我的平衡面板数据显示为不平衡面板数据。我不能使用无效的 "make.pbalanced()" 和 "is.pbalanced()"
My balanced panel data shows as unbalanced panel data. I cannot use "make.pbalanced()" and "is.pbalanced()" which have no effect
我有一个没有缺失值的面板数据集，除了日期是“month/day/year”格式但按季度频率外，所有都是数值。
完全没有缺失值。但是，我仍然不明白为什么当我运行“is.pbalanced()”代码命令时我的数据显示为不平衡。
我也无法通过运行宁“make.pbalanced()”代码显示我不明白的错误来平衡它。
即使我 运行 "table(DATA$Firm, DATA$Date)"（下面附有截图），table 输出也只显示 1 和 0。因此， id-time 匹配似乎没有重复这些。
DATA也是我在底部使用的数据文件（下面附上截图）。数据和输出太大，无法在此处附上完整文件（仅快照除外），请理解。
如果我能知道如何使这个面板数据可用，尽管它具有明显的平衡特性，我将不胜感激。谢谢。
> DATA=pdata.frame(data,index=c("Firm","Date"))
> DATA<-make.pbalanced(DATA)
Error in seq.default(from = min_value, to = max_value, by = 1) :
'from' must be a finite number
In addition: Warning messages:
1: In make.pconsecutive.indexes(x, balanced = balanced, ...) :
NAs introduced by coercion
2: In min(df_index[, "times"]) :
no non-missing arguments to min; returning Inf
3: In max(df_index[, "times"]) :
no non-missing arguments to max; returning -Inf
> is.pbalanced(DATA)
[1] FALSE
如果我为DATA中的前20行提供dput(DATA)，输出如下：
> dput(DATA)
structure(list(Date = structure(c(3L, 18L, 35L, 52L, 54L, 27L,
28L, 44L, 45L, 60L, 61L, 10L, 11L, 12L, 13L, 28L, 30L, 45L, 47L,
63L), .Label = c("12/31/1998", "12/31/1999", "12/31/2000", "12/31/2002",
"12/31/2003", "12/31/2004", "12/31/2005", "12/31/2008", "12/31/2009",
"12/31/2010", "12/31/2011", "12/31/2013", "12/31/2014", "12/31/2015",
"12/31/2016", "12/31/2019", "12/31/2020", "3/31/1998", "3/31/1999",
"3/31/2000", "3/31/2001", "3/31/2004", "3/31/2005", "3/31/2006",
"3/31/2007", "3/31/2009", "3/31/2010", "3/31/2011", "3/31/2012",
"3/31/2015", "3/31/2016", "3/31/2017", "3/31/2018", "3/31/2021",
"6/30/1998", "6/30/1999", "6/30/2000", "6/30/2001", "6/30/2004",
"6/30/2005", "6/30/2006", "6/30/2007", "6/30/2009", "6/30/2010",
"6/30/2011", "6/30/2012", "6/30/2015", "6/30/2016", "6/30/2017",
"6/30/2018", "6/30/2021", "9/30/1998", "9/30/1999", "9/30/2000",
"9/30/2003", "9/30/2004", "9/30/2005", "9/30/2006", "9/30/2009",
"9/30/2010", "9/30/2011", "9/30/2012", "9/30/2014", "9/30/2015",
"9/30/2016", "9/30/2017", "9/30/2020"), class = "factor"), Firm = structure(c(1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L), .Label = c("296", "10718", "52239", "100263", "100432",
"101273", "102798", "102931", "103660", "105309", "105334", "106599",
"106801", "107495", "107501", "107559", "107574", "107737", "107755",
"107766", "107791", "108048", "108297", "108299", "108679", "108729",
"108731", "110803", "111464", "111469", "111483", "111484", "111487",
"111489", "111492", "111493", "111503", "111506", "111509", "111514",
"111522", "111536", "111555", "111589", "111590", "111600", "111695",
"111703", "111716", "111727", "111750", "111751", "111752", "111775",
"111796", "111808", "111938", "111940", "111941", "111942", "111955",
"111956", "112001", "112028", "112066", "112137", "112153", "112347",
"112367", "112371", "112427", "112472", "112666", "112738", "112852",
"113501", "113582", "113848", "113959", "114957", "114958", "116126",
"116324", "117005", "135894", "135939", "146262", "154189", "1000001",
"1000132", "1000181", "1000198", "1000234", "1000242", "1000517",
"1000757", "1000858", "1000881", "1000897", "1001061", "1001172",
"1001283", "1001526", "1001577", "1001616", "1001915", "1002018",
"1002061", "1002312", "1002320", "1002374", "1002376", "1002587",
"1002650", "1002815", "1002827", "1002835", "1002839", "1002923",
"1003021", "1003053", "1003057", "1003059", "1003229", "1003260",
"1003405", "1003495", "1003683", "1003698", "1003943", "1004349",
"1004369", "1004594", "1004595", "1004628", "1004823", "1005002",
"1005330", "1005419", "1005420", "1005519", "1005570", "1005575",
