How to deal with error of purtest on panel data

Question

I'm currently working with panel data and need to perform a stationarity test. Using The package plm I ran into the following error message:

Error in urca::punitroot(x, N = Inf, trend = punitroot.exo) : NAs are not allowed when na.rm=FALSE

I use panel data without missing values, as I approximated these values with the AMELIA II algorithm.

My code is the following:

STATIONARYTEST <- make.pbalanced(FINALDATA, balance.type = "shared.times")
BALANCED <- data.frame(split(STATIONARYTEST$v2x_pubcorr, STATIONARYTEST$country_name))

purtest(BALANCED, test = "madwu")

Unfortunately I cannot post the dput(FINALDATA) simply because it is too large of data frame.

What I can tell you is, that FINALDATA (a pdata.frame) is unbalanced, which is why is used the make.pbalanced command.

BALANCED looks as follows:

>dput(BALANCED)
structure(list(Albania = c(0.594, 0.606, 0.586, 0.559, 0.586, 
0.586, 0.586, 0.442, 0.442, 0.442, 0.691, 0.691, 0.681, 0.681, 
0.681, 0.611, 0.611, 0.611, 0.611), Austria = c(0.111, 0.111, 
0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 
0.111, 0.111, 0.111, 0.111, 0.047, 0.047, 0.047, 0.047), Belarus = c(0.424, 
0.318, 0.318, 0.292, 0.292, 0.292, 0.292, 0.292, 0.292, 0.29, 
0.29, 0.29, 0.29, 0.29, 0.29, 0.299, 0.299, 0.299, 0.292), Belgium = c(0.03, 
0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 
0.03, 0.03, 0.03, 0.025, 0.025, 0.025, 0.025), Bosnia.and.Herzegovina = c(0.773, 
0.773, 0.773, 0.773, 0.773, 0.773, 0.773, 0.773, 0.773, 0.773, 
0.773, 0.773, 0.773, 0.773, 0.773, 0.79, 0.79, 0.788, 0.782), 
    Bulgaria = c(0.45, 0.45, 0.45, 0.409, 0.409, 0.409, 0.409, 
    0.409, 0.377, 0.361, 0.395, 0.587, 0.542, 0.542, 0.542, 0.471, 
    0.471, 0.566, 0.566), Croatia = c(0.708, 0.708, 0.313, 0.313, 
    0.313, 0.313, 0.54, 0.54, 0.54, 0.54, 0.54, 0.314, 0.317, 
    0.317, 0.317, 0.277, 0.276, 0.274, 0.361), Czech.Republic = c(0.301, 
    0.301, 0.301, 0.301, 0.301, 0.301, 0.301, 0.301, 0.301, 0.301, 
    0.297, 0.302, 0.262, 0.262, 0.263, 0.248, 0.229, 0.227, 0.227
    ), Denmark = c(0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 
    0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 
    0.005, 0.005, 0.013, 0.013), Estonia = c(0.211, 0.151, 0.151, 
    0.151, 0.151, 0.151, 0.105, 0.056, 0.056, 0.056, 0.055, 0.055, 
