Saran Keterbatasan Penelitian Saran Penelitian Lanjutan

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 Abdelaziz, M., Chortareas, G., and Cipollini, A. 2008. ‘Stock Prices, Exchange Rates and Oil: Evidence from Middle East Oil Exporting Countries’, 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 th 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