The SAS System 1 12:59 Monday, October 10, 2005 The MEANS Procedure Variable N Mean Std Dev Minimum Maximum ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ firm 159 81.8113208 49.1825803 1.0000000 181.0000000 year 159 1955.00 0 1955.00 1955.00 cost 159 14.7172013 22.0337387 0.0820000 139.4220000 output 159 2420.30 3341.56 2.0000000 19170.00 l_p 159 1.9769811 0.2338769 1.4500000 2.3200000 l_shr 159 0.1057799 0.0447009 0.0393000 0.3164000 k_p 159 174.0411321 17.9332343 138.0000000 233.0000000 k_shr 159 0.4268365 0.1164632 0.0904000 0.8448000 f_p 159 26.3266667 7.7042377 10.3000000 42.8000000 f_shr 159 0.4678264 0.1250340 0.0703000 0.7587000 ln_fp 159 3.2177223 0.3484989 2.3321439 3.7565381 ln_t_lp 159 -2.5433591 0.3277734 -3.1969223 -1.6141218 ln_t_kp 159 1.9365696 0.3505497 1.3381946 2.8440058 ln_t_C 159 -1.3820619 1.4957511 -5.6761945 1.7283578 ln_t_lp2 159 6.5754351 1.5842591 2.6053891 10.2203123 ln_t_kp2 159 3.8724141 1.4833043 1.7907647 8.0883692 i_lpkp 159 -4.8254226 0.4304154 -6.0248735 -3.7477501 ln_Y 159 6.6709485 1.9309404 0.6931472 9.8611018 ln_Y2 159 48.2066343 22.6684757 0.4804530 97.2413294 i_Ylp 159 -16.8445033 5.0603714 -26.1594031 -1.4886283 i_Ykp 159 13.0043808 4.6218481 1.6113492 23.5495411 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ The SAS System 2 12:59 Monday, October 10, 2005 The REG Procedure Model: MODEL1 Dependent Variable: ln_t_C Number of Observations Read 159 Number of Observations Used 159 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 9 339.38960 37.70996 398.52 <.0001 Error 149 14.09929 0.09463 Corrected Total 158 353.48889 Root MSE 0.30761 R-Square 0.9601 Dependent Mean -1.38206 Adj R-Sq 0.9577 Coeff Var -22.25758 Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > |t| Intercept 1 -15.20448 14.50948 -1.05 0.2964 ln_t_lp 1 -5.19363 6.76104 -0.77 0.4436 ln_t_kp 1 3.84421 6.09524 0.63 0.5292 ln_t_lp2 1 -0.60715 0.81447 -0.75 0.4572 ln_t_kp2 1 -0.30379 0.70269 -0.43 0.6661 i_lpkp 1 1.05673 1.35969 0.78 0.4383 ln_Y 1 0.27526 0.39399 0.70 0.4859 ln_Y2 1 0.05116 0.00519 9.87 <.0001 i_Ylp 1 0.06512 0.09146 0.71 0.4776 i_Ykp 1 0.01777 0.08415 0.21 0.8331 The SAS System 3 12:59 Monday, October 10, 2005 The REG Procedure Model: MODEL2 Dependent Variable: l_shr Number of Observations Read 159 Number of Observations Used 159 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 3 0.14875 0.04958 46.03 <.0001 Error 155 0.16696 0.00108 Corrected Total 158 0.31571 Root MSE 0.03282 R-Square 0.4712 Dependent Mean 0.10578 Adj R-Sq 0.4609 Coeff Var 31.02708 Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > |t| Intercept 1 0.41443 0.07226 5.74 <.0001 ln_t_lp 1 0.05061 0.01674 3.02 0.0029 ln_t_kp 1 -0.03729 0.01548 -2.41 0.0172 ln_Y 1 -0.01615 0.00138 -11.67 <.0001 The SAS System 4 12:59 Monday, October 10, 2005 The REG Procedure Model: MODEL3 Dependent Variable: k_shr Number of Observations Read 159 Number of Observations Used 159 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 3 0.41518 0.13839 12.41 <.0001 Error 155 1.72789 0.01115 Corrected Total 158 2.14306 Root MSE 0.10558 R-Square 0.1937 Dependent Mean 0.42684 Adj R-Sq 0.1781 Coeff Var 24.73605 Parameter Estimates Parameter Standard Variable DF Estimate Error t Value Pr > |t| Intercept 1 0.46664 0.23245 2.01 0.0464 ln_t_lp 1 0.06592 0.05385 1.22 0.2228 ln_t_kp 1 0.09030 0.04980 1.81 0.0717 ln_Y 1 -0.00705 0.00445 -1.58 0.1154 The SAS System 5 12:59 Monday, October 10, 2005 The MODEL Procedure Model Summary Model Variables 12 Endogenous 3 Exogenous 9 Parameters 10 Equations 3 Number of Statements 3 Model Variables ln_t_lp ln_t_kp ln_t_lp2 ln_t_kp2 i_lpkp ln_Y ln_Y2 i_Ylp i_Ykp ln_t_C l_shr k_shr Parameters alpha beta_lp beta_kp delt_lp2 delt_kp2 delt_i gamm_Ylp gamm_Ykp beta_Y beta_Y2 Equations C ls ks NOTE: The parameter beta_lp is shared by 2 of the equations to be estimated. NOTE: The parameter beta_kp is shared by 2 of the equations to be estimated. NOTE: The parameter delt_lp2 is shared by 2 of the equations to be estimated. NOTE: The parameter delt_kp2 is shared by 2 of the equations to be estimated. NOTE: The parameter delt_i is shared by all 3 of the equations to be estimated. NOTE: The parameter gamm_Ylp is shared by 2 of the equations to be estimated. NOTE: The parameter gamm_Ykp is shared by 2 of the equations to be estimated. The 3 Equations to Estimate C = F(alpha(-1), beta_lp, beta_kp, delt_lp2, delt_kp2, delt_i, gamm_Ylp, gamm_Ykp, beta_Y, beta_Y2) ls = F(beta_lp(-1), delt_lp2, delt_i, gamm_Ylp) ks = F(beta_kp(-1), delt_kp2, delt_i, gamm_Ykp) NOTE: At SUR Iteration 1 CONVERGE=0.001 Criteria Met. The SAS System 6 12:59 Monday, October 10, 2005 The MODEL Procedure SUR Estimation Summary Data Set Options DATA= COSTS Minimization Summary Parameters Estimated 10 Method Gauss Iterations 1 Final Convergence Criteria R 0 PPC 3.14E-12 RPC(gamm_Ykp) 6.169378 Object 0.10443 Trace(S) 0.115615 Objective Value 2.630419 Observations Processed Read 159 Solved 159 The SAS System 7 12:59 Monday, October 10, 2005 The MODEL Procedure Nonlinear SUR Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq C 6.333 152.7 15.7771 0.1033 0.3215 ls 1.833 157.2 0.1680 0.00107 0.0327 ks 1.833 157.2 1.7607 0.0112 0.1058 Nonlinear SUR Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| alpha -4.81575 0.2433 -19.79 <.0001 beta_lp 0.350732 0.0798 4.40 <.0001 beta_kp 0.069623 0.0895 0.78 0.4376 delt_lp2 0.037298 0.0186 2.01 0.0462 delt_kp2 0.17267 0.0277 6.24 <.0001 delt_i -0.02254 0.0170 -1.33 0.1860 gamm_Ylp -0.01596 0.00160 -9.98 <.0001 gamm_Ykp -0.00536 0.00440 -1.22 0.2253 beta_Y 0.199088 0.0562 3.54 0.0005 beta_Y2 0.043495 0.00473 9.19 <.0001 Number of Observations Statistics for System Used 159 Objective 2.6304 Missing 0 Objective*N 418.2366 NOTE: The parameter beta_lp is shared by 2 of the equations to be estimated. NOTE: The parameter beta_kp is shared by 2 of the equations to be estimated. NOTE: The parameter delt_lp2 is shared by 2 of the equations to be estimated. NOTE: The parameter delt_kp2 is shared by 2 of the equations to be estimated. NOTE: The parameter delt_i is shared by all 3 of the equations to be estimated. NOTE: The parameter gamm_Ylp is shared by 2 of the equations to be estimated. NOTE: The parameter gamm_Ykp is shared by 2 of the equations to be estimated. The 3 Equations to Estimate C = F(alpha(-1), beta_lp, beta_kp, delt_lp2, delt_kp2, delt_i, gamm_Ylp, gamm_Ykp, beta_Y, beta_Y2) ls = F(beta_lp(-1), delt_lp2, delt_i, gamm_Ylp) ks = F(beta_kp(-1), delt_kp2, delt_i, gamm_Ykp) NOTE: At FIML Iteration 3 CONVERGE=0.001 Criteria Met. The SAS System 8 12:59 Monday, October 10, 2005 The MODEL Procedure FIML Estimation Summary Data Set Options DATA= COSTS Minimization Summary Parameters Estimated 10 Method Gauss Hessian GLS Covariance Estimator Cross Iterations 3 Final Convergence Criteria R 0.000212 PPC(beta_Y) 0.000929 RPC(beta_Y) 0.005016 Object 7.692E-7 Trace(S) 0.113511 Gradient norm 0.000041 Log likelihood 431.5215 Observations Processed Read 159 Solved 159 The SAS System 9 12:59 Monday, October 10, 2005 The MODEL Procedure Nonlinear FIML Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq C 6.333 152.7 16.1168 0.1056 0.3249 ls 1.833 157.2 0.1675 0.00107 0.0327 ks 1.833 157.2 1.7640 0.0112 0.1059 Nonlinear FIML Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| alpha -4.8887 0.2357 -20.74 <.0001 beta_lp 0.367257 0.0796 4.62 <.0001 beta_kp 0.052105 0.0973 0.54 0.5930 delt_lp2 0.040902 0.0179 2.29 0.0234 delt_kp2 0.177539 0.0303 5.86 <.0001 delt_i -0.02604 0.0180 -1.44 0.1505 gamm_Ylp -0.01604 0.00125 -12.84 <.0001 gamm_Ykp -0.00547 0.00367 -1.49 0.1385 beta_Y 0.243866 0.0505 4.83 <.0001 beta_Y2 0.039592 0.00478 8.29 <.0001 Number of Observations Statistics for System Used 159 Log Likelihood 431.5215 Missing 0 The SAS System 10 12:59 Monday, October 10, 2005 The MODEL Procedure Model Summary Model Variables 12 Endogenous 3 Exogenous 9 Parameters 8 Equations 3 Number of Statements 3 Model Variables ln_t_lp ln_t_kp ln_t_lp2 ln_t_kp2 i_lpkp ln_Y ln_Y2 i_Ylp i_Ykp ln_t_C l_shr k_shr Parameters alpha beta_lp beta_kp delt_lp2 delt_kp2 delt_i beta_Y beta_Y2 Equations C ls ks NOTE: The parameter beta_lp is shared by 2 of the equations to be estimated. NOTE: The parameter beta_kp is shared by 2 of the equations to be estimated. NOTE: The parameter delt_lp2 is shared by 2 of the equations to be estimated. NOTE: The parameter delt_kp2 is shared by 2 of the equations to be estimated. NOTE: The parameter delt_i is shared by all 3 of the equations to be estimated. The 3 Equations to Estimate C = F(alpha(-1), beta_lp, beta_kp, delt_lp2, delt_kp2, delt_i, beta_Y, beta_Y2) ls = F(beta_lp(-1), delt_lp2, delt_i) ks = F(beta_kp(-1), delt_kp2, delt_i) NOTE: At SUR Iteration 