The SAS System 1 14:41 Tuesday, October 18, 2005 The MEANS Procedure Variable N Mean Std Dev Minimum Maximum ャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャ coalp 48 1.5352083 0.5100688 0.7300000 3.6200000 coalq 48 410.2452083 388.9985671 0.0700000 1432.32 gasp 48 4.5231250 0.9258260 2.5000000 6.9900000 gasq 48 425.7514583 648.4359399 5.0400000 3846.01 pop 48 5205.79 5597.59 460.0000000 30380.00 income 48 29035.15 4729.76 20178.00 40805.00 cdd 48 1203.42 906.4234564 190.0000000 4198.00 hdd 48 5013.02 2078.57 200.0000000 8968.00 ctop5 48 0.1041667 0.3087093 0 1.0000000 cadj 48 0.3541667 0.4833211 0 1.0000000 gtop5 48 0.1041667 0.3087093 0 1.0000000 gadj 48 0.2083333 0.4104141 0 1.0000000 lnpop 48 8.0972992 0.9962410 6.1312265 10.3215398 lninc 48 10.2635529 0.1606359 9.9123482 10.6165599 lnp_g 48 1.4885999 0.2066607 0.9162907 1.9444806 lnp_c 48 0.3847975 0.2908235 -0.3147107 1.2864740 lnq_g 48 5.3268848 1.3117949 1.6174061 8.2547915 lnq_c 48 5.1926172 2.0020005 -2.6592600 7.2670508 ャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャャ The SAS System 2 14:41 Tuesday, October 18, 2005 The MODEL Procedure Model Summary Model Variables 12 Exogenous 8 Parameters 36 Equations 4 Number of Statements 4 The 4 Equations to Estimate lnp_c = F(b1(1), b2(lnpop), b3(lninc), b4(cdd), b5(hdd), b6(ctop5), b7(cadj), b8(gtop5), b9(gadj)) lnq_c = F(b10(1), b11(lnpop), b12(lninc), b13(cdd), b14(hdd), b15(ctop5), b16(cadj), b17(gtop5), b18(gadj)) lnp_g = F(b19(1), b20(lnpop), b21(lninc), b22(cdd), b23(hdd), b24(ctop5), b25(cadj), b26(gtop5), b27(gadj)) lnq_g = F(b28(1), b29(lnpop), b30(lninc), b31(cdd), b32(hdd), b33(ctop5), b34(cadj), b35(gtop5), b36(gadj)) NOTE: At SUR Iteration 0 CONVERGE=0.001 Criteria Met. The SAS System 3 14:41 Tuesday, October 18, 2005 The MODEL Procedure SUR Estimation Summary Data Set Options DATA= COALGAS Minimization Summary Parameters Estimated 36 Method Gauss Iterations 0 Final Convergence Criteria R 0 PPC 1.16E-11 RPC . Object . Trace(S) 2.782134 Objective Value 3.25 Observations Processed Read 48 Solved 48 The SAS System 4 14:41 Tuesday, October 18, 2005 The MODEL Procedure Nonlinear SUR Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq lnp_c 9 39 2.5113 0.0644 0.2538 0.3683 0.2387 lnq_c 9 39 92.2744 2.3660 1.5382 0.5102 0.4097 lnp_g 9 39 0.7138 0.0183 0.1353 0.6444 0.5715 lnq_g 9 39 13.0038 0.3334 0.5774 0.8392 0.8062 Nonlinear SUR Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| b1 -0.86437 2.9879 -0.29 0.7739 b2 -0.05836 0.0480 -1.22 0.2310 b3 0.220596 0.2961 0.74 0.4608 b4 -0.00007 0.000076 -0.92 0.3634 b5 -0.00006 0.000035 -1.69 0.0997 b6 -0.20349 0.1306 -1.56 0.1272 b7 -0.17218 0.0878 -1.96 0.0571 b8 -0.28791 0.1312 -2.19 0.0343 b9 -0.22386 0.1109 -2.02 0.0505 b10 21.80754 18.1117 1.20 0.2358 b11 1.223931 0.2907 4.21 0.0001 b12 -2.91613 1.7950 -1.62 0.1123 b13 0.000865 0.000459 1.88 0.0670 b14 0.000342 0.000215 1.59 0.1200 b15 1.896988 0.7914 2.40 0.0214 b16 1.032145 0.5322 1.94 0.0597 b17 0.95092 0.7956 1.20 0.2392 b18 -0.05402 0.6724 -0.08 0.9364 b19 -2.63528 1.5929 -1.65 0.1061 b20 -0.00432 0.0256 -0.17 0.8669 b21 0.393887 0.1579 2.49 0.0169 b22 0.000014 0.000040 0.35 0.7252 b23 0.000032 0.000019 1.71 0.0956 b24 0.021214 0.0696 0.30 0.7622 b25 0.00127 0.0468 0.03 0.9785 b26 -0.33144 0.0700 -4.74 <.0001 b27 -0.1489 0.0591 -2.52 0.0160 b28 1.549764 6.7991 0.23 0.8209 b29 1.214545 0.1091 11.13 <.0001 b30 -0.60193 0.6739 -0.89 0.3772 b31 -0.00011 0.000172 -0.65 0.5170 b32 -0.00002 0.000081 -0.25 0.8037 b33 0.353868 0.2971 1.19 0.2408 b34 0.121567 0.1998 0.61 0.5464 b35 1.566062 0.2987 5.24 <.0001 b36 0.548391 0.2524 2.17 0.0360 The SAS System 5 14:41 Tuesday, October 18, 2005 The MODEL Procedure Number of Observations Statistics for System Used 48 Objective 3.2500 Missing 0 Objective*N 156.0000 The SAS System 6 14:41 Tuesday, October 18, 2005 The MODEL Procedure Model Summary Model Variables 8 Exogenous 8 Parameters 22 Equations 4 Number of Statements 4 Model Variables lnpop lninc cdd hdd ctop5 cadj gtop5 gadj Parameters b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 b12 b13 b14 b15 b16 b17 b18 b19 b20 b21 b22 Equations c_demand c_supply g_demand g_supply The Equation to Estimate is c_demand = F(b1(-1), b2, b3, b4, b5, b6, b7) NOTE: At OLS Iteration 1 CONVERGE=0.001 Criteria Met. The SAS System 7 14:41 Tuesday, October 18, 2005 The MODEL Procedure OLS Estimation Summary Data Set Options DATA= COALGAS Minimization Summary Parameters Estimated 7 Method Gauss Iterations 1 Final Convergence Criteria R 0 PPC 0 RPC(b1) 12184.77 Object 0.839891 Trace(S) 0.033645 Objective Value 0.028738 Observations Processed Read 48 Solved 48 The SAS System 8 14:41 Tuesday, October 18, 2005 The MODEL Procedure Nonlinear OLS Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq c_demand 7 41 1.3794 0.0336 0.1834 Nonlinear OLS Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| b1 1.230762 2.1539 0.57 0.5708 b2 -0.11699 0.0176 -6.66 <.0001 b3 0.429019 0.1727 2.48 0.0172 b4 0.098202 0.0412 2.38 0.0218 b5 -0.14374 0.2252 -0.64 0.5269 b6 0.000016 0.000056 0.29 0.7760 b7 -0.00004 0.000027 -1.59 0.1194 Number of Observations Statistics for System Used 48 Objective 0.0287 Missing 0 Objective*N 1.3794 The Equation to Estimate is c_supply = F(b8(-1), b9, b10, b11) NOTE: At OLS Iteration 1 CONVERGE=0.001 Criteria Met. The SAS System 9 14:41 Tuesday, October 18, 2005 The MODEL Procedure OLS Estimation Summary Data Set Options DATA= COALGAS Minimization Summary Parameters Estimated 4 Method Gauss Iterations 1 Final Convergence Criteria R 0 PPC 0 RPC(b8) 8586.722 Object 0.794172 Trace(S) 0.051745 Objective Value 0.047433 Observations Processed Read 48 Solved 48 The SAS System 10 14:41 Tuesday, October 18, 2005 The MODEL Procedure Nonlinear OLS Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq c_supply 4 44 2.2768 0.0517 0.2275 Nonlinear OLS Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| b8 0.867359 0.0938 9.25 <.0001 b9 -0.08038 0.0175 -4.60 <.0001 b10 -0.06932 0.1164 -0.60 0.5547 b11 -0.16368 0.0721 -2.27 0.0282 