"1005625", "1005629", "1006105", "1006110", "1006155", "1006217",
"1006232", "1006379", "1006460", "1006474", "1006511", "1006676",
"1006720", "1006781", "1006799", "1007050", "1007451", "1007518",
"1007544", "1007561", "1007564", "1007606", "1007631", "1007708",
"1007780", "1007831", "1007879", "1007890", "1007923", "1008222",
"1008290", "1008336", "1008494", "1008501", "1008521", "1008541",
"1008974", "1009297", "1009608", "1009702", "1009707", "1010040",
"1010079", "1010118", "1010171", "1010179", "1010218", "1010383",
"1010384", "1010456", "1010469", "1010513", "1010515", "1010523",
"1010559", "1010680", "1010697", "1010871", "1010884", "1010892",
"1011249", "1011315", "1011369", "1011532", "1011549", "1011550",
"1011601", "1011608", "1011628", "1011633", "1011636", "1011666",
"1011793", "1011813", "1011965", "1012183", "1012304", "1012356",
"1012472", "1012850", "1012854", "1021617", "1024280", "1028649",
"1032627", "1032628", "1037429", "1047191", "1078689", "1079592",
"1085370", "1094670", "1095030", "1095890", "1098870", "1103990",
"1116650", "1130830", "1136430", "1150911", "1164070", "1165550",
"1167911", "1169072", "1169451", "1169570", "1169574", "1177670",
"1199506", "1200034", "1200141", "1200336", "1201617", "1203212",
"1203998", "1204112", "1204249", "1205697", "1205991", "1206695",
"1209238", "1209508", "1231250", "1236950", "1239130", "1254611",
"1261831", "1278491", "1299590", "1308650", "1349851", "1364272",
"1371810", "1373451", "1415470", "1461924", "1462905", "1468726",
"1470067", "1471922", "1475575", "1492469", "1493548", "1494156",
"1497186", "1502005", "1503676", "1510039"), class = "factor"),
Country = c(30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L), X1 = c(3.28071e+11,
2.47603e+11, 2.68036e+11, 2.8843e+11, 3.12936e+11, 1.63006e+11,
1.62064e+11, 1.62003e+11, 1.75994e+11, 1.66539e+11, 1.90875e+11,
8.48942e+11, 9.11332e+11, 9.38555e+11, 9.11507e+11, 8.80528e+11,
9.15665e+11, 8.83188e+11, 8.59914e+11, 9.23223e+11), X2 = c(420.9,
109.62, 115.46, 170.57, 256.84, 245.79, 28.1, 320.61, 37.39,
51.84, 24.73, 28.56, 149.12, 176.7, 204.86, 241.27, 245.69,
328.73, 270.17, 225.57), X3 = c(1.397e+09, 6.826e+09, 8.407e+09,
6.218e+09, 1.96e+09, 4.39e+08, 3.011e+09, 4.27e+08, 2.918e+09,
1.738e+09, 3.219e+09, 2e+05, 2e+05, 2e+05, 2e+05, 1.7844e+10,
2e+05, 1.7161e+10, 2e+05, 2e+05), X4 = c(41.6563, 21.4688,
29.8125, 37.0938, 33.6875, 28.25, 30.88, 29.31, 24.69, 28.99,
26.13, 168.84, 168.16, 127.56, 177.26, 170.63, 163.85, 131.27,
167.44, 158.21), X5 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), X6 = c(0.931431568,
0.931431568, 0.931431568, 0.931431568, 0.931431568, 0.931431568,
0.931431568, 0.931431568, 0.931431568, 0.931431568, 0.931431568,
0.931431568, 0.931431568, 0.931431568, 0.931431568, 0.931431568,
0.931431568, 0.931431568, 0.931431568, 0.931431568), X7 = c(0.270710059,
0.277063061, 0.291823581, 0.431113358, 0.165191665, 0.031089322,
0.00946807, 0.040553104, 0.012598261, 0.006557103, 0.008332575,
0.003612478, 0.050244788, 0.387559494, 0.250535044, 0.081293992,
0.179216725, 0.110762938, 0.197073477, 0.275862491), X8 = c(0.000327816,
0.002603413, 0.002742109, 0.004050941, 0.000200038, 0.000115447,
1.27133e-05, 0.000150589, 1.69164e-05, 2.43491e-05, 1.11887e-05,
1.34145e-05, 6.74667e-05, 0.00044596, 0.000278949, 0.000109158,
0.000133225, 0.000148728, 0.0001465, 0.000307149), X9 = c(0.270893931,
0.318213603, 0.391916461, 0.289869936, 0.38006593, 0.011946002,
0.04790828, 0.01161946, 0.046428549, 0.047294196, 0.051217786,
4.59817e-07, 4.59817e-07, 4.59817e-07, 4.59817e-07, 0.283917419,
4.59817e-07, 0.273050148, 4.59817e-07, 4.59817e-07), X10 = c(0.0002414,