    0.04, 0.04, 0.039, 0.041, 0.042, 0.04, 0.041), Finland = c(0.04, 
    0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04, 
    0.04, 0.04, 0.04, 0.04, 0.039, 0.04, 0.042, 0.041), France = c(0.072, 
    0.072, 0.052, 0.052, 0.052, 0.052, 0.052, 0.052, 0.052, 0.052, 
    0.052, 0.052, 0.054, 0.054, 0.054, 0.059, 0.059, 0.059, 0.059
    ), Germany = c(0.011, 0.011, 0.011, 0.011, 0.011, 0.011, 
    0.011, 0.011, 0.011, 0.011, 0.011, 0.011, 0.011, 0.011, 0.012, 
    0.017, 0.017, 0.031, 0.023), Greece = c(0.399, 0.399, 0.399, 
    0.399, 0.399, 0.399, 0.399, 0.399, 0.399, 0.399, 0.399, 0.399, 
    0.399, 0.376, 0.376, 0.258, 0.258, 0.258, 0.258), Hungary = c(0.156, 
    0.162, 0.162, 0.162, 0.162, 0.168, 0.168, 0.168, 0.168, 0.168, 
    0.168, 0.168, 0.189, 0.207, 0.207, 0.215, 0.215, 0.215, 0.215
    ), Iceland = c(0.018, 0.018, 0.018, 0.018, 0.018, 0.018, 
    0.018, 0.018, 0.018, 0.018, 0.018, 0.018, 0.018, 0.018, 0.018, 
    0.02, 0.02, 0.02, 0.02), Ireland = c(0.05, 0.05, 0.05, 0.05, 
    0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.046, 0.046, 
    0.046, 0.056, 0.056, 0.056, 0.056), Italy = c(0.177, 0.177, 
    0.203, 0.203, 0.203, 0.203, 0.203, 0.203, 0.189, 0.189, 0.2, 
    0.2, 0.186, 0.186, 0.186, 0.217, 0.217, 0.217, 0.217), Latvia = c(0.208, 
    0.194, 0.204, 0.204, 0.184, 0.163, 0.162, 0.171, 0.171, 0.161, 
    0.144, 0.144, 0.129, 0.129, 0.125, 0.093, 0.093, 0.093, 0.19
    ), Lithuania = c(0.162, 0.162, 0.162, 0.138, 0.138, 0.138, 
    0.138, 0.138, 0.138, 0.112, 0.112, 0.112, 0.112, 0.112, 0.112, 
    0.119, 0.119, 0.119, 0.126), Luxembourg = c(0.054, 0.054, 
    0.054, 0.054, 0.054, 0.054, 0.054, 0.054, 0.054, 0.054, 0.054, 
    0.054, 0.054, 0.054, 0.054, 0.054, 0.054, 0.054, 0.054), 
    Malta = c(0.118, 0.118, 0.118, 0.118, 0.118, 0.118, 0.118, 
    0.118, 0.118, 0.118, 0.118, 0.118, 0.118, 0.118, 0.118, 0.118, 
    0.118, 0.118, 0.118), Moldova = c(0.667, 0.667, 0.667, 0.651, 
    0.662, 0.662, 0.662, 0.662, 0.662, 0.662, 0.662, 0.662, 0.559, 
    0.559, 0.521, 0.611, 0.609, 0.683, 0.802), Montenegro = c(0.568, 
    0.568, 0.568, 0.568, 0.568, 0.568, 0.568, 0.568, 0.568, 0.57, 
    0.57, 0.57, 0.57, 0.57, 0.57, 0.561, 0.561, 0.561, 0.561), 
    Netherlands = c(0.031, 0.031, 0.031, 0.031, 0.031, 0.031, 
    0.031, 0.031, 0.031, 0.031, 0.031, 0.031, 0.031, 0.031, 0.031, 
    0.031, 0.031, 0.028, 0.028), North.Macedonia = c(0.412, 0.412, 
    0.412, 0.412, 0.412, 0.398, 0.398, 0.398, 0.398, 0.398, 0.418, 
    0.418, 0.418, 0.459, 0.459, 0.508, 0.508, 0.508, 0.499), 
    Norway = c(0.013, 0.013, 0.013, 0.013, 0.013, 0.013, 0.013, 
    0.013, 0.013, 0.013, 0.014, 0.014, 0.014, 0.014, 0.014, 0.014, 
    0.014, 0.013, 0.013), Poland = c(0.143, 0.143, 0.143, 0.143, 
    0.143, 0.143, 0.143, 0.135, 0.128, 0.129, 0.139, 0.139, 0.139, 
    0.139, 0.144, 0.147, 0.147, 0.119, 0.11), Portugal = c(0.12, 
    0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 
    0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 0.086, 0.125), Romania = c(0.833, 
    0.833, 0.846, 0.799, 0.799, 0.799, 0.799, 0.799, 0.682, 0.667, 
    0.667, 0.644, 0.644, 0.644, 0.628, 0.582, 0.51, 0.51, 0.522
    ), Russia = c(0.883, 0.883, 0.827, 0.827, 0.827, 0.827, 0.827, 
    0.827, 0.827, 0.827, 0.827, 0.827, 0.827, 0.827, 0.828, 0.766, 
    0.766, 0.766, 0.799), Serbia = c(0.853, 0.853, 0.882, 0.722, 
    0.678, 0.678, 0.678, 0.678, 0.678, 0.678, 0.674, 0.674, 0.674, 
    0.674, 0.674, 0.642, 0.602, 0.602, 0.676), Slovakia = c(0.316, 
    0.261, 0.261, 0.261, 0.261, 0.261, 0.261, 0.261, 0.261, 0.261, 
    0.261, 0.261, 0.253, 0.253, 0.262, 0.233, 0.233, 0.233, 0.233
    ), Slovenia = c(0.087, 0.087, 0.091, 0.091, 0.091, 0.084, 
    0.084, 0.091, 0.091, 0.108, 0.108, 0.108, 0.108, 0.108, 0.108, 
    0.105, 0.105, 0.105, 0.104), Spain = c(0.033, 0.033, 0.033, 
    0.033, 0.033, 0.033, 0.033, 0.033, 0.033, 0.033, 0.033, 0.033, 
    0.042, 0.042, 0.042, 0.045, 0.045, 0.031, 0.031), Sweden = c(0.009, 
    0.009, 0.009, 0.009, 0.009, 0.009, 0.009, 0.009, 0.009, 0.009, 
    0.009, 0.009, 0.009, 0.009, 0.009, 0.011, 0.011, 0.018, 0.018
    ), Switzerland = c(0.032, 0.032, 0.032, 0.032, 0.032, 0.032, 
    0.032, 0.032, 0.032, 0.032, 0.032, 0.032, 0.032, 0.032, 0.032, 
    0.032, 0.032, 0.013, 0.013), Ukraine = c(0.921, 0.92, 0.854, 
    0.856, 0.856, 0.877, 0.689, 0.682, 0.76, 0.729, 0.699, 0.761, 
    0.792, 0.791, 0.792, 0.792, 0.72, 0.646, 0.61), United.Kingdom = c(0.032, 
    0.032, 0.032, 0.032, 0.032, 0.032, 0.032, 0.032, 0.032, 0.032, 
    0.032, 0.032, 0.032, 0.032, 0.032, 0.035, 0.035, 0.035, 0.035
    ), na.rm = c(TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, 
    TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, 
    TRUE)), class = "data.frame", row.names = c(NA, -19L))

Additional Information: STATIONARYTEST$v2x_pubcorr is my main dependent variable of interest. STATIONARYTEST$country_name is the cross sectional variable.

FURTHERMORE: In an attempt to see how the command behaves when I use a balanced data set (without using make.pbalanced command) I isolated the countries of Austria and Belgium. Using these two countries alone resulted in a balanced data set.

STATIONARYTEST222 <- FINALDATA %>% filter(country_name == "Belgium" | country_name == "Austria")
is.pbalanced(STATIONARYTEST222)
> TRUE

BALANCED <- data.frame(split(STATIONARYTEST222$v2x_pubcorr, STATIONARYTEST222$country_name))

When I tried to execute the last command I got the following error:

Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows: 0, 67

> dput(STATIONARITYTEST222)
structure(list(country_name = structure(c(2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L), .Label = c("Albania", "Austria", "Belarus", "Belgium", "Bosnia and Herzegovina", 
"Bulgaria", "Croatia", "Czech Republic", "Denmark", "Estonia", 
"Finland", "France", "Germany", "Greece", "Hungary", "Iceland", 
"Ireland", "Italy", "Latvia", "Lithuania", "Luxembourg", "Malta", 
"Moldova", "Montenegro", "Netherlands", "North Macedonia", "Norway", 
"Poland", "Portugal", "Romania", "Russia", "Serbia", "Slovakia", 
"Slovenia", "Spain", "Sweden", "Switzerland", "Ukraine", "United Kingdom"
), class = "factor"), year = structure(c(1L, 2L, 3L, 4L, 5L, 
6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 
32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 
45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 
58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 1L, 2L, 3L, 
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 
31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 
44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 
57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L), .Label = c("1950", 
"1951", "1952", "1953", "1954", "1955", "1956", "1957", "1958", 
"1959", "1960", "1961", "1962", "1963", "1964", "1965", "1966", 
"1967", "1968", "1969", "1970", "1971", "1972", "1973", "1974", 
"1975", "1976", "1977", "1978", "1979", "1980", "1981", "1982", 
"1983", "1984", "1985", "1986", "1987", "1988", "1989", "1990", 
"1991", "1992", "1993", "1994", "1995", "1996", "1997", "1998", 
"1999", "2000", "2001", "2002", "2003", "2004", "2005", "2006", 
"2007", "2008", "2009", "2010", "2011", "2012", "2013", "2014", 
"2015", "2016"), class = "factor"), country_id = c(144, 144, 
144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 
144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 
144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 
144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 
144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 
148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 
148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 
148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 
148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 
148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 
148, 148), v2elffelr = c(2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 
2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 
2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 
2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 
2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 
2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 
2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 2.281, 
1.612, 2.24, 2.24, 2.187, 2.187, 2.187, 2.187, 2.404, 2.404, 
2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 
2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 
2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 
2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 
2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 
2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 
2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.404, 2.329, 2.329, 
2.329, 2.329), v2elffelrbin = c(1.239, 1.239, 1.239, 1.239, 1.239, 
1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 
1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 
1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 
1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 
1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 
1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 1.239, 
1.239, 1.239, 1.239, 1.239, 1.157, 1.157, 1.157, 1.157, -0.823, 
-0.823, -0.823, -0.823, -0.823, -0.823, -0.823, -0.823, -0.823, 
-0.823, -0.823, -0.823, -0.823, -0.823, -0.823, -0.823, -0.823, 
-0.823, -0.823, -0.823, -0.823, -0.823, -0.823, -0.823, -0.823, 
-0.823, -0.823, -0.823, -0.823, -0.823, -0.823, -0.823, -0.823, 
-0.823, -0.823, -0.823, -0.823, -0.823, -0.823, -0.823, -0.823, 
-0.823, -0.823, -0.823, -0.823, 1.105, -0.821, -0.821, -0.821, 
1.128, -0.813, -0.813, -0.813, -0.813, 1.096, -0.913, -0.461, 
-0.915, -0.915, -0.337, -0.914, -0.914, -0.472, -0.908, -0.351, 
-0.965, -0.965), e_migdppc = c(4560, 4845, 5066, 5432, 5945, 
6519, 7056, 7468, 7837, 8081, 8508, 9025, 9416, 9755, 10195, 
10551, 11132, 11495, 12053, 12671, 13523, 14266, 15115, 15732, 
16052, 16305, 16770, 17362, 17210, 17891, 18019, 17855, 18021, 
18488, 18361, 18781, 19626, 20468, 21853, 23223, 24175, 25456, 
26127, 26424, 27796, 28938, 29266, 31019, 32638, 33821, 35714, 
34946, 35923, 35820, 36845, 37653, 39100, 40418, 40828, 40055, 
40500, 41446, 43052, 43175, 44894, 44845, 45010, 6975, 7338, 
7388, 7701, 8027, 8453, 8690, 8799, 8844, 9104, 9113, 9635, 10445, 
10917, 11672, 12048, 12548, 13142, 13747, 14763, 15724, 16337, 
17359, 18446, 18728, 18421, 19691, 19867, 20396, 21042, 22057, 
20536, 20060, 19497, 19417, 18703, 19640, 20574, 22312, 23118, 
23658, 24295, 25562, 25349, 26373, 27199, 26748, 28630, 29919, 
31291, 33427, 33294, 34649, 34312, 34665, 35284, 35065, 35943, 
36634, 37260, 38592, 38130, 38907, 39398, 39182, 39531, 39733
), v2x_pubcorr = c(0.076, 0.076, 0.076, 0.076, 0.049, 0.049, 
0.078, 0.078, 0.078, 0.078, 0.078, 0.078, 0.078, 0.078, 0.078, 
0.078, 0.078, 0.078, 0.078, 0.078, 0.078, 0.078, 0.078, 0.078, 
0.078, 0.078, 0.078, 0.078, 0.078, 0.078, 0.158, 0.158, 0.158, 
0.158, 0.158, 0.158, 0.158, 0.111, 0.111, 0.111, 0.111, 0.111, 
0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 
0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 0.111, 
0.111, 0.111, 0.111, 0.047, 0.047, 0.047, 0.047, 0.03, 0.03, 
0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 
0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 
0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 
0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 
0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 
0.03, 0.03, 0.03, 0.03, 0.03, 0.03, 0.025, 0.025, 0.025, 0.025
), v2xnp_client = c(0.344, 0.332, 0.325, 0.307, 0.304, 0.346, 
0.299, 0.273, 0.273, 0.341, 0.378, 0.378, 0.373, 0.349, 0.349, 
0.297, 0.263, 0.263, 0.263, 0.263, 0.289, 0.274, 0.203, 0.203, 
0.202, 0.207, 0.225, 0.225, 0.225, 0.21, 0.192, 0.163, 0.163, 
0.173, 0.187, 0.187, 0.15, 0.147, 0.147, 0.147, 0.152, 0.179, 
0.148, 0.134, 0.138, 0.153, 0.093, 0.07, 0.068, 0.074, 0.095, 
0.095, 0.092, 0.069, 0.077, 0.081, 0.078, 0.064, 0.063, 0.062, 
0.057, 0.059, 0.059, 0.064, 0.062, 0.095, 0.088, 0.195, 0.202, 
0.202, 0.202, 0.172, 0.16, 0.16, 0.16, 0.168, 0.173, 0.153, 0.173, 
0.179, 0.179, 0.179, 0.152, 0.135, 0.135, 0.148, 0.152, 0.152, 
0.149, 0.131, 0.131, 0.147, 0.151, 0.151, 0.14, 0.136, 0.121, 
