Saran Penelitian Lanjutan Impact of world oil price shock on domestic rice price (cointegration analysis)

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Augmented Dickey-Fuller test statistic -2.134524 0.2327 Test critical values: 1 level -3.596616 5 level -2.933158 10 level -2.604867 MacKinnon 1996 one-sided p-values. Null Hypothesis: PB has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -1.618171 0.4646 Test critical values: 1 level -3.596616 5 level -2.933158 10 level -2.604867 MacKinnon 1996 one-sided p-values. Null Hypothesis: HMMD has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -2.091376 0.2490 Test critical values: 1 level -3.596616 5 level -2.933158 10 level -2.604867 MacKinnon 1996 one-sided p-values. Null Hypothesis: HBD has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -10.01369 0.0000 Test critical values: 1 level -3.596616 5 level -2.933158 10 level -2.604867 MacKinnon 1996 one-sided p-values. Null Hypothesis: HBI has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -1.514812 0.5165 Test critical values: 1 level -3.596616 5 level -2.933158 10 level -2.604867 MacKinnon 1996 one-sided p-values. Null Hypothesis: NT has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -0.354653 0.9076 Test critical values: 1 level -3.596616 5 level -2.933158 10 level -2.604867 MacKinnon 1996 one-sided p-values. Null Hypothesis: TFP has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -7.795568 0.0000 Test critical values: 1 level -3.600987 5 level -2.935001 10 level -2.605836 MacKinnon 1996 one-sided p-values. Lampiran 2 Unit root test first difference Null Hypothesis: DHBDOM has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -5.673936 0.0000 Test critical values: 1 level -3.600987 5 level -2.935001 10 level -2.605836 MacKinnon 1996 one-sided p-values. Null Hypothesis: DPB has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -6.552085 0.0000 Test critical values: 1 level -3.600987 5 level -2.935001 10 level -2.605836 MacKinnon 1996 one-sided p-values. Null Hypothesis: DHMMD has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -5.698329 0.0000 Test critical values: 1 level -3.600987 5 level -2.935001 10 level -2.605836 MacKinnon 1996 one-sided p-values. Null Hypothesis: DHBD has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -7.951440 0.0000 Test critical values: 1 level -3.600987 5 level -2.935001 10 level -2.605836 MacKinnon 1996 one-sided p-values. Null Hypothesis: DHBI has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -6.121479 0.0000 Test critical values: 1 level -3.600987 5 level -2.935001 10 level -2.605836 MacKinnon 1996 one-sided p-values. Null Hypothesis: DNT has a unit root Exogenous: Constant Lag Length: 0 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -5.738095 0.0000 Test critical values: 1 level -3.600987 5 level -2.935001 10 level -2.605836 MacKinnon 1996 one-sided p-values. Null Hypothesis: DTFP has a unit root Exogenous: Constant Lag Length: 1 Automatic based on SIC, MAXLAG=9 t-Statistic Prob. Augmented Dickey-Fuller test statistic -8.564531 0.0000 Test critical values: 1 level -3.610453 5 level -2.938987 10 level -2.607932 MacKinnon 1996 one-sided p-values. Lampiran 3 Uji selang optimal VAR Lag Order Selection Criteria Endogenous variables: DHBDOM DHBD DHBI DPB DTFP DHMMD DNT DM