-421.1054 447.8327
340.3478 141.8134
Akaike AIC -2.217593
6.773314 -6.910751
-5.218075 -2.091550
Schwarz SC -2.016036
6.974871 -6.709194
-5.016519 -1.889993
Mean dependent 0.010268
-0.004724 0.005139
0.000233 0.007407
S.D. dependent 0.078693
8.704230 0.007610
0.018015 0.092083
Determinant resid covariance dof adj. 2.08E-11
Determinant resid covariance 1.44E-11
Log likelihood 684.1098
Akaike information criterion -9.985981
Schwarz criterion -8.866223
Impulse Response Function
Period 1
0.000000 2
-0.003715 3
-0.004910 4
-0.006126 5
-0.006661 6
-0.006825 7
-0.006863 8
-0.006860 9
-0.006850 10
-0.006843 11
-0.006840 12
-0.006839 13
-0.006838 14
-0.006838 15
-0.006838 16
-0.006838 17
-0.006838 18
-0.006838 19
-0.006838 20
-0.006838 21
-0.006838 22
-0.006838 23
-0.006838 24
-0.006838 25
-0.006838 26
-0.006838 27
-0.006838 28
-0.006838 29
-0.006838 30
-0.006838 31
-0.006838 32
-0.006838 33
-0.006838 34
-0.006838 35
-0.006838 36
-0.006838 37
-0.006838 38
-0.006838 39
-0.006838 40
-0.006838 41
-0.006838 42
-0.006838 43
-0.006838 44
-0.006838 45
-0.006838 46
-0.006838 47
-0.006838 48
-0.006838 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.077162 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.114102
98.14677 0.017626
0.011547 1.718025
0.106030 3
0.144030 96.99124
0.212120 0.044907
2.568989 0.182746
4 0.170238
96.21379 0.319918
0.103176 3.102829
0.260285 5
0.193209 95.68874
0.378908 0.153608
3.457834 0.320913
6 0.213755
95.33885 0.412616
0.192006 3.692392
0.364132 7
0.232467 95.09746
0.433202 0.219808
3.854507 0.395027
8 0.249756
94.92299 0.447193
0.240148 3.972008
0.417665 9
0.265910 94.79123
0.457513 0.255501
4.060930 0.434821
10 0.281132
94.68798 0.465560
0.267488 4.130707
0.448264 11
0.295569 94.60468
0.472062 0.277130
4.187032 0.459097
12 0.309333
94.53595 0.477439
0.285072 4.233512
0.468027 13
0.322510 94.47823
0.481963 0.291736
4.272545 0.475523
14 0.335170
94.42907 0.485820
0.297412 4.305794
0.481906 15
0.347368 94.38668
0.489146 0.302304
4.334457 0.487409
16 0.359153
94.34977 0.492043
0.306566 4.359422
0.492202 17
0.370563 94.31733
0.494589 0.310311
4.381359 0.496414
18 0.381632
94.28860 0.496844
0.313627 4.400789
0.500145 19
0.392388 94.26297
0.498854 0.316585
4.418117 0.503472
20 0.402858
94.23998 0.500659
0.319240 4.433668
0.506457 21
0.413062 94.21922
0.502288 0.321636
4.447700 0.509152
22 0.423021
94.20040 0.503764
0.323808 4.460427
0.511595 23
0.432750 94.18326
0.505110 0.325788
4.472023 0.513821
24 0.442265
94.16757 0.506341
0.327599 4.482631
0.515858 25
0.451580 94.15317
0.507472 0.329262
4.492373 0.517729
26 0.460706
94.13989 0.508513
0.330794 4.501350
0.519452 27
0.469656 94.12762
0.509477 0.332211
4.509650 0.521046
28 0.478437
94.11624 0.510370
0.333525 4.517346
0.522523 29
0.487061 94.10565
0.511200 0.334746
4.524502 0.523897
30 0.495534
94.09579 0.511974
0.335885 4.531173
0.525178 31
0.503865 94.08657
0.512698 0.336949
4.537406 0.526375
32 0.512061
94.07794 0.513375
0.337946 4.543243
0.527496 33
0.520127 94.06984
0.514011 0.338881
4.548721 0.528547
34 0.528070
94.06222 0.514608
0.339760 4.553871
0.529536 35
0.535896 94.05505
0.515172 0.340588
4.558724 0.530468
36 0.543608
94.04828 0.515703
0.341370 4.563302
0.531347 37
0.551213 94.04188
0.516205 0.342109
4.567630 0.532178
38 0.558715
94.03582 0.516681
0.342808 4.571727
0.532964 39
0.566117 94.03008
0.517131 0.343471
4.575611 0.533710
40 0.573423
94.02462 0.517559
0.344101 4.579298
0.534418 41
0.580638 94.01944
0.517966 0.344699
4.582804 0.535091
42 0.587764
94.01451 0.518353
0.345269 4.586140
0.535732 43
0.594804 94.00981
0.518722 0.345811
4.589319 0.536342
44 0.601762
94.00532 0.519074
0.346329 4.592352
0.536924 45
0.608641 94.00104
0.519410 0.346824
4.595249 0.537481
46 0.615443
93.99694 0.519732
0.347296 4.598018
0.538012 47
0.622170 93.99302
0.520039 0.347749
4.600669 0.538521
48 0.628826
93.98927 0.520334
0.348182 4.603207
0.539009 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 4 Hasil Analisis VECM, IRF, dan FEVD Indonesia
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 22:08
Sample adjusted: 2000M04 2010M10 Included observations: 127 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 CointEq2
LNSP-1 1.000000
0.000000 I-1
0.000000 1.000000
LNINF-1 45.46488
488.2103 9.79679
100.635 [ 4.64079]
[ 4.85131] LNER-1
6.437369 44.35577
13.8825 142.604
[ 0.46370] [ 0.31104]
LNOIL-1 -21.65599
-213.7556 4.57857
47.0320 [-4.72986]
[-4.54489] C
-191.4848 -1836.704
Error Correction: DLNSP
DI DLNINF
DLNER DLNOIL
CointEq1 0.021786
1.682494 0.002241
0.012358 0.101611
0.02220 0.53636
0.00278 0.01190
0.02609 [ 0.98151]
[ 3.13690] [ 0.80605]
[ 1.03854] [ 3.89511]
CointEq2 -0.001582
-0.168741 -0.000246
-0.001374 -0.009643
0.00215 0.05200
0.00027 0.00115
0.00253 [-0.73528]
[-3.24501] [-0.91401]
[-1.19110] [-3.81269]
DLNSP-1 0.185434
-2.323070 0.019238
-0.162574 -0.101910
0.11132 2.68990
0.01395 0.05968
0.13083 [ 1.66581]
[-0.86363] [ 1.37951]
[-2.72427] [-0.77896]
DLNSP-2 0.015342
-6.473258 -0.022981
-0.099951 0.074832
0.11446 2.76587
0.01434 0.06136
0.13452 [ 0.13404]
[-2.34040] [-1.60265]
[-1.62889] [ 0.55627]
DI-1 -0.000545
-0.467251 -4.75E-05
0.001062 -0.002332
0.00382 0.09233
0.00048 0.00205
0.00449 [-0.14275]
[-5.06076] [-0.09932]
[ 0.51828] [-0.51929]
DI-2 -0.006974
-0.152708 0.000347
0.004447 -0.004325
0.00363 0.08760
0.00045 0.00194
0.00426 [-1.92360]
[-1.74315] [ 0.76428]
[ 2.28829] [-1.01502]
DLNINF-1 -0.059756
2.495813 0.191683
-0.342639 -0.371422
0.73221 17.6932
0.09173 0.39253
0.86055 [-0.08161]
[ 0.14106] [ 2.08970]
[-0.87290] [-0.43161]
DLNINF-2 0.963275
47.58044 -0.063470
-0.773280 1.175048
0.72250 17.4587
0.09051 0.38733
0.84914 [ 1.33325]
[ 2.72532] [-0.70124]
[-1.99646] [ 1.38381]
DLNER-1 0.406073
-8.782041 0.033417
-0.158513 -0.653485
0.20479 4.94854
0.02565 0.10978
0.24068 [ 1.98289]
[-1.77467] [ 1.30258]
[-1.44386] [-2.71514]
DLNER-2 0.428077
-6.031809 -0.016731
-0.313794 -0.007227
0.21186 5.11941
0.02654 0.11358
0.24899 [ 2.02057]
[-1.17822] [-0.63040]
[-2.76287] [-0.02902]
DLNOIL-1 0.174633
0.991846 -0.004439
-0.038359 0.186184
0.07743 1.87113
0.00970 0.04151
0.09101 [ 2.25524]
[ 0.53008] [-0.45757]
[-0.92405] [ 2.04584]
DLNOIL-2 0.113111
-1.797484 0.004506
-0.077243 0.153967
0.07495 1.81111
0.00939 0.04018
0.08809 [ 1.50915]
[-0.99248] [ 0.47994]
[-1.92243] [ 1.74790]
C 0.011698
-0.363748 0.005963
0.012774 0.007218
0.01068 0.25804
0.00134 0.00572
0.01255 [ 1.09548]
[-1.40963] [ 4.45727]
[ 2.23126] [ 0.57512]
DUMMY -0.031293
0.390837 -8.76E-06
0.004366 -0.019305
0.01492 0.36062
0.00187 0.00800
0.01754 [-2.09688]
[ 1.08380] [-0.00468]
[ 0.54578] [-1.10070]
R-squared 0.314040
0.385819 0.158078
0.277084 0.339733
Adj. R-squared 0.235124
0.315161 0.061219
0.193917 0.263773
Sum sq. resids 0.513511
299.8412 0.008059
0.147578 0.709291
S.E. equation 0.067412
1.628945 0.008445
0.036139 0.079227
F-statistic 3.979425
5.460367 1.632052
3.331653 4.472527
Log likelihood 169.7224
-234.7559 433.5329
248.9016 149.2123
Akaike AIC -2.452322
3.917416 -6.606818
-3.699238 -2.129327
Schwarz SC -2.138789
4.230948 -6.293285
-3.385706 -1.815794
Mean dependent 0.014408
-0.027953 0.006836
0.001278 0.007949
S.D. dependent 0.077080
1.968394 0.008716
0.040251 0.092335
Determinant resid covariance dof adj. 5.11E-12
Determinant resid covariance 2.85E-12
Log likelihood 787.0811
Akaike information criterion -11.13514
Schwarz criterion -9.343522
Impulse Response Function
Period 1
0.000000 2
0.003208 3
0.001860 4
-0.011258 5
-0.023962 6
-0.035716 7
-0.045103 8
-0.052144 9
-0.057182 10
-0.060405 11
-0.061806 12
-0.061765 13
-0.060750 14
-0.059093 15
-0.057048 16
-0.054840 17
-0.052648 18
-0.050592 19
-0.048749 20
-0.047158 21
-0.045832 22
-0.044763 23
-0.043930 24
-0.043305 25
-0.042856 26
-0.042548 27
-0.042353 28
-0.042242 29
-0.042193 30
-0.042185 31
-0.042203 32
-0.042235 33
-0.042274 34
-0.042313 35
-0.042349 36
-0.042379 37
-0.042404 38
-0.042422 39
-0.042434 40
-0.042442 41
-0.042446 42
-0.042446 43
-0.042445 44
-0.042442 45
-0.042438 46
-0.042434 47
-0.042430 48
-0.042426 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.067412 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.100816
97.55653 0.168293
0.007306 2.166603
0.101272 3
0.125148 89.68080
2.324981 0.193359
7.713035 0.087820
4 0.143622
84.78355 2.880030
0.283422 11.37188
0.681119 5
0.160308 80.55728
3.060818 0.227917
13.37294 2.781036
6 0.176246
75.49462 3.169663
0.190020 14.73839
6.407308 7
0.192198 70.05570
3.053319 0.174665
15.82145 10.89486
8 0.207579
64.96951 2.772424
0.171518 16.43630
15.65025 9
0.222036 60.46649
2.462500 0.188395
16.57160 20.31101
10 0.235625
56.59033 2.186961
0.246092 16.36882
24.60780 11
0.248345 53.34103
1.990688 0.356981
15.96610 28.34520
12 0.260147
50.65288 1.897542
0.529676 15.45122
31.46867 13
0.271079 48.43519
1.911763 0.771188
14.87789 34.00397
14 0.281248
46.60510 2.026838
1.081314 14.28253
36.00422 15
0.290760 45.09026
2.227826 1.454418
13.69092 37.53658
16 0.299717
43.82846 2.495811
1.881946 13.11923
38.67456 17
0.308211 42.76955
2.811953 2.352258
12.57612 39.49012
18 0.316319
41.87397 3.158750
2.852178 12.06556
40.04954 19
0.324105 41.11028
3.520963 3.369068
11.58877 40.41092
20 0.331616
40.45354 3.886432
3.891605 11.14527
40.62315 21
0.338894 39.88392
4.246092 4.410152
10.73358 40.72625
22 0.345966
39.38542 4.593618
4.917095 10.35171
40.75217 23
0.352859 38.94509
4.924996 5.406859
9.997408 40.72564
24 0.359591
38.55246 5.238046
5.875687 9.668422
40.66538 25
0.366178 38.19902
5.531942 6.321359
9.362551 40.58513
26 0.372635
37.87789 5.806806
6.742890 9.077721
40.49470 27
0.378971 37.58354
6.063389 7.140226
8.812008 40.40083
28 0.385197
37.31159 6.302809
7.513983 8.563647
40.30797 29
0.391321 37.05856
6.526374 7.865221
8.331038 40.21881
30 0.397350
36.82171 6.735448
8.195271 8.112735
40.13483 31
0.403288 36.59892
6.931366 8.505598
7.907443 40.05667
32 0.409141
36.38852 7.115387
8.797702 7.714003
39.98439 33
0.414913 36.18921
7.288660 9.073054
7.531383 39.91769
34 0.420608
35.99997 7.452215
9.333047 7.358666
39.85611 35
0.426229 35.81995
7.606960 9.578974
7.195036 39.79908
36 0.431778
35.64849 7.753693
9.812016 7.039768
39.74604 37
0.437258 35.48500
7.893105 10.03324
6.892216 39.69645
38 0.442672
35.32898 8.025800
10.24359 6.751803
39.64983 39
0.448021 35.18000
8.152299 10.44392
6.618012 39.60577
40 0.453308
35.03764 8.273061
10.63498 6.490380
39.56394 41
0.458534 34.90153
8.388486 10.81744
6.368489 39.52406
42 0.463702
34.77131 8.498928
10.99191 6.251958
39.48590 43
0.468813 34.64665
8.604705 11.15890
6.140442 39.44930
44 0.473869
34.52723 8.706102
11.31891 6.033628
39.41413 45
0.478872 34.41276
8.803378 11.47236
5.931227 39.38027
46 0.483823
34.30296 8.896769
11.61966 5.832975
39.34764 47
0.488724 34.19755
8.986494 11.76115
5.738626 39.31618
48 0.493576
34.09629 9.072756
11.89716 5.647956
39.28584 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 5 Hasil Analisis VECM, IRF, dan FEVD Inggris
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 20:44
Sample adjusted: 2000M03 2010M10 Included observations: 128 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 LNSP-1
1.000000 I-1
-0.574153 0.08874
[-6.47013] LNINF-1
24.69836 7.98770
[ 3.09205] LNER-1
4.628389 0.91709
[ 5.04683] LNOIL-1
0.886751 0.30849
[ 2.87452] TREND00M01
-0.089310 C
-120.1360 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
0.003630 0.021978
7.65E-05 -0.036175
-0.104915 0.01426
0.04456 0.00111
0.00736 0.02434
[ 0.25465] [ 0.49327]
[ 0.06886] [-4.91534]
[-4.31081] DLNSP-1
0.027479 1.482334
0.006801 0.196388
0.642174 0.09273
0.28981 0.00723
0.04787 0.15831
[ 0.29635] [ 5.11479]
[ 0.94086] [ 4.10240]
[ 4.05651] DI-1
-0.008062 0.490525
0.008421 0.022769
0.194634 0.02441
0.07629 0.00190
0.01260 0.04167
[-0.33030] [ 6.42972]
[ 4.42591] [ 1.80680]
[ 4.67053] DLNINF-1
-0.313935 -0.841179
-0.062494 0.848167
2.026930 1.13556
3.54916 0.08852
0.58625 1.93869
[-0.27646] [-0.23701]
[-0.70601] [ 1.44676]
[ 1.04552] DLNER-1
0.128332 0.726560
-0.023501 0.058747
0.305517 0.16522
0.51640 0.01288
0.08530 0.28208
[ 0.77672] [ 1.40697]
[-1.82474] [ 0.68871]
[ 1.08309] DLNOIL-1
0.031150 0.362958
0.013978 0.052978
0.052869
0.04986 0.15583
0.00389 0.02574
0.08512 [ 0.62479]
[ 2.32925] [ 3.59662]
[ 2.05822] [ 0.62113]
C -0.017873
-0.029502 0.002166
0.004089 0.035267
0.00994 0.03105
0.00077 0.00513
0.01696 [-1.79895]
[-0.95008] [ 2.79739]
[ 0.79723] [ 2.07918]
TREND00M01 0.000413
0.000554 7.49E-06
-0.000116 -0.000767
0.00019 0.00060
1.5E-05 9.9E-05
0.00033 [ 2.15441]
[ 0.92593] [ 0.50188]
[-1.17131] [-2.34471]
DUMMY -0.030967
-0.088888 0.000187
0.007038 0.084299
0.01605 0.05016
0.00125 0.00829
0.02740 [-1.92959]
[-1.77211] [ 0.14967]
[ 0.84941] [ 3.07672]
R-squared 0.057533
0.615209 0.344122
0.324155 0.376225
Adj. R-squared -0.005826
0.589340 0.300030
0.278720 0.334291
Sum sq. resids 0.229911
2.245907 0.001397
0.061279 0.670128
S.E. equation 0.043955
0.137380 0.003426
0.022692 0.075042
F-statistic 0.908046
23.78231 7.804528
7.134468 8.971751
Log likelihood 222.9899
77.12280 549.6052
307.6144 154.5241
Akaike AIC -3.343592
-1.064419 -8.446956
-4.665851 -2.273815
Schwarz SC -3.143058
-0.863885 -8.246423
-4.465317 -2.073281
Mean dependent -0.000732
-0.041562 0.002333
0.000000 0.008011
S.D. dependent 0.043827
0.214379 0.004095
0.026720 0.091974
Determinant resid covariance dof adj. 1.09E-15
Determinant resid covariance 7.60E-16
Log likelihood 1319.896
Akaike information criterion -19.84212
Schwarz criterion -18.72805
Impulse Response Function
Period 1
0.000000 2
0.002530 3
0.002449 4
0.002415 5
0.002098 6
0.001807 7
0.001533 8
0.001302 9
0.001118 10
0.000981 11
0.000886 12
0.000824 13
0.000789 14
0.000772 15
0.000767 16
0.000770 17
0.000777 18
0.000786 19
0.000794 20
0.000802 21
0.000808 22
0.000813 23
0.000817 24
0.000819 25
0.000820 26
0.000821 27
0.000822 28
0.000822 29
0.000821 30
0.000821 31
0.000821 32
0.000821 33
0.000821 34
0.000820 35
0.000820 36
0.000820 37
0.000820 38
0.000820 39
0.000820 40
0.000820 41
0.000820 42
0.000820 43
0.000820 44
0.000820 45
0.000820 46
0.000820 47
0.000820 48
0.000820 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.043955 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.063072
99.54870 7.20E-05
0.019342 0.271038
0.160852 3
0.078434 99.42985
0.008512 0.018821
0.341278 0.201537
4 0.091381
99.37606 0.029858
0.028436 0.347316
0.218332 5
0.102731 99.35319
0.052373 0.043284
0.336714 0.214439
6 0.112881
99.34639 0.069159
0.060938 0.320271
0.203238 7
0.122093 99.34931
0.079303 0.079345
0.302544 0.189494
8 0.130554
99.35760 0.084010
0.097204 0.285523
0.175666 9
0.138408 99.36849
0.084960 0.113699
0.270030 0.162818
10 0.145764
99.38033 0.083614
0.128423 0.256305
0.151328 11
0.152709 99.39215
0.081032 0.141259
0.244320 0.141241
12 0.159311
99.40343 0.077901
0.152278 0.233932
0.132455 13
0.165621 99.41394
0.074630 0.161650
0.224956 0.124822
14 0.171681
99.42358 0.071443
0.169592 0.217201
0.118185 15
0.177524 99.43233
0.068454 0.176327
0.210487 0.112399
16 0.183176
99.44024 0.065710
0.182063 0.204654
0.107337 17
0.188656 99.44735
0.063222 0.186983
0.199559 0.102888
18 0.193982
99.45374 0.060982
0.191242 0.195081
0.098956 19
0.199167 99.45948
0.058971 0.194965
0.191118 0.095461
20 0.204221
99.46466 0.057166
0.198255 0.187586
0.092335 21
0.209156 99.46933
0.055545 0.201192
0.184415 0.089522
22 0.213978
99.47356 0.054083
0.203838 0.181548
0.086976 23
0.218696 99.47740
0.052759 0.206241
0.178940 0.084658
24 0.223315
99.48091 0.051556
0.208440 0.176553
0.082537 25
0.227841 99.48413
0.050456 0.210463
0.174359 0.080587
26 0.232279
99.48710 0.049446
0.212334 0.172333
0.078787 27
0.236634 99.48984
0.048513 0.214070
0.170455 0.077119
28 0.240911
99.49239 0.047650
0.215687 0.168708
0.075568 29
0.245114 99.49476
0.046846 0.217197
0.167078 0.074123
30 0.249245
99.49697 0.046096
0.218611 0.165555
0.072771 31
0.253309 99.49904
0.045394 0.219936
0.164127 0.071505
32 0.257309
99.50098 0.044735
0.221181 0.162787
0.070317 33
0.261248 99.50281
0.044116 0.222353
0.161526 0.069199
34 0.265128
99.50453 0.043532
0.223457 0.160338
0.068146 35
0.268952 99.50615
0.042981 0.224499
0.159216 0.067152
36 0.272722
99.50769 0.042460
0.225485 0.158156
0.066212 37
0.276441 99.50914
0.041966 0.226418
0.157152 0.065323
38 0.280111
99.51052 0.041498
0.227302 0.156201
0.064480 39
0.283733 99.51183
0.041054 0.228142
0.155298 0.063679
40 0.287310
99.51307 0.040631
0.228939 0.154439
0.062918 41
0.290842 99.51426
0.040229 0.229699
0.153622 0.062194
42 0.294332
99.51538 0.039846
0.230422 0.152844
0.061504 43
0.297781 99.51646
0.039480 0.231112
0.152101 0.060846
44 0.301191
99.51749 0.039131
0.231771 0.151392
0.060217 45
0.304563 99.51847
0.038798 0.232401
0.150715 0.059616
46 0.307897
99.51941 0.038478
0.233004 0.150066
0.059041 47
0.311196 99.52031
0.038172 0.233581
0.149445 0.058491
48 0.314460
99.52117 0.037879
0.234134 0.148849
0.057963 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 6 Hasil Analisis VAR first difference, IRF, dan FEVD Jepang
VAR first difference
Vector Autoregression Estimates Date: 071011 Time: 20:42
Sample adjusted: 2000M02 2010M10 Included observations: 129 after adjustments
Standard errors in t-statistics in [ ] LNSP
I LNINF
LNER LNOIL
LNSP-1 0.966339
0.064531 0.002099
-0.002840 0.164469
0.02976 0.01688
0.00146 0.01370
0.04247 [ 32.4713]
[ 3.82285] [ 1.44167]
[-0.20736] [ 3.87290]
I-1 0.026691
0.949731 -0.000577
0.051785 -0.038608
0.05563 0.03155
0.00272 0.02560
0.07938 [ 0.47982]
[ 30.0999] [-0.21214]
[ 2.02291] [-0.48638]
LNINF-1 -2.269864
-1.020993 0.911558
-0.155354 -5.535362
0.77225 0.43803
0.03779 0.35538
1.10198 [-2.93930]
[-2.33086] [ 24.1223]
[-0.43714] [-5.02313]
LNER-1 -0.056015
0.016809 0.005109
0.878847 0.006343
0.08414 0.04773
0.00412 0.03872
0.12006 [-0.66574]
[ 0.35220] [ 1.24089]
[ 22.6972] [ 0.05283]
LNOIL-1 -0.001627
0.003836 0.000540
-0.008971 0.888505
0.02119 0.01202
0.00104 0.00975
0.03024 [-0.07677]
[ 0.31912] [ 0.52054]
[-0.92001] [ 29.3850]
C 11.05495
4.014724 0.361648
1.349164 24.36419
3.64579 2.06796
0.17840 1.67778
5.20245 [ 3.03225]
[ 1.94139] [ 2.02714]
[ 0.80414] [ 4.68321]
DUMMY -0.034865
0.000717 0.000926
-0.036107 0.095123
0.02437 0.01382
0.00119 0.01122
0.03478 [-1.43062]
[ 0.05184] [ 0.77670]
[-3.21942] [ 2.73527]
R-squared 0.946485
0.968538 0.888826
0.942440 0.971791
Adj. R-squared 0.943853
0.966991 0.883358
0.939610 0.970404
Sum sq. resids 0.406306
0.130724 0.000973
0.086048 0.827342
S.E. equation 0.057709
0.032734 0.002824
0.026558 0.082350
F-statistic 359.6234
625.9459 162.5632
332.9240 700.4891
Log likelihood 188.5067
261.6510 577.7363
288.6239 142.6399
Akaike AIC -2.814058
-3.948077 -8.848625
-4.366262 -2.102945
Schwarz SC -2.658874
-3.792893 -8.693441
-4.211079 -1.947761
Mean dependent 9.396790
0.131860 4.611351
4.696370 3.864276
S.D. dependent 0.243548
0.180168 0.008269
0.108070 0.478682
Determinant resid covariance dof adj. 1.08E-16
Determinant resid covariance 8.17E-17
Log likelihood 1474.122
Akaike information criterion -22.31197
Schwarz criterion -21.53605
Impulse Response Function
Period 1
0.000000 2
-0.000127 3
-0.000283 4
-0.000454 5
-0.000628 6
-0.000795 7
-0.000949 8
-0.001086 9
-0.001202 10
-0.001296 11
-0.001368 12
-0.001416 13
-0.001443 14
-0.001449 15
-0.001437 16
-0.001406 17
-0.001361 18
-0.001301 19
-0.001230 20
-0.001149 21
-0.001060 22
-0.000965 23
-0.000865 24
-0.000762 25
-0.000657 26
-0.000552 27
-0.000447 28
-0.000343 29
-0.000242 30
-0.000144 31
-4.96E-05 32
4.04E-05 33
0.000126 34
0.000206 35
0.000281 36
0.000350 37
0.000413 38
0.000471 39
0.000523 40
0.000569 41
0.000610 42
0.000644 43
0.000674 44
0.000698 45
0.000716 46
0.000730 47
0.000740 48
0.000744 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.057709 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.080107
99.37670 0.000986
0.590717 0.031349
0.000250 3
0.096553 98.04246
0.003335 1.841479
0.111691 0.001033
4 0.109961
96.13648 0.007178
3.607805 0.246032
0.002503 5
0.121467 93.79787
0.012709 5.748772
0.435923 0.004724
6 0.131644
91.15636 0.020177
8.135831 0.679960
0.007670 7
0.140815 88.32647
0.029874 10.65794
0.974469 0.011248
8 0.149178
85.40475 0.042129
13.22360 1.314198
0.015321 9
0.156857 82.46938
0.057299 15.76064
1.692950 0.019732
10 0.163932
79.58132 0.075759
18.21451 2.104095
0.024318 11
0.170461 76.78626
0.097895 20.54596
2.540952 0.028928
12 0.176482
74.11702 0.124093
22.72840 2.997056
0.033429 13
0.182024 71.59589
0.154727 24.74536
3.466321 0.037710
14 0.187113
69.23678 0.190158
26.58824 3.943134
0.041688 15
0.191769 67.04717
0.230714 28.25443
4.422391 0.045300
16 0.196011
65.02960 0.276691
29.74570 4.899500
0.048508 17
0.199859 63.18301
0.328335 31.06700
5.370360 0.051292
18 0.203333
61.50366 0.385841
32.22551 5.831334
0.053650 19
0.206452 59.98596
0.449337 33.22990
6.279212 0.055590
20 0.209239
58.62301 0.518883
34.08980 6.711179
0.057136 21
0.211713 57.40701
0.594460 34.81543
7.124786 0.058316
22 0.213898
56.32962 0.675964
35.41733 7.517920
0.059166 23
0.215817 55.38213
0.763202 35.90615
7.888793 0.059726
24 0.217491
54.55564 0.855888
36.29251 8.235922
0.060037 25
0.218945 53.84116
0.953643 36.58693
8.558120 0.060144
26 0.220200
53.22969 1.055992
36.79973 8.854495
0.060087 27
0.221280 52.71227
1.162373 36.94101
9.124443 0.059910
28 0.222206
52.28002 1.272137
37.02055 9.367649
0.059650 29
0.222999 51.92420
1.384559 37.04781
9.584084 0.059344
30 0.223678
51.63624 1.498850
37.03188 9.774003
0.059026 31
0.224264 51.40778
1.614167 36.98139
9.937940 0.058723
32 0.224773
51.23070 1.729634
36.90451 10.07669
0.058460 33
0.225222 51.09722
1.844354 36.80885
10.19132 0.058259
34 0.225625
50.99989 1.957434
36.70144 10.28310
0.058134 35
0.225995 50.93168
2.067998 36.58868
10.35355 0.058098
36 0.226345
50.88604 2.175210
36.47626 10.40433
0.058157 37
0.226683 50.85692
2.278293 36.36920
10.43727 0.058317
38 0.227018
50.83883 2.376540
36.27174 10.45431
0.058575 39
0.227358 50.82688
2.469335 36.18740
10.45746 0.058930
40 0.227707
50.81679 2.556159
36.11893 10.44875
0.059374 41
0.228070 50.80491
2.636603 36.06838
10.43021 0.059899
42 0.228450
50.78822 2.710366
36.03709 10.40382
0.060496 43
0.228847 50.76432
2.777262 36.02577
10.37149 0.061153
44 0.229263
50.73139 2.837215
36.03452 10.33501
0.061857 45
0.229697 50.68818
2.890256 36.06294
10.29603 0.062597
46 0.230149
50.63393 2.936512
36.11014 10.25605
0.063359 47
0.230615 50.56837
2.976200 36.17489
10.21640 0.064131
48 0.231094
50.49162 3.009612
36.25563 10.17824
0.064902 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 7 Hasil Analisis VECM, IRF, dan FEVD Jerman
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 22:07
Sample adjusted: 2000M04 2010M10 Included observations: 127 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 CointEq2
LNSP-1 1.000000
0.000000 I-1
0.000000 1.000000
LNINF-1 -55.78275
-237.7094 12.2434
36.8253 [-4.55617]
[-6.45506] LNER-1
-1.524239 -0.475096
0.66306 1.99433
[-2.29880] [-0.23822]
LNOIL-1 0.198707
0.457267 0.31573
0.94965 [ 0.62935]
[ 0.48151] TREND00M01
0.064128 0.331934
C 243.2637
1068.960 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
0.027622 0.299883
0.000492 0.028044
0.067969 0.03648
0.06912 0.00148
0.01720 0.04637
[ 0.75709] [ 4.33875]
[ 0.33119] [ 1.63006]
[ 1.46565] CointEq2
0.005051 -0.054977
0.001694 -0.011604
-0.012089 0.01172
0.02221 0.00048
0.00553 0.01490
[ 0.43090] [-2.47587]
[ 3.55113] [-2.09955]
[-0.81138] DLNSP-1
-0.012838 -0.016306
0.000937 -0.060189
0.298075 0.10050
0.19040 0.00409
