Iteration 0: log likelihood = -222.98673 | ||||||
Iteration 1: log likelihood = -212.20882 | ||||||
Iteration 2: log likelihood = -211.99688 | ||||||
Iteration 3: log likelihood = -211.99621 | ||||||
Iteration 4: log likelihood = -211.99621 | ||||||
Probit regression | Number of obs | = | 658 | |||
LR chi2(9) | = | 21.98 | ||||
Prob > chi2 | = | 0.0089 | ||||
Log likelihood = -211.99621 | Pseudo R2 | = | 0.0493 | |||
Coef. | Std. Err. | z | P>|z| | [96% Conf. | Interval] | |
corruptions .0096498 | 0.0096498 | 0.0050124 | 1.93 | 0.054 | -0.0001745 | 0.019474 |
tech .1215263 | 0.1215263 | 0.2734328 | 0.44 | 0.657 | -0.4143922 | 0.6574447 |
vc .3047315 | 0.3047315 | 0.1733195 | 1.76 | 0.079 | -0.0349685 | 0.6444315 |
wealth -2.05e-10 | -2.05E-10 | 1.46E-10 | -1.4 | 0.16 | -4.90E-11 | 8.10E-11 |
lnsales -.0380477 | -0.0380477 | 0.0395428 | -0.96 | 0.336 | -0.1155503 | 0.0394548 |
bkvlps -.0326366 | -0.0326366 | 0.0155686 | -2.1 | 0.036 | -0.0631507 | -0.0021227 |
industry dummy | ||||||
Manufacturing, Energy, and Ut.. | 0.2344603 | 0.2939736 | 0.8 | 0.425 | -0.3417175 | 0.8106381 |
Business Equipment, Telephone.. | -0.1042878 | 0.371006 | -0.28 | 0.779 | -0.8314463 | 0.6228707 |
Healthcare, Medical Equipment.. | -0.6229488 | 0.3229318 | -1.93 | 0.054 | -1.255884 | 0.0099858 |
Other -- Mines, Constr, BldMt.. | 0.0851314 | 0.2623148 | 0.32 | 0.746 | -0.4289963 | 0.599259 |
_cons | -1.157827 | 0.3509818 | -3.3 | 0.001 | -1.845739 | -0.4699148 |
LR chi2(9),Prob>chi2,Pseudo R2,分别指什么意思?单从这个回归结果中看,能看出我这个模型设定的有误么?回归结果能用么?
非常感谢,请大家帮我看看~我还需要做什么检验?