1 CONVERGE=0.001 Criteria Met. The SAS System 11 12:59 Monday, October 10, 2005 The MODEL Procedure SUR Estimation Summary Data Set Options DATA= COSTS Minimization Summary Parameters Estimated 8 Method Gauss Iterations 1 Final Convergence Criteria R 0 PPC 7.81E-12 RPC(beta_lp) 4.07815 Object 0.029849 Trace(S) 0.116409 Objective Value 2.861665 Observations Processed Read 159 Solved 159 The SAS System 12 12:59 Monday, October 10, 2005 The MODEL Procedure Nonlinear SUR Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq C 5.333 153.7 15.8543 0.1032 0.3212 ls 1.333 157.7 0.3145 0.00199 0.0447 ks 1.333 157.7 1.7723 0.0112 0.1060 Nonlinear SUR Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| alpha -5.3706 0.2529 -21.24 <.0001 beta_lp 0.130646 0.0902 1.45 0.1494 beta_kp 0.104149 0.0944 1.10 0.2715 delt_lp2 0.00461 0.0216 0.21 0.8312 delt_kp2 0.156915 0.0285 5.50 <.0001 delt_i -0.00683 0.0198 -0.34 0.7307 beta_Y 0.242222 0.0560 4.33 <.0001 beta_Y2 0.044597 0.00477 9.36 <.0001 Number of Observations Statistics for System Used 159 Objective 2.8617 Missing 0 Objective*N 455.0047 NOTE: The parameter beta_lp is shared by 2 of the equations to be estimated. NOTE: The parameter beta_kp is shared by 2 of the equations to be estimated. NOTE: The parameter delt_lp2 is shared by 2 of the equations to be estimated. NOTE: The parameter delt_kp2 is shared by 2 of the equations to be estimated. NOTE: The parameter delt_i is shared by all 3 of the equations to be estimated. The 3 Equations to Estimate C = F(alpha(-1), beta_lp, beta_kp, delt_lp2, delt_kp2, delt_i, beta_Y, beta_Y2) ls = F(beta_lp(-1), delt_lp2, delt_i) ks = F(beta_kp(-1), delt_kp2, delt_i) NOTE: At FIML Iteration 7 CONVERGE=0.001 Criteria Met. The SAS System 13 12:59 Monday, October 10, 2005 The MODEL Procedure FIML Estimation Summary Data Set Options DATA= COSTS Minimization Summary Parameters Estimated 8 Method Gauss Hessian GLS Covariance Estimator Cross Iterations 7 Final Convergence Criteria R 0.000944 PPC(delt_i) 0.025306 RPC(delt_i) 0.045196 Object 2.324E-6 Trace(S) 0.123916 Gradient norm 0.000594 Log likelihood 380.8165 Observations Processed Read 159 Solved 159 The SAS System 14 12:59 Monday, October 10, 2005 The MODEL Procedure Nonlinear FIML Summary of Residual Errors DF DF Adj Equation Model Error SSE MSE Root MSE R-Square R-Sq C 5.333 153.7 17.6148 0.1146 0.3386 ls 1.333 157.7 0.3156 0.00200 0.0447 ks 1.333 157.7 1.7722 0.0112 0.1060 Nonlinear FIML Parameter Estimates Approx Approx Parameter Estimate Std Err t Value Pr > |t| alpha -5.74935 0.2544 -22.60 <.0001 beta_lp 0.112456 0.0985 1.14 0.2553 beta_kp 0.119581 0.1028 1.16 0.2465 delt_lp2 0.001893 0.0235 0.08 0.9360 delt_kp2 0.156532 0.0304 5.15 <.0001 delt_i -0.00103 0.0219 -0.05 0.9626 beta_Y 0.331139 0.0456 7.26 <.0001 beta_Y2 0.039334 0.00401 9.80 <.0001 Number of Observations Statistics for System Used 159 Log Likelihood 380.8165 Missing 0