Exogenous variables: C Date: 011213 Time: 20:17 Sample: 1970 2011 Included observations: 38 Lag LogL LR FPE AIC SC HQ -1233.548 NA 3.30e+18 65.34463 65.68938 65.46729 1 -1177.646 85.32465 5.44e+18 65.77082 68.87362 66.87477 2 -1071.515 117.3021 9.50e+17 63.55343 69.41426 65.63867 3 -953.5382 80.72109 2.62e+17 60.71253 69.33141 63.77906 indicates lag order selected by the criterion LR: sequential modified LR test statistic each test at 5 level FPE: Final prediction error AIC: Akaike information criterion SC: Schwarz information criterion HQ: Hannan-Quinn information criterion Lampiran 4 Uji stabilitas Roots of Characteristic Polynomial Endogenous variables: DHBDOM DHBD DHBI DPB DTFP DHMMD DNT DM Exogenous variables: C Lag specification: 1 2 Date: 011213 Time: 20:17 Root Modulus -0.127725 - 0.829495i 0.839271 -0.127725 + 0.829495i 0.839271 -0.625920 - 0.544767i 0.829787 -0.625920 + 0.544767i 0.829787 0.773969 0.773969 -0.363359 - 0.651937i 0.746359 -0.363359 + 0.651937i 0.746359 0.353820 - 0.654374i 0.743905 0.353820 + 0.654374i 0.743905 -0.037720 - 0.710147i 0.711149 -0.037720 + 0.710147i 0.711149 -0.679049 0.679049 -0.617783 0.617783 0.510652 0.510652 0.045290 - 0.263132i 0.267001 0.045290 + 0.263132i 0.267001 No root lies outside the unit circle. VAR satisfies the stability condition. Lampiran 5 Uji kointegrasi Date: 011213 Time: 20:20 Sample: 1970 2011 Included observations: 39 Series: HBDOM HBD HBI PB HMMD NT TFP M Lags interval: 1 to 2 Selected 0.05 level Number of Cointegrating Relations by Model Data Trend: None None Linear Linear Quadratic Test Type No Intercept Intercept Intercept Intercept Intercept No Trend No Trend No Trend Trend Trend Trace 8 7 8 6 5 Max-Eig 8 7 8 6 4 Critical values based on MacKinnon-Haug-Michelis 1999 Information Criteria by Rank and Model Data Trend: None None Linear Linear Quadratic Rank or No Intercept Intercept Intercept Intercept Intercept No. of CEs No Trend No Trend No Trend Trend Trend Log Likelihood by Rank rows and Model columns -1127.319 -1127.319 -1117.624 -1117.624 -1101.416 1 -1069.132 -1063.149 -1054.602 -1051.582 -1036.258 2 -1030.128 -1015.842 -1008.553 -1005.504 -990.2221 3 -1006.102 -985.7222 -978.8057 -967.5569 -952.5052 4 -985.4609 -962.9680 -956.2232 -938.2496 -927.1541 5 -969.0210 -946.0303 -940.1286 -920.7228 -911.9969 6 -957.5273 -931.2420 -926.9975 -906.8288 -902.1901 7 -951.8659 -919.7810 -919.7641 -898.1420 -894.5993 8 -949.0549 -916.3774 -916.3774 -894.5871 -894.5871 Akaike Information Criteria by Rank rows and Model columns 64.37533 64.37533 64.28841 64.28841 63.86748 1 62.21192 61.95635 61.87703 61.77344 61.34657 2 61.03221 60.40217 60.33606 60.28223 59.80626 3 60.62062 59.72934 59.63106 59.20805 58.69258 4 60.38261 59.43425 59.29350 58.57690 58.21303 5 60.36005 59.43745 59.28865 58.54989 58.25625 6 60.59114 59.55087 59.43577 58.70917 58.57385 7 61.12133 59.83492 59.88534 59.13549 59.00509 8 61.79769 60.53218 60.53218 59.82498 59.82498 Schwarz Criteria by Rank rows and Model columns 69.83522 69.83522 70.08955 70.08955 70.00986 1 68.35430 68.14139 68.36066 68.29972 68.17144 2 67.85707 67.31234 67.50218 67.53365 67.31361 3 68.12798 67.36466 67.47966 67.18461 66.88242 4 68.57245 67.79472 67.82458 67.27861 67.08536 5 69.23238 68.52306 68.50222 67.97674 67.81107 6 70.14596 69.36162 69.33183 68.86116 68.81115 7 71.35863 70.37081 70.46388 70.01262 69.92488 8 72.71747 71.79321 71.79321 71.42725 71.42725 Date: 011213 Time: 20:22 Sample adjusted: 1973 2011 Included observations: 39 after adjustments Trend assumption: Quadratic deterministic trend Series: HBDOM HBD HBI PB HMMD NT TFP M Lags interval in first differences: 1 to 2 Unrestricted Cointegration Rank Test Trace Hypothesized Trace 0.05 No. of CEs Eigenvalue Statistic Critical Value Prob. None 0.964613 413.6576 175.1715 0.0000 At most 1 0.905657 283.3421 139.2753 0.0000 At most 2 0.855460 191.2700 107.3466 0.0000 At most 3 0.727484 115.8363 79.34145 0.0000 At most 4 0.540351 65.13412 55.24578 0.0053 At most 5 0.395235 34.81970 35.01090 0.0524 At most 6 0.322448 15.20600 18.39771 0.1323 At most 7 0.000629 0.024528 3.841466 0.8755 Trace test indicates 5 cointegrating eqns at the 0.05 level denotes rejection of the hypothesis at the 0.05 level MacKinnon-Haug-Michelis 1999 p-values Lampiran 6 Uji granger causality Pairwise Granger Causality Tests Date: 011213 Time: 20:29 Sample: 1970 2011 Lags: 2 Null Hypothesis: Obs F-Statistic Prob. DHBD does not Granger Cause DHBDOM 39 0.33800 0.7156 DHBDOM does not Granger Cause DHBD 1.73265 0.1921 DHBI does not Granger Cause DHBDOM 39 3.28754 0.0495 DHBDOM does not Granger Cause DHBI 7.93050 0.0015 DPB does not Granger Cause DHBDOM 39 0.13525 0.8740 DHBDOM does not Granger Cause DPB 4.68122 0.0160 DHMMD does not Granger Cause DHBDOM 39 0.84891 0.4367 DHBDOM does not Granger Cause DHMMD 6.78054 0.0033 DNT does not Granger Cause DHBDOM 39 0.01251 0.9876 DHBDOM does not Granger Cause DNT 0.15763 0.8548 DTFP does not Granger Cause DHBDOM 39 0.46759 0.6305 DHBDOM does not Granger Cause DTFP 0.49689 0.6128 DHBI does not Granger Cause DHBD 39 2.61659 0.0877 DHBD does not Granger Cause DHBI 4.51505 0.0182 DPB does not Granger Cause DHBD 39 3.34584 0.0472 DHBD does not Granger Cause DPB 1.03417 0.3664 DHMMD does not Granger Cause DHBD 39 5.74368 0.0071 DHBD does not Granger Cause DHMMD 1.25379 0.2983 DNT does not Granger Cause DHBD 39 0.01102 0.9890 DHBD does not Granger Cause DNT 0.01174 0.9883 DTFP does not Granger Cause DHBD 39 0.80665 0.4547 DHBD does not Granger Cause DTFP 0.22339 0.8010 DPB does not Granger Cause DHBI 39 0.65509 0.5258 DHBI does not Granger Cause DPB 1.83156 0.1756 DHMMD does not Granger Cause DHBI 39 0.38517 0.6833 DHBI does not Granger Cause DHMMD 3.09544 0.0582 DNT does not Granger Cause DHBI 39 0.23430 0.7924 DHBI does not Granger Cause DNT 1.08608 0.3490 DTFP does not Granger Cause DHBI 39 0.42408 0.6578 DHBI does not Granger Cause DTFP 0.24163 0.7867 DHMMD does not Granger Cause DPB 39 0.09636 0.9084 DPB does not Granger Cause DHMMD 0.60807 0.5502 DNT does not Granger Cause DPB 39 0.46685 0.6309 DPB does not Granger Cause DNT 0.18522 0.8318 DTFP does not Granger Cause DPB 39 3.91307 0.0295 DPB does not Granger Cause DTFP 0.29733 0.7447 DNT does not Granger Cause DHMMD 39 0.26778 0.7667 DHMMD does not Granger Cause DNT 0.10296 0.9024 DTFP does not Granger Cause DHMMD 39 0.61780 0.5451 DHMMD does not Granger Cause DTFP 0.00198 0.9980 DTFP does not Granger Cause DNT 39 0.35338 0.7049 DNT does not Granger Cause DTFP 0.20359 0.8168 Lampiran 7 Hasil estimasi VECM Vector Error Correction Estimates Date: 011213 Time: 20:31 Sample adjusted: 1973 