The SAS System 16:49 Wednesday, November 10, 1999 34 OBS GI GV GK WI WV WK 1 33.1 1170.6 97.8 12.93 191.5 1.8 2 45.0 2015.8 104.4 25.90 516.0 0.8 3 77.2 2803.3 118.0 35.05 729.0 7.4 4 44.6 2039.7 156.2 22.89 560.4 18.1 5 48.1 2256.2 172.6 18.84 519.9 23.5 6 74.4 2132.2 186.6 28.57 628.5 26.5 7 113.0 1834.1 220.9 48.51 537.1 36.2 8 91.9 1588.0 287.8 43.34 561.2 60.8 9 61.3 1749.4 319.9 37.02 617.2 84.4 10 56.8 1687.2 321.3 37.81 626.7 91.2 11 93.6 2007.7 319.6 39.27 737.2 92.4 12 159.9 2208.3 346.0 53.46 760.5 86.0 13 147.2 1656.7 456.4 55.56 581.4 111.1 14 146.3 1604.4 543.4 49.56 662.3 130.6 15 98.3 1431.8 618.3 32.04 583.8 141.8 16 93.5 1610.5 647.4 32.24 635.2 136.7 17 135.2 1819.4 671.3 54.38 723.8 129.7 18 157.3 2079.7 726.1 71.78 864.1 145.5 19 179.5 2371.6 800.3 90.08 1193.5 174.8 20 189.6 2759.9 888.9 68.60 1188.9 213.5 The SAS System 16:49 Wednesday, November 10, 1999 35 MODEL Procedure Model Summary Model Variables 2 Parameters 6 Equations 2 Number of Statements 2 Model Variables: GI WI Parameters: G1 G2 G3 W1 W2 W3 Equations: GI WI The SAS System 16:49 Wednesday, November 10, 1999 36 MODEL Procedure The 2 Equations to Estimate are: GI = F( G1(1), G2(GV), G3(GK) ) WI = F( W1(1), W2(WV), W3(WK) ) The SAS System 16:49 Wednesday, November 10, 1999 37 MODEL Procedure OLS Estimation OLS Estimation Summary Dataset Option Dataset DATA= ONE Parameters Estimated 6 Minimization Summary Method GAUSS Iterations 1 Final Convergence Criteria R 0 PPC 0 RPC(G1) 98578.28 Object 0.94947478 Trace(S) 881.754218 Objective Value 749.491085 Observations Processed Read 20 Solved 20 The SAS System 16:49 Wednesday, November 10, 1999 38 MODEL Procedure OLS Estimation Nonlinear OLS Summary of Residual Errors DF DF Equation Model Error SSE MSE Root MSE R-Square Adj R-Sq GI 3 17 13217 777.44634 27.88272 0.7053 0.6706 WI 3 17 1773 104.30788 10.21312 0.7444 0.7144 Nonlinear OLS Parameter Estimates Approx. 'T' Approx. Parameter Estimate Std Err Ratio Prob>|T| G1 -9.956306 31.37425 -0.32 0.7548 G2 0.026551 0.01557 1.71 0.1063 G3 0.151694 0.02570 5.90 0.0001 W1 -0.509390 8.01529 -0.06 0.9501 W2 0.052894 0.01571 3.37 0.0037 W3 0.092406 0.05610 1.65 0.1179 Number of Observations Statistics for System Used 20 Objective 749.4911 Missing 0 Objective*N 14990 Covariance of Residuals S GI WI GI 777.4463 207.5871 WI 207.5871 104.3079 The SAS System 16:49 Wednesday, November 10, 1999 39 MODEL Procedure SUR Estimation SUR Estimation Summary Dataset Option Dataset DATA= ONE Parameters Estimated 6 Minimization Summary Method GAUSS Iterations 1 Final Convergence Criteria R 0 PPC 0 RPC(G1) 1.784096 Object 0.02812639 Trace(S) 917.039807 Objective Value 1.65218511 Observations Processed Read 20 Solved 20 The SAS System 16:49 Wednesday, November 10, 1999 40 MODEL Procedure SUR Estimation Nonlinear SUR Summary of Residual Errors DF DF Equation Model Error SSE MSE Root MSE R-Square Adj R-Sq GI 3 17 13788 811.08093 28.47948 0.6926 0.6564 WI 3 17 1801 105.95888 10.29363 0.7404 0.7099 Nonlinear SUR Parameter Estimates Approx. 'T' Approx. Parameter Estimate Std Err Ratio Prob>|T| G1 -27.719317 29.32122 -0.95 0.3577 G2 0.038310 0.01442 2.66 0.0166 G3 0.139036 0.02499 5.56 0.0001 W1 -1.251988 7.54522 -0.17 0.8702 W2 0.057630 0.01455 3.96 0.0010 W3 0.063978 0.05304 1.21 0.2443 Number of Observations Statistics for System Used 20 Objective 1.6522 Missing 0 Objective*N 33.0437 Covariance of Residuals Matrix Used for Estimation S GI WI GI 777.4463 207.5871 WI 207.5871 104.3079 Covariance of Residuals S GI WI GI 811.0809 224.2779 WI 224.2779 105.9589