Luca Gagliardone
2015-Aug-14 12:13 UTC
[R] System exactly singular with pgmm (package plm)
his is my first post, I'll do my best to be clear and complete.
I am trying to run a pgmm regression (Arellano Bond estimator) following
the example online with the EmplUK dataset.
My dataset is unbalanced, