用plm模型进行F检验

Question

我想对一个plm模型进行f测试，并测试

model <- plm(y ~ a + b)

如果

# a = b

和

# a = 0 and b = 0

我试过这样的linearHypothesis

linearHypothesis(ur.model, c("a", "b")) to test for a = 0 and b = 0

但是得到了错误

Error in constants(lhs, cnames_symb) : 
  The hypothesis "sgp1" is not well formed: contains bad coefficient/variable names.
Calls: linearHypothesis ... makeHypothesis -> rbind -> Recall -> makeHypothesis -> constants
In addition: Warning message:
In constants(lhs, cnames_symb) : NAs introduced by coercion
Execution halted

我上面的例子使用了一些代码，如果问题很容易的话会稍微简化一些。如果问题出在细节中，这里是实际的代码。

model3 <- formula(balance.agr ~ sgp1 + sgp2 + cp + eu + election + gdpchange.imf + ue.ameco)
ur.model<-plm(model3, data=panel.l.fullsample, index=c("country","year"), model="within", effect="twoways")
linearHypothesis(ur.model, c("sgp1", "sgp2"), vcov.=vcovHC(plmmodel1, method="arellano", type = "HC1", clustering="group"))

Answer 1

我不能用一个内置的数据集重现你的错误，即使在相当多的摆弄之后也是如此。

这对你有效吗？

require(plm)
require(car)
data(Grunfeld)
form <- formula(inv ~ value + capital)
re <- plm(form, data = Grunfeld, model = "within", effect = "twoways")
linearHypothesis(re, c("value", "capital"), 
                 vcov. = vcovHC(re, method="arellano", type = "HC1"))

还要注意，您所显示的更复杂的代码中似乎有一个错误。您在object ur.model上使用linearHypothesis()，但在object plmmodel1上调用vcovHC()。不确定这是否是问题所在，但请检查一下，以防万一。

有没有可能提供数据？最后，编辑您的问题以包含来自sessionInfo()的输出。我的是(来自一个相当繁忙的R实例)：

> sessionInfo()
R version 2.11.1 Patched (2010-08-25 r52803)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_GB.utf8       LC_NUMERIC=C             
 [3] LC_TIME=en_GB.utf8        LC_COLLATE=en_GB.utf8    
 [5] LC_MONETARY=C             LC_MESSAGES=en_GB.utf8   
 [7] LC_PAPER=en_GB.utf8       LC_NAME=C                
 [9] LC_ADDRESS=C              LC_TELEPHONE=C           
[11] LC_MEASUREMENT=en_GB.utf8 LC_IDENTIFICATION=C      

attached base packages:
[1] splines   grid      stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] car_2.0-2        nnet_7.3-1       plm_1.2-6        Formula_1.0-0   
 [5] kinship_1.1.0-23 lattice_0.19-11  nlme_3.1-96      survival_2.35-8 
 [9] mgcv_1.6-2       chron_2.3-37     MASS_7.3-7       vegan_1.17-4    
[13] lmtest_0.9-27    sandwich_2.2-6   zoo_1.6-4        moments_0.11    
[17] ggplot2_0.8.8    proto_0.3-8      reshape_0.8.3    plyr_1.2.1      

loaded via a namespace (and not attached):
[1] Matrix_0.999375-44 tools_2.11.1

Answer 2

会不会是因为你在“混合”模型？你有一个方差规范，它是这样开始的：

, ...vcov.=vcovHC(plmmodel1, 

..。然而，您正在使用ur.model。