* Model RAS Tabel IO KEPRI Tahun 2017 * Basis data : Tabel IO updating KEPRI Tahun 2010 * Struktur Tabel RAS : 17 sektor * Disusun oleh : Meirina Anggraeni * PWL - IPB SETS i sektor input antara/1*17/; ALIAS (i,j); SCALAR TotM Total Impor KEPRI 2017/344698.20/ TotF Total Final Demand KEPRI 2017/574441.31/ TotV Total PDRB KEPRI 2017/229743.11/; PARAMETERS Q2017(j) total input tabel I-O Dugaan KEPRI 2017 17 sektor/ 1 12576.99 2 4895.65 3 46417.16 4 162543.00 5 3076.01 6 209.08 7 58574.09 8 22764.15 9 6179.93 10 23213.79 11 3161.63 12 10507.64 13 16563.98 14 11110.42 15 1656.71 16 37861.88 17 2115.51 / PDRB2017(j) PDRB KEPRI tiap sektor tahun 2017/ 1 2790.54 2 5150.40 3 33209.78 4 84434.95 5 2689.97 6 284.13 7 41409.19 8 20233.11 9 5061.47 10 7507.03 11 4575.79 12 6269.84 13 3530.39 14 5973.81 15 2119.21 16 3428.41 17 1075.07 /; TABLE A2010(i,j) Koefisien Teknis KEPRI Tahun 2010 17 Sektor 1 2 3 4 5 6 7 8 1 0.0125 0.0012 0.0000 0.0044 0.0000 0.0000 0.0000 0.0000 2 0.0000 0.0030 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 3 0.0000 0.0000 0.0000 0.0007 0.0716 0.0000 0.0176 0.0000 4 0.3445 0.0127 0.1249 0.2284 0.1347 0.1146 0.2889 0.0297 5 0.0000 0.0000 0.0044 0.0032 0.0315 0.0027 0.0001 0.0014 6 0.0003 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 7 0.0005 0.0000 0.0000 0.0000 0.0000 0.0000 0.0008 0.0000 8 0.0136 0.0006 0.0040 0.0079 0.0077 0.0036 0.0101 0.0010 9 0.0000 0.0000 0.0001 0.0003 0.0008 0.0027 0.0000 0.0002 10 0.0072 0.0068 0.0414 0.0530 0.0000 0.0055 0.0000 0.0016 11 0.0000 0.0000 0.0001 0.0001 0.0004 0.0008 0.0003 0.0001 12 0.0008 0.0005 0.0008 0.0021 0.0026 0.0134 0.0134 0.0064 13 0.0026 0.0022 0.0026 0.0052 0.0490 0.0167 0.0268 0.0020 14 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 15 0.0000 0.0000 0.0000 0.0000 0.0001 0.0002 0.0000 0.0000 16 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 17 0.0054 0.0015 0.0014 0.0035 0.0045 0.0016 0.0009 0.0122 + 9 10 11 12 13 14 15 16 1 0.0705 0.0000 0.0000 0.0000 0.0000 0.0010 0.0000 0.0000 2 0.0135 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 3 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 4 0.0935 0.1816 0.0444 0.0160 0.0361 0.4339 0.1152 0.0077 5 0.0014 0.0009 0.0091 0.0001 0.0093 0.0001 0.0094 0.0019 6 0.0016 0.0001 0.0000 0.0000 0.0000 0.0000 0.0000 0.0003 7 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 8 0.0072 0.0057 0.0015 0.0005 0.0011 0.0163 0.0039 0.0003 9 0.0000 0.0023 0.0000 0.0323 0.0053 0.0026 0.0122 0.3936 10 0.0000 0.0498 0.0539 0.0122 0.0376 0.0020 0.0004 0.0004 11 0.0001 0.0006 0.0015 0.0001 0.0020 0.0146 0.0021 0.0006 12 0.0025 0.0301 0.0000 0.3010 0.0000 0.0000 0.0000 0.0000 13 0.1260 0.0276 0.0067 0.0172 0.0252 0.0000 0.0000 0.0095 14 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0105 0.0000 15 0.0000 0.0000 0.0000 0.0001 0.0000 0.0002 0.0010 0.0000 16 0.0086 0.0000 0.0000 0.0012 0.0000 0.0000 0.0000 0.0435 17 0.0222 0.0206 0.0043 