0.04739 0.12775
[-0.12774] [-0.08564]
[ 0.22919] [-1.27001]
[ 2.33325] DLNSP-2
-0.113864 -0.319287
0.007301 0.021776
0.080449 0.10023
0.18989 0.00408
0.04727 0.12741
[-1.13598] [-1.68145]
[ 1.78980] [ 0.46072]
[ 0.63143] DI-1
-0.067174 0.075398
-0.004597 0.026319
-0.046350 0.04829
0.09149 0.00197
0.02277 0.06138
[-1.39099] [ 0.82414]
[-2.33884] [ 1.15574]
[-0.75509] DI-2
-0.024473 0.195562
-0.002077 -0.004873
-0.058690 0.04724
0.08950 0.00192
0.02228 0.06005
[-0.51804] [ 2.18516]
[-1.08009] [-0.21873]
[-0.97738]
DLNINF-1 1.156136
1.221476 -0.228274
1.580990 3.167303
2.23373 4.23167
0.09091 1.05331
2.83928 [ 0.51758]
[ 0.28865] [-2.51101]
[ 1.50098] [ 1.11553]
DLNINF-2 -0.995772
7.328524 0.053882
1.328964 -0.166516
2.13136 4.03774
0.08674 1.00503
2.70916 [-0.46720]
[ 1.81501] [ 0.62117]
[ 1.32231] [-0.06146]
DLNER-1 -0.096901
0.184677 -0.002621
0.036295 -0.460749
0.19854 0.37613
0.00808 0.09362
0.25237 [-0.48806]
[ 0.49100] [-0.32431]
[ 0.38768] [-1.82572]
DLNER-2 0.284911
0.337277 0.014025
-0.087162 0.011650
0.20711 0.39236
0.00843 0.09766
0.26326 [ 1.37564]
[ 0.85961] [ 1.66388]
[-0.89249] [ 0.04425]
DLNOIL-1 0.097665
0.282233 0.009422
-0.086328 0.176276
0.07959 0.15077
0.00324 0.03753
0.10116 [ 1.22717]
[ 1.87194] [ 2.90879]
[-2.30033] [ 1.74253]
DLNOIL-2 0.117374
0.259399 0.005151
-0.040103 0.094626
0.07839 0.14851
0.00319 0.03697
0.09965 [ 1.49722]
[ 1.74663] [ 1.61439]
[-1.08485] [ 0.94961]
C -0.035668
-0.045719 0.002875
-0.009175 0.010025
0.01614 0.03058
0.00066 0.00761
0.02052 [-2.20957]
[-1.49503] [ 4.37544]
[-1.20536] [ 0.48859]
TREND00M01 0.000716
0.000617 -3.77E-05
6.17E-05 -0.000209
0.00032 0.00060
1.3E-05 0.00015
0.00040 [ 2.25334]
[ 1.02533] [-2.91217]
[ 0.41159] [-0.51809]
DUMMY -0.052122
-0.082249 0.002751
-0.000801 0.009360
0.02579 0.04885
0.00105 0.01216
0.03278 [-2.02118]
[-1.68358] [ 2.62131]
[-0.06585] [ 0.28555]
R-squared 0.137289
0.547437 0.410615
0.125084 0.225995
Adj. R-squared 0.029450
0.490866 0.336942
0.015720 0.129244
Sum sq. resids 0.514628
1.846953 0.000852
0.114430 0.831474
S.E. equation 0.067786
0.128416 0.002759
0.031964 0.086162
F-statistic 1.273095
9.677080 5.573471
1.143738 2.335848
Log likelihood 169.5844
88.44108 576.1837
265.0553 139.1199
Akaike AIC -2.434400
-1.156552 -8.837538
-3.937878 -1.954645
Schwarz SC -2.098472
-0.820625 -8.501610
-3.601950 -1.618717
Mean dependent -0.001109
-0.022362 0.001266
-0.002971 0.007949
S.D. dependent 0.068806
0.179971 0.003388
0.032218 0.092335
Determinant resid covariance dof adj. 3.30E-15
Determinant resid covariance 1.76E-15
Log likelihood 1256.336
Akaike information criterion -18.44624
Schwarz criterion -16.54265
Impulse Response Function
Period 1
0.000000 2
0.008303 3
0.017936 4
0.014856 5
0.013450 6
0.013485 7
0.012737 8
0.012327 9
0.012346 10
0.012477 11
0.012643 12
0.012823 13
0.012965 14
0.013072 15
0.013149 16
0.013205 17
0.013248 18
0.013283 19
0.013313 20
0.013339 21
0.013362 22
0.013381 23
0.013398 24
0.013411 25
0.013421 26
0.013430 27
0.013437 28
0.013442 29
0.013446 30
0.013449 31
0.013451 32
0.013453 33
0.013455 34
0.013456 35
0.013456 36
0.013457 37
0.013457 38
0.013457 39
0.013457 40
0.013457 41
0.013457 42
0.013457 43
0.013457 44
0.013457 45
0.013457 46
0.013457 47
0.013456 48
0.013456 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.067786 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.096277
98.71551 0.161098
0.082248 0.297309
0.743833 3
0.116516 95.96224
0.363995 0.593209
0.203143 2.877414
4 0.135244
95.05503 0.495928
0.921416 0.185303
3.342319 5
0.152344 94.33478
0.632209 1.363922
0.255494 3.413598
6 0.167652
93.73986 0.712027
1.798563 0.283909
3.465642 7
0.181618 93.31908
0.754198 2.171708
0.310051 3.444960
8 0.194575
93.02568 0.774518
2.458523 0.338492
3.402785 9
0.206775 92.78847
0.782960 2.692643
0.366346 3.369581
10 0.218407
92.59385 0.786358
2.879811 0.393402
3.346582 11
0.229579 92.42268
0.788657 3.034959
0.421621 3.332079
12 0.240364
92.26676 0.791785
3.166827 0.450253
3.324372 13
0.250807 92.12233
0.796298 3.281719
0.479118 3.320533
14 0.260937
91.98802 0.802275
3.383238 0.507795
3.318674 15
0.270777 91.86321
0.809442 3.473753
0.535906 3.317688
16 0.280343
91.74758 0.817491
3.554784 0.563141
3.317004 17
0.289654 91.64073
0.826129 3.627451
0.589296 3.316390
18 0.298723
91.54212 0.835122
3.692717 0.614245
3.315797 19
0.307567 91.45113
0.844292 3.751424
0.637921 3.315230
20 0.316197
91.36714 0.853503
3.804349 0.660307
3.314701 21
0.324627 91.28953
0.862654 3.852187
0.681414 3.314219
22 0.332866
91.21773 0.871665
3.895559 0.701272
3.313779 23
0.340927 91.15122
0.880474 3.935004
0.719927 3.313372
24 0.348816
91.08955 0.889033
3.970992 0.737432
3.312991 25
0.356545 91.03230
0.897309 4.003924
0.753845 3.312626
26 0.364120
90.97908 0.905275
4.034149 0.769229
3.312272 27
0.371548 90.92954
0.912917 4.061969
0.783646 3.311926
28 0.378838
90.88338 0.920226
4.087643 0.797159
3.311589 29
0.385996 90.84031
0.927203 4.111400
0.809829 3.311258
30 0.393027
90.80006 0.933849
4.133438 0.821715
3.310935 31
0.399938 90.76240
0.940173 4.153931
0.832875 3.310621
32 0.406734
90.72711 0.946184
4.173033 0.843360
3.310316 33
0.413420 90.69399
0.951894 4.190878
0.853221 3.310021
34 0.420002
90.66286 0.957316
4.207585 0.862505
3.309736 35
0.426483 90.63356
0.962464 4.223260
0.871255 3.309460
36 0.432867
90.60595 0.967353
4.237994 0.879511
3.309195 37
0.439160 90.57988
0.971995 4.251870
0.887310 3.308940
38 0.445364
90.55525 0.976405
4.264962 0.894686
3.308694 39
0.451483 90.53194
0.980598 4.277336
0.901671 3.308459
40 0.457520
90.50984 0.984585
4.289048 0.908292
3.308233 41
0.463479 90.48888
0.988379 4.300152
0.914576 3.308016
42 0.469363
90.46896 0.991992
4.310694 0.920548
3.307808 43
0.475173 90.45001
0.995436 4.320716
0.926228 3.307608
44 0.480913
90.43197 0.998720
4.330258 0.931639
3.307417 45
0.486586 90.41476
1.001855 4.339352
0.936797 3.307234
46 0.492193
90.39834 1.004851
4.348030 0.941720
3.307058 47
0.497737 90.38265
1.007714 4.356321
0.946424 3.306889
48 0.503220
90.36765 1.010455
4.364250 0.950923
3.306727 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 8 Hasil Analisis VECM, IRF, dan FEVD Kanada
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 22:44
Sample adjusted: 2000M04 2010M10 Included observations: 127 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 CointEq2
CointEq3 LNSP-1
1.000000 0.000000
0.000000 I-1
0.000000 1.000000
0.000000 LNINF-1
0.000000 0.000000
1.000000 LNER-1
18.49512 103.5505
-0.698822 3.44505
19.6401 0.13947
[ 5.36861] [ 5.27239]
[-5.01071] LNOIL-1
4.719371 24.56018
-0.223918 0.96907
5.52464 0.03923
[ 4.87000] [ 4.44557]
[-5.70771] TREND00M01
0.013861 0.147821
-0.001871 C
-32.55580 -131.1222
-3.451520 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
-0.227902 0.102552
-0.007315 0.066688
-0.002046 0.05671
0.27300 0.00457
0.03349 0.10777
[-4.01868] [ 0.37565]
[-1.59931] [ 1.99107]
[-0.01898] CointEq2
0.023165 -0.039517
0.000398 -0.012845
0.001473 0.00650
0.03127 0.00052
0.00384 0.01234
[ 3.56620] [-1.26376]
[ 0.75894] [-3.34809]
[ 0.11937] CointEq3
-2.172334 -3.363621
-0.129661 0.027312
1.172609 0.79455
3.82485 0.06408
0.46926 1.50987
[-2.73403] [-0.87941]
[-2.02346] [ 0.05820]
[ 0.77663] DLNSP-1
0.285927 -0.704920
0.009274 -0.210219
0.547289 0.10975
0.52832 0.00885
0.06482 0.20856
[ 2.60523] [-1.33426]
[ 1.04782] [-3.24316]
[ 2.62418] DLNSP-2
-0.029288 1.245243
0.009295 0.036101
0.025815 0.11640
0.56033 0.00939
0.06875 0.22119
[-0.25162] [ 2.22234]
[ 0.99014] [ 0.52513]
[ 0.11671] DI-1
-0.005682 0.015794
0.001810 -0.007989
0.028842 0.01786
0.08595 0.00144
0.01055 0.03393
[-0.31826] [ 0.18375]
[ 1.25666] [-0.75756]
[ 0.85007] DI-2
-0.015937 0.084027
-0.001967 0.009350
-0.003009
0.01753 0.08437
0.00141 0.01035
0.03331 [-0.90928]
[ 0.99589] [-1.39156]
[ 0.90324] [-0.09035]
DLNINF-1 0.322706
4.615495 0.055516
1.415137 -0.481459
1.38394 6.66204
0.11161 0.81735
2.62985 [ 0.23318]
[ 0.69280] [ 0.49741]
[ 1.73136] [-0.18307]
DLNINF-2 0.885255
13.76775 0.089761
-0.204581 0.812556
1.29632 6.24027
0.10454 0.76561
2.46335 [ 0.68290]
[ 2.20627] [ 0.85859]
[-0.26721] [ 0.32986]
DLNER-1 0.379827
-1.173498 0.016458
-0.212649 0.163102
0.18706 0.90049
0.01509 0.11048
0.35547 [ 2.03048]
[-1.30318] [ 1.09092]
[-1.92478] [ 0.45884]
DLNER-2 0.131340
-0.683783 0.021249
-0.089693 0.145120
0.18503 0.89069
0.01492 0.10928
0.35160 [ 0.70984]
[-0.76770] [ 1.42401]
[-0.82079] [ 0.41274]
DLNOIL-1 0.066867
-0.034222 0.016484
-0.093848 0.199054
0.05962 0.28700
0.00481 0.03521
0.11329 [ 1.12156]
[-0.11924] [ 3.42826]
[-2.66529] [ 1.75699]
DLNOIL-2 0.113727
-0.299460 -0.005716
-0.086821 0.107331
0.05642 0.27158
0.00455 0.03332
0.10721 [ 2.01582]
[-1.10265] [-1.25621]
[-2.60569] [ 1.00115]
C -0.019802
-0.178727 0.001372
-0.000843 0.018534
0.01122 0.05401
0.00090 0.00663
0.02132 [-1.76508]
[-3.30941] [ 1.51645]
[-0.12729] [ 0.86939]
TREND00M01 0.000447
0.002856 5.66E-06
-7.72E-05 -0.000378
0.00020 0.00096
1.6E-05 0.00012
0.00038 [ 2.24455]
[ 2.97945] [ 0.35259]
[-0.65655] [-0.99976]
DUMMY -0.034632
-0.242586 -0.001105
0.006934 0.037149
0.01631 0.07853
0.00132 0.00964
0.03100 [-2.12276]
[-3.08890] [-0.84005]
[ 0.71960] [ 1.19828]
R-squared 0.273864
0.324069 0.276707
0.269226 0.310859
Adj. R-squared 0.175738
0.232727 0.178965
0.170473 0.217731
Sum sq. resids 0.205014
4.750796 0.001333
0.071511 0.740309
S.E. equation 0.042976
0.206882 0.003466
0.025382 0.081667
F-statistic 2.790929
3.547856 2.830989
2.726247 3.338001
Log likelihood 228.0276
28.44786 547.7714
294.9077 146.4943
Akaike AIC -3.339017
-0.196029 -8.374352
-4.392247 -2.055029
Schwarz SC -2.980694
0.162293 -8.016029
-4.033924 -1.696706
Mean dependent 0.002302
-0.034331 0.001684
-0.002770 0.007949
S.D. dependent 0.047337
0.236182 0.003825
0.027868 0.092335
Determinant resid covariance dof adj. 1.59E-15
Determinant resid covariance 8.09E-16
Log likelihood 1305.626
Akaike information criterion -19.06498
Schwarz criterion -16.93744
Impulse Response Function
Period 1
0.000000 2
0.002972 3
0.006280 4
0.003984 5
0.001514 6
-0.000507 7
-0.001683 8
-0.002491 9
-0.002840 10
-0.002776 11
-0.002436 12
-0.001854 13
-0.001113 14
-0.000281 15
0.000584 16
0.001425 17
0.002200 18
0.002879 19
0.003443 20
0.003883 21
0.004203 22
0.004410 23
0.004520 24
0.004549 25
0.004516 26
0.004439 27
0.004333 28
0.004215 29
0.004094 30
0.003981 31
0.003880 32
0.003797 33
0.003732 34
0.003686 35
0.003657 36
0.003643 37
0.003642 38
0.003650 39
0.003664 40
0.003683 41
0.003703 42
0.003724 43
0.003743 44
0.003759 45
0.003773 46
0.003784 47
0.003791 48
0.003795 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.042976 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.062888
99.00172 0.230521
0.472168 0.072318
0.223275 3
0.074607 97.45773
0.582135 0.798823
0.294169 0.867146
4 0.085671
92.73435 1.864136
2.499582 2.028089
0.873838 5
0.096117 85.43581
3.654329 5.745595
4.445216 0.719046
6 0.106100
77.53019 5.836959
9.026551 7.013921
0.592376 7
0.115608 70.11876
8.388335 11.84214
9.130616 0.520149
8 0.124285
63.85119 11.07944
13.99449 10.58465
0.490228 9
0.132049 58.75523
13.84386 15.47474
11.44563 0.480538
10 0.138914
54.65715 16.59902
16.43481 11.83487
0.474148 11
0.144970 51.35709
19.27356 17.01120
11.89457 0.463586
12 0.150352
48.67014 21.82088
17.31997 11.74281
0.446196 13
0.155189 46.45450
24.20251 17.45053
11.46849 0.423962
14 0.159597
44.60410 26.39586
17.46550 11.13337
0.401172 15
0.163678 43.04089
28.39042 17.40938
10.77663 0.382691
16 0.167510
41.70784 30.18534
17.31284 10.42137
0.372613 17
0.171160 40.56211
31.78764 17.19692
10.07991 0.373415
18 0.174678
39.57053 33.20947
17.07610 9.758205
0.385694 19
0.178104 38.70637
34.46632 16.96015
9.458796 0.408364
20 0.181468
37.94724 35.57543
16.85551 9.182670