2011 Included observations: 39 after adjustments Standard errors in t-statistics in [ ] Cointegrating Eq: CointEq1 HBDOM-1 1.000000 HBD-1 1.126585 0.40740 [ 2.76532] HBI-1 -6.458455 0.30263 [-21.3412] PB-1 7.26E-05 3.4E-05 [ 2.10426] HMMD-1 -0.001303 0.00106 [-1.22905] NT-1 -1.99E-05 2.1E-05 [-0.93801] TFP-1 -0.013564 0.01885 [-0.71951] C 0.435840 Error Correction: DHBDOM DHBD DHBI DPB DHMMD DNT DTFP CointEq1 0.762663 0.071987 0.129605 -23.56802 -14.68627 -82.92917 -1.800337 0.13112 0.03356 0.03513 310.849 7.19368 367.456 2.58370 [ 5.81667] [ 2.14521] [ 3.68949] [-0.07582] [-2.04155] [-0.22568] [-0.69681] DHBDOM-1 -0.898211 -0.103426 -0.017534 139.2733 17.36398 41.14925 0.665113 0.19281 0.04935 0.05166 457.115 10.5786 540.358 3.79943 [-4.65847] [-2.09589] [-0.33942] [ 0.30468] [ 1.64143] [ 0.07615] [ 0.17506] DHBDOM-2 -0.784347 -0.051800 -0.005653 -1154.596 -24.06003 125.6475 3.136219 0.16238 0.04156 0.04350 384.967 8.90891 455.071 3.19975 [-4.83032] [-1.24645] [-0.12994] [-2.99921] [-2.70067] [ 0.27611] [ 0.98015] DHBD-1 -0.547494 -0.148941 -0.035033 -4402.534 26.51228 -131.6899 8.218586 0.75350 0.19284 0.20187 1786.38 41.3404 2111.68 14.8479 [-0.72660] [-0.77233] [-0.17354] [-2.46451] [ 0.64132] [-0.06236] [ 0.55352] DHBD-2 0.189235 -0.080433 0.248078 -1150.666 49.49117 -534.9760 0.780942 0.39411 0.10087 0.10559 934.349 21.6227 1104.50 7.76608 [ 0.48016] [-0.79743] [ 2.34949] [-1.23152] [ 2.28885] [-0.48436] [ 0.10056] DHBI-1 2.935679 -0.112306 0.180502 2458.988 -19.54508 924.2168 -7.070810 0.69895 0.17888 0.18726 1657.05 38.3474 1958.80 13.7730 [ 4.20015] [-0.62782] [ 0.96392] [ 1.48396] [-0.50968] [ 0.47183] [-0.51338] DHBI-2 2.455006 0.037935 0.211486 -4402.872 -71.17165 -1365.805 -1.627206 0.54202 0.13872 0.14521 1285.00 29.7375 1519.00 10.6806 [ 4.52941] [ 0.27346] [ 1.45638] [-3.42637] [-2.39333] [-0.89915] [-0.15235] DPB-1 -0.000110 -3.92E-05 -1.61E-05 0.011334 -0.003293 -0.061848 -0.000617 7.3E-05 1.9E-05 1.9E-05 0.17204 0.00398 0.20338 0.00143 [-1.51737] [-2.11199] [-0.83010] [ 0.06588] [-0.82710] [-0.30411] [-0.43153] DPB-2 -0.000156 -4.10E-05 -6.66E-07 -0.508254 -0.002679 -0.029184 0.001548 8.0E-05 2.0E-05 2.1E-05 0.18906 0.00438 0.22348 0.00157 [-1.95201] [-2.01085] [-0.03116] [-2.68837] [-0.61242] [-0.13059] [ 0.98480] DHMMD-1 0.010460 0.002049 0.001314 -1.088284 -0.017186 1.456307 0.003201 0.00307 0.00079 0.00082 7.28965 0.16870 8.61713 0.06059 [ 3.40191] [ 2.60342] [ 1.59530] [-0.14929] [-0.10188] [ 0.16900] [ 0.05282] DHMMD-2 0.006856 -0.000758 -0.000975 15.57057 -0.171787 -0.634308 -0.041771 0.00329 0.00084 0.00088 7.80959 0.18073 9.23175 0.06491 [ 2.08127] [-0.89963] [-1.10494] [ 1.99378] [-0.95052] [-0.06871] [-0.64350] DNT-1 -6.60E-05 -2.06E-06 -5.49E-06 0.063327 -0.001151 0.085767 0.000428 8.1E-05 2.1E-05 2.2E-05 0.19207 0.00444 0.22705 0.00160 [-0.81438] [-0.09918] [-0.25283] [ 0.32971] [-0.25898] [ 0.37775] [ 0.26813] DNT-2 0.000166 -2.22E-05 -4.40E-06 -0.122619 -0.004224 -0.047829 0.000934 8.8E-05 2.2E-05 2.3E-05 0.20773 0.00481 0.24556 0.00173 [ 1.89260] [-0.99123] [-0.18735] [-0.59028] [-0.87861] [-0.19477] [ 0.54109] DTFP-1 0.019590 -0.003250 0.002092 -51.02504 -0.887540 14.61118 -1.157670 0.01070 0.00274 0.00287 25.3613 0.58691 29.9797 0.21080 [ 1.83130] [-1.18705] [ 0.73001] [-2.01192] [-1.51222] [ 0.48737] [-5.49187] DTFP-2 