0.003316004, 0.004084039, 0.003020644, 0.000338686, 8.42066e-06,
5.44127e-05, 8.19048e-06, 5.27321e-05, 3.33374e-05, 5.81716e-05,
4.80818e-09, 4.80818e-09, 4.80818e-09, 4.80818e-09, 0.000322465,
4.80818e-09, 0.000310122, 4.80818e-09, 4.80818e-09), X11 = c(0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L), X12 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), X13 = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L), X14 = c(0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 0L), X15 = c(7L,
4L, 2L, 2L, 3L, 25L, 12L, 24L, 15L, 22L, 10L, 18L, 10L, 9L,
9L, 12L, 15L, 15L, 20L, 8L), X16 = c(0.579324474, 0.67828913,
0.797352123, 0.65619424, 0.643443626, 1.362389303, 1.076926757,
1.158663556, 1.326649492, 1.070007097, 1.263384865, 0.976581992,
1.299930534, 1.665132357, 1.202016572, 1.076926757, 1.111254141,
1.326649492, 0.885775977, 1.319718044), X17 = c(13.07130455,
8.316492188, 8.766790769, 9.539716667, 12.43554545, 8.205709375,
11.61956875, 9.233861538, 11.37893538, 10.52281061, 11.20804697,
11.50165758, 12.36111364, 13.1170197, 16.01679545, 11.61956875,
16.46697656, 11.37893538, 16.98400462, 15.10651515)), row.names = c("296- 12/31/2000",
"296-3/31/1998", "296-6/30/1998", "296-9/30/1998", "296-9/30/2000",
"10718-3/31/2010", "10718-3/31/2011", "10718-6/30/2010", "10718-6/30/2011",
"10718-9/30/2010", "10718-9/30/2011", "52239-12/31/2010", "52239-12/31/2011",
52239-12/31/2013", "52239-12/31/2014", "52239-3/31/2011", "52239-3/31/2015",
"52239-6/30/2011", "52239-6/30/2015", "52239-9/30/2014"), class = c("pdata.frame",
"data.frame"), index = structure(list(Firm = structure(c(1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L), .Label = c("296", "10718", "52239"), class = "factor"),
Date = structure(c(1L, 6L, 10L, 14L, 15L, 7L, 8L, 11L, 12L,
16L, 17L, 2L, 3L, 4L, 5L, 8L, 9L, 12L, 13L, 18L), .Label = c("12/31/2000",
"12/31/2010", "12/31/2011", "12/31/2013", "12/31/2014", "3/31/1998",
"3/31/2010", "3/31/2011", "3/31/2015", "6/30/1998", "6/30/2010",
"6/30/2011", "6/30/2015", "9/30/1998", "9/30/2000", "9/30/2010",
"9/30/2011", "9/30/2014"), class = "factor")), row.names = c(220L,
7L, 11L, 13L, 196L, 1713L, 2161L, 1816L, 2274L, 1930L, 2379L,
2052L, 2504L, 2983L, 3278L, 2162L, 3413L, 2275L, 3554L, 3121L
), class = c("pindex", "data.frame")))
DATA的前20行（rows）如下。这是在我输入“pdata.frame”之后，因此第一列会相应地自动添加：
DATA=pdata.frame(data,index=c("Firm","Date"))
DATA[1:20,]
Date Firm Country X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17
296-12/31/2000 12/31/2000 296 30 3.28071e+11 420.90 1.3970e+09 41.6563 0 0.9314316 0.270710059 0.0003278160 2.708939e-01 2.414000e-04 0 0 0 0 7 0.5793245 13.071305
296-3/31/1998 3/31/1998 296 30 2.47603e+11 109.62 6.8260e+09 21.4688 0 0.9314316 0.277063061 0.0026034130 3.182136e-01 3.316004e-03 0 0 0 0 4 0.6782891 8.316492
296-6/30/1998 6/30/1998 296 30 2.68036e+11 115.46 8.4070e+09 29.8125 0 0.9314316 0.291823581 0.0027421090 3.919165e-01 4.084039e-03 0 0 0 0 2 0.7973521 8.766791
296-9/30/1998 9/30/1998 296 30 2.88430e+11 170.57 6.2180e+09 37.0938 0 0.9314316 0.431113358 0.0040509410 2.898699e-01 3.020644e-03 1 0 0 0 2 0.6561942 9.539717
296-9/30/2000 9/30/2000 296 30 3.12936e+11 256.84 1.9600e+09 33.6875 0 0.9314316 0.165191665 0.0002000380 3.800659e-01 3.386860e-04 0 0 0 0 3 0.6434436 12.435545
10718-3/31/2010 3/31/2010 10718 30 1.63006e+11 245.79 4.3900e+08 28.2500 0 0.9314316 0.031089322 0.0001154470 1.194600e-02 8.420660e-06 0 0 0 1 25 1.3623893 8.205709
10718-3/31/2011 3/31/2011 10718 30 1.62064e+11 28.10 3.0110e+09 30.8800 0 0.9314316 0.009468070 0.0000127133 4.790828e-02 5.441270e-05 0 0 0 1 12 1.0769268 11.619569