0.439161 21
0.184792 37.27396
36.55462 16.76605
8.930139 0.475235
22 0.188091
36.67001 37.42145
16.69371 8.701132
0.513695 23
0.191374 36.12132
38.19263 16.63885
8.495176 0.552012
24 0.194644
35.61621 38.88360
16.60063 8.311310
0.588243 25
0.197903 35.14531
39.50824 16.57731
8.148033 0.621105
26 0.201147
34.70143 40.07868
16.56661 8.003359
0.649923 27
0.204374 34.27933
40.60525 16.56594
7.874953 0.674526
28 0.207576
33.87538 41.09648
16.57272 7.760317
0.695100 29
0.210750 33.48729
41.55916 16.58452
7.656979 0.712061
30 0.213890
33.11371 41.99850
16.59920 7.562653
0.725943 31
0.216992 32.75396
42.41835 16.61503
7.475354 0.737310
32 0.220054
32.40777 42.82140
16.63067 7.393450
0.746710 33
0.223072 32.07508
43.20944 16.64518
7.315677 0.754629
34 0.226047
31.75591 43.58354
16.65795 7.241113
0.761488 35
0.228978 31.45024
43.94431 16.66869
7.169131 0.767628
36 0.231866
31.15798 44.29204
16.67732 7.099341
0.773316 37
0.234711 30.87893
44.62685 16.68394
7.031533 0.778751
38 0.237517
30.61276 44.94879
16.68875 6.965624
0.784074 39
0.240284 30.35906
45.25793 16.69203
6.901609 0.789374
40 0.243016
30.11730 45.55439
16.69408 6.839530
0.794699 41
0.245713 29.88691
45.83838 16.69520
6.779445 0.800064
42 0.248379
29.66724 46.11022
16.69567 6.721409
0.805463 43
0.251014 29.45764
46.37030 16.69572
6.665463 0.810872
44 0.253621
29.25746 46.61909
16.69556 6.611628
0.816259 45
0.256201 29.06602
46.85714 16.69535
6.559900 0.821590
46 0.258756
28.88272 47.08501
16.69520 6.510247
0.826828 47
0.261286 28.70696
47.30330 16.69518
6.462619 0.831943
48 0.263793
28.53819 47.51263
16.69533 6.416945
0.836909 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 9 Hasil Analisis VECM, IRF, dan FEVD Korea
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 22:13
Sample adjusted: 2000M05 2010M09 Included observations: 125 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 CointEq2
CointEq3 CointEq4
LNSP-1 1.000000
0.000000 0.000000
0.000000 I-1
0.000000 1.000000
0.000000 0.000000
LNINF-1 0.000000
0.000000 1.000000
0.000000 LNER-1
0.000000 0.000000
0.000000 1.000000
LNOIL-1 -8.288456
-62.04090 0.377345
4.394511 1.97530
15.0159 0.09458
1.01181 [-4.19604]
[-4.13169] [ 3.98956]
[ 4.34324] TREND00M01
0.083014 0.713219
-0.006793 -0.048446
C 19.61330
188.7219 -5.609662
-20.80662 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
-0.207905 0.140598
-0.004752 -0.058449
0.106282 0.07767
0.10419 0.00406
0.03639 0.08879
[-2.67675] [ 1.34940]
[-1.17177] [-1.60602]
[ 1.19704] CointEq2
-0.014947 -0.067871
-0.000328 0.006060
-0.040179 0.00972
0.01304 0.00051
0.00455 0.01111
[-1.53808] [-5.20629]
[-0.64550] [ 1.33082]
[-3.61684] CointEq3
-2.957678 -4.219648
-0.280760 0.902912
0.767472 1.78447
2.39381 0.09316
0.83614 2.03988
[-1.65745] [-1.76273]
[-3.01359] [ 1.07986]
[ 0.37623] CointEq4
-0.368470 -0.324464
0.012137 -0.096472
-0.475818 0.16912
0.22687 0.00883
0.07925 0.19333
[-2.17870] [-1.43015]
[ 1.37456] [-1.21738]
[-2.46117] DLNSP-1
0.067542 0.159083
0.007454 -0.007800
0.060709 0.10393
0.13942 0.00543
0.04870 0.11881
[ 0.64988] [ 1.14104]
[ 1.37381] [-0.16018]
[ 0.51099] DLNSP-2
0.172564 -0.178972
0.001883 -0.004401
0.063636 0.10056
0.13490 0.00525
0.04712 0.11495
[ 1.71602] [-1.32671]
[ 0.35863] [-0.09339]
[ 0.55358] DLNSP-3
0.140365 0.076678
0.002936 -0.045108
-0.046056
0.09606 0.12886
0.00502 0.04501
0.10981 [ 1.46126]
[ 0.59506] [ 0.58551]
[-1.00220] [-0.41943]
DI-1 0.024988
0.450351 0.000712
0.054534 0.154857
0.06729 0.09027
0.00351 0.03153
0.07692 [ 0.37135]
[ 4.98906] [ 0.20270]
[ 1.72960] [ 2.01319]
DI-2 -0.035583
0.048631 -0.002116
0.019237 -0.160726
0.07344 0.09852
0.00383 0.03441
0.08395 [-0.48452]
[ 0.49364] [-0.55189]
[ 0.55904] [-1.91457]
DI-3 -0.051320
-0.194466 0.000722
-0.005900 0.047092
0.06204 0.08322
0.00324 0.02907
0.07092 [-0.82723]
[-2.33668] [ 0.22296]
[-0.20296] [ 0.66403]
DLNINF-1 -2.385813
7.944009 0.337531
0.029398 1.511165
2.09107 2.80510
0.10917 0.97980
2.39036 [-1.14095]
[ 2.83198] [ 3.09175]
[ 0.03000] [ 0.63219]
DLNINF-2 2.638506
-0.307416 -0.073617
-0.111615 2.264450
2.09073 2.80464
0.10915 0.97964
2.38997 [ 1.26200]
[-0.10961] [-0.67443]
[-0.11393] [ 0.94748]
DLNINF-3 -0.682843
6.878897 -0.166869
-0.168054 1.237030
2.02983 2.72295
0.10597 0.95111
2.32035 [-0.33640]
[ 2.52627] [-1.57462]
[-0.17669] [ 0.53312]
DLNER-1 0.387040
0.216042 0.007693
-0.164517 0.116579
0.24669 0.33093
0.01288 0.11559
0.28200 [ 1.56894]
[ 0.65284] [ 0.59734]
[-1.42328] [ 0.41341]
DLNER-2 0.798672
-0.356558 -0.007490
-0.290048 0.093419
0.23029 0.30893
0.01202 0.10791
0.26326 [ 3.46805]
[-1.15416] [-0.62293]
[-2.68793] [ 0.35486]
DLNER-3 0.033508
0.274323 0.002032
0.030536 -0.200098
0.23450 0.31457
0.01224 0.10988
0.26806 [ 0.14289]
[ 0.87206] [ 0.16598]
[ 0.27791] [-0.74647]
DLNOIL-1 -0.009686
0.103348 0.006630
-0.082861 0.098983
0.09101 0.12208
0.00475 0.04264
0.10403 [-0.10643]
[ 0.84655] [ 1.39535]
[-1.94318] [ 0.95148]
DLNOIL-2 -0.005045
0.261085 -0.000260
-0.047871 -0.021777
0.08633 0.11581
0.00451 0.04045
0.09869 [-0.05844]
[ 2.25446] [-0.05758]
[-1.18343] [-0.22067]
DLNOIL-3 0.191695
0.065286 0.001447
-0.136391 -0.016646
0.08563 0.11488
0.00447 0.04013
0.09789 [ 2.23851]
[ 0.56831] [ 0.32375]
[-3.39912] [-0.17004]
C 0.006766
-0.042878 0.002522
0.020062 0.033779
0.02254 0.03024
0.00118 0.01056
0.02577 [ 0.30013]
[-1.41786] [ 2.14305]
[ 1.89927] [ 1.31079]
TREND00M01 -8.84E-05
-0.000279 -2.80E-06
-0.000447 -0.001027
0.00042 0.00056
2.2E-05 0.00019
0.00048 [-0.21256]
[-0.50093] [-0.12903]
[-2.29145] [-2.16053]
DUMMY 0.007496
0.014593 -0.000111
0.046075 0.095105
0.03630 0.04870
0.00190 0.01701
0.04150 [ 0.20651]
[ 0.29968] [-0.05851]
[ 2.70882] [ 2.29189]
R-squared 0.330987
0.739945 0.339036
0.340348 0.404096
Adj. R-squared 0.194586
0.686924 0.204277
0.205856 0.282601
Sum sq. resids 0.476000
0.856578 0.001297
0.104507 0.622008
S.E. equation 0.067981
0.091194 0.003549
0.031853 0.077710
F-statistic 2.426577
13.95569 2.515862
2.530614 3.326034
Log likelihood 170.7983
134.0779 539.8622
265.5585 154.0774
Akaike AIC -2.380773
-1.793246 -8.285795
-3.896936 -2.113239
Schwarz SC -1.882990
-1.295463 -7.788012
-3.399153 -1.615456
Mean dependent 0.007588
-0.022640 0.002700
0.000221 0.008587
S.D. dependent 0.075749
0.162982 0.003979
0.035744 0.091749
Determinant resid covariance dof adj. 2.10E-15
Determinant resid covariance 7.99E-16
Log likelihood 1285.870
Akaike information criterion -18.49391
Schwarz criterion -15.55247
Impulse Response Function
Period 1
0.000000 2
-0.006644 3
-0.016569 4
-0.009959 5
-0.018680 6
-0.024818 7
-0.024257 8
-0.024098 9
-0.024507 10
-0.023192 11
-0.020982 12
-0.019309 13
-0.017816 14
-0.016781 15
-0.016081 16
-0.015519 17
-0.014963 18
-0.014385 19
-0.013762 20
-0.013118 21
-0.012509 22
-0.011973 23
-0.011538 24
-0.011214 25
-0.010999 26
-0.010878 27
-0.010834 28
-0.010849 29
-0.010907 30
-0.010997 31
-0.011110 32
-0.011237 33
-0.011372 34
-0.011511 35
-0.011647 36
-0.011777 37
-0.011896 38
-0.012002 39
-0.012093 40
-0.012168 41
-0.012227 42
-0.012271 43
-0.012301 44
-0.012319 45
-0.012326 46
-0.012325 47
-0.012316 48
-0.012302 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.067981 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.093210
94.00100 0.097733
5.372013 0.021164
0.508092 3
0.111474 86.72848
0.156781 9.147048
1.403184 2.564503
4 0.125511
82.92010 0.311874
13.00466 1.110868
2.652506 5
0.136712 77.01979
0.366326 16.99322
1.517987 4.102674
6 0.146376
70.32603 0.652169
20.76034 1.807837
6.453624 7
0.154178 64.69625
0.753558 23.71933
2.538480 8.292379
8 0.160382
60.51614 0.731600
25.58999 3.241482
9.920795 9
0.165557 57.15756
0.688639 26.88693
3.765416 11.50145
10 0.169479
54.76572 0.706996
27.52878 4.150587
12.84792 11
0.172462 53.06726
0.817686 27.82494
4.402668 13.88745
12 0.174875
51.77162 1.004657
27.96109 4.536491
14.72613 13
0.176955 50.71065
1.240401 28.06112
4.592255 15.39557
14 0.178866
49.77022 1.506647
28.17317 4.601267
15.94870 15
0.180684 48.89517
1.787349 28.31773
4.578248 16.42150
16 0.182443
48.06178 2.079345
28.49164 4.537295
16.82994 17
0.184144 47.27021
2.382320 28.68012
4.486726 17.18063
18 0.185787
46.52299 2.696487
28.87140 4.431478
17.47764 19
0.187365 45.82543
3.019089 29.05665
4.374856 17.72398
20 0.188879
45.17915 3.345432
29.23330 4.318905
17.92321 21
0.190338 44.58194
3.668896 29.40296
4.264680 18.08153
22 0.191751
44.02887 3.982639
29.57000 4.212696
18.20579 23
0.193134 43.51366
4.281029 29.73912
4.163222 18.30297
24 0.194498
43.02971 4.560201
29.91413 4.116403
18.37955 25
0.195854 42.57098
4.818225 30.09719
4.072406 18.44119
26 0.197211
42.13255 5.054777
30.28869 4.031428
18.49256 27
0.198573 41.71062
5.270683 30.48768
3.993662 18.53735
28 0.199944
41.30243 5.467432
30.69243 3.959236
18.57847 29
0.201324 40.90593
5.646831 30.90094
3.928185 18.61812
30 0.202714
40.51957 5.810768
31.11127 3.900426
18.65797 31
0.204114 40.14208
5.961087 31.32178
3.875772 18.69928
32 0.205521
39.77243 6.099545
31.53112 3.853946
18.74296 33
0.206936 39.40973
6.227795 31.73823
3.834616 18.78963
34 0.208355
39.05332 6.347388
31.94222 3.817413
18.83966 35
0.209778 38.70271
6.459760 32.14239
3.801960 18.89318
36 0.211203
38.35763 6.566229
32.33814 3.787889
18.95011 37
0.212627 38.01799
6.667971 32.52899
3.774856 19.01019
38 0.214048
37.68385 6.766011
32.71456 3.762557
19.07303 39
0.215464 37.35533
6.861216 32.89460
3.750727 19.13812
40 0.216874
37.03266 6.954290
33.06899 3.739151
19.20491 41
0.218275 36.71602
7.045784 33.23771
3.727663 19.27282
42 0.219668
36.40562 7.136107
33.40086 3.716140
19.34127 43
0.221051 36.10160
7.225542 33.55861
3.704502 19.40975
44 0.222423
35.80408 7.314265
33.71119 3.692706
19.47777 45
0.223784 35.51311
7.402365 33.85887
3.680735 19.54492
46 0.225135
35.22873 7.489859
34.00193 3.668599
19.61088 47
0.226474 34.95091
7.576714 34.14069
3.656323 19.67536
48 0.227802
34.67959 7.662854
34.27543 3.643942
19.73819 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 10 Hasil Analisis VECM, IRF, dan FEVD Malaysia
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 21:44
Sample adjusted: 2000M03 2010M10 Included observations: 128 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 CointEq2
LNSP-1 1.000000
0.000000 I-1
0.000000 1.000000
LNINF-1 -20.79920
25.60123 4.70845
8.05405 [-4.41742]
[ 3.17868] LNER-1
0.043906 18.31419
2.14236 3.66461
[ 0.02049] [ 4.99758]
LNOIL-1 -0.883228
-1.561629 0.25892
0.44290 [-3.41119]
[-3.52594] TREND00M01
0.045073 -0.009244
C 89.61994
-138.0137 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
0.051438 -0.067250
-2.33E-05 -0.010018
0.119628 0.01294
0.04946 0.00117
0.00321 0.02288
[ 3.97465] [-1.35955]
[-0.02001] [-3.11644]
[ 5.22858] CointEq2
0.024178 -0.123842
-0.002787 -0.003764
0.003829 0.00695
0.02658 0.00063
0.00173 0.01229
[ 3.47719] [-4.65982]
[-4.44698] [-2.17945]
[ 0.31145] DLNSP-1
-0.079128 -0.191136
-0.014278 0.016565
0.174265 0.09428
0.36036 0.00850
0.02342 0.16668
[-0.83927] [-0.53040]
[-1.68006] [ 0.70734]
[ 1.04550] DI-1
0.000140 -0.239098
-0.001005 -0.009415
-0.008513 0.02182
0.08341 0.00197
0.00542 0.03858
[ 0.00640] [-2.86652]
[-0.51115] [-1.73688]
[-0.22066] DLNINF-1
-2.476418 -3.401373
0.182805 -0.261806
6.222405 1.00060
3.82446 0.09019
0.24853 1.76897
[-2.47493] [-0.88937]
[ 2.02682] [-1.05341]
[ 3.51753] DLNER-1
0.916483 0.982159
0.085807 0.186279
-0.626952 0.41081
1.57018 0.03703
0.10204 0.72628
[2.23091] [ 0.62551]
[ 2.31723] [ 1.82557]
[-0.86324]
DLNOIL-1 -0.005315
-0.108706 0.001215
-0.014254 0.074697
0.04908 0.18759
0.00442 0.01219
0.08677 [-0.10829]
[-0.57948] [ 0.27457]
[-1.16927] [ 0.86086]
C -0.013655
-0.055530 0.000686
-2.82E-05 0.020525
0.00975 0.03726
0.00088 0.00242
0.01724 [-1.40067]
[-1.49027] [ 0.78016]
[-0.01164] [ 1.19089]