0.0094 0.0201 0.0000 0.0018 0.0021 + 17 1 0.0000 2 0.0000 3 0.0000 4 0.1496 5 0.0070 6 0.0003 7 0.0000 8 0.0048 9 0.0000 10 0.0077 11 0.0009 12 0.0000 13 0.0000 14 0.0000 15 0.0000 16 0.0000 17 0.0217 ; PARAMETERS TB(i) Original estimate for sectoral Total Output or Input cells 2017 QB(i,j) Original estimate for intersectoral IO transaction cells 2017 VB(j) Original estimate for sectoral Value Added cells 2017 MB(j) Original estimate for sectoral Import cells 2017 FB(i) Original estimate for sectoral Final Demand cells 2017 TW(i) Weight for sectoral Total Output or Input cells QW(i,j) Weight for sectoral intersectoral IO transaction cells VW(j) Weight for sectoral Value Added cells MW(j) Weight for sectoral Import cells FW(i) Weight for sectoral Final Demand cells; TB(i) = Q2017(i); QB(i,j) = A2010(i,j)*TB(j); VB(j) = PDRB2017(j); MB(j) = TB(j)-VB(j)- Sum(i,QB(i,j)); FB(i) = TB(i)-Sum(j,QB(i,j)); TW(i)$(TB(i) GT 0) = 1; QW(i,j)$(QB(i,j) GT 0) = 1; VW(j)$(VB(j) GT 0) = 1; MW(j)$(MB(j) GT 0) = 1; FW(i)$(FB(i) GT 0) = 1; TW(i)$(TB(i) EQ 0) = 0; QW(i,j)$(QB(i,j) EQ 0) = 0; VW(j)$(VB(j) EQ 0) = 0; MW(j)$(MB(j) EQ 0) = 0; FW(i)$(FB(i) EQ 0) = 0; VARIABLES SSDEV Sum of Squared Deviation estimating Information Gain T(i) Optimal estimates for Sectoral Total Output or Input cells 2017 Q(i,j) Optimal estimates for Intersectoral Transaction cells 2017 M(j) Optimal estimates for Sectoral Import cells 2017 F(i) Optimal estimates for Sectoral Final Demand cells 2017 FM Optimal estimates for Final Demand for Import cells 2017 FF Optimal estimates for Final Demand for Final Demand cells 2017; POSITIVE VARIABLES T,Q,M,F,FM,FF; EQUATIONS OBJ Objective Function CBal(j) Column Balance Constraint Function RBal(i) Row Balance Constraint Function TBal total Balance Constraint Function TM Total Import Constraint Function TF Total Final Demand Constraint Function; OBJ .. SSDEV=E=Sum((i,j)$ (QW(i,j) GT 0), QW(i,j)* SQR(Q(i,j)- QB(i,j) )/QB(i,j))+ Sum((i)$ (TW(i) GT 0), TW(i)* SQR(T(i)- TB(i))/TB(i)) + Sum((j)$ (MW(j) GT 0), MW(j)* SQR(M(j)- MB(j))/MB(j)) + Sum((i)$ (FW(i) GT 0), FW(i)* SQR(F(i)- FB(i))/FB(i)); CBal(j) ..T(j)=E=Sum(i,Q(i,j)$(QB(i,j) GT 0))+ M(j)$ (MB(j) GT 0) + VB(j); RBal(i) ..T(i)=E=Sum(j,Q(i,j)$(QB(i,j) GT 0))+ F(i); TM ..Sum(j,M(j)$ (MB(j) GT 0))+FM=E=TotM; TF ..Sum(i,F(i))+FF=E=TotF; TBal ..TotV+TotM - TotF=E=0; MODEL ModelRAS/ALL/; Q.L(i,j)=QB(i,j)$QW(i,j) ; T.L(i)=TB(i)$TW(i) ; M.L(i)=MB(i)$MW(i) ; F.L(i)=FB(i)$FW(i) ; OPTION NLP = MINOS5 ; OPTION RESLIM = 9000 ; OPTION ITERLIM = 100000 ; SOLVE ModelRAS USING NLP MINIMIZING SSDEV; SETS Item/MP2017,FD2017,TO2017 /; PARAMETERS HslL (i,Item) Tabel Hasil Level Optimal HslM (i,Item) Tabel Hasil Marginal Value ; HslL(i,"MP2017")=M.L(i) ; HslL(i,"FD2017")=F.L(i) ; HslL(i,"TO2017")=T.L(i) ; HslM(i,"MP2017")=M.L(i); HslM(i,"FD2017")=F.L(i); HslM(i,"TO2017")=T.L(i); DISPLAY Q.L, Q.M, T.L, M.L, F.L, HslL, HslM, FM.L, FM.M, FF.L, FF.M;