10718-6/30/2010 6/30/2010 10718 30 1.62003e+11 320.61 4.2700e+08 29.3100 0 0.9314316 0.040553104 0.0001505890 1.161946e-02 8.190480e-06 0 0 0 1 24 1.1586636 9.233862
10718-6/30/2011 6/30/2011 10718 30 1.75994e+11 37.39 2.9180e+09 24.6900 0 0.9314316 0.012598261 0.0000169164 4.642855e-02 5.273210e-05 0 0 0 1 15 1.3266495 11.378935
10718-9/30/2010 9/30/2010 10718 30 1.66539e+11 51.84 1.7380e+09 28.9900 0 0.9314316 0.006557103 0.0000243491 4.729420e-02 3.333740e-05 0 0 0 1 22 1.0700071 10.522811
10718-9/30/2011 9/30/2011 10718 30 1.90875e+11 24.73 3.2190e+09 26.1300 0 0.9314316 0.008332575 0.0000111887 5.121779e-02 5.817160e-05 0 0 0 1 10 1.2633849 11.208047
52239-12/31/2010 12/31/2010 52239 30 8.48942e+11 28.56 2.0000e+05 168.8400 0 0.9314316 0.003612478 0.0000134145 4.598170e-07 4.808180e-09 0 0 0 1 18 0.9765820 11.501658
52239-12/31/2011 12/31/2011 52239 30 9.11332e+11 149.12 2.0000e+05 168.1600 0 0.9314316 0.050244788 0.0000674667 4.598170e-07 4.808180e-09 0 0 0 1 10 1.2999305 12.361114
52239-12/31/2013 12/31/2013 52239 30 9.38555e+11 176.70 2.0000e+05 127.5600 0 0.9314316 0.387559494 0.0004459600 4.598170e-07 4.808180e-09 0 0 0 0 9 1.6651324 13.117020
52239-12/31/2014 12/31/2014 52239 30 9.11507e+11 204.86 2.0000e+05 177.2600 0 0.9314316 0.250535044 0.0002789490 4.598170e-07 4.808180e-09 0 0 0 0 9 1.2020166 16.016795
52239-3/31/2011 3/31/2011 52239 30 8.80528e+11 241.27 1.7844e+10 170.6300 0 0.9314316 0.081293992 0.0001091580 2.839174e-01 3.224650e-04 0 0 0 1 12 1.0769268 11.619569
52239-3/31/2015 3/31/2015 52239 30 9.15665e+11 245.69 2.0000e+05 163.8500 0 0.9314316 0.179216725 0.0001332250 4.598170e-07 4.808180e-09 0 0 0 0 15 1.1112541 16.466977
52239-6/30/2011 6/30/2011 52239 30 8.83188e+11 328.73 1.7161e+10 131.2700 0 0.9314316 0.110762938 0.0001487280 2.730501e-01 3.101220e-04 0 0 0 1 15 1.3266495 11.378935
52239-6/30/2015 6/30/2015 52239 30 8.59914e+11 270.17 2.0000e+05 167.4400 0 0.9314316 0.197073477 0.0001465000 4.598170e-07 4.808180e-09 0 0 0 0 20 0.8857760 16.984005
52239-9/30/2014 9/30/2014 52239 30 9.23223e+11 225.57 2.0000e+05 158.2100 0 0.9314316 0.275862491 0.0003071490 4.598170e-07 4.808180e-09 0 0 0 0 8 1.3197180 15.106515
>
根据is.pbalanced的定义：
Balanced data are data for which each individual has the same time periods
举个例子：
library(plm)
data("Grunfeld", package = "plm")
is.pbalanced(Grunfeld)
#> [1] TRUE
table(Grunfeld$firm,Grunfeld$year)
#>
#> 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 7 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 8 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 9 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 10 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
non.balanced <- Grunfeld[-sample(200,10),]
is.pbalanced(non.balanced)
#> [1] FALSE
table(non.balanced$firm,non.balanced$year)
#> 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 2 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1
#> 3 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1
#> 4 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1
#> 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 7 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 8 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1
#> 9 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1
#> 10 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1
如上所示，pbalanced 数据集的 table 没有零：每个公司的周期都相同。
您可以在 pbalanced source code:
中验证
is.pbalanced.default <- function(x, y, ...) {
if (length(x) != length(y)) stop("The length of the two vectors differs\n")
x <- x[drop = TRUE] # drop unused factor levels so that table
y <- y[drop = TRUE] # gives only needed combinations
z <- table(x, y)
if (any(v <- as.vector(z) == 0L)) {
balanced <- FALSE # Any zero means False
} else { balanced <- TRUE