TREND00M01 0.000191
0.001830 1.69E-05
9.90E-06 -0.000664
0.00020 0.00076
1.8E-05 4.9E-05
0.00035 [ 0.95960]
[ 2.40940] [ 0.94411]
[ 0.20054] [-1.89102]
DUMMY -0.003150
-0.172367 -0.000871
-0.004337 0.057307
0.01615 0.06171
0.00146 0.00401
0.02854 [-0.19509]
[-2.79318] [-0.59835]
[-1.08140] [ 2.00772]
R-squared 0.244733
0.220703 0.269326
0.161084 0.327408
Adj. R-squared 0.187128
0.161265 0.213596
0.097099 0.276108
Sum sq. resids 0.231187
3.377385 0.001878
0.014263 0.722573
S.E. equation 0.044263
0.169180 0.003990
0.010994 0.078253
F-statistic 4.248468
3.713172 4.832740
2.517531 6.382291
Log likelihood 222.6357
51.01129 530.6558
400.9118 149.7017
Akaike AIC -3.322433
-0.640801 -8.135248
-6.107997 -2.182840
Schwarz SC -3.099618
-0.417987 -7.912433
-5.885183 -1.960025
Mean dependent 0.003337
0.000937 0.001762
-0.001565 0.008011
S.D. dependent 0.049094
0.184730 0.004499
0.011570 0.091974
Determinant resid covariance dof adj. 5.72E-16
Determinant resid covariance 3.81E-16
Log likelihood 1364.180
Akaike information criterion -20.37782
Schwarz criterion -19.04093
Impulse Response Function
Period 1
0.000000 2
-0.006734 3
-0.011518 4
-0.016558 5
-0.020661 6
-0.023867 7
-0.026164 8
-0.027581 9
-0.028183 10
-0.028071 11
-0.027369 12
-0.026217 13
-0.024757 14
-0.023126 15
-0.021449 16
-0.019831 17
-0.018358 18
-0.017092 19
-0.016073 20
-0.015321 21
-0.014834 22
-0.014597 23
-0.014583 24
-0.014756 25
-0.015074 26
-0.015494 27
-0.015976 28
-0.016479 29
-0.016972 30
-0.017427 31
-0.017824 32
-0.018148 33
-0.018393 34
-0.018558 35
-0.018646 36
-0.018666 37
-0.018626 38
-0.018540 39
-0.018419 40
-0.018278 41
-0.018127 42
-0.017978 43
-0.017838 44
-0.017714 45
-0.017611 46
-0.017532 47
-0.017476 48
-0.017445 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.044263 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.063080
97.11274 0.093701
1.040414 0.613429
1.139712 3
0.078039 95.48711
0.297091 0.890549
0.402246 2.923002
4 0.091166
92.93613 0.499348
0.652744 0.471161
5.440620 5
0.103265 89.52658
0.781123 0.597402
0.851472 8.243425
6 0.114664
85.68299 1.099876
0.664104 1.534437
11.01860 7
0.125474 81.79044
1.430809 0.744825
2.483889 13.55004
8 0.135703
78.11840 1.748954
0.776215 3.641202
15.71523 9
0.145332 74.81775
2.038080 0.746503
4.935152 17.46252
10 0.154346
71.95084 2.288274
0.678540 6.292339
18.79001 11
0.162752 69.52302
2.494947 0.610499
7.644587 19.72695
12 0.170579
67.50772 2.657417
0.580920 8.933665
20.32028 13
0.177872 65.86361
2.777845 0.619199
10.11409 20.62526
14 0.184688
64.54514 2.860333
0.740965 11.15445
20.69911 15
0.191083 63.50840
2.910173 0.947354
12.03741 20.59666
16 0.197116
62.71373 2.933203
1.227105 12.75848
20.36749 17
0.202835 62.12634
2.935280 1.560349
13.32384 20.05419
18 0.208285
61.71583 2.921875
1.923002 13.74751
19.69178 19
0.213503 61.45515
2.897811 2.290853
14.04840 19.30778
20 0.218520
61.31963 2.867131
2.642725 14.24753
18.92298 21
0.223363 61.28611
2.833081 2.962424
14.36594 18.55244
22 0.228054
61.33261 2.798162
3.239486 14.42310
18.20664 23
0.232617 61.43821
2.764235 3.468959
14.43614 17.89246
24 0.237070
61.58339 2.732626
3.650520 14.41947
17.61399 25
0.241432 61.75047
2.704232 3.787285
14.38488 17.37313
26 0.245718
61.92413 2.679600
3.884568 14.34171
17.17000 27
0.249941 62.09178
2.658997 3.948781
14.29721 17.00323
28 0.254111
62.24387 2.642456
3.986585 14.25684
16.87025 29
0.258237 62.37392
2.629814 4.004311
14.22448 16.76748
30 0.262322
62.47830 2.620757
4.007619 14.20268
16.69064 31
0.266369 62.55591
2.614847 4.001364
14.19282 16.63506
32 0.270378
62.60770 2.611572
3.989567 14.19525
16.59591 33
0.274348 62.63611
2.610374 3.975472
14.20949 16.56855
34 0.278277
62.64460 2.610696
3.961618 14.23434
16.54875 35
0.282163 62.63711
2.612007 3.949920
14.26813 16.53284
36 0.286002
62.61772 2.613833
3.941735 14.30887
16.51784 37
0.289794 62.59035
2.615776 3.937922
14.35446 16.50149
38 0.293537
62.55852 2.617518
3.938895 14.40281
16.48226 39
0.297230 62.52523
2.618833 3.944685
14.45200 16.45925
40 0.300873
62.49293 2.619572
3.954995 14.50037
16.43214 41
0.304467 62.46346
2.619664 3.969279
14.54658 16.40102
42 0.308012
62.43811 2.619099
3.986811 14.58965
16.36633 43
0.311510 62.41767
2.617916 4.006762
14.62891 16.32874
44 0.314962
62.40246 2.616188
4.028273 14.66404
16.28904 45
0.318371 62.39245
2.614012 4.050517
14.69497 16.24805
46 0.321739
62.38730 2.611496
4.072750 14.72186
16.20660 47
0.325068 62.38646
2.608750 4.094341
14.74502 16.16543
48 0.328359
62.38923 2.605881
4.114799 14.76490
16.12519 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 11 Hasil Analisis VECM, IRF, dan FEVD Meksiko
Vector Error Correction Model
Vector Error Correction Estimates Date: 052711 Time: 10:08
Sample adjusted: 2000M03 2010M10 Included observations: 128 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 LNSP-1
1.000000 I-1
0.003618 0.01445
[ 0.25045] LNINF-1
22.58736 3.72087
[ 6.07044] LNER-1
0.087237 0.56467
[ 0.15449] LNOIL-1
-0.284785 0.17769
[-1.60272] TREND00M01
-0.096313 C
-106.2024 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
-0.049042 -0.054375
-0.008120 -0.005353
0.114577 0.03811
0.47288 0.00174
0.01781 0.05377
[-1.28670] [-0.11499]
[-4.66822] [-0.30054]
[ 2.13072] DLNSP-1
-0.056305 -3.239922
-0.002436 0.049769
0.258163 0.09974
1.23745 0.00455
0.04661 0.14072
[-0.56451] [-2.61823]
[-0.53514] [1.06773]
[ 1.83461] DI-1
-0.002675 0.008952
0.000133 -0.003983
0.007166 0.00752
0.09324 0.00034
0.00351 0.01060
[-0.35599] [ 0.09601]
[ 0.38698] [-1.13406]
[ 0.67585] DLNINF-1
2.081691 40.00589
0.420870 0.077862
-8.340905 1.79708
22.2958 0.08201
0.83984 2.53540
[ 1.15837] [ 1.79432]
[ 5.13207] [ 0.09271]
[-3.28977] DLNER-1
0.530751 2.182126
0.010645 0.093968
-0.322390 0.21732
2.69621 0.00992
0.10156 0.30660
[2.44227] [ 0.80933]
[ 1.07341] [ 0.92524]
[-1.05149] DLNOIL-1
0.021252 1.066692
0.001728 -0.026828
0.148051
0.06299 0.78148
0.00287 0.02944
0.08887 [ 0.33740]
[ 1.36496] [ 0.60127]
[-0.91139] [ 1.66598]
C -0.030904
-0.536390 0.002319
0.001958 0.062762
0.01743 0.21624
0.00080 0.00815
0.02459 [-1.77310]
[-2.48054] [ 2.91567]
[ 0.24039] [ 2.55232]
TREND00M01 0.000922
0.007287 1.54E-06
4.01E-06 -0.000645
0.00028 0.00346
1.3E-05 0.00013
0.00039 [ 3.30833]
[ 2.10702] [ 0.12115]
[ 0.03076] [-1.63913]
DUMMY -0.076100
-0.506001 -0.000663
-1.35E-05 0.052694
0.02253 0.27949
0.00103 0.01053
0.03178 [-3.37813]
[-1.81046] [-0.64515]
[-0.00128] [ 1.65797]
R-squared 0.139116
0.119069 0.341676
0.056159 0.213266
Adj. R-squared 0.081241
0.059846 0.297419
-0.007292 0.160377
Sum sq. resids 0.424618
65.35989 0.000884
0.092737 0.845197
S.E. equation 0.059735
0.741109 0.002726
0.027916 0.084276
F-statistic 2.403741
2.010537 7.720256
0.885072 4.032291
Log likelihood 183.7260
-138.6084 578.8754
281.0970 139.6697
Akaike AIC -2.730094
2.306381 -8.904304
-4.251515 -2.041714
Schwarz SC -2.529561
2.506914 -8.703770
-4.050982 -1.841181
Mean dependent 0.012299
-0.092031 0.003825
0.002239 0.008011
S.D. dependent 0.062320
0.764333 0.003252
0.027815 0.091974
Determinant resid covariance dof adj. 5.40E-14
Determinant resid covariance 3.75E-14
Log likelihood 1070.451
Akaike information criterion -15.94454
Schwarz criterion -14.83047
Impulse Response Function
Period 1
0.000000 2
0.002719 3
0.004935 4
0.006017 5
0.006365 6
0.006421 7
0.006372 8
0.006303 9
0.006246 10
0.006210 11
0.006191 12
0.006185 13
0.006184 14
0.006186 15
0.006189 16
0.006191 17
0.006192 18
0.006193 19
0.006193 20
0.006193 21
0.006193 22
0.006193 23
0.006193 24
0.006193 25
0.006193 26
0.006193 27
0.006193 28
0.006193 29
0.006193 30
0.006193 31
0.006193 32
0.006193 33
0.006193 34
0.006193 35
0.006193 36
0.006193 37
0.006193 38
0.006193 39
0.006193 40
0.006193 41
0.006193 42
0.006193 43
0.006193 44
0.006193 45
0.006193 46
0.006193 47
0.006193 48
0.006193 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.059735 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.086067
97.00803 0.105182
0.043427 2.743573
0.099786 3
0.106298 95.82675
0.070891 0.053969
3.767442 0.280947
4 0.122816
94.79134 0.054974
0.239054 4.464162
0.450473 5
0.137401 93.87286
0.046417 0.582812
4.923379 0.574537
6 0.150716
93.06820 0.042418
0.969151 5.261205
0.659025 7
0.163083 92.41250
0.040635 1.316378
5.514978 0.715505
8 0.174666
91.90199 0.039816
1.594112 5.710132
0.753953 9
0.185576 91.51231
0.039313 1.804629
5.862554 0.781191
10 0.195900
91.21385 0.038881
1.962109 5.983646
0.801510 11
0.205711 90.98090
0.038456 2.081616
6.081569 0.817463
12 0.215073
90.79412 0.038038
2.175096 6.162210
0.830531 13
0.224041 90.64014
0.037643 2.250869
6.229784 0.841565
14 0.232660
90.51002 0.037281
2.314328 6.287300
0.851068 15
0.240968 90.39792
0.036959 2.368848
6.336920 0.859355
16 0.248998
90.29994 0.036675
2.416528 6.380213
0.866639 17
0.256776 90.21343
0.036425 2.458719
6.418345 0.873083
18 0.264326
90.13644 0.036205
2.496341 6.452197
0.878813 19
0.271665 90.06752
0.036010 2.530078
6.482453 0.883937
20 0.278812
90.00550 0.035836
2.560471 6.509656
0.888542 21
0.285780 89.94941
0.035679 2.587966
6.534244 0.892701
22 0.292583
89.89847 0.035537
2.612942 6.556574
0.896476 23
0.299230 89.85201
0.035407 2.635722
6.576942 0.899918
24 0.305734
89.80947 0.035288
2.656579 6.595596
0.903070 25
0.312101 89.77037
0.035179 2.675746
6.612742 0.905967
26 0.318342
89.73431 0.035078
2.693422 6.628557
0.908639 27
0.324462 89.70094
0.034985 2.709774
6.643189 0.911111
28 0.330469
89.66998 0.034898
2.724948 6.656768
0.913405 29
0.336369 89.64118
0.034817 2.739066
6.669401 0.915539
30 0.342167
89.61431 0.034742
2.752236 6.681186
0.917530 31
0.347869 89.58918
0.034672 2.764549
6.692204 0.919392
32 0.353478
89.56564 0.034606
2.776087 6.702529
0.921137 33
0.359000 89.54354
0.034544 2.786921
6.712223 0.922774
34 0.364439
89.52274 0.034486
2.797113 6.721343
0.924315 35
0.369797 89.50314
0.034431 2.806718
6.729938 0.925768
36 0.375079
89.48464 0.034379
2.815787 6.738053
0.927139 37
0.380287 89.46715
0.034330 2.824361
6.745725 0.928435
38 0.385425
89.45058 0.034284
2.832482 6.752992
0.929663 39
0.390495 89.43487
0.034240 2.840184
6.759884 0.930827
40 0.395501
89.41994 0.034198
2.847498 6.766428
0.931933 41
0.400444 89.40575
0.034159 2.854453
6.772652 0.932985
42 0.405326
89.39224 0.034121
2.861075 6.778578
0.933986 43
0.410151 89.37936
0.034085 2.867388
6.784226 0.934940
44 0.414919
89.36707 0.034050
2.873412 6.789617
0.935851 45
0.419633 89.35533
0.034018 2.879167
6.794766 0.936721
46 0.424295
89.34410 0.033986
2.884670 6.799690
0.937553 47
0.428906 89.33335
0.033956 2.889938
6.804404 0.938349
48 0.433468
89.32305 0.033927
2.894985 6.808921
0.939112 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 12 Hasil Analisis VECM, IRF, dan FEVD Perancis
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 21:44
Sample adjusted: 2000M03 2010M10 Included observations: 128 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 CointEq2
LNSP-1 1.000000
0.000000 I-1
0.000000 1.000000
LNINF-1 -16374.06
-77312.05 3668.49
17328.1 [-4.46344]
[-4.46165] LNER-1
-978.7866 -4622.265
224.570 1060.76
[-4.35850] [-4.35752]
LNOIL-1 18.60631
83.85969 84.5019
399.145 [ 0.22019]
[ 0.21010] TREND00M01
19.80875 93.58315
C 73777.91
348399.5 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
-0.012159 0.261622
-0.000748 0.029996
-0.057371 0.02111
0.06377 0.00095
0.01242 0.03243
[-0.57592] [ 4.10263]
[-0.79038] [ 2.41554]
[-1.76931] CointEq2
0.002607 -0.055353
0.000161 -0.006336
0.012195 0.00447
0.01350 0.00020
0.00263 0.00687
[ 0.58311] [-4.09888]
[ 0.80134] [-2.40944]
[ 1.77597] DLNSP-1
0.022195 0.565196
0.001470 -0.063844
0.405928 0.09351
0.28244 0.00419
0.05500 0.14361
[ 0.23736] [ 2.00115]
[ 0.35089] [-1.16083]
[ 2.82653] DI-1
0.010112 0.054168
0.001150 -0.028185
0.084524 0.03299