0.012270 -0.001124 0.000860 -71.55049 -0.836290 12.74710 -0.607739 0.01271 0.00325 0.00340 30.1280 0.69722 35.6144 0.25042 [ 0.96550] [-0.34544] [ 0.25263] [-2.37489] [-1.19946] [ 0.35792] [-2.42692] C -0.182073 0.002061 0.009942 568.4130 5.922589 261.0652 -0.187079 0.09754 0.02496 0.02613 231.250 5.35160 273.362 1.92209 [-1.86661] [ 0.08255] [ 0.38045] [ 2.45800] [ 1.10669] [ 0.95502] [-0.09733] R-squared 0.748962 0.683431 0.719620 0.657749 0.658885 0.111418 0.654941 Adj. R-squared 0.585242 0.476972 0.536763 0.434542 0.436419 -0.468093 0.429902 Sum sq. resids 3.130962 0.205083 0.224734 17597838 9424.597 24590737 1215.752 S.E. equation 0.368956 0.094428 0.098849 874.7133 20.24265 1034.003 7.270403 F-statistic 4.574640 3.310261 3.935434 2.946808 2.961728 0.192262 2.910347 Log likelihood -6.155290 46.99553 45.21116 -309.2232 -162.3452 -315.7478 -122.4099 Akaike AIC 1.136169 -1.589514 -1.498008 16.67811 9.145906 17.01271 7.097946 Schwarz SC 1.818656 -0.907027 -0.815522 17.36060 9.828393 17.69520 7.780433 Mean dependent -0.113333 -0.018479 -0.013921 597.8718 1.317978 214.2628 -0.056357 S.D. dependent 0.572898 0.130568 0.145234 1163.230 26.96430 853.3852 9.629056 Determinant resid covariance dof adj. 1.46E+10 Determinant resid covariance 3.62E+08 Log likelihood -771.6510 Akaike information criterion 45.67441 Schwarz criterion 50.75040 Lampiran 8 Analisis IRF Period HBDOM HBD HBI PB HMMD NT TFP 1 0.368956 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2 0.375126 0.075942 -0.051704 -0.018205 0.069119 -0.058298 0.048750 3 0.296116 0.171262 -0.063587 -0.096399 0.122375 0.062142 -0.039861 4 0.250496 0.216341 -0.340114 -0.095048 0.099353 0.032215 -0.034648 5 0.173233 0.185900 -0.410414 -0.115950 0.040324 -0.015975 0.023887 Choles ky Orderin g: HBDO M HBD HBI PB HMMD NT TFP Lampiran 9 Analisis FEVD Period S.E. HBDOM HBD HBI PB HMMD NT TFP 1 0.368956 100.0000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2 0.544218 93.47521 1.947260 0.902612 0.111905 1.613058 1.147535 0.802423 3 0.668544 81.56006 7.852726 1.502757 2.153288 4.419528 1.624407 0.887230 4 0.832660 61.62802 11.81284 17.65327 2.691139 4.272778 1.196858 0.745098 5 0.970684 48.53299 12.36006 30.86663 3.407099 3.316626 0.907775 0.608824 Choles ky Orderin g: HBDO M HBD HBI PB HMMD NT TFP -.6 -.4 -.2 .0 .2 .4 1 2 3 4 5 Response of HBDOM to HBDOM -.6 -.4 -.2 .0 .2 .4 1 2 3 4 5 Response of HBDOM to HBD -.6 -.4 -.2 .0 .2 .4 1 2 3 4 5 Response of HBDOM to HBI -.6 -.4 -.2 .0 .2 .4 1 2 3 4 5 Response of HBDOM to PB -.6 -.4 -.2 .0 .2 .4 1 2 3 4 5 Response of HBDOM to HMMD -.6 -.4 -.2 .0 .2 .4 1 2 3 4 5 Response of HBDOM to NT -.6 -.4 -.2 .0 .2 .4 1 2 3 4 5 Response of HBDOM to TFP Response to Cholesky One S.D. Innovations 10 20 30 40 50 60 70 80 90 100 1 2 3 4 5 TFP NT HMMD PB HBI HBD HBDOM ABSTRACT SANTI CHINTIA. Impact of World Oil Price Shock on Domestic Rice Price Cointegration Analysis. Supervised by DEDI BUDIMAN HAKIM and HENY K. DARYANTO. Rice is a substantial strategic and food comodity in Indonesia and also in some countries in the world, particularly in Asia. Therefore, the stability of rice price and the availability should be maintained, especially rice is also known as unstable commodity. Starting in 1994, Indonesia became a net importer of rice commodity, then, Indonesia‟s rice market