您正在使用的数据集的 table 有很多零，这解释了为什么 is.pbalanced(DATA)==FALSE
提供 dput(data) 以找出 make.pbalanced 不起作用的原因会很有用。
我有一个没有缺失值的面板数据集，除了日期是“month/day/year”格式但按季度频率外，所有都是数值。
完全没有缺失值。但是，我仍然不明白为什么当我运行“is.pbalanced()”代码命令时我的数据显示为不平衡。
我也无法通过运行宁“make.pbalanced()”代码显示我不明白的错误来平衡它。
即使我 运行 "table(DATA$Firm, DATA$Date)"（下面附有截图），table 输出也只显示 1 和 0。因此， id-time 匹配似乎没有重复这些。
DATA也是我在底部使用的数据文件（下面附上截图）。数据和输出太大，无法在此处附上完整文件（仅快照除外），请理解。
如果我能知道如何使这个面板数据可用，尽管它具有明显的平衡特性，我将不胜感激。谢谢。
> DATA=pdata.frame(data,index=c("Firm","Date"))
> DATA<-make.pbalanced(DATA)
Error in seq.default(from = min_value, to = max_value, by = 1) :
'from' must be a finite number
In addition: Warning messages:
1: In make.pconsecutive.indexes(x, balanced = balanced, ...) :
NAs introduced by coercion
2: In min(df_index[, "times"]) :
no non-missing arguments to min; returning Inf
3: In max(df_index[, "times"]) :
no non-missing arguments to max; returning -Inf
> is.pbalanced(DATA)
[1] FALSE
如果我为DATA中的前20行提供dput(DATA)，输出如下：
> dput(DATA)
structure(list(Date = structure(c(3L, 18L, 35L, 52L, 54L, 27L,
28L, 44L, 45L, 60L, 61L, 10L, 11L, 12L, 13L, 28L, 30L, 45L, 47L,
63L), .Label = c("12/31/1998", "12/31/1999", "12/31/2000", "12/31/2002",
"12/31/2003", "12/31/2004", "12/31/2005", "12/31/2008", "12/31/2009",
"12/31/2010", "12/31/2011", "12/31/2013", "12/31/2014", "12/31/2015",
"12/31/2016", "12/31/2019", "12/31/2020", "3/31/1998", "3/31/1999",
"3/31/2000", "3/31/2001", "3/31/2004", "3/31/2005", "3/31/2006",
"3/31/2007", "3/31/2009", "3/31/2010", "3/31/2011", "3/31/2012",
"3/31/2015", "3/31/2016", "3/31/2017", "3/31/2018", "3/31/2021",
"6/30/1998", "6/30/1999", "6/30/2000", "6/30/2001", "6/30/2004",
"6/30/2005", "6/30/2006", "6/30/2007", "6/30/2009", "6/30/2010",
"6/30/2011", "6/30/2012", "6/30/2015", "6/30/2016", "6/30/2017",
"6/30/2018", "6/30/2021", "9/30/1998", "9/30/1999", "9/30/2000",
"9/30/2003", "9/30/2004", "9/30/2005", "9/30/2006", "9/30/2009",
"9/30/2010", "9/30/2011", "9/30/2012", "9/30/2014", "9/30/2015",
"9/30/2016", "9/30/2017", "9/30/2020"), class = "factor"), Firm = structure(c(1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L), .Label = c("296", "10718", "52239", "100263", "100432",
"101273", "102798", "102931", "103660", "105309", "105334", "106599",
"106801", "107495", "107501", "107559", "107574", "107737", "107755",
"107766", "107791", "108048", "108297", "108299", "108679", "108729",
"108731", "110803", "111464", "111469", "111483", "111484", "111487",
"111489", "111492", "111493", "111503", "111506", "111509", "111514",
"111522", "111536", "111555", "111589", "111590", "111600", "111695",
"111703", "111716", "111727", "111750", "111751", "111752", "111775",
"111796", "111808", "111938", "111940", "111941", "111942", "111955",
"111956", "112001", "112028", "112066", "112137", "112153", "112347",
"112367", "112371", "112427", "112472", "112666", "112738", "112852",
"113501", "113582", "113848", "113959", "114957", "114958", "116126",
"116324", "117005", "135894", "135939", "146262", "154189", "1000001",
"1000132", "1000181", "1000198", "1000234", "1000242", "1000517",
"1000757", "1000858", "1000881", "1000897", "1001061", "1001172",
"1001283", "1001526", "1001577", "1001616", "1001915", "1002018",
"1002061", "1002312", "1002320", "1002374", "1002376", "1002587",
"1002650", "1002815", "1002827", "1002835", "1002839", "1002923",
"1003021", "1003053", "1003057", "1003059", "1003229", "1003260",
"1003405", "1003495", "1003683", "1003698", "1003943", "1004349",
"1004369", "1004594", "1004595", "1004628", "1004823", "1005002",
"1005330", "1005419", "1005420", "1005519", "1005570", "1005575",
"1005625", "1005629", "1006105", "1006110", "1006155", "1006217",
