Question

我正在从Stata迁移到R（plm package）以进行面板模型计量经济学。在Stata中，随机效应等面板模型通常会报告内部，中间和整体R平方。

I have found在plm随机效应模型中报告的R平方对应于R平方内。那么，是否有任何方法可以使用R中的plm package获得整体和R平方之间的平方？

参见R和Stata的相同例子：

library(plm)
library(foreign) # read Stata files
download.file('http://fmwww.bc.edu/ec-p/data/wooldridge/wagepan.dta','wagepan.dta',mode="wb")
wagepan <- read.dta('wagepan.dta')

# Random effects
plm.re <- plm(lwage ~ educ + black + hisp + exper + expersq + married + union + d81 + d82 + d83 + d84 + d85 + d86 + d87,
              data=wagepan,
              model='random',
              index=c('nr','year'))
summary(plm.re)

在Stata：

use http://fmwww.bc.edu/ec-p/data/wooldridge/wagepan.dta
xtset nr year
xtreg lwage educ  black  hisp  exper  expersq  married  union  d81  d82  d83  d84  d85  d86  d87, re

R中报告的R平方（0.18062），至少在这种情况下，类似于Stata报道的R-sq Within（0.1799）。有没有什么方法可以获得R-sq在（0.1860）和Stata报告的总体（0.1830）之间？

Answer 1

this website有完整的代码来重现Wooldridge 2013 p中的例14.4。 494-5与R平方。报告所有型号，

# install.packages(c("wooldridge"), dependencies = TRUE) 
# devtools::install_github("JustinMShea/wooldridge")
library(wooldridge) 
data(wagepan)

# install.packages(c("plm", "stargazer","lmtest"), dependencies = TRUE)
library(plm); library(lmtest); library(stargazer)

model <- as.formula("lwage ~ educ + black + hisp + exper+I(exper^2)+married + union+yr")
reg.ols <- plm(model, data = wagepan.p, model="pooling")

reg.re <- plm(lwage ~ educ + black + hisp + exper +
              I(exper^2) + married + union + yr, data = wagepan.p, model="random") 

reg.fe <- plm(lwage ~ I(exper^2) + married+union+yr, data=wagepan.p, model="within")

# Pretty table of selected results (not reporting year dummies)
stargazer(reg.ols,reg.re,reg.fe, type="text",
     column.labels=c("OLS","RE","FE"),
     keep.stat=c("n","rsq"),
     keep=c("ed","bl","hi","exp","mar","un"))

输出，

#> ==========================================
#>                   Dependent variable:     
#>              -----------------------------
#>                          lwage            
#>                 OLS       RE        FE    
#>                 (1)       (2)       (3)   
#> ------------------------------------------
#> educ         0.091***  0.092***           
#>               (0.005)   (0.011)           
#>                                           
#> black        -0.139*** -0.139***          
#>               (0.024)   (0.048)           
#>                                           
#> hisp           0.016     0.022            
#>               (0.021)   (0.043)           
#>                                           
#> exper        0.067***  0.106***           
#>               (0.014)   (0.015)           
#>                                           
#> I(exper2)    -0.002*** -0.005*** -0.005***
#>               (0.001)   (0.001)   (0.001) 
#>                                           
#> married      0.108***  0.064***   0.047** 
#>               (0.016)   (0.017)   (0.018) 
#>                                           
#> union        0.182***  0.106***  0.080*** 
#>               (0.017)   (0.018)   (0.019) 
#>                                           
#> ------------------------------------------
#> Observations   4,360     4,360     4,360  
#> R2             0.189     0.181     0.181  
#> ==========================================
#> Note:          *p<0.1; **p<0.05; ***p<0.01

计算R内的R平方，在R之间或之间

1 个答案: