我正在看呢,哪位高手指点一二,听说bootstrap能修正估计的偏差,下面是我估计的结果,用的是最简单的命令
(running xtreg on estimation sample)
Bootstrap replications (50)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5
.................................................. 50
Fixed-effects (within) regression Number of obs = 232
Group variable (i): n Number of groups = 29
R-sq: within = 0.1165 Obs per group: min = 8
between = 0.0087 avg = 8.0
overall = 0.0070 max = 8
Wald chi2(8) = 21.60
corr(u_i, Xb) = -0.5687 Prob > chi2 = 0.0057
------------------------------------------------------------------------------
| Bootstrap
y1 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x11 | .0299174 .037529 0.80 0.425 -.0436382 .103473
x2 | -.001709 .0035098 -0.49 0.626 -.008588 .00517
x3 | -.1030626 .0728897 -1.41 0.157 -.2459237 .0397985
x5 | .0120006 .0037163 3.23 0.001 .0047168 .0192845
x6 | -.0006948 .0007497 -0.93 0.354 -.0021642 .0007745
x7 | -.0002269 .0002382 -0.95 0.341 -.0006938 .0002399
x9 | -.0040276 .0019661 -2.05 0.041 -.0078812 -.0001741
x10 | -.0019916 .0009764 -2.04 0.041 -.0039054 -.0000779
_cons | -.039287 .0561457 -0.70 0.484 -.1493306 .0707566
-------------+----------------------------------------------------------------
sigma_u | .02322199
sigma_e | .0228256
rho | .50860756 (fraction of variance due to u_i)
------------------------------------------------------------------------------
而采用的面版数据固定效应模型中的估计结果是
Fixed-effects (within) regression Number of obs = 232
Group variable (i): n Number of groups = 29
R-sq: within = 0.1165 Obs per group: min = 8
between = 0.0087 avg = 8.0
overall = 0.0070 max = 8
F(8,195) = 3.22
corr(u_i, Xb) = -0.5687 Prob > F = 0.0019
------------------------------------------------------------------------------
y1 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x11 | .0299174 .0294872 1.01 0.312 -.0282374 .0880722
x2 | -.001709 .0023167 -0.74 0.462 -.006278 .00286
x3 | -.1030626 .0593385 -1.74 0.084 -.2200903 .0139651
x5 | .0120006 .0032738 3.67 0.000 .005544 .0184572
x6 | -.0006948 .000594 -1.17 0.244 -.0018663 .0004767
x7 | -.0002269 .0002763 -0.82 0.412 -.0007718 .0003179
x9 | -.0040276 .0015183 -2.65 0.009 -.0070221 -.0010331
x10 | -.0019916 .0009712 -2.05 0.042 -.0039071 -.0000762
_cons | -.039287 .0534978 -0.73 0.464 -.1447955 .0662215
-------------+----------------------------------------------------------------
sigma_u | .02322199
sigma_e | .0228256
rho | .50860756 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(28, 195) = 3.48 Prob > F = 0.0000
1。上面两个结果的系数估计值是一样的,只是标准误差不同,这是什么意思呢?是不是表明没必要用Bootstrap方法啊?
2.如果增加选择项,应该怎么增加呢?bca、mse
3.“exp_list”什么意思?如何运用?
请高手指点一下