"1006232", "1006379", "1006460", "1006474", "1006511", "1006676",
"1006720", "1006781", "1006799", "1007050", "1007451", "1007518",
"1007544", "1007561", "1007564", "1007606", "1007631", "1007708",
"1007780", "1007831", "1007879", "1007890", "1007923", "1008222",
"1008290", "1008336", "1008494", "1008501", "1008521", "1008541",
"1008974", "1009297", "1009608", "1009702", "1009707", "1010040",
"1010079", "1010118", "1010171", "1010179", "1010218", "1010383",
"1010384", "1010456", "1010469", "1010513", "1010515", "1010523",
"1010559", "1010680", "1010697", "1010871", "1010884", "1010892",
"1011249", "1011315", "1011369", "1011532", "1011549", "1011550",
"1011601", "1011608", "1011628", "1011633", "1011636", "1011666",
"1011793", "1011813", "1011965", "1012183", "1012304", "1012356",
"1012472", "1012850", "1012854", "1021617", "1024280", "1028649",
"1032627", "1032628", "1037429", "1047191", "1078689", "1079592",
"1085370", "1094670", "1095030", "1095890", "1098870", "1103990",
"1116650", "1130830", "1136430", "1150911", "1164070", "1165550",
"1167911", "1169072", "1169451", "1169570", "1169574", "1177670",
"1199506", "1200034", "1200141", "1200336", "1201617", "1203212",
"1203998", "1204112", "1204249", "1205697", "1205991", "1206695",
"1209238", "1209508", "1231250", "1236950", "1239130", "1254611",
"1261831", "1278491", "1299590", "1308650", "1349851", "1364272",
"1371810", "1373451", "1415470", "1461924", "1462905", "1468726",
"1470067", "1471922", "1475575", "1492469", "1493548", "1494156",
"1497186", "1502005", "1503676", "1510039"), class = "factor"),
Country = c(30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L), X1 = c(3.28071e+11,
2.47603e+11, 2.68036e+11, 2.8843e+11, 3.12936e+11, 1.63006e+11,
1.62064e+11, 1.62003e+11, 1.75994e+11, 1.66539e+11, 1.90875e+11,
8.48942e+11, 9.11332e+11, 9.38555e+11, 9.11507e+11, 8.80528e+11,
9.15665e+11, 8.83188e+11, 8.59914e+11, 9.23223e+11), X2 = c(420.9,
109.62, 115.46, 170.57, 256.84, 245.79, 28.1, 320.61, 37.39,
51.84, 24.73, 28.56, 149.12, 176.7, 204.86, 241.27, 245.69,
328.73, 270.17, 225.57), X3 = c(1.397e+09, 6.826e+09, 8.407e+09,
6.218e+09, 1.96e+09, 4.39e+08, 3.011e+09, 4.27e+08, 2.918e+09,
1.738e+09, 3.219e+09, 2e+05, 2e+05, 2e+05, 2e+05, 1.7844e+10,
2e+05, 1.7161e+10, 2e+05, 2e+05), X4 = c(41.6563, 21.4688,
29.8125, 37.0938, 33.6875, 28.25, 30.88, 29.31, 24.69, 28.99,
26.13, 168.84, 168.16, 127.56, 177.26, 170.63, 163.85, 131.27,
167.44, 158.21), X5 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), X6 = c(0.931431568,
0.931431568, 0.931431568, 0.931431568, 0.931431568, 0.931431568,
0.931431568, 0.931431568, 0.931431568, 0.931431568, 0.931431568,
0.931431568, 0.931431568, 0.931431568, 0.931431568, 0.931431568,
0.931431568, 0.931431568, 0.931431568, 0.931431568), X7 = c(0.270710059,
0.277063061, 0.291823581, 0.431113358, 0.165191665, 0.031089322,
0.00946807, 0.040553104, 0.012598261, 0.006557103, 0.008332575,
0.003612478, 0.050244788, 0.387559494, 0.250535044, 0.081293992,
0.179216725, 0.110762938, 0.197073477, 0.275862491), X8 = c(0.000327816,
0.002603413, 0.002742109, 0.004050941, 0.000200038, 0.000115447,
1.27133e-05, 0.000150589, 1.69164e-05, 2.43491e-05, 1.11887e-05,
1.34145e-05, 6.74667e-05, 0.00044596, 0.000278949, 0.000109158,
0.000133225, 0.000148728, 0.0001465, 0.000307149), X9 = c(0.270893931,
0.318213603, 0.391916461, 0.289869936, 0.38006593, 0.011946002,
0.04790828, 0.01161946, 0.046428549, 0.047294196, 0.051217786,
4.59817e-07, 4.59817e-07, 4.59817e-07, 4.59817e-07, 0.283917419,
4.59817e-07, 0.273050148, 4.59817e-07, 4.59817e-07), X10 = c(0.0002414,
0.003316004, 0.004084039, 0.003020644, 0.000338686, 8.42066e-06,
5.44127e-05, 8.19048e-06, 5.27321e-05, 3.33374e-05, 5.81716e-05,