is allegedly integrated with the world‟s rice market. Consequently, any changes or shock in the world‟s rice market, which is one of its shocks caused by world oil price shock, will affect the domestic rice market. The objectives of this study are: 1 to analyze factors that influence the domestic rice price, 2 to analyze the effect of changes on the world oil price shocks to the domestic rice price. The applicable method for this study is vector error correction model VECM with analysis tools are IRF, FEVD, and pass-through. The estimation results indicate that there is a cointegration in the models studied. In the short-term, factors variables that affect the domestic rice price are the price of imported rice, domestic rice price, and the price of crude oil. Besides, in the long run, factors variables that affect the domestic rice price are the price of imported rice, world rice price, and production rice. The variables that largely influence the domestic rice price are world rice price and price of imported rice. On the other hand, a variable that slightly affect is the total factor productivity TFP. Key words: rice, rice price, world oil price shock, TFP, VECM, pass through RINGKASAN SANTI CHINTIA. Dampak Guncangan Harga Minyak Mentah Dunia terhadap Harga Beras Domestik Suatu Analisis Kointegrasi DEDI BUDIMAN HAKIM sebagai Ketua dan HENY K. DARYANTO sebagai Anggota Komisi Pembimbing. Beras merupakan salah satu komoditas tanaman pangan strategis baik di Indonesia maupun di sebagian besar negara-negara di dunia. Oleh karena itu, beras sering digunakan sebagai instrumen pengatur baik dari dimensi ekonomi, sosial, maupun politik. Di Indonesia beras merupakan makanan pokok masyarakat Indonesia. Karena beras merupakan komoditi yang menguasai hajat hidup orang banyak maka pemeintah harus terus menjaga kestabilan beras baik dari sisi harga maupun ketersediaannya. Tetapi karena Indonesia termasuk net importir beras, maka diduga pasar beras domestik terintegrasi dengan pasar beras dunia. Situasi ini menyebabkan kejadian atau shocks yang terjadi di pasar beras dunia akan mempengaruhi kondisi pasar beras domestik yang pada akhirnya akan mempengaruhi fluktuasi harga beras domestik. Penelitian ini bertujuan untuk : 1 mengkaji pola dan karakteristik pergerakan harga beras domestik 2 menganalisis dampak guncangan harga minyak mentah dunia terhadap dinamika harga beras domestik. 3 mengukur besar pengaruh guncangan harga minyak mentah dunia terhadap harga beras domestik. Penelitian ini menggunakan data sekunder deret waktu time series sejak tahun 1969-2011. Analisis menggunakan Vector Error Correction Model VECM. Hasil analisis menunjukkan harga beras domestik memiliki pola berfluktuatif dan memiliki tren yang terus meningkat, tetapi harga beras domestik selalu berfluktuatif pada trennya. Karakteristik menarik dari harga beras domestik adalah selalu berada diatas harga beras dunia. Hal ini terjadi karena beras merupakan komoditi yang banyak diintervensi oleh pemerintah untuk menjaga kestabilan harga beras domestik untuk menjaga daya beli masyarakat sebagai konsumen dan petani sebagai produsen. Hasil estimasi VECM menunjukkan bahwa pada jangka pendek harga beras domestik dipengaruhi oleh harga beras domestik itu sendiri, harga beras impor, dan harga minyak mentah