r - plm回归中的错误

Question

同事们!我有面板数据:

    Company year       Beta     NI   Sales  Export Hedge      FL     QR     AT Foreign
1       1 2010 -2.2052800 293000 1881000 78.6816     0 23.5158  1.289 0.6554    3000
2       1 2011 -2.2536069 316000 2647000 81.4885     0 21.7945 1.1787 0.8282   22000
3       1 2012  0.3258693 363000 2987000 82.4908     0 24.5782 1.2428  0.813  -11000
4       1 2013  0.4006030 549000 4546000 79.4325     0 31.4168 0.6038 0.7905   71000
5       1 2014 -0.4508811 348000 5376000 79.2411     0 37.1451 0.6563  0.661  -64000
6       1 2015  0.1494696 355000 5038000 77.1735     0 33.3852 0.9798 0.5483   37000

但是当我尝试使用 plm 包进行回归时，R 显示了错误:

panel <- read.csv("Panel.csv",  header=T, sep=";")
p=plm(data=panel,Beta~NI, model="within",index=c("id","year"))


Error in pdim.default(index[[1]], index[[2]]) : 
  duplicate couples (id-time)
In addition: Warning messages:
1: In pdata.frame(data, index) :
  duplicate couples (id-time) in resulting pdata.frame
 to find out which, use e.g. table(index(your_pdataframe), useNA = "ifany")
2: In is.pbalanced.default(index[[1]], index[[2]]) :
  duplicate couples (id-time)

3: In is.pbalanced.default(index[[1]], index[[2]]) :
  duplicate couples (id-time)

我在网上搜索了这个错误，发现它与公司的id和年份有关。但我没有找到如何避免这个问题的方法。另外，当我执行 na.omit(panel) 时，R 不会显示错误，但保留 NA 数据和数据中的公司很重要。请告诉我如何解决这个问题。谢谢。

Answer 1

让我们考虑 plm 包中的 Produc 数据集。

data("Produc", package = "plm")
head(Produc)

    state year region     pcap     hwy   water    util       pc   gsp    emp unemp
1 ALABAMA 1970      6 15032.67 7325.80 1655.68 6051.20 35793.80 28418 1010.5   4.7
2 ALABAMA 1971      6 15501.94 7525.94 1721.02 6254.98 37299.91 29375 1021.9   5.2
3 ALABAMA 1972      6 15972.41 7765.42 1764.75 6442.23 38670.30 31303 1072.3   4.7
4 ALABAMA 1973      6 16406.26 7907.66 1742.41 6756.19 40084.01 33430 1135.5   3.9
5 ALABAMA 1974      6 16762.67 8025.52 1734.85 7002.29 42057.31 33749 1169.8   5.5
6 ALABAMA 1975      6 17316.26 8158.23 1752.27 7405.76 43971.71 33604 1155.4   7.7

在此数据集中，信息是在一段时间内(17 年)和相同样本单位(美国 48 个州)收集的。

table(Produc$state, Produc$year)
                 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
  ALABAMA           1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1
  ARIZONA           1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1
  ARKANSAS          1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1
  CALIFORNIA        1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1
  ...

plm 要求每个(州、年份)对都是唯一的。

any(table(Produc$state, Produc$year)!=1)
[1] FALSE

命令 plm 可以很好地处理此数据集:

plmFit1 <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
          data = Produc, index = c("state","year"))
summary(plmFit1)


Oneway (individual) effect Within Model
Call:
plm(formula = log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, 
    data = Produc, index = c("state", "year"))

Balanced Panel: n=48, T=17, N=816

Residuals :
    Min.  1st Qu.   Median  3rd Qu.     Max. 
-0.12000 -0.02370 -0.00204  0.01810  0.17500 

Coefficients :
             Estimate  Std. Error t-value  Pr(>|t|)    
log(pcap) -0.02614965  0.02900158 -0.9017    0.3675    
log(pc)    0.29200693  0.02511967 11.6246 < 2.2e-16 ***
log(emp)   0.76815947  0.03009174 25.5273 < 2.2e-16 ***
unemp     -0.00529774  0.00098873 -5.3582 1.114e-07 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Total Sum of Squares:    18.941
Residual Sum of Squares: 1.1112
R-Squared:      0.94134
Adj. R-Squared: 0.93742
F-statistic: 3064.81 on 4 and 764 DF, p-value: < 2.22e-16

现在我们复制其中一个(州、年份)对:

 Produc[2,2] <- 1970
 any(table(Produc$state, Produc$year)>1)
 [1] TRUE

和 plm 现在会生成与上面描述的相同的错误消息:

zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
      data = Produc, index = c("state","year"))

Error in pdim.default(index[[1]], index[[2]]) : 
  duplicate couples (id-time)
Inoltre: Warning messages:
1: In pdata.frame(data, index) :
  duplicate couples (id-time) in resulting pdata.frame
 to find out which, use e.g. table(index(your_pdataframe), useNA = "ifany")
2: In is.pbalanced.default(index[[1]], index[[2]]) :
  duplicate couples (id-time)

3: In is.pbalanced.default(index[[1]], index[[2]]) :
  duplicate couples (id-time)

希望这可以帮助你。