4.80818e-09, 4.80818e-09, 4.80818e-09, 4.80818e-09, 0.000322465,
4.80818e-09, 0.000310122, 4.80818e-09, 4.80818e-09), X11 = c(0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L), X12 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), X13 = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L), X14 = c(0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 0L), X15 = c(7L,
4L, 2L, 2L, 3L, 25L, 12L, 24L, 15L, 22L, 10L, 18L, 10L, 9L,
9L, 12L, 15L, 15L, 20L, 8L), X16 = c(0.579324474, 0.67828913,
0.797352123, 0.65619424, 0.643443626, 1.362389303, 1.076926757,
1.158663556, 1.326649492, 1.070007097, 1.263384865, 0.976581992,
1.299930534, 1.665132357, 1.202016572, 1.076926757, 1.111254141,
1.326649492, 0.885775977, 1.319718044), X17 = c(13.07130455,
8.316492188, 8.766790769, 9.539716667, 12.43554545, 8.205709375,
11.61956875, 9.233861538, 11.37893538, 10.52281061, 11.20804697,
11.50165758, 12.36111364, 13.1170197, 16.01679545, 11.61956875,
16.46697656, 11.37893538, 16.98400462, 15.10651515)), row.names = c("296- 12/31/2000",
"296-3/31/1998", "296-6/30/1998", "296-9/30/1998", "296-9/30/2000",
"10718-3/31/2010", "10718-3/31/2011", "10718-6/30/2010", "10718-6/30/2011",
"10718-9/30/2010", "10718-9/30/2011", "52239-12/31/2010", "52239-12/31/2011",
52239-12/31/2013", "52239-12/31/2014", "52239-3/31/2011", "52239-3/31/2015",
"52239-6/30/2011", "52239-6/30/2015", "52239-9/30/2014"), class = c("pdata.frame",
"data.frame"), index = structure(list(Firm = structure(c(1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L), .Label = c("296", "10718", "52239"), class = "factor"),
Date = structure(c(1L, 6L, 10L, 14L, 15L, 7L, 8L, 11L, 12L,
16L, 17L, 2L, 3L, 4L, 5L, 8L, 9L, 12L, 13L, 18L), .Label = c("12/31/2000",
"12/31/2010", "12/31/2011", "12/31/2013", "12/31/2014", "3/31/1998",
"3/31/2010", "3/31/2011", "3/31/2015", "6/30/1998", "6/30/2010",
"6/30/2011", "6/30/2015", "9/30/1998", "9/30/2000", "9/30/2010",
"9/30/2011", "9/30/2014"), class = "factor")), row.names = c(220L,
7L, 11L, 13L, 196L, 1713L, 2161L, 1816L, 2274L, 1930L, 2379L,
2052L, 2504L, 2983L, 3278L, 2162L, 3413L, 2275L, 3554L, 3121L
), class = c("pindex", "data.frame")))
DATA的前20行（rows）如下。这是在我输入“pdata.frame”之后，因此第一列会相应地自动添加：
DATA=pdata.frame(data,index=c("Firm","Date"))
DATA[1:20,]
Date Firm Country X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17
296-12/31/2000 12/31/2000 296 30 3.28071e+11 420.90 1.3970e+09 41.6563 0 0.9314316 0.270710059 0.0003278160 2.708939e-01 2.414000e-04 0 0 0 0 7 0.5793245 13.071305
296-3/31/1998 3/31/1998 296 30 2.47603e+11 109.62 6.8260e+09 21.4688 0 0.9314316 0.277063061 0.0026034130 3.182136e-01 3.316004e-03 0 0 0 0 4 0.6782891 8.316492
296-6/30/1998 6/30/1998 296 30 2.68036e+11 115.46 8.4070e+09 29.8125 0 0.9314316 0.291823581 0.0027421090 3.919165e-01 4.084039e-03 0 0 0 0 2 0.7973521 8.766791
296-9/30/1998 9/30/1998 296 30 2.88430e+11 170.57 6.2180e+09 37.0938 0 0.9314316 0.431113358 0.0040509410 2.898699e-01 3.020644e-03 1 0 0 0 2 0.6561942 9.539717
296-9/30/2000 9/30/2000 296 30 3.12936e+11 256.84 1.9600e+09 33.6875 0 0.9314316 0.165191665 0.0002000380 3.800659e-01 3.386860e-04 0 0 0 0 3 0.6434436 12.435545
10718-3/31/2010 3/31/2010 10718 30 1.63006e+11 245.79 4.3900e+08 28.2500 0 0.9314316 0.031089322 0.0001154470 1.194600e-02 8.420660e-06 0 0 0 1 25 1.3623893 8.205709
10718-3/31/2011 3/31/2011 10718 30 1.62064e+11 28.10 3.0110e+09 30.8800 0 0.9314316 0.009468070 0.0000127133 4.790828e-02 5.441270e-05 0 0 0 1 12 1.0769268 11.619569
10718-6/30/2010 6/30/2010 10718 30 1.62003e+11 320.61 4.2700e+08 29.3100 0 0.9314316 0.040553104 0.0001505890 1.161946e-02 8.190480e-06 0 0 0 1 24 1.1586636 9.233862