0.09965 0.00148
0.01940 0.05067
[ 0.30651] [ 0.54358]
[ 0.77786] [-1.45250]
[ 1.66811] DLNINF-1
3.656010 4.968048
0.031647 0.966812
1.859357 2.04105
6.16489 0.09146
1.20048 3.13475
[ 1.79124] [ 0.80586]
[ 0.34601] [ 0.80535]
[ 0.59314] DLNER-1
0.033383 0.137438
0.016224 0.020632
-0.251323 0.16335
0.49338 0.00732
0.09608 0.25088
[ 0.20437] [ 0.27856]
[ 2.21639] [ 0.21475]
[-1.00178]
DLNOIL-1 -0.021551
0.178788 0.009119
-0.047654 0.142105
0.06353 0.19187
0.00285 0.03736
0.09757 [-0.33925]
[ 0.93180] [ 3.20324]
[-1.27541] [ 1.45651]
C -0.032505
-0.021978 0.001724
-0.003184 0.005210
0.01211 0.03658
0.00054 0.00712
0.01860 [-2.68395]
[-0.60081] [ 3.17755]
[-0.44695] [ 0.28011]
TREND00M01 0.000592
0.000320 -6.11E-06
-4.04E-05 -2.58E-05
0.00022 0.00067
1.0E-05 0.00013
0.00034 [ 2.65339]
[ 0.47472] [-0.61145]
[-0.30829] [-0.07536]
DUMMY -0.046679
-0.082170 0.000121
0.004110 0.010505
0.01806 0.05454
0.00081 0.01062
0.02773 [-2.58510]
[-1.50661] [ 0.14974]
[ 0.38702] [ 0.37880]
R-squared 0.124896
0.350902 0.248297
0.090604 0.242271
Adj. R-squared 0.058151
0.301395 0.190964
0.021244 0.184478
Sum sq. resids 0.345101
3.148399 0.000693
0.119385 0.814037
S.E. equation 0.054079
0.163344 0.002423
0.031808 0.083058
F-statistic 1.871240
7.087862 4.330768
1.306279 4.192047
Log likelihood 196.9965
55.50459 594.4732
264.9316 142.0738
Akaike AIC -2.921820
-0.711009 -9.132393
-3.983307 -2.063653
Schwarz SC -2.699006
-0.488194 -8.909578
-3.760492 -1.840838
Mean dependent -0.003745
-0.021719 0.001406
-0.002797 0.008011
S.D. dependent 0.055724
0.195428 0.002694
0.032151 0.091974
Determinant resid covariance dof adj. 2.01E-15
Determinant resid covariance 1.34E-15
Log likelihood 1283.730
Akaike information criterion -19.12079
Schwarz criterion -17.78390
Impulse Response Function
Period 1
0.000000 2
-0.002099 3
-0.001582 4
-0.003258 5
-0.004980 6
-0.006537 7
-0.007859 8
-0.008952 9
-0.009845 10
-0.010571 11
-0.011161 12
-0.011643 13
-0.012036 14
-0.012359 15
-0.012625 16
-0.012844 17
-0.013026 18
-0.013177 19
-0.013302 20
-0.013407 21
-0.013494 22
-0.013567 23
-0.013628 24
-0.013679 25
-0.013722 26
-0.013758 27
-0.013788 28
-0.013813 29
-0.013834 30
-0.013852 31
-0.013867 32
-0.013880 33
-0.013891 34
-0.013900 35
-0.013907 36
-0.013913 37
-0.013919 38
-0.013923 39
-0.013927 40
-0.013930 41
-0.013933 42
-0.013935 43
-0.013937 44
-0.013939 45
-0.013940 46
-0.013941 47
-0.013942 48
-0.013943 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.054079 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.077410
99.54793 0.084716
0.093786 0.200026
0.073543 3
0.096098 98.79661
0.256223 0.177199
0.695149 0.074815
4 0.113177
97.08389 0.423186
0.710256 1.645878
0.136792 5
0.128951 94.96430
0.553171 1.524761
2.703243 0.254525
6 0.143531
92.85012 0.641819
2.413452 3.681778
0.412836 7
0.156980 90.94325
0.697964 3.253913
4.509110 0.595766
8 0.169374
89.30821 0.731005
3.994290 5.175393
0.791105 9
0.180810 87.94113
0.748308 4.622651
5.697262 0.990646
10 0.191393
86.81085 0.755109
5.145722 6.099155
1.189161 11
0.201228 85.87922
0.754995 5.577176
6.405192 1.383421
12 0.210411
85.10990 0.750394
5.931978 6.636241
1.571484 13
0.219030 84.47156
0.742942 6.223966
6.809303 1.752229
14 0.227161
83.93836 0.733744
6.465029 6.937804
1.925058 15
0.234869 83.48955
0.723543 6.665004
7.032178 2.089720
16 0.242209
83.10864 0.712843
6.831867 7.100460
2.246186 17
0.249230 82.78261
0.701981 6.972017
7.148816 2.394578
18 0.255971
82.50117 0.691183
7.090557 7.181969
2.535117 19
0.262464 82.25623
0.680597 7.191551
7.203538 2.668089
20 0.268739
82.04133 0.670317
7.278237 7.216300
2.793819 21
0.274819 81.85135
0.660402 7.353199
7.222388 2.912657
22 0.280724
81.68221 0.650883
7.418501 7.223442
3.024963 23
0.286472 81.53060
0.641777 7.475803
7.220726 3.131097
24 0.292077
81.39384 0.633085
7.526441 7.215215
3.231416 25
0.297551 81.26978
0.624802 7.571495
7.207660 3.326268
26 0.302906
81.15661 0.616918
7.611841 7.198642
3.415988 27
0.308151 81.05288
0.609418 7.648197
7.188606 3.500896
28 0.313294
80.95737 0.602286
7.681149 7.177897
3.581296 29
0.318341 80.86906
0.595506 7.711179
7.166777 3.657478
30 0.323301
80.78710 0.589058
7.738686 7.155448
3.729711 31
0.328177 80.71076
0.582924 7.764003
7.144062 3.798252
32 0.332975
80.63943 0.577089
7.787407 7.132734
3.863338 33
0.337699 80.57260
0.571533 7.809129
7.121549 3.925193
34 0.342354
80.50980 0.566242
7.829365 7.110569
3.984025 35
0.346942 80.45065
0.561199 7.848283
7.099838 4.040026
36 0.351467
80.39482 0.556389
7.866023 7.089388
4.093378 37
0.355932 80.34201
0.551800 7.882707
7.079239 4.144247
38 0.360339
80.29195 0.547417
7.898438 7.069401
4.192789 39
0.364691 80.24443
0.543228 7.913306
7.059881 4.239150
40 0.368990
80.19925 0.539223
7.927391 7.050680
4.283462 41
0.373239 80.15621
0.535389 7.940759
7.041794 4.325851
42 0.377438
80.11516 0.531717
7.953471 7.033218
4.366432 43
0.381591 80.07596
0.528199 7.965580
7.024944 4.405313
44 0.385698
80.03849 0.524824
7.977132 7.016965
4.442593 45
0.389761 80.00261
0.521584 7.988168
7.009270 4.478365
46 0.393782
79.96824 0.518473
7.998727 7.001849
4.512716 47
0.397761 79.93526
0.515483 8.008841
6.994692 4.545725
48 0.401701
79.90360 0.512607
8.018540 6.987787
4.577467 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 13 Hasil Analisis VECM, IRF, dan FEVD Singapura
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 22:29
Sample adjusted: 2000M05 2010M10 Included observations: 126 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 CointEq2
LNSP-1 1.000000
0.000000 I-1
0.000000 1.000000
LNINF-1 -24.42827
-54.75778 5.97786
19.3953 [-4.08646]
[-2.82326] LNER-1
-6.688271 -20.12431
3.66374 11.8870
[-1.82553] [-1.69296]
LNOIL-1 -1.344792
-6.826632 0.47483
1.54058 [-2.83218]
[-4.43121] TREND00M01
0.026043 0.106671
C 112.0079
280.8385 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
-0.057214 0.201952
0.010524 0.013033
0.033539 0.03023
0.11265 0.00210
0.00706 0.04270
[-1.89286] [ 1.79267]
[ 5.01845] [ 1.84601]
[ 0.78545] CointEq2
0.029090 -0.104627
-0.002505 -0.006352
0.012087 0.00944
0.03520 0.00066
0.00221 0.01334
[ 3.08049] [-2.97274]
[-3.82367] [-2.87994]
[ 0.90607] DLNSP-1
0.033470 1.219951
-0.008234 -0.056251
0.146300 0.10299
0.38387 0.00715
0.02406 0.14550
[ 0.32497] [ 3.17805]
[-1.15242] [-2.33819]
[ 1.00550] DLNSP-2
0.122004 0.465144
0.003369 -0.000744
0.185613 0.10556
0.39342 0.00732
0.02466 0.14912
[ 1.15582] [ 1.18232]
[ 0.46000] [-0.03016]
[ 1.24473] DLNSP-3
-0.105535 -0.331526
0.001942 0.028612
0.054054 0.10399
0.38758 0.00721
0.02429 0.14691
[-1.01484] [-0.85536]
[ 0.26922] [ 1.17790]
[ 0.36794] DI-1
-0.056499 0.085401
0.001015 0.004499
0.027782 0.02472
0.09213 0.00171
0.00577 0.03492
[-2.28555] [ 0.92694]
[ 0.59214] [ 0.77916]
[ 0.79555]
DI-2 -0.035745
-0.101412 0.000838
-0.002943 -0.020955
0.02447 0.09119
0.00170 0.00572
0.03456 [-1.46094]
[-1.11209] [ 0.49347]
[-0.51501] [-0.60625]
DI-3 -0.002434
0.016452 -0.000349
-0.012664 -0.037789
0.02311 0.08614
0.00160 0.00540
0.03265 [-0.10531]
[ 0.19099] [-0.21789]
[-2.34590] [-1.15739]
DLNINF-1 -2.225664
-3.476874 -0.436772
-0.104528 -0.826347
1.27596 4.75560
0.08852 0.29804
1.80254 [-1.74430]
[-0.73111] [-4.93409]
[-0.35072] [-0.45843]
DLNINF-2 0.588383
-8.130608 -0.224731
-0.805986 -1.001578
1.39713 5.20722
0.09693 0.32635
1.97372 [ 0.42114]
[-1.56141] [-2.31854]
[-2.46973] [-0.50746]
DLNINF-3 -0.610321
-6.428653 0.210768
-0.264006 0.095613
1.35188 5.03854
0.09379 0.31577
1.90978 [-0.45146]
[-1.27590] [ 2.24729]
[-0.83606] [ 0.05006]
DLNER-1 0.723422
3.084356 0.016713
-0.131846 -0.788327
0.42552 1.58594
0.02952 0.09939
0.60113 [ 1.70009]
[ 1.94481] [ 0.56613]
[-1.32651] [-1.31141]
DLNER-2 0.399663
1.289337 0.040617
-0.158652 -0.050131
0.42100 1.56912
0.02921 0.09834
0.59475 [ 0.94931]
[ 0.82170] [ 1.39063]
[-1.61332] [-0.08429]
DLNER-3 0.613813
-1.050566 0.029087
0.073121 -0.477089
0.42318 1.57724
0.02936 0.09885
0.59783 [ 1.45047]
[-0.66608] [ 0.99073]
[ 0.73974] [-0.79804]
DLNOIL-1 0.168050
-0.417521 0.002854
-0.050797 0.094986
0.07170 0.26722
0.00497 0.01675
0.10129 [ 2.34386]
[-1.56244] [ 0.57382]
[-3.03311] [ 0.93779]
DLNOIL-2 0.143856
0.169267 0.004512
0.003225 0.096931
0.07006 0.26114
0.00486 0.01637
0.09898 [ 2.05319]
[ 0.64819] [ 0.92829]
[ 0.19704] [ 0.97930]
DLNOIL-3 0.104390
-0.141123 -0.002681
-0.049482 0.020423
0.06706 0.24993
0.00465 0.01566
0.09473 [ 1.55673]
[-0.56466] [-0.57632]
[-3.15910] [ 0.21559]
C -0.019091
-0.049042 0.002193
0.001389 0.044148
0.01399 0.05214
0.00097 0.00327
0.01976 [-1.36464]
[-0.94059] [ 2.25956]
[ 0.42519] [ 2.23384]
TREND00M01 0.000458
0.001574 -3.23E-05
-4.72E-06 -0.000956
0.00028 0.00105
2.0E-05 6.6E-05
0.00040 [ 1.63037]
[ 1.50270] [-1.65531]
[-0.07194] [-2.40742]
DUMMY -0.020579
-0.127787 0.006703
-0.004018 0.080393
0.02471 0.09208
0.00171 0.00577
0.03490 [-0.83297]
[-1.38779] [ 3.91084]
[-0.69631] [ 2.30343]
R-squared 0.319493
0.292664 0.494165
0.301440 0.336841
Adj. R-squared 0.197516
0.165878 0.403497
0.176227 0.217973
Sum sq. resids 0.348760
4.844649 0.001679
0.019029 0.696020
S.E. equation 0.057360
0.213785 0.003979
0.013398 0.081032
F-statistic 2.619278
2.308321 5.450242
2.407409 2.833738
Log likelihood 192.2619
26.49340 528.4568
375.4939 148.7292
Akaike AIC -2.734316
-0.103070 -8.070742
-5.642760 -2.043321
Schwarz SC -2.284112
0.347134 -7.620539
-5.192557 -1.593118
Mean dependent 0.002961
-0.015079 0.001399
-0.002129 0.009191
S.D. dependent 0.064031
0.234079 0.005152
0.014762 0.091632
Determinant resid covariance dof adj. 2.06E-15
Determinant resid covariance 8.70E-16
Log likelihood 1290.811
Akaike information criterion -18.74303
Schwarz criterion -16.26692
Impulse Response Function
Period 1
0.000000 2
0.003550 3
0.002928 4
0.000795 5
-0.011113 6
-0.019385 7
-0.026783 8
-0.029357 9
-0.031807 10
-0.030873 11
-0.029176 12
-0.025829 13
-0.021787 14
-0.017432 15
-0.013408 16
-0.009634 17
-0.006600 18
-0.004267 19
-0.002686 20
-0.001831 21
-0.001590 22
-0.001811 23
-0.002390 24
-0.003171 25
-0.004036 26
-0.004893 27
-0.005660 28
-0.006290 29
-0.006760 30
-0.007065 31
-0.007215 32
-0.007234 33
-0.007150 34
-0.006996 35
-0.006801 36
-0.006592 37
-0.006391 38
-0.006214 39
-0.006071 40
-0.005966 41
-0.005901 42
-0.005870 43
-0.005870 44
-0.005892 45
-0.005930 46
-0.005976 47
-0.006024 48
-0.006070 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.057360 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.080982
96.98726 0.308379
2.018453 0.493725
0.192178 3
0.098374 97.00307
0.535758 1.584929
0.657452 0.218795
4 0.108109
96.03263 0.446269
2.134558 1.199978
0.186568 5
0.116824 94.50664
0.572371 2.179667
1.676666 1.064652
6 0.124614
91.15405 0.890017
2.037152 2.563063
3.355715 7
0.132444 86.09714
1.340977 1.872632
3.629367 7.059882
8 0.139812
80.33390 2.097948
1.712627 5.111110
10.74441 9
0.147227 74.34514
2.910096 1.547543
6.840459 14.35676
10 0.154179
69.11806 3.659026
1.420289 8.701827
17.10079 11
0.160490 64.85247
4.182971 1.314722
10.56246 19.08738
12 0.165935
61.57124 4.517414
1.231530 12.40159
20.27823 13
0.170550 59.15762
4.710712 1.167837
14.13636 20.82747
14 0.174498
57.42964 4.802153
1.116985 15.75749
20.89373 15
0.177972 56.23755
4.810765 1.075030
17.22308 20.65357
16 0.181133
55.46580 4.764101
1.040085 18.50829
20.22172 17
0.184126 55.00256
4.681213 1.008965
19.60905 19.69822
18 0.187039
54.76436 4.579204
0.980643 20.53433
19.14147 19
0.189924 54.69024
4.469063 0.954616
21.30168 18.58441
20 0.192799
54.72730 4.357595
0.930056 21.94186
18.04320 21
0.195663 54.83404
4.249339 0.906923
22.48424 17.52546
22 0.198507
54.97528 4.147556
0.885186 22.95670
17.03527 23
0.201321 55.12105
4.054341 0.864512
23.38371 16.57639
24 0.204102
55.24906 3.971078
0.844873 23.78303
16.15196 25
0.206848 55.34432
3.898339 0.826153
24.16710 15.76409
26 0.209559
55.39832 3.835904
0.808187 24.54436
15.41323 27
0.212239 55.40937
3.782926 0.790942
24.91916 15.09760
28 0.214888
55.38082 3.738058
0.774370 25.29334
14.81341 29
0.217505 55.31936
3.699621 0.758432
25.66695 14.55563
30 0.220091
55.23370 3.665899
0.743135 26.03862
14.31865 31
0.222644 55.13283
3.635297 0.728472
26.40627 14.09713
32 0.225164
55.02500 3.606482
0.714431 26.76754
13.88654 33
0.227651 54.91712
3.578459 0.701007
27.11998 13.68344
34 0.230106
54.81433 3.550569
0.688178 27.46143
13.48549 35
0.232530 54.72008
3.522451 0.675917
27.79017 13.29138
36 0.234924
54.63625 3.493988
0.664197 28.10501
13.10055 37
0.237291 54.56342
3.465239 0.652984
28.40533 12.91302
38 0.239633
54.50117 3.436372
0.642244 28.69109
12.72911 39
0.241951 54.44843
3.407613 0.631946
28.96269 12.54932
40 0.244247
54.40370 3.379202
0.622056 29.22088
12.37416 41
0.246522 54.36529
3.351366 0.612548
29.46668 12.20412
42 0.248777
54.33156 3.324296
0.603392 29.70120
12.03955 43
0.251013 54.30097
3.298140 0.594566
29.92560 11.88072
44 0.253230
54.27224 3.272992
0.586048 30.14098
11.72774 45
0.255429 54.24435
3.248904 0.577818
30.34833 11.58060
46 0.257610
54.21658 3.225880
0.569859 30.54852
11.43917 47
0.259773 54.18847
3.203890 0.562158
30.74224 11.30324
48 0.261918
54.15984 3.182878
0.554701 30.93008
11.17250 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 14 Hasil Analisis VECM, IRF, dan FEVD Swiss
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 22:44
Sample adjusted: 2000M05 2010M10 Included observations: 126 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 CointEq2
CointEq3 LNSP-1
1.000000 0.000000
0.000000 I-1
0.000000 1.000000
0.000000 LNINF-1
0.000000 0.000000
1.000000 LNER-1
-3.674409 -23.53232
-0.004527 1.07254
12.6565 0.01156
[-3.42589] [-1.85931]
[-0.39161] LNOIL-1
0.797372 14.65528
-0.014274 0.28017
3.30619 0.00302
[ 2.84598] [ 4.43268]
[-4.72653] TREND00M01
-0.024991 -0.249311
-0.000633 C
-9.269490 -35.26722
-4.508575 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
-0.125208 0.260897
0.002455 0.110971
0.270341 0.06197
0.33597 0.00352
0.04725 0.11549
[-2.02046] [ 0.77656]
[ 0.69665] [ 2.34867]
[ 2.34076] CointEq2
0.009505 -0.027617
-5.07E-05 -0.006511
-0.027714 0.00513
0.02783 0.00029
0.00391 0.00957
[ 1.85137] [-0.99226]
[-0.17383] [-1.66353]
[-2.89657] CointEq3
-3.126899 -16.76439
-0.153365 3.568672
-0.907072 1.67167
9.06288 0.09506
1.27455 3.11548
[-1.87052] [-1.84979]
[-1.61329] [ 2.79995]
[-0.29115] DLNSP-1
0.286454 0.765764
0.005464 -0.022857
0.223684 0.10590
0.57412 0.00602
0.08074 0.19736
[ 2.70501] [ 1.33381]
[ 0.90726] [-0.28309]
[ 1.13338] DLNSP-2
-0.027612 -0.732704
0.005049 0.013731
-0.266481 0.10446
0.56634 0.00594
0.07965 0.19469
[-0.26432] [-1.29375]
[ 0.84995] [ 0.17240]
[-1.36877] DLNSP-3
0.143830 0.166645
-0.020406 0.071988
-0.001861 0.10377
0.56256 0.00590
0.07911 0.19339
[ 1.38611] [ 0.29623]
[-3.45815] [ 0.90992]
[-0.00963] DI-1
0.001881 -0.205344
-0.000563 -0.004677
0.111576
0.01726 0.09357
0.00098 0.01316
0.03217 [ 0.10896]
[-2.19444] [-0.57315]
[-0.35540] [ 3.46860]
DI-2 0.001960
-0.019368 0.000510
0.007001 0.076234
0.01780 0.09651
0.00101 0.01357
0.03318 [ 0.11013]
[-0.20069] [ 0.50365]
[ 0.51578] [ 2.29783]
DI-3 -0.032163
-0.023931 -0.000203
-0.017095 -0.025152
0.01753 0.09505
0.00100 0.01337
0.03267 [-1.83459]
[-0.25179] [-0.20328]
[-1.27894] [-0.76982]
DLNINF-1 2.589996
10.55522 0.041615
-2.010284 -1.019421
1.34080 7.26905
0.07625 1.02228
2.49883 [ 1.93169]
[ 1.45208] [ 0.54578]
[-1.96648] [-0.40796]
DLNINF-2 0.625112
12.01243 0.106980
-2.264420 1.945703
1.34412 7.28710
0.07644 1.02481
2.50503 [ 0.46507]
[ 1.64845] [ 1.39958]
[-2.20959] [ 0.77672]
DLNINF-3 0.872171
18.32446 -0.702371
-2.117411 1.081235
1.23142 6.67606
0.07003 0.93888
2.29498 [ 0.70827]
[ 2.74480] [-10.0299]
[-2.25525] [ 0.47113]
DLNER-1 -0.207432
0.204932 0.005641
0.005027 0.007781
0.13404 0.72671
0.00762 0.10220
0.24982 [-1.54749]
[ 0.28200] [ 0.74007]
[ 0.04919] [ 0.03115]
DLNER-2 0.077872
0.964755 0.014684
0.012597 0.431746
0.13083 0.70931
0.00744 0.09975
0.24383 [ 0.59520]
[ 1.36013] [ 1.97358]
[ 0.12628] [ 1.77066]
DLNER-3 -0.150448
0.222506 0.007859
0.012216 -0.423777
0.13247 0.71815
0.00753 0.10100
0.24687 [-1.13576]
[ 0.30983] [ 1.04326]
[ 0.12096] [-1.71657]
DLNOIL-1 -0.015122
0.228613 0.012456
0.047392 0.237317
0.05329 0.28890
0.00303 0.04063
0.09931 [-0.28378]
[ 0.79131] [ 4.11029]
[ 1.16645] [ 2.38956]
DLNOIL-2 0.023952
0.081689 -0.002878
0.035510 0.163315
0.05328 0.28885
0.00303 0.04062
0.09930 [ 0.44955]
[ 0.28281] [-0.95005]
[ 0.87415] [ 1.64474]
DLNOIL-3 -0.034253
-0.428425 0.005212
-0.025031 -0.055674
0.05285 0.28651
0.00301 0.04029
0.09849 [-0.64816]
[-1.49534] [ 1.73422]
[-0.62124] [-0.56527]
C -0.016326
-0.089843 0.002233
-0.005428 0.036126
0.00991 0.05375
0.00056 0.00756
0.01848 [-1.64669]
[-1.67145] [ 3.96079]
[-0.71809] [ 1.95511]
TREND00M01 0.000285
0.000841 -2.85E-05
0.000145 -0.000760
0.00020 0.00109
1.1E-05 0.00015
0.00038 [ 1.41393]
[ 0.76886] [-2.48078]
[ 0.94273] [-2.02325]
DUMMY -0.023363
-0.045225 0.002335
-0.015131 0.071147
0.01719 0.09319
0.00098 0.01311
0.03203 [-1.35923]
[-0.48531] [ 2.38920]
[-1.15458] [ 2.22099]
R-squared 0.247440
0.249927 0.729341
0.220290 0.414431
Adj. R-squared 0.104095
0.107056 0.677787
0.071773 0.302894
Sum sq. resids 0.176944
5.200748 0.000572
0.102860 0.614586
S.E. equation 0.041051
0.222555 0.002334
0.031299 0.076506
F-statistic 1.726185
1.749316 14.14708
1.483270 3.715632
Log likelihood 235.0106
22.02495 596.2565
269.1858 156.5683
Akaike AIC -3.396994
-0.016269 -9.131056
-3.939458 -2.151878
Schwarz SC -2.924280
0.456445 -8.658342
-3.466744 -1.679164
Mean dependent -0.001093
-0.023016 0.000706
-0.004430 0.009191
S.D. dependent 0.043370
0.235519 0.004113
0.032486 0.091632
Determinant resid covariance dof adj. 1.90E-15
Determinant resid covariance 7.65E-16
Log likelihood 1298.929
Akaike information criterion -18.71315
Schwarz criterion -16.01193
Impulse Response Function
Period 1
0.000000 2
0.005033 3
0.013600 4
0.015556 5
0.016657 6
0.014223 7
0.013717 8
0.012178 9
0.012271 10
0.011170 11
0.010072 12
0.008033 13
0.006996 14
0.006325 15
0.006709 16
0.006712 17
0.006692 18
0.006182 19
0.006213 20
0.006541 21
0.007432 22
0.008066 23
0.008545 24
0.008660 25
0.008998 26
0.009484 27
0.010221 28
0.010734 29
0.011035 30
0.011047 31
0.011126 32
0.011277 33
0.011546 34
0.011659 35
0.011605 36
0.011369 37
0.011173 38
0.011052 39
0.011023 40
0.010926 41
0.010740 42
0.010469 43
0.010251 44
0.010119 45
0.010075 46
0.010016 47
0.009918 48
0.009785 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decompostion
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.041051 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.063407
99.16334 0.189368
0.000162 0.017114
0.630012 3
0.081660 94.81659
0.600220 0.225715
1.204038 3.153433
4 0.098778
92.26657 0.483498
0.817996 1.796585
4.635351 5
0.113907 89.58257
0.551926 1.732363
2.508802 5.624336
6 0.127641
88.13971 0.531168
2.484752 3.123664
5.720711 7
0.140141 86.99591
0.478274 3.036248
3.785785 5.703784
8 0.151977
86.13176 0.421392
3.392586 4.562211
5.492051 9
0.163484 85.06250
0.368874 3.788408
5.470657 5.309565
10 0.174559
83.99133 0.325094
4.213780 6.403148
5.066647 11
0.185077 82.92421
0.289197 4.649911
7.333407 4.803273
12 0.194856
82.11088 0.263934
4.921433 8.200504
4.503247 13
0.203994 81.45586
0.251863 5.029009
9.036833 4.226431
14 0.212673
80.91995 0.249843
5.001354 9.851902
3.976949 15
0.221008 80.37874
0.251436 4.934478
10.66055 3.774796
16 0.228966
79.86475 0.252666
4.850964 11.42874
3.602877 17
0.236464 79.39699
0.254701 4.758187
12.13204 3.458081
18 0.243468
79.03788 0.258953
4.628186 12.74852
3.326460 19
0.250052 78.76144
0.265486 4.468659
13.28910 3.215314
20 0.256331
78.54630 0.271248
4.294278 13.76334
3.124836 21
0.262373 78.35358
0.273652 4.125995
14.18395 3.062822
22 0.268177
78.19001 0.272174
3.969830 14.54583
3.022151 23
0.273721 78.06024
0.268489 3.826921
14.84592 2.998431
24 0.279013
77.97990 0.263962
3.692271 15.08176
2.982105 25
0.284109 77.93611
0.259097 3.564939
15.26346 2.976394
26 0.289078
77.91742 0.253488
3.444921 15.40160
2.982579 27
0.293959 77.90744
0.246948 3.332971
15.50740 3.005246
28 0.298754
77.90763 0.239829
3.229464 15.58442
3.038659 29
0.303448 77.91979
0.232731 3.134661
15.63521 3.077614
30 0.308046
77.95059 0.225946
3.046747 15.66167
3.115048 31
0.312575 77.99414
0.219512 2.964232
15.66997 3.152142
32 0.317070
78.04374 0.213357
2.886569 15.66644
3.189898 33
0.321552 78.08972
0.207451 2.815161
15.65715 3.230519
34 0.326015
78.13162 0.201826
2.751416 15.64458
3.270556 35
0.330446 78.17103
0.196483 2.695690
15.63001 3.306787
36 0.334835
78.21264 0.191382
2.645854 15.61418
3.335946 37
0.339192 78.25450
0.186497 2.600162
15.59954 3.359298
38 0.343533
78.29297 0.181820
2.558116 15.58866
3.378434 39
0.347865 78.32272
0.177339 2.520961
15.58376 3.395220
40 0.352180
78.34382 0.173051
2.489263 15.58509
3.408776 41
0.356463 78.35861
0.168979 2.462246
15.59203 3.418138
42 0.360702
78.37108 0.165167
2.437517 15.60373
3.422499 43
0.364900 78.38152
0.161646 2.413410
15.62030 3.423127
44 0.369064
78.38854 0.158398
2.389528 15.64203
3.421506 45
0.373196 78.38991
0.155366 2.366673
15.66902 3.419037
46 0.377291
78.38629 0.152514
2.345197 15.70029
3.415705 47
0.381338 78.37983
0.149856 2.324626
15.73446 3.411232
48 0.385331
78.37329 0.147417
2.303755 15.77015
3.405384 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Lampiran 15 Hasil Analisis VECM, IRF, dan FEVD Thailand
Vector Error Correction Model
Vector Error Correction Estimates Date: 070311 Time: 22:30
Sample adjusted: 2000M05 2009M12 Included observations: 116 after adjustments
Standard errors in t-statistics in [ ] Cointegrating Eq:
CointEq1 CointEq2
LNSP-1 1.000000
0.000000 I-1
0.000000 1.000000
LNINF-1 459.9940
1627.279 1218.48
4535.43 [ 0.37751]
[ 0.35879] LNER-1
2697.136 10024.04
464.142 1727.63
[ 5.81102] [ 5.80219]
LNOIL-1 393.2815
1462.709 115.255
429.004 [ 3.41226]
[ 3.40955] TREND00M01
0.920677 3.618486
2.21469 8.24353
[ 0.41571] [ 0.43895]
C -13554.82
-49993.75 Error Correction:
DLNSP DI
DLNINF DLNER
DLNOIL CointEq1
-0.171650 0.360097
-0.002057 0.023680
-0.043133 0.04111
0.08142 0.00293
0.00838 0.04425
[-4.17562] [ 4.42250]
[-0.70094] [ 2.82576]
[-0.97469] CointEq2
0.046169 -0.096684
0.000553 -0.006381
0.011532 0.01105
0.02188 0.00079
0.00225 0.01189
[ 4.17872] [-4.41800]
[ 0.70165] [-2.83306]
[ 0.96959] DLNSP-1
-0.028617 -0.531424
0.027259 -0.035113
0.447435 0.11225
0.22233 0.00801
0.02288 0.12084
[-0.25495] [-2.39025]
[ 3.40149] [-1.53454]
[ 3.70286] DLNSP-2
0.281719 -0.102273
0.007964 -0.016796
0.208210 0.12112
0.23990 0.00865
0.02469 0.13039
[ 2.32599] [-0.42631]
[ 0.92102] [-0.68027]
[ 1.59688] DLNSP-3
0.301486 0.598383
-0.008108 -0.040918
0.168480 0.11666
0.23107 0.00833
0.02378 0.12558
[ 2.58438] [ 2.58965]
[-0.97348] [-1.72064]
[ 1.34157] DI-1
0.047692 -0.102175
-0.001736 0.008893
0.000115
0.04612 0.09136
0.00329 0.00940
0.04965 [ 1.03400]
[-1.11840] [-0.52729]
[ 0.94581] [ 0.00231]
DI-2 -0.030172
-0.083431 0.001334
-0.006457 0.043498
0.04332 0.08580
0.00309 0.00883
0.04663 [-0.69650]
[-0.97233] [ 0.43132]
[-0.73115] [ 0.93275]
DI-3 -0.051916
0.092253 0.002691
0.006346 0.013776
0.03974 0.07872
0.00284 0.00810
0.04278 [-1.30630]
[ 1.17191] [ 0.94824]
[ 0.78336] [ 0.32198]
DLNINF-1 1.940199
-7.890675 0.256922
-0.218833 3.913653
1.54880 3.06777
0.11058 0.31573
1.66731 [ 1.25271]
[-2.57212] [ 2.32349]
[-0.69311] [ 2.34728]
DLNINF-2 4.871450
-2.455438 0.096334
0.143240 4.285334
1.61559 3.20006
0.11534 0.32934
1.73922 [ 3.01528]
[-0.76731] [ 0.83518]
[ 0.43493] [ 2.46395]
DLNINF-3 2.898917
