【正确答案】解：首先，估计Logit模型。在Eviews软件中，选择“Quick/Estimate Equation”在出现的对话框中输入“Y C X D”，在“Quick/Estimate Setting”的“Methods”栏内选择“Binary”，再在新出现的选项中选择“Logit”，点击OK,可得下表所示输出结果。 Dependent Variable:Y Method: ML-Binary Logit(Quadratic hill climbing) Date:02/20/06 Time:21:26 Sample:185 included observations:85 Convergence achieved after 12 iterations Covariance matrix computed using second derivatives Variable Coefficient Std.Error z-Statistic Prob C -242.4576 124.5183 -1.947165 0.0515 X 0.677061 0.348036 1.945380 0.0517 D1 -0.476605 2.984586 -0.159689 0.8731 Mean dependent var 0.164706 S.D. dependent var 0.373116 SE.of regression 0.122531 Akaike info criterion 0.164223 Sum squared resid 1.251316 Schwarz criterion 0.250434 Log likelihood -3.979482 Hannan-Quinn Criter 0.198900 Restr log likelihood -38.02828 Avg. log likelihood -0.046817 LR statistic(2 df) 68.09760 McFadden R-Squared 0.895355 Probability(LR stat) 1.67E-15 Obs with Dep=0 71 Total obs 85 Obs with DeP=1 14 根据输出结果可得到估计的Logit模型： (-1.95) (1.95) (-0.16) ＝0.8953 LR(2)＝68.10 接下来，估计Probit模型，在上面Eviews操作步骤中的“Methods”栏内选择“Binary”后，在新出现的选项中选择“Probit”，点击OK，可得下表所示输出结果。 Dependent Variable:Y Method: ML-Binary Logit(Quadratic hill climbing) Date:02/20/06 Time:21:29 Sample:185 included observations:85 Convergence achieved after 11 iterations Covariance matrix computed using second derivatives Variable Coefficient Std.Error z-Statistic Prob C -143.3214 69.81266 -2.052942 0.0401 X 0.400315 0.195064 2.052221 0.0401 D1 -0.247079 1.643146 -0.150369 0.8805 Mean dependent var 0.164706 S.D. dependent var 0.373116 SE.of regression 0.124527 Akaike info criterion 0.162953 Sum squared resid 1.271570 Schwarz criterion 0.249164 Log likelihood -3.925501 Hannan-Quinn Criter 0.197630 Restr log likelihood -38.02828 Avg. log likelihood -0.046182 LR statistic(2 df) 68.20556 McFadden R-Squared 0.896774 Probability(LR stat) 1.55E-15 Obs with Dep=0 71 Total obs 85 Obs with DeP=1 14 根据输出结果可得到估计的Probit模型： (-2.05) (2.05) (-0.15) ＝0.8968 LR(2)＝68.21