为什么运行“demoLMsarsem_panel.m”时,会有下列这么多的结果?是不是因为设定模型的不同啊?那么,在用于选择空间滞后模型、空间误差模型时,LMsar、LMerr到底应该选择哪组数据?请解释原因,多谢。我是个外行,请高手指点,不胜感激。
Ordinary Least-squares Estimates
Dependent Variable = logcit
R-squared = 0.3861
Rbar-squared = 0.3794
sigma^2 = 0.0320
Durbin-Watson = 1.8047
Nobs, Nvars = 276, 4
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Variable Coefficient t-statistic t-probability
intercept 1.605485 5.435955 0.000000
logp -1.041989 -8.610354 0.000000
logpn 0.146363 1.176771 0.240316
logy 0.703143 10.651591 0.000000
loglikols =
85.5537
LM test no spatial lag, probability = 2.8677, 0.090
robust LM test no spatial lag, probability = 1.5139, 0.219
LM test no spatial error, probability = 6.3199, 0.012
robust LM test no spatial error, probability = 4.9661, 0.026
Ordinary Least-squares Estimates
Dependent Variable = logcit
R-squared = 0.4634
Rbar-squared = 0.4595
sigma^2 = 0.0015
Durbin-Watson = 1.8004
Nobs, Nvars = 276, 3
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Variable Coefficient t-statistic t-probability
logp -0.597372 -12.071931 0.000000
logpn 0.162570 2.598087 0.009883
logy 0.335686 9.102462 0.000000
FE_rsqr2 =
0.9716
loglikfe =
509.8241
LM test no spatial lag, probability = 12.7208, 0.000
robust LM test no spatial lag, probability = 4.7332, 0.030
LM test no spatial error, probability = 23.6084, 0.000
robust LM test no spatial error, probability = 15.6207, 0.000
Ordinary Least-squares Estimates
Dependent Variable = logcit
R-squared = 0.4272
Rbar-squared = 0.4230
sigma^2 = 0.0013
Durbin-Watson = 2.0461
Nobs, Nvars = 276, 3
***************************************************************
Variable Coefficient t-statistic t-probability
logp -0.648719 -13.267854 0.000000
logpn 0.067473 1.072247 0.284556
logy 0.317823 4.891167 0.000002
LM test no spatial lag, probability = 0.9402, 0.332
robust LM test no spatial lag, probability = 3.8306, 0.050
LM test no spatial error, probability = 4.0933, 0.043
robust LM test no spatial error, probability = 6.9837,