Number of Observations Statistics for System Used 48 Objective 0.0474 Missing 0 Objective*N 2.2768 The Equation to Estimate is g_demand = F(b12(-1), b13, b14, b15, b16, b17, b18) NOTE: At OLS Iteration 1 CONVERGE=0.001 Criteria Met. The SAS System 11 14:41 Tuesday, October 18, 2005 The MODEL Procedure OLS Estimation Summary Data Set Options DATA= COALGAS Minimization Summary Parameters Estimated 7 Method Gauss Iterations 1 Final Convergence Criteria R 0 PPC 7.8E-12 RPC(b12) 28310.67 Object 0.98178 Trace(S) 0.01682 Objective Value 0.014367 Observations Processed Read 48 Solved 48 The SAS System 12 14:41 Tuesday, October 18, 2005 The MODEL Procedure Nonlinear OLS Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq g_demand 7 41 0.6896 0.0168 0.1297 Nonlinear OLS Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| b12 -2.85928 1.4317 -2.00 0.0525 b13 -0.12949 0.0303 -4.28 0.0001 b14 0.076001 0.0791 0.96 0.3423 b15 0.17069 0.0405 4.22 0.0001 b16 0.335321 0.1468 2.28 0.0276 b17 -3.2E-6 0.000039 -0.08 0.9352 b18 0.000038 0.000019 1.99 0.0529 Number of Observations Statistics for System Used 48 Objective 0.0144 Missing 0 Objective*N 0.6896 The Equation to Estimate is g_supply = F(b19(-1), b20, b21, b22) NOTE: At OLS Iteration 1 CONVERGE=0.001 Criteria Met. The SAS System 13 14:41 Tuesday, October 18, 2005 The MODEL Procedure OLS Estimation Summary Data Set Options DATA= COALGAS Minimization Summary Parameters Estimated 4 Method Gauss Iterations 1 Final Convergence Criteria R 0 PPC 0 RPC(b19) 17592.6 Object 0.99078 Trace(S) 0.022689 Objective Value 0.020798 Observations Processed Read 48 Solved 48 The SAS System 14 14:41 Tuesday, October 18, 2005 The MODEL Procedure Nonlinear OLS Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq g_supply 4 44 0.9983 0.0227 0.1506 Nonlinear OLS Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| b19 1.776952 0.0964 18.43 <.0001 b20 -0.039 0.0176 -2.22 0.0319 b21 -0.37247 0.0751 -4.96 <.0001 b22 -0.20056 0.0547 -3.67 0.0007 Number of Observations Statistics for System Used 48 Objective 0.0208 Missing 0 Objective*N 0.9983 The 4 Equations to Estimate c_demand = F(b1(-1), b2, b3, b4, b5, b6, b7) c_supply = F(b8(-1), b9, b10, b11) g_demand = F(b12(-1), b13, b14, b15, b16, b17, b18) g_supply = F(b19(-1), b20, b21, b22) Instruments 1 lnpop lninc cdd hdd ctop5 cadj gtop5 gadj NOTE: At 3SLS Iteration 1 CONVERGE=0.001 Criteria Met. The SAS System 15 14:41 Tuesday, October 18, 2005 The MODEL Procedure 3SLS Estimation Summary Data Set Options DATA= COALGAS Minimization Summary Parameters Estimated 22 Method Gauss Iterations 1 Final Convergence Criteria R 0 PPC 5.82E-11 RPC(b6) 2.210877 Object 0.315846 Trace(S) 0.145981 Objective Value 0.799766 Observations Processed Read 48 Solved 48 The SAS System 16 14:41 Tuesday, October 18, 2005 The MODEL Procedure Nonlinear 3SLS Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq c_demand 7 41 1.5323 0.0374 0.1933 c_supply 4 44 2.7789 0.0632 0.2513 g_demand 7 41 0.9198 0.0224 0.1498 g_supply 4 44 1.0127 0.0230 0.1517 Nonlinear 3SLS Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| b1 0.252961 2.1212 0.12 0.9057 b2 -0.11527 0.0397 -2.90 0.0059 b3 0.251617 0.2474 1.02 0.3152 b4 0.107433 0.0607 1.77 0.0844 b5 -0.05449 0.2348 -0.23 0.8176 b6 0.000046 0.000056 0.82 0.4151 b7 -1.98E-6 0.000029 -0.07 0.9452 b8 0.610373 0.1403 4.35 <.0001 b9 -0.03034 0.0280 -1.08 0.2839 b10 -0.2147 0.1271 -1.69 0.0982 b11 -0.12897 0.0722 -1.79 0.0809 b12 -0.11246 1.3969 -0.08 0.9362 b13 -0.21544 0.0628 -3.43 0.0014 b14 0.020685 0.2011 0.10 0.9186 b15 0.251725 0.0697 3.61 0.0008 b16 0.063001 0.1472 0.43 0.6709 b17 -0.00002 0.000040 -0.49 0.6289 b18 0.000016 0.000023 0.69 0.4920 b19 1.717125 0.1049 16.36 <.0001 b20 -0.02903 0.0194 -1.50 0.1409 b21 -0.34607 0.0746 -4.64 <.0001 b22 -0.18167 0.0490 -3.71 0.0006 Number of Observations Statistics for System Used 48 Objective 0.7998 Missing 0 Objective*N 38.3887 The SAS System 17 14:41 Tuesday, October 18, 2005 The MODEL Procedure Model Summary Model Variables 8 Exogenous 8 Parameters 22 Equations 4 Number of Statements 4 Model Variables lnpop lninc cdd hdd ctop5 cadj gtop5 gadj Parameters(Value) b1 b2 b3 b4 b5 b6 b7 b8 b9(0) b10 b11 b12 b13 b14 b15 b16 b17 b18 b19 b20(0) b21 b22 Equations c_demand c_supply g_demand g_supply The 4 Equations to Estimate c_demand = F(b1(-1), b2, b3, b4, b5, b6, b7) c_supply = F(b8(-1), b10, b11) g_demand = F(b12(-1), b13, b14, b15, b16, b17, b18) g_supply = F(b19(-1), b21, b22) Instruments 1 lnpop lninc cdd hdd ctop5 cadj gtop5 gadj NOTE: At 3SLS Iteration 1 CONVERGE=0.001 Criteria Met. The SAS System 18 14:41 Tuesday, October 18, 2005 The MODEL Procedure 3SLS Estimation Summary Data Set Options DATA= COALGAS Minimization Summary Parameters Estimated 20 Method Gauss Iterations 1 Final Convergence Criteria R 0 PPC 1.46E-11 RPC(b6) 2.469531 Object 0.255391 Trace(S) 0.159379 Objective Value 0.79324 Observations Processed Read 48 Solved 48 The SAS System 19 14:41 Tuesday, October 18, 2005 The MODEL Procedure Nonlinear 3SLS Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq c_demand 7 41 1.4895 0.0363 0.1906 c_supply 3 45 3.4415 0.0765 0.2765 g_demand 7 41 0.8881 0.0217 0.1472 g_supply 3 45 1.1210 0.0249 0.1578 Nonlinear 3SLS Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| b1 0.524359 2.2209 0.24 0.8145 b2 -0.11294 0.0402 -2.81 0.0075 b3 0.335405 0.2558 1.31 0.1972 b4 0.102421 0.0603 1.70 0.0972 b5 -0.08849 0.2450 -0.36 0.7198 b6 0.00005 0.000057 0.87 0.3872 b7 -6.61E-6 0.000029 -0.22 0.8234 b8 0.46724 0.0526 8.89 <.0001 b10 -0.26813 0.1278 -2.10 0.0416 b11 -0.15392 0.0776 -1.98 0.0534 b12 -0.46248 1.4603 -0.32 0.7531 b13 -0.21044 0.0634 -3.32 0.0019 b14 0.006499 0.2055 0.03 0.9749 b15 0.262232 0.0696 3.77 0.0005 b16 0.086679 0.1538 0.56 0.5760 b17 -0.00002 0.000042 -0.51 0.6116 b18 0.000016 0.000024 0.69 0.4923 b19 1.563068 0.0269 58.02 <.0001 b21 -0.36785 0.0737 -4.99 <.0001 b22 -0.17352 0.0514 -3.37 0.0015 Number of Observations Statistics for System Used 48 Objective 0.7932 Missing 0 Objective*N 38.0755