Hello,
I have posted this problem before, but thought I try to explain it a bit
better.
I'm using the function plm to create a fixed effects model for panel data,
my method is therefor "within" my effect is "twoways".
My Data contains unbalanced Panels due to missing Values, but contains 309
observation for 11 variables (incl. response), with no missing Values. These
309 observations distribute over 25 individuals and 18 years.
The fuction plm only uses 286 of these observations (also if the model is
changed to first differences and the effect to individual) and omits 23
observations due to na.action, but in my dataset they do not contain NAs.
Is this due to the Transformation used in the plm function?
If it is of any help, these are the observations that are omitted (which
obviously don't contain NAs):
TIME GEO
98 1993 Deutschland (einschließlich der ehemaligen DDR seit 1991)
99 1994 Deutschland (einschließlich der ehemaligen DDR seit 1991)
100 1995 Deutschland (einschließlich der ehemaligen DDR seit 1991)
101 1996 Deutschland (einschließlich der ehemaligen DDR seit 1991)
370 1999 Österreich
372 2001 Österreich
375 2004 Österreich
385 1995 Polen
386 1996 Polen
387 1997 Polen
495 1991 Schweden
439 1992 Slowenien
440 1993 Slowenien
441 1994 Slowenien
442 1995 Slowenien
443 1996 Slowenien
172 1991 Spanien
173 1992 Spanien
174 1993 Spanien
175 1994 Spanien
176 1995 Spanien
177 1996 Spanien
178 1997 Spanien
Verkehrstote_Quote Autobahnlaenge_Quote PKW_Quote$Value LKW$Value
98 123 0.0310283316 479 19.62343
99 121 0.0312047562 489 25.99028
100 116 0.0313363746 496 27.16505
101 107 0.0314931965 501 27.78134
370 135 0.0194823002 502 39.96261
372 119 0.0196134540 521 41.26695
375 108 0.0199949923 505 40.89616
385 179 0.0007867343 195 33.66977
386 165 0.0008251115 209 35.50949
387 189 0.0008443002 221 36.80187
495 87 0.0021512832 421 31.19678
439 247 0.0125413519 304 16.00871
440 247 0.0132326075 317 17.05044
441 254 0.0136769861 330 18.09584
442 209 0.0144669925 351 20.10579
443 195 0.0153063744 366 21.10271
172 227 0.0103736290 322 110.86938
173 200 0.0128525994 336 67.96822
174 163 0.0130329241 343 69.89171
175 143 0.0128743969 350 72.00581
176 146 0.0137958367 361 74.65096
177 139 0.0144557065 374 77.52797
178 142 0.0153573304 387 81.11232
Motorraeder$Value Bevoelkerungsquote Quote_Jung Quote_Alt
98 19.561682 226.76063 12.31254 3.928754
99 23.297817 227.77846 11.82362 4.011330
100 27.802782 228.33996 11.40332 4.087582
101 30.189141 229.12098 11.19176 4.026278
370 32.947233 95.17546 11.98196 3.378319
372 36.778704 95.63432 11.90409 3.558421
375 38.808372 97.08449 12.20926 4.066773
385 24.079461 123.38487 15.48095 2.154967
386 22.688776 123.47698 15.82873 2.102519
387 21.791262 123.57274 16.09662 2.027340
495 5.238265 19.09182 13.55292 4.302106
439 5.502994 98.69708 14.60535 2.364486
440 5.516317 98.45870 14.58509 2.464340
441 4.523959 98.22782 14.64697 2.535880
442 4.523802 98.23123 14.74327 2.612043
443 4.019563 98.27018 14.93248 2.567195
172 30.199689 77.03350 16.89450 2.962978
173 32.074025 77.28903 16.86363 3.062267
174 32.684277 77.54355 16.80052 3.163572
175 32.817935 77.77117 16.69243 3.261328
176 33.068060 77.96193 16.53155 3.352908
177 33.171926 78.13598 16.31481 3.438006
178 33.548015 78.32325 16.02780 3.510471
Quote_Erstzulassungen BIP$Value Alkohol.Wert
98 0.09782568 21100 13.50
99 0.08070474 22200 13.37
100 0.08202309 23600 13.35
101 0.08530314 23400 13.12
370 0.07834963 24900 13.40
372 0.07018843 26600 12.80
375 0.07575858 28700 12.50
385 0.05996661 2800 8.14
386 0.07789285 3200 8.08
387 0.08464139 3600 8.64
495 0.05298563 24200 6.28
439 0.05147030 4800 13.64
440 0.09212000 5400 14.31
441 0.07068413 6100 13.38
442 0.08677918 8100 13.36
443 0.07988964 8400 12.04
172 0.07290907 11400 13.23
173 0.07695772 11800 12.50
174 0.05522833 10800 12.03
175 0.06836836 10800 11.70
176 0.06125084 11600 11.38
177 0.06563393 12400 11.07
178 0.07133359 12800 11.95
TIME and GEO are the Index of my Paneldata, "Verkehrstoten_Quote" is the
dependent, all others the independent variables.
If anyone could help me understand, why these observations (or generally
any) are left out, I would be very glad.
Thank you for dealing with my Problem.
Regards,
Daniel
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