自动计算plm的稳健标准错误?

时间:2020-05-21 13:33:54

标签: regression panel plm standard-error robust

今天,我使用N >> T(N = 5970和T = 10)的不平衡面板数据在plm中运行了固定效果模型。不幸的是,数据来自不允许我共享的数据库。但是,我的方程式如下: pl <- plm(LS~FIAS+EXPT+EMPL+AV+TURN+FIPL+EBIT+FIEX, index=c("IDNR", "CLOSDATE_year"), effect = "twoways", model="within", data=data) LS是微观水平上的工资份额。该模型可以平滑运行并打印我的结果。我在另一篇论文中读到,由于数据的结构,我必须通过用Driscoll-Kraay健壮的标准误差代替它们来调整标准误差。据我所理解, coeftest(pl, vocov.=vcovSCC) 应该可以。结果完全相同。所以我的问题是:我执行的校正是否错误或plm是否会自动进行调整?

附录:

> summary(pl)
Twoways effects Within Model

Call:
plm(formula = LS ~ FIAS + EXPT + EMPL + AV + TURN + FIPL + EBIT + 
    FIEX, data = data, effect = "twoways", model = "within", 
    index = c("IDNR", "CLOSDATE_year"))

Unbalanced Panel: n = 2718, T = 1-10, N = 12942

Residuals:
      Min.    1st Qu.     Median    3rd Qu.       Max. 
-1.1183188 -0.0191726 -0.0003545  0.0160751  0.5363292 

Coefficients:
        Estimate  Std. Error  t-value  Pr(>|t|)    
FIAS -4.8960e-02  1.0766e-02  -4.5475 5.490e-06 ***
EXPT -1.4202e-02  2.6751e-03  -5.3093 1.124e-07 ***
EMPL  5.3522e+03  3.0152e+02  17.7510 < 2.2e-16 ***
AV   -2.6384e-01  1.0277e-02 -25.6739 < 2.2e-16 ***
TURN  5.9762e-02  2.8426e-03  21.0235 < 2.2e-16 ***
FIPL -6.6372e-01  5.0019e-02 -13.2692 < 2.2e-16 ***
EBIT -8.5062e-01  1.2782e-02 -66.5489 < 2.2e-16 ***
FIEX -6.8813e-01  8.4500e-02  -8.1436 4.285e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Total Sum of Squares:    81.846
Residual Sum of Squares: 41.643
R-Squared:      0.4912
Adj. R-Squared: 0.35479
F-statistic: 1231.5 on 8 and 10205 DF, p-value: < 2.22e-16

> coeftest(pl, vocov.=vcovSCC)
t test of coefficients:

        Estimate  Std. Error  t value  Pr(>|t|)    
FIAS -4.8960e-02  1.0766e-02  -4.5475 5.490e-06 ***
EXPT -1.4202e-02  2.6751e-03  -5.3093 1.124e-07 ***
EMPL  5.3522e+03  3.0152e+02  17.7510 < 2.2e-16 ***
AV   -2.6384e-01  1.0277e-02 -25.6739 < 2.2e-16 ***
TURN  5.9762e-02  2.8426e-03  21.0235 < 2.2e-16 ***
FIPL -6.6372e-01  5.0019e-02 -13.2692 < 2.2e-16 ***
EBIT -8.5062e-01  1.2782e-02 -66.5489 < 2.2e-16 ***
FIEX -6.8813e-01  8.4500e-02  -8.1436 4.285e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

更新: 我使用lm()运行了相同的模型,并收到以下输出:

> l <- lm(LS~FIAS+EXPT+EMPL+AV+TURN+FIPL+EBIT+FIEX+factor(CLOSDATE_year)+factor(IDNR), data)
> summary(l)

Call:
lm(formula = LS ~ FIAS + EXPT + EMPL + AV + TURN + FIPL + EBIT + 
    FIEX + factor(CLOSDATE_year) + factor(IDNR), data = data)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.11832 -0.01917 -0.00035  0.01608  0.53633 

Coefficients:
                            Estimate Std. Error t value Pr(>|t|)    
(Intercept)                1.011e+00  3.316e-02  30.493  < 2e-16 ***
FIAS                      -4.896e-02  1.077e-02  -4.548 5.49e-06 ***
EXPT                      -1.420e-02  2.675e-03  -5.309 1.12e-07 ***
EMPL                       5.352e+03  3.015e+02  17.751  < 2e-16 ***
AV                        -2.638e-01  1.028e-02 -25.674  < 2e-16 ***
TURN                       5.976e-02  2.843e-03  21.023  < 2e-16 ***
FIPL                      -6.637e-01  5.002e-02 -13.269  < 2e-16 ***
EBIT                      -8.506e-01  1.278e-02 -66.549  < 2e-16 ***
FIEX                      -6.881e-01  8.450e-02  -8.144 4.29e-16 ***
factor(CLOSDATE_year)2009  6.487e-04  1.573e-02   0.041 0.967102    

> coeftest(l, vocov.=vcovSCC)

t test of coefficients:

                             Estimate  Std. Error  t value  Pr(>|t|)    
(Intercept)                1.0112e+00  3.3160e-02  30.4930 < 2.2e-16 ***
FIAS                      -4.8960e-02  1.0766e-02  -4.5475 5.490e-06 ***
EXPT                      -1.4203e-02  2.6750e-03  -5.3093 1.124e-07 ***
EMPL                       5.3522e+03  3.0152e+02  17.7510 < 2.2e-16 ***
AV                        -2.6384e-01  1.0277e-02 -25.6739 < 2.2e-16 ***
TURN                       5.9762e-02  2.8426e-03  21.0235 < 2.2e-16 ***
FIPL                      -6.6372e-01  5.0019e-02 -13.2692 < 2.2e-16 ***
EBIT                      -8.5062e-01  1.2782e-02 -66.5489 < 2.2e-16 ***
FIEX                      -6.8813e-01  8.4500e-02  -8.1436 4.285e-16 ***
factor(CLOSDATE_year)2009  6.4867e-04  1.5728e-02   0.0412 0.9671020

由于系数相同,但是SE已更新,这表明plm确实在直接估算可靠的标准误差,对吧?

0 个答案:

没有答案