dunia. Pada jangka panjang harga beras domestik dipengaruhi oleh harga beras dunia, harga beras impor, dan produksi beras. Hasil analisis IRF memberikan simpulan bahwa harga beras domestik memberikan respon yang fluktuatif dengan shock dari semua variabel. Hal ini membuktikan bahwa variabel harga beras adalah variabel yang volatil. Artinya, harga beras akan selalu berfluktuasi pada trennya dari waktu ke waktu. Berdasarkan hasil analisis FEVD harga beras domestik paling besar dipengaruhi oleh harga beras domestik itu sendiri yaitu rata-rata sebesar 77.03 persen, harga beras impor sebesar 10.18 persen, harga beras dunia sebesar 6.79 persen, harga minyak mentah dunia sebesar 2.72 persen, produksi beras dan nilai tukar masing-masing sebesar 1.67 dan 0.97 persen, sedangkan total faktor produktivitas hanya berpengaruh sebesar 0.61 persen terhadap perubahan harga beras domestik. Berdasarkan hasil analisis pass through yang telah dilakukan, maka dapat disimpulkan bahwa terdapat dua kelompok pengaruh. Pertama , kelompok “faktor harga” yang terdiri dari harga beras dunia, harga beras impor, dan harga minyak mentah dunia. Kedua , adalah kelompok “faktor non harga” yang terdiri dari variabel produksi beras, total faktor produktivitas, nilai tukar. Dilihat dari besaran koefisien hasil analisis pass through, maka kelompok faktor harga memiliki pengaruh yang lebih besar dibanding faktor non harga. Kata kunci: beras, harga beras, harga minyak mentah dunia, total faktor produktivitas TFP, VECM, pass through 1 PENDAHULUAN

1.1 Latar Belakang

Beras merupakan salah satu komoditas tanaman pangan strategis baik di Indonesia maupun di sebagian besar negara-negara di dunia. Di Indonesia beras merupakan makanan pokok masyarakat Indonesia. Konsumsi beras per kapita di Indonesia merupakan tertinggi di dunia yaitu sebesar 139,15 kg BPS, 2011. Karena beras merupakan bagian yang dominan dari masyarakat Indonesia, maka pasar beras diduga memiliki keterkaitan erat baik dalam hal mendorong pertumbuhan ekonomi maupun penciptaan lapangan kerja. Di tingkat dunia beras dikonsumsi oleh sebagian besar masyarakat dunia yaitu sebesar 437,9 juta ton pada tahun 2010, naik 0,2 persen dibandingkan tahun 2009 USDA, 2011. Keberadaan pasar beras dunia telah mengalami fluktuasi terutama dari segi harga. Pasar beras dunia terus dipandang sebagai pasar yang terdistorsi, lemah, dan berubah-ubah Kang, 2009. Selain itu, di pasar dunia beras dikenal dengan istilah thin market, artinya beras adalah komoditi yang sedikit diperdagangkan. Hal inilah yang menyebabkan pasar beras dunia bersifat labil. Sama halnya dengan pasar beras dunia, pasar beras domestik pun merupakan pasar yang bersifat labil dan banyak dipengaruhi oleh faktor-faktor luar. Simatupang et.al. 2004 menyebutkan bahwa banyak faktor yang dapat mempengaruhi harga gabah dan beras di tingkat petani, salahsatunya adalah pengaruh integrasi pasar beras dunia dan domestik. Sehingga kejadian atau shocks yang terjadi di pasar dunia akan mempengaruhi kondisi pasar beras domestik. Terdapat dua komoditi yang banyak mempengaruhi perdagangan dunia atau dikenal dengan “komoditi shocks”. Dua komoditi tersebut adalah emas dan minyak mentah. Minyak mentah dunia sering dijadikan sebagai tolok ukur dalam analisis penelitian berbagai komoditi yang diperdagangkan