0.137, 0.139, 0.151, 0.151, 0.151, 0.152, 0.086, 0.087, 0.114, 
0.114, 0.114, 0.108, 0.055, 0.055, 0.055, 0.068, 0.073, 0.073, 
0.073, 0.063, 0.054, 0.054, 0.054, 0.053, 0.053, 0.053, 0.053, 
0.044, 0.036, 0.034, 0.034, 0.033, 0.041, 0.037, 0.036, 0.035, 
0.035), e_total_fuel_income_pc = c(53.63, 65.12, 71.28, 85.26, 
89.59, 95.07, 94.4, 90.18, 82.48, 75.49, 71.19, 66.02, 66.03, 
45.85, 67.08, 66.3, 63.19, 59.55, 53.1, 49.94, 51.7, 57.15, 57.94, 
69.03, 161.46, 145.03, 140.7, 146.03, 144.94, 220.9, 201, 161.78, 
151.65, 129.92, 118.6, 109.27, 71.69, 71.54, 62.25, 63.51, 73.43, 
64.89, 59.23, 55.3, 46.73, 43.44, 50.01, 47.48, 38.7, 47.73, 
72.39, 65.97, 58.13, 81.32, 84.8, 106.72, 110.09, 3679.89855133674, 
8185.62755709757, 4652.91030179564, 7086.47857954613, 6763.0077814627, 
3839.20809400641, 7344.36553794882, 7180.27833621883, 4857.87269571732, 
4733.90176929056, 148.06, 150.99, 149.66, 146.94, 129.7, 131.81, 
136.29, 135.26, 117.03, 95.53, 91.03, 83.67, 79.36, 76.78, 75.83, 
68.57, 59.84, 55.3, 48.35, 43.61, 45.03, 47.45, 47.89, 42.52, 
65.21, 68.68, 64, 61.82, 60, 54.02, 52.54, 49.74, 50.96, 44.67, 
42.79, 41.96, 34.32, 25.32, 15.59, 9.43, 3.19, 1.13, 0.05, 0.04, 
0.01, 0, 0.02, 0, 0, 0, 0.03, 0, 0, 0, 0, 0, 0, 1911.7747504759, 
-1199.38536156022, 1411.03507725042, 891.666005834158, 373.197200461489, 
2173.00097561386, 2747.12988859581, -27.9550493962888, 1754.64945758216, 
4520.91449062753), v2elfrfair = c(1.40132792033515, 1.679, 0.541049141075401, 
1.659, 1.60773056697027, 2.8258795416579, 1.664, 1.664, 2.41927270152404, 
1.737, 1.71067576513315, 1.61268794176647, 1.668, 1.668, 2.04097689835134, 
1.677, 1.677, 1.20718430716776, 0.493204265346457, 2.09457456857527, 
1.631, 1.674, 0.377462635065878, 2.13319630561236, 1.712, 1.715, 
1.66212044961192, 1.47203087375343, 1.84302996311272, 1.692, 
1.684, 2.40176273182624, 1.76907579063065, 1.692, 2.29454682806757, 
1.14771611990067, 1.667, 1.73551010714927, 0.365263591522678, 
1.17970893416492, 1.666, 2.51327076346352, 1.672, 1.58598030071915, 
1.705, 1.703, 2.37540965999566, 2.25362095360046, 1.644, 1.653, 
0.376495098917595, 1.82065149356349, 1.645, 1.93587143874116, 
1.66, 2.40439785003682, 1.907, 1.28214464690115, 1.891, 2.06539931190712, 
1.874, 1.65663063170703, 1.66208239440504, 1.882, 2.40976724048327, 
1.17051141409222, 1.038, 1.817, 2.48706887310882, 2.97990251044591, 
1.92482550102507, 1.829, 1.25286195347918, 1.95302302093176, 
1.68042812924957, 1.831, 1.89041661507571, 1.16215892247556, 
1.817, 2.18979828209219, 2.88972026358515, 2.61820894432001, 
1.82, 1.07273773829965, 0.935363024284767, 1.826, 2.1705206292172, 
1.89259383034004, 1.862, 1.77542675299113, 1.95823662958056, 
1.814, 1.7712287688162, 1.73589815811926, 1.876, 1.876, 2.74022402681816, 
2.00132073910227, 1.805, 1.26907258714646, 2.21011519378473, 
1.38254077621057, 1.858, 2.56569886000421, 1.852, 1.54799194277065, 
1.35332732418557, 2.20864519677777, 1.785, 2.34650687424493, 
1.77353325866748, 3.13950482610678, 1.827, 2.55173735229479, 
1.90836027680683, 2.05224931822916, 1.836, 2.3599183465524, 2.27012267487134, 
2.77699381804334, 1.825, 2.71359722355756, 2.00088726810414, 
2.10951173384588, 2.145, 2.60046614539633, 2.62040183409194, 
2.186, 2.36306647393869, 2.46423986463719, 2.31772202617049, 
2.133, 1.64062311419701, 2.92901421425319), e_miurbani = c(0.358, 
0.358, 0.359, 0.359, 0.359, 0.36, 0.36, 0.36, 0.361, 0.361, 0.361, 
0.36, 0.359, 0.358, 0.356, 0.355, 0.354, 0.353, 0.352, 0.351, 
0.349, 0.35, 0.35, 0.351, 0.351, 0.352, 0.352, 0.353, 0.353, 
0.354, 0.354, 0.354, 0.354, 0.354, 0.354, 0.354, 0.354, 0.354, 
0.354, 0.354, 0.354, 0.353, 0.352, 0.351, 0.351, 0.35, 0.349, 
0.348, 0.347, 0.346, 0.345, 0.625104104430152, 0.589183642300823, 
0.36174005549091, 0.734486489201076, 0.367615560442693, 0.292709220149293, 
0.597384210534355, 0.285554798083621, 0.414711015952627, 0.657507598229605, 
0.119745577612342, 0.43489643233861, 0.259398811624056, 0.293541234504069, 
0.0284031870313866, -0.0804629746576592, 0.256, 0.257, 0.258, 
0.26, 0.261, 0.262, 0.263, 0.264, 0.265, 0.266, 0.268, 0.269, 
0.27, 0.27, 0.271, 0.272, 0.273, 0.274, 0.275, 0.276, 0.277, 
0.279, 0.28, 0.282, 0.284, 0.286, 0.287, 0.289, 0.291, 0.293, 
0.294, 0.296, 0.298, 0.3, 0.302, 0.304, 0.306, 0.308, 0.31, 0.312, 
0.314, 0.315, 0.316, 0.318, 0.319, 0.32, 0.322, 0.323, 0.324, 
0.326, 0.327, 0.411135722414429, 0.673550869261708, 0.373587901979434, 
0.750520482216727, 0.638336666054789, 0.516649360481536, 0.406651564692971, 
0.780544843654102, 0.859511524190551, 0.67568530495162, 0.284587641481792, 
0.552833092208023, 0.534306603141291, 0.619534615117042, 0.572040557257485, 
0.666466866573874), v2x_horacc = c(0.851, 0.856, 0.844, 0.856, 
0.853, 0.843, 0.803, 0.805, 0.791, 0.778, 0.796, 0.799, 0.791, 
0.805, 0.795, 0.798, 0.851, 0.889, 0.887, 0.873, 0.882, 0.892, 
0.881, 0.999, 0.982, 0.985, 1.018, 1.023, 1.015, 1.034, 1.023, 
1.19, 1.186, 1.196, 1.179, 1.194, 1.201, 1.415, 1.406, 1.412, 
1.327, 1.318, 1.326, 1.317, 1.326, 1.315, 1.329, 1.328, 1.314, 
1.329, 1.404, 1.399, 1.406, 1.407, 1.411, 1.419, 1.41, 1.525, 
1.512, 1.521, 1.525, 1.514, 1.517, 1.505, 1.498, 1.495, 1.551, 
1.256, 1.25, 1.259, 1.258, 1.257, 1.255, 1.258, 1.261, 1.27, 
1.269, 1.27, 1.267, 1.271, 1.261, 1.274, 1.264, 1.263, 1.266, 
1.275, 1.257, 1.261, 1.258, 1.262, 1.254, 1.259, 1.264, 1.245, 
1.258, 1.271, 1.272, 1.27, 1.282, 1.268, 1.288, 1.289, 1.282, 
1.28, 1.276, 1.286, 1.24, 1.398, 1.394, 1.439, 1.441, 1.446, 
1.445, 1.551, 1.539, 1.543, 1.606, 1.622, 1.606, 1.62, 1.614, 
1.603, 1.625, 1.616, 1.682, 1.613, 1.647, 1.61, 1.609, 1.61, 
1.693, 1.689, 1.689, 1.684), v2x_gencs = c(0.541, 0.541, 0.541, 
0.541, 0.541, 0.541, 0.572, 0.572, 0.572, 0.572, 0.572, 0.631, 
0.631, 0.631, 0.631, 0.631, 0.609, 0.609, 0.609, 0.609, 0.609, 
0.609, 0.659, 0.659, 0.659, 0.659, 0.705, 0.705, 0.705, 0.705, 
0.801, 0.801, 0.801, 0.801, 0.801, 0.801, 0.869, 0.889, 0.889, 
0.889, 0.889, 0.889, 0.889, 0.889, 0.889, 0.889, 0.893, 0.871, 
0.898, 0.898, 0.898, 0.898, 0.898, 0.898, 0.898, 0.898, 0.886, 
0.884, 0.884, 0.884, 0.914, 0.914, 0.914, 0.894, 0.894, 0.894, 
0.894, 0.507, 0.507, 0.507, 0.507, 0.507, 0.507, 0.507, 0.507, 
0.507, 0.507, 0.535, 0.535, 0.535, 0.535, 0.535, 0.535, 0.535, 
0.535, 0.535, 0.535, 0.591, 0.629, 0.629, 0.629, 0.629, 0.629, 
0.626, 0.626, 0.626, 0.626, 0.61, 0.61, 0.702, 0.702, 0.702, 
0.702, 0.708, 0.708, 0.708, 0.708, 0.853, 0.853, 0.853, 0.853, 
0.853, 0.853, 0.853, 0.853, 0.853, 0.853, 0.882, 0.882, 0.882, 
0.882, 0.882, 0.882, 0.882, 0.882, 0.881, 0.881, 0.859, 0.882, 
0.882, 0.875, 0.884, 0.896, 0.875), v2x_corr = c(0.062, 0.062, 
0.062, 0.062, 0.054, 0.054, 0.068, 0.068, 0.068, 0.068, 0.068, 
0.068, 0.068, 0.068, 0.068, 0.068, 0.068, 0.068, 0.068, 0.068, 
0.067, 0.067, 0.067, 0.08, 0.08, 0.08, 0.08, 0.08, 0.08, 0.08, 
0.105, 0.105, 0.105, 0.105, 0.105, 0.105, 0.105, 0.094, 0.094, 
0.094, 0.094, 0.094, 0.094, 0.094, 0.094, 0.094, 0.094, 0.094, 
0.094, 0.094, 0.104, 0.12, 0.12, 0.104, 0.124, 0.124, 0.109, 
0.086, 0.086, 0.086, 0.086, 0.091, 0.085, 0.048, 0.048, 0.048, 
0.048, 0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 
0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 
0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 0.041, 
0.041, 0.042, 0.042, 0.042, 0.042, 0.042, 0.042, 0.042, 0.042, 
0.042, 0.042, 0.042, 0.042, 0.042, 0.05, 0.05, 0.05, 0.05, 0.05, 
0.05, 0.05, 0.028, 0.028, 0.028, 0.028, 0.028, 0.028, 0.028, 
0.028, 0.028, 0.028, 0.028, 0.028, 0.028, 0.028, 0.028, 0.028, 
0.025, 0.025, 0.025, 0.025), v2elsnlsff = c(0.814, 0.814, 0.814, 