10718-6/30/2011 6/30/2011 10718 30 1.75994e+11 37.39 2.9180e+09 24.6900 0 0.9314316 0.012598261 0.0000169164 4.642855e-02 5.273210e-05 0 0 0 1 15 1.3266495 11.378935
10718-9/30/2010 9/30/2010 10718 30 1.66539e+11 51.84 1.7380e+09 28.9900 0 0.9314316 0.006557103 0.0000243491 4.729420e-02 3.333740e-05 0 0 0 1 22 1.0700071 10.522811
10718-9/30/2011 9/30/2011 10718 30 1.90875e+11 24.73 3.2190e+09 26.1300 0 0.9314316 0.008332575 0.0000111887 5.121779e-02 5.817160e-05 0 0 0 1 10 1.2633849 11.208047
52239-12/31/2010 12/31/2010 52239 30 8.48942e+11 28.56 2.0000e+05 168.8400 0 0.9314316 0.003612478 0.0000134145 4.598170e-07 4.808180e-09 0 0 0 1 18 0.9765820 11.501658
52239-12/31/2011 12/31/2011 52239 30 9.11332e+11 149.12 2.0000e+05 168.1600 0 0.9314316 0.050244788 0.0000674667 4.598170e-07 4.808180e-09 0 0 0 1 10 1.2999305 12.361114
52239-12/31/2013 12/31/2013 52239 30 9.38555e+11 176.70 2.0000e+05 127.5600 0 0.9314316 0.387559494 0.0004459600 4.598170e-07 4.808180e-09 0 0 0 0 9 1.6651324 13.117020
52239-12/31/2014 12/31/2014 52239 30 9.11507e+11 204.86 2.0000e+05 177.2600 0 0.9314316 0.250535044 0.0002789490 4.598170e-07 4.808180e-09 0 0 0 0 9 1.2020166 16.016795
52239-3/31/2011 3/31/2011 52239 30 8.80528e+11 241.27 1.7844e+10 170.6300 0 0.9314316 0.081293992 0.0001091580 2.839174e-01 3.224650e-04 0 0 0 1 12 1.0769268 11.619569
52239-3/31/2015 3/31/2015 52239 30 9.15665e+11 245.69 2.0000e+05 163.8500 0 0.9314316 0.179216725 0.0001332250 4.598170e-07 4.808180e-09 0 0 0 0 15 1.1112541 16.466977
52239-6/30/2011 6/30/2011 52239 30 8.83188e+11 328.73 1.7161e+10 131.2700 0 0.9314316 0.110762938 0.0001487280 2.730501e-01 3.101220e-04 0 0 0 1 15 1.3266495 11.378935
52239-6/30/2015 6/30/2015 52239 30 8.59914e+11 270.17 2.0000e+05 167.4400 0 0.9314316 0.197073477 0.0001465000 4.598170e-07 4.808180e-09 0 0 0 0 20 0.8857760 16.984005
52239-9/30/2014 9/30/2014 52239 30 9.23223e+11 225.57 2.0000e+05 158.2100 0 0.9314316 0.275862491 0.0003071490 4.598170e-07 4.808180e-09 0 0 0 0 8 1.3197180 15.106515
>
根据is.pbalanced的定义：
Balanced data are data for which each individual has the same time periods
举个例子：
library(plm)
data("Grunfeld", package = "plm")
is.pbalanced(Grunfeld)
#> [1] TRUE
table(Grunfeld$firm,Grunfeld$year)
#>
#> 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 7 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 8 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 9 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 10 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
non.balanced <- Grunfeld[-sample(200,10),]
is.pbalanced(non.balanced)
#> [1] FALSE
table(non.balanced$firm,non.balanced$year)
#> 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 2 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1
#> 3 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1
#> 4 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1
#> 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 7 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 8 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1
#> 9 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1
#> 10 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1
如上所示，pbalanced 数据集的 table 没有零：每个公司的周期都相同。
您可以在 pbalanced source code:
is.pbalanced.default <- function(x, y, ...) {
if (length(x) != length(y)) stop("The length of the two vectors differs\n")
x <- x[drop = TRUE] # drop unused factor levels so that table
y <- y[drop = TRUE] # gives only needed combinations
z <- table(x, y)
if (any(v <- as.vector(z) == 0L)) {
balanced <- FALSE # Any zero means False
} else { balanced <- TRUE
table 有很多零，这解释了为什么 is.pbalanced(DATA)==FALSE
提供 dput(data) 以找出 make.pbalanced 不起作用的原因会很有用。