This function extracts the information about the structure of the individual and time dimensions of panel data. Grouping information can also be extracted if the panel data were created with a grouping variable.
# S3 method for class 'pindex'
index(x, which = NULL, ...)
# S3 method for class 'pdata.frame'
index(x, which = NULL, ...)
# S3 method for class 'pseries'
index(x, which = NULL, ...)
# S3 method for class 'panelmodel'
index(x, which = NULL, ...)A vector or an object of class c("pindex","data.frame")
containing either one index, individual and time index, or (any
combination of) individual, time and group indexes.
Panel data are stored in a "pdata.frame" which has an "index"
attribute. Fitted models in "plm" have a "model" element which
is also a "pdata.frame" and therefore also has an "index"
attribute. Finally, each series, once extracted from a
"pdata.frame", becomes of class "pseries", which also has this
"index" attribute. "index" methods are available for all these
objects. The argument "which" indicates which index should be
extracted. If which = NULL, all indexes are extracted. "which"
can also be a vector of length 1, 2, or 3 (3 only if the pdata
frame was constructed with an additional group index) containing
either characters (the names of the individual variable and/or of
the time variable and/or the group variable or "id" and "time")
and "group" or integers (1 for the individual index, 2 for the
time index, and 3 for the group index (the latter only if the pdata
frame was constructed with such).)
data("Grunfeld", package = "plm")
Gr <- pdata.frame(Grunfeld, index = c("firm", "year"))
m <- plm(inv ~ value + capital, data = Gr)
index(Gr, "firm")
#> [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2
#> [26] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3
#> [51] 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [76] 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [101] 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7
#> [126] 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8
#> [151] 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9
#> [176] 9 9 9 9 9 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
#> Levels: 1 2 3 4 5 6 7 8 9 10
index(Gr, "time")
#> [1] 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949
#> [16] 1950 1951 1952 1953 1954 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944
#> [31] 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1935 1936 1937 1938 1939
#> [46] 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954
#> [61] 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949
#> [76] 1950 1951 1952 1953 1954 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944
#> [91] 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1935 1936 1937 1938 1939
#> [106] 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954
#> [121] 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949
#> [136] 1950 1951 1952 1953 1954 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944
#> [151] 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1935 1936 1937 1938 1939
#> [166] 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954
#> [181] 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949
#> [196] 1950 1951 1952 1953 1954
#> 20 Levels: 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 ... 1954
index(Gr$inv, c(2, 1))
#> year firm
#> 1 1935 1
#> 2 1936 1
#> 3 1937 1
#> 4 1938 1
#> 5 1939 1
#> 6 1940 1
#> 7 1941 1
#> 8 1942 1
#> 9 1943 1
#> 10 1944 1
#> 11 1945 1
#> 12 1946 1
#> 13 1947 1
#> 14 1948 1
#> 15 1949 1
#> 16 1950 1
#> 17 1951 1
#> 18 1952 1
#> 19 1953 1
#> 20 1954 1
#> 21 1935 2
#> 22 1936 2
#> 23 1937 2
#> 24 1938 2
#> 25 1939 2
#> 26 1940 2
#> 27 1941 2
#> 28 1942 2
#> 29 1943 2
#> 30 1944 2
#> 31 1945 2
#> 32 1946 2
#> 33 1947 2
#> 34 1948 2
#> 35 1949 2
#> 36 1950 2
#> 37 1951 2
#> 38 1952 2
#> 39 1953 2
#> 40 1954 2
#> 41 1935 3
#> 42 1936 3
#> 43 1937 3
#> 44 1938 3
#> 45 1939 3
#> 46 1940 3
#> 47 1941 3
#> 48 1942 3
#> 49 1943 3
#> 50 1944 3
#> 51 1945 3
#> 52 1946 3
#> 53 1947 3
#> 54 1948 3
#> 55 1949 3
#> 56 1950 3
#> 57 1951 3
#> 58 1952 3
#> 59 1953 3
#> 60 1954 3
#> 61 1935 4
#> 62 1936 4
#> 63 1937 4
#> 64 1938 4
#> 65 1939 4
#> 66 1940 4
#> 67 1941 4
#> 68 1942 4
#> 69 1943 4
#> 70 1944 4
#> 71 1945 4
#> 72 1946 4
#> 73 1947 4
#> 74 1948 4
#> 75 1949 4
#> 76 1950 4
#> 77 1951 4
#> 78 1952 4
#> 79 1953 4
#> 80 1954 4
#> 81 1935 5
#> 82 1936 5
#> 83 1937 5
#> 84 1938 5
#> 85 1939 5
#> 86 1940 5
#> 87 1941 5
#> 88 1942 5
#> 89 1943 5
#> 90 1944 5
#> 91 1945 5
#> 92 1946 5
#> 93 1947 5
#> 94 1948 5
#> 95 1949 5
#> 96 1950 5
#> 97 1951 5
#> 98 1952 5
#> 99 1953 5
#> 100 1954 5
#> 101 1935 6
#> 102 1936 6
#> 103 1937 6
#> 104 1938 6
#> 105 1939 6
#> 106 1940 6
#> 107 1941 6
#> 108 1942 6
#> 109 1943 6
#> 110 1944 6
#> 111 1945 6
#> 112 1946 6
#> 113 1947 6
#> 114 1948 6
#> 115 1949 6
#> 116 1950 6
#> 117 1951 6
#> 118 1952 6
#> 119 1953 6
#> 120 1954 6
#> 121 1935 7
#> 122 1936 7
#> 123 1937 7
#> 124 1938 7
#> 125 1939 7
#> 126 1940 7
#> 127 1941 7
#> 128 1942 7
#> 129 1943 7
#> 130 1944 7
#> 131 1945 7
#> 132 1946 7
#> 133 1947 7
#> 134 1948 7
#> 135 1949 7
#> 136 1950 7
#> 137 1951 7
#> 138 1952 7
#> 139 1953 7
#> 140 1954 7
#> 141 1935 8
#> 142 1936 8
#> 143 1937 8
#> 144 1938 8
#> 145 1939 8
#> 146 1940 8
#> 147 1941 8
#> 148 1942 8
#> 149 1943 8
#> 150 1944 8
#> 151 1945 8
#> 152 1946 8
#> 153 1947 8
#> 154 1948 8
#> 155 1949 8
#> 156 1950 8
#> 157 1951 8
#> 158 1952 8
#> 159 1953 8
#> 160 1954 8
#> 161 1935 9
#> 162 1936 9
#> 163 1937 9
#> 164 1938 9
#> 165 1939 9
#> 166 1940 9
#> 167 1941 9
#> 168 1942 9
#> 169 1943 9
#> 170 1944 9
#> 171 1945 9
#> 172 1946 9
#> 173 1947 9
#> 174 1948 9
#> 175 1949 9
#> 176 1950 9
#> 177 1951 9
#> 178 1952 9
#> 179 1953 9
#> 180 1954 9
#> 181 1935 10
#> 182 1936 10
#> 183 1937 10
#> 184 1938 10
#> 185 1939 10
#> 186 1940 10
#> 187 1941 10
#> 188 1942 10
#> 189 1943 10
#> 190 1944 10
#> 191 1945 10
#> 192 1946 10
#> 193 1947 10
#> 194 1948 10
#> 195 1949 10
#> 196 1950 10
#> 197 1951 10
#> 198 1952 10
#> 199 1953 10
#> 200 1954 10
index(m, "id")
#> [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2
#> [26] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3
#> [51] 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [76] 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [101] 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7
#> [126] 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8
#> [151] 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9
#> [176] 9 9 9 9 9 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
#> Levels: 1 2 3 4 5 6 7 8 9 10
# with additional group index
data("Produc", package = "plm")
pProduc <- pdata.frame(Produc, index = c("state", "year", "region"))
index(pProduc, 3)
#> [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2
#> [112] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
#> [149] 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> [186] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> [223] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [260] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [297] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [334] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [371] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [408] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [445] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [482] 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
#> [519] 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
#> [556] 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
#> [593] 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
#> [630] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
#> [667] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
#> [704] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
#> [741] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 9 9
#> [778] 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9
#> [815] 9 9
#> Levels: 1 2 3 4 5 6 7 8 9
index(pProduc, "region")
#> [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2
#> [112] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
#> [149] 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> [186] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> [223] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [260] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [297] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [334] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [371] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [408] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [445] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [482] 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
#> [519] 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
#> [556] 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
#> [593] 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
#> [630] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
#> [667] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
#> [704] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
#> [741] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 9 9
#> [778] 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9
#> [815] 9 9
#> Levels: 1 2 3 4 5 6 7 8 9
index(pProduc, "group")
#> [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2
#> [112] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
#> [149] 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> [186] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> [223] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [260] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [297] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
#> [334] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [371] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [408] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [445] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
#> [482] 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
#> [519] 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
#> [556] 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
#> [593] 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
#> [630] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
#> [667] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
#> [704] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
#> [741] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 9 9
#> [778] 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9
#> [815] 9 9
#> Levels: 1 2 3 4 5 6 7 8 9