0.814, 0.814, 0.814, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 
1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 
1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 
1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 
1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 
1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 
1.921, 1.921, 1.921, 1.921, 1.921, 1.921, 1.908, 1.908, 1.908, 
1.908, 1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 
1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 
1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 1.713, 
1.713, 1.713, 1.713, 1.713, 1.976, 1.976, 1.976, 1.976, 1.976, 
1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 
1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 
1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 1.976, 
1.976, 1.906, 1.906, 1.888, 1.841), v2pssunpar = c(1.704, 1.704, 
1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 
1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 
1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 
1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 
1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 
1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 
1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 1.704, 2.1, 2.1, 2.1, 
2.1, 0.733, 0.733, 0.733, 0.733, 0.733, 1.418, 2.111, 2.111, 
2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 
2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 
2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 
2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 
2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 
2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 2.111, 
2.111, 2.161, 2.161, 2.091, 2.091), v2clrgunev = c(0.635, 0.635, 
0.635, 0.635, 0.635, 0.635, 1.206, 1.206, 1.206, 1.206, 1.206, 
1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 
1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 
1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 1.206, 2.088, 
2.088, 2.088, 2.088, 2.088, 2.088, 2.088, 2.088, 2.088, 2.088, 
2.088, 2.088, 2.088, 2.088, 2.088, 2.088, 2.088, 2.088, 2.088, 
2.088, 2.088, 2.088, 2.088, 2.088, 2.088, 2.088, 2.216, 2.216, 
2.216, 2.216, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 
2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 
2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 
2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 
2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 
2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 2.52, 
2.52, 2.52, 2.52, 2.52), v2clsnlpct = c(12.5, 12.5, 12.5, 12.5, 
12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 
12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 3.333, 3.333, 3.333, 3.333, 
3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 
3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 
3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 
3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 3.333, 
3.333, 3.333, 50, 50, 50, 50, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), continent = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L), .Label = "Europe", class = "factor"), CountryShortcut = structure(c(2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L), .Label = c("ALB", "AUT", "BEL", "BGR", "BIH", 
"BLR", "CHE", "CZE", "DEU", "DNK", "ESP", "EST", "FIN", "FRA", 
"GBR", "GRC", "HRV", "HUN", "IRL", "ISL", "ITA", "LTU", "LUX", 
"LVA", "MDA", "MKD", "MLT", "MNE", "NLD", "NOR", "POL", "PRT", 
"ROU", "RUS", "SRB", "SVK", "SVN", "SWE", "UKR"), class = "factor"), 
    POSTCOM = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0)), row.names = c(NA, -134L), class = "data.frame")