-5.144002 -0.240312
-0.193354 0.744004
1.67719 3.32207
0.11974 0.34190
1.80553 [ 1.72844]
[-1.54843] [-2.00691]
[-0.56553] [ 0.41207]
DLNER-1 0.418299
-4.233704 0.140088
0.091281 1.486526
0.54481 1.07912
0.03890 0.11106
0.58649 [ 0.76779]
[-3.92330] [ 3.60160]
[ 0.82190] [ 2.53459]
DLNER-2 0.626758
0.544558 -0.057687
0.053438 0.065396
0.64347 1.27454
0.04594 0.13117
0.69271 [ 0.97403]
[ 0.42726] [-1.25570]
[ 0.40739] [ 0.09441]
DLNER-3 0.593671
0.461449 -0.071497
-0.072567 0.422966
0.57727 1.14342
0.04121 0.11768
0.62144 [ 1.02841]
[ 0.40357] [-1.73478]
[-0.61665] [ 0.68062]
DLNOIL-1 -0.165629
0.345600 0.017382
0.024028 0.044356
0.09761 0.19334
0.00697 0.01990
0.10508 [-1.69684]
[ 1.78751] [ 2.49423]
[ 1.20754] [ 0.42212]
DLNOIL-2 -0.154790
0.275204 -0.002242
0.008839 -0.047764
0.09763 0.19337
0.00697 0.01990
0.10510 [-1.58551]
[ 1.42317] [-0.32172]
[ 0.44415] [-0.45447]
DLNOIL-3 0.042527
0.244958 0.007792
-0.060375 -0.029780
0.09446 0.18711
0.00674 0.01926
0.10169 [ 0.45019]
[ 1.30918] [ 1.15531]
[-3.13528] [-0.29284]
C -0.021682
0.050230 0.001270
0.003025 -0.008450
0.01155 0.02287
0.00082 0.00235
0.01243 [-1.87805]
[ 2.19651] [ 1.54026]
[ 1.28549] [-0.67987]
DUMMY 0.035158
-0.149097 0.001073
-0.010864 -0.006265
0.02329 0.04613
0.00166 0.00475
0.02507 [ 1.50971]
[-3.23233] [ 0.64544]
[-2.28851] [-0.24992]
R-squared 0.339981
0.597014 0.375430
0.336040 0.390777
Adj. R-squared 0.217504
0.522233 0.259530
0.212831 0.277726
Sum sq. resids 0.534172
2.095736 0.002723
0.022198 0.619050
S.E. equation 0.074209
0.146988 0.005298
0.015128 0.079887
F-statistic 2.775865
7.983513 3.239268
2.727402 3.456628
Log likelihood 147.4795
68.19688 453.6653
331.9608 138.9263
Akaike AIC -2.215164
-0.848222 -7.494229
-5.395876 -2.067695
Schwarz SC -1.764145
-0.397203 -7.043210
-4.944857 -1.616676
Mean dependent 0.005449
-0.008448 0.002084
-0.001138 0.009165
S.D. dependent 0.083891
0.212654 0.006157
0.017051 0.094000
Determinant resid covariance dof adj. 2.54E-15
Determinant resid covariance 1.04E-15
Log likelihood 1177.969
Akaike information criterion -18.46498
Schwarz criterion -15.92503
Impulse Response Function
Period 1
0.000000 2
-0.009942 3
-0.015348 4
-0.004124 5
-0.005844 6
-0.005268 7
-0.006174 8
-0.005196 9
-0.001880 10
-0.001117 11
3.55E-05 12
0.000906 13
0.000816 14
0.000362 15
-0.000400 16
-0.001092 17
-0.001629 18
-0.002006 19
-0.002163 20
-0.002200 21
-0.002143 22
-0.002022 23
-0.001888 24
-0.001744 25
-0.001602 26
-0.001474 27
-0.001370 28
-0.001295 29
-0.001252 30
-0.001240 31
-0.001254 32
-0.001286 33
-0.001327 34
-0.001369 35
-0.001408 36
-0.001438 37
-0.001458 38
-0.001469 39
-0.001471 40
-0.001466 41
-0.001457 42
-0.001446 43
-0.001435 44
-0.001424 45
-0.001416 46
-0.001410 47
-0.001406 48
-0.001405 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Forecast Error Variance Decomposition
Period S.E.
LNSP I
LNINF LNER
LNOIL 1
0.074209 100.0000
0.000000 0.000000
0.000000 0.000000
2 0.094565
95.72873 0.793808
2.013158 0.358937
1.105371 3
0.112791 93.78542
0.721711 2.426374
0.437834 2.628658
4 0.129211
92.84483 0.579921
3.082257 1.388071
2.104918 5
0.142802 88.25094
0.723644 6.793316
2.341296 1.890807
6 0.154088
83.48856 0.751983
11.75195 2.266637
1.740870 7
0.165139 76.88366
0.659714 18.59907
2.202094 1.655461
8 0.177465
68.87811 0.572505
26.96837 2.061801
1.519217 9
0.190086 61.19546
0.500318 35.11033
1.859929 1.333962
10 0.202118
54.69148 0.454171
41.93916 1.732260
1.182927 11
0.212944 49.66124
0.416075 47.12230
1.734680 1.065710
12 0.222242
45.90648 0.383318
50.84683 1.883309
0.980062 13
0.229968 43.19801
0.358017 53.36421
2.163182 0.916575
14 0.236471
41.27782 0.340749
54.95546 2.558885
0.867088 15
0.242159 39.90916
0.332514 55.91077
3.020453 0.827104
16 0.247312
38.95448 0.331700
56.43434 3.484538
0.794945 17
0.252182 38.29683
0.335412 56.67586
3.923190 0.768713
18 0.256934
37.83439 0.342469
56.75891 4.317596
0.746634 19
0.261643 37.49028
0.350971 56.77503
4.656883 0.726835
20 0.266352
37.19943 0.359143
56.78842 4.944814
0.708189 21
0.271084 36.91438
0.366333 56.84201
5.187347 0.689929
22 0.275843
36.60441 0.371979
56.96164 5.390271
0.671705 23
0.280621 36.25473
0.375695 57.15531
5.560711 0.653552
24 0.285408
35.86409 0.377556
57.41675 5.706054
0.635547 25
0.290187 35.43962
0.377886 57.73163
5.833031 0.617835
26 0.294934
34.99427 0.377081
58.08037 5.947675
0.600605 27
0.299628 34.54291
0.375578 58.44215
6.055340 0.584026
28 0.304249
34.09919 0.373800
58.79874 6.160040
0.568232 29
0.308783 33.67423
0.372070 59.13615
6.264237 0.553311
30 0.313223
33.27570 0.370601
59.44529 6.369108
0.539304 31
0.317568 32.90772
0.369523 59.72187
6.474683 0.526208
32 0.321822
32.57138 0.368878
59.96560 6.580161
0.513984 33
0.325993 32.26539
0.368641 60.17905
6.684344 0.502570
34 0.330092
31.98686 0.368745
60.36655 6.785964
0.491887 35
0.334128 31.73193
0.369105 60.53322
6.883897 0.481849
36 0.338111
31.49645 0.369627
60.68424 6.977317
0.472374 37
0.342046 31.27641
0.370224 60.82424
7.065740 0.463383
38 0.345941
31.06830 0.370825
60.95705 7.149009
0.454809 39
0.349799 30.86928
0.371377 61.08551
7.227235 0.446600
40 0.353622
30.67726 0.371847
61.21144 7.300735
0.438715 41
0.357412 30.49088
0.372222 61.33583
7.369951 0.431124
42 0.361168
30.30939 0.372501
61.45892 7.435390
0.423807 43
0.364891 30.13253
0.372695 61.58046
7.497563 0.416750
44 0.368579
29.96038 0.372822
61.69991 7.556948
0.409944 45
0.372233 29.79317
0.372901 61.81659
7.613955 0.403383
46 0.375851
29.63122 0.372954
61.92986 7.668912
0.397060 47
0.379434 29.47479
0.372996 62.03918
7.722064 0.390970
48 0.382982
29.32407 0.373040
62.14421 7.773578
0.385105 Cholesky Ordering: LNSP I LNINF LNER LNOIL
Halaman ini sengaja dikosongkan
iv
ABSTRACT
FATHURRAHMAN RAMADHANI AMIRUDDIN ABU. Oil Price and Macroeconomics Variables Effects on Stock Price Index Comparative Study :
South East Asia, East Asia, Europe, and America. Supervised by NOER AZAM ACHSANI and DEDI BUDIMAN HAKIM.
Crude oil is one factor that drive the world economy today. Its price performance is benchmark for the performance of the world economy because of its role is
considered important in production process. Seven major stock indices in Asia has increased significantly as well as the increase in oil price since early 2002. Data
shows since 2003 until 2008, Hang Seng rose 54,78 percent, BSE increased 71,22 percent, JKSE increased 74,80 percent, KLSE rose 45,06 percent, Nikkei rose
30,25 percent, Strait Times rose 49,33 percent, and KOSPI rose 57,27 percent. The improvement of global oil price followed by rising indices in Asia is not in
accordance with the transmission mechanism and raises the question whether there is positive movement towards the oil price movement of stock price indices
in Asia, whereas some countries in Asia are oil importers, particularly East Asia and India. Influence oil price on the economy may be different. Oil exporting
countries got advantange from positive trends in oil price because of their income increases with rising oil price, while higher oil price would make oil importing
countries have to pay more for their oil needs. The purpose of this study was to analyze how oil price and macroeconomic
variables affect on stock price index in South East Asia, East Asia, Europe, and America countries. The data is monthly time series data from January 2000 until
December 2009. Then, it analyzed using VARVECM with analysis tools IRF, and FEVD. The result showed that generally in Asia, stock price index in all
Southeast Asia as well as India and South Korea would respond negatively to the oil price. If there were an increase in world oil price, it would lower the stock
price index in each of these Asian countries. Stock price indices in European countries, namely FTSE, DAX, CAC, and SMI indicate different results. In
general, FTSE, DAX, and SMI would positively respond to oil price movements, different from others, CAC would respond negatively. As in Europe, mostly stock
price indices in America has also responded positively in oil price, except in Brazil which responded negatively.
Keywords
: Oil price, stock price indices, macroeconomic variables, VECM, IRF, FEVD
I. PENDAHULUAN
1.1 Latar Belakang
Salah satu faktor penggerak perekonomian dunia saat ini adalah minyak mentah. Kinerja dari harga minyak mentah dunia menjadi tolok ukur bagi kinerja
perekonomian dunia karena perannya dipandang penting dalam fungsi produksi, dimana bahan bakar minyak, yang merupakan produk olahan dari minyak mentah
masih menjadi sumber energi utama dalam proses produksi bagi sebagian besar industri di negara-negara dunia.
Selama periode tahun 2002 hingga 2008, pasar minyak mentah dunia mengalami peningkatan yang berkelanjutan dengan harga minyak mentah dunia
rata-rata meningkat selama tujuh tahun berturut-turut. Data tahun 2010 dari U.S. Energy Information Administration Gambar 1 menjelaskan bahwa baik minyak
mentah jenis West Texas Intermediate maupun brent mengalami peningkatan harga yang cukup signifikan. Pada awal tahun 2002, harga minyak mentah jenis
West Texas Intermediate berada di posisi 19,71 US Dollar per barel sedangkan
minyak mentah jenis brent berada di posisi 19,42 US Dollar per barel. Peningkatan harga terus terjadi selama tujuh tahun hingga harga minyak mentah
dunia jenis West Texas Intermediate menembus harga 133,88 US Dollar per barel pada pertengahan tahun 2008 sedangkan harga minyak mentah dunia jenis brent
mencapai 132,32 US Dollar per barel pada periode yang sama. Organisasi negara- negara pengekspor minyak dunia OPEC berusaha menstabilkan harga minyak
mentah dunia yang terus meningkat dan dikhawatirkan mengganggu kestabilan perekonomian dunia dengan meningkatkan volume produksi minyak dari negara-
negara anggotanya British Petroleum 2010. Berdasarkan data yang dirilis oleh British Petroleum Statistical Review of World Energy Market tahun 2010,
produksi minyak mentah dunia yang berasal dari negara-negara OPEC meningkat setiap tahun mulai tahun 2002. Sekitar 35.568 ribu barel per hari minyak mentah
atau sekitar 43,3 persen dari total produksi minyak mentah dunia diproduksi negara-negara OPEC pada tahun 2008 untuk mengantisipasi melonjaknya harga
minyak mentah dunia. Kebijakan OPEC tersebut akhirnya membuat fenomena kenaikan harga minyak dunia berakhir menjelang akhir tahun 2008.
Data dari British Petroleum Statistical Review of World Energy Market 2004 yang disajikan dalam penelitian Masih et al. 2010 menyatakan bahwa
kenaikan harga minyak dunia sejak tahun 2002 disebabkan oleh peningkatan permintaan dari negara industri baru seperti China dan India. Konsumsi minyak di
kedua negara ini tidak lebih dari 3,5 juta barel per hari, atau mendekati 5 persen dari penggunaan minyak dunia, pada tahun 1990. Namun 13 tahun kemudian pada
tahun 2003, kedua negara ini mencatatkan konsumsi minyak mereka mencapai lebih dari 10 persen konsumsi minyak dunia.
Sumber: U.S. Energy Information Administration, 2010 diolah
Gambar 1 Harga Minyak Dunia Jenis WTI dan Brent Tahun 2000 – 2009
US Dollarbarel
Jika melihat data konsumsi minyak mentah negara-negara industri besar yang dirilis oleh British Petroleum Statistical Review of World Energy Market
tahun 2010 Gambar 2, maka sebenarnya tidak ada peningkatan permintaan minyak mentah yang cukup signifikan dari negara-negara maju seperti Amerika
Serikat, Jerman, dan Jepang. Amerika Serikat yang menjadi salah satu konsumen minyak terbesar di dunia hanya mengkonsumsi minyak mentah berkisar antara
880 – 950 juta ton per tahun selama 9 tahun. Jepang yang menjadi kompetitor Amerika Serikat di bidang otomotif, tidak mengalami perubahan konsumsi
minyak mentah yang cukup besar. Jepang justru mengalami penurunan konsumsi