terutama penelitian mengenai pangan. Diikutsertakannya minyak mentah dunia sebagai salahsatu faktor yang paling berpengaruh mempengaruhi perubahan berbagai permintaan dan penawaran berbagai komoditi yang diperdagangkan karena perannya yang begitu vital. Fluktuasi harga diantara dua komoditas ini sering dijadikan tolok ukur bagi kestabilan kondisi perdagangan dunia. Tetapi semenjak ditandatanganinya persetujuan Bretton Woods tahun 1944, sistem moneter internasional SMI didasarkan pada sistem kurs tetap fixed exchange rate. Artinya mata uang Dollar AS USD dapat ditukar dan dijamin sepenuhnya dengan emas, dengan ketentuan USD 35 ekuivalen dengan 1 troy once emas. Semenjak nilai tukar USD tidak lagi dikaitkan dengan emas, maka harga minyak mentah dunia dihubungkan dengan pergerakan mata uang. Amerika Serikat AS yang dikenal sebagai negara yang membutuhkan konsumsi minyak cukup besar di dunia, sehingga US dollar sering disebut dengan Petro Dollar. Naiknya harga minyak mentah dunia secara tidak langsung akan berdampak pada naiknya harga-harga produksi dan harga barang-barang konsumsi di AS. Naiknya harga barang-barang dapat memicu naiknya tingkat inflasi yang lebih lanjut membuat nilai tukar US dollar cenderung tertekan di pasar. Oleh sebab itu para pelaku pasar selalu memantau pergerakan harga minyak mentah dunia dan persediaan minyak mentah AS. Karena perubahan kecil di kedua hal tersebut dapat berpengaruh cukup besar pada nilai tukar USD yang nantinya akan berimbas terhadap komoditi-komoditi yang diperdagangkan di dunia termasuk perdagangan beras. Berdasarkan pemaparan mengenai besarnya peranan beras baik di Indonesia maupun di sebagian besar negara-negara di dunia serta adanya minyak mentah dunia yang sering dijadikan tolok ukur perdagangan komoditi dunia, maka analisis mengenai dampak guncangan harga minyak mentah dunia terhadap harga beras domestik menjadi menarik dan penting untuk dilakukan.

1.2 Perumusan Masalah

Harga beras dunia dalam tiga puluh tahun terakhir sangat tidak stabil dan kemungkinan besar terjadinya volatilitas harga beras di pasar internasional tidak hanya didorong oleh penawaran dan permintaan tetapi juga oleh kekuatan- kekuatan ekonomi eksternal lainnya Mondi, 2010. Menurut Mondi salahsatu kekuatan ekonomi eksternal yang besar mempengaruhi pasokan dan harga beras dunia adalah fluktuatifnya harga minyak mentah dunia. Minyak mentah dunia mempengaruhi harga beras melalui lima saluran kemungkinan utama, yaitu : 1 Harga pupuk. 2 Biaya transportasi. 3 Ekspektasi pasar dan permintaan pencegahan. 4 Spekulasi di pasar berjangka. 5 Efek substitusi produksi beras dengan biji-bijian lainnya yang digunakan dalam pembuatan biofuel. Sumber : BPS 1990 – 2011 Gambar 1 Grafik fluktuasi harga beras dunia, domestik, dan harga gabah kering panen tahun 1990-2011 rpkg Gambar 1 menunjukkan, baik harga beras dunia maupun harga beras domestik selain berfluktuasi juga terus memiliki tren harga yang meningkat. Kenaikan harga beras dunia diprediksi akan terus terjadi mengikuti kenaikan harga minyak mentah dunia yang terus meningkat. Syahputra 2009 memprediksikan masih akan terjadi kenaikan harga minyak mentah dunia dalam lima tahun ke depan. Lima tahun ke depan harga minyak mentah dunia akan 1000 2000 3000 4000 5000 6000 7000 8000 Rpkg P.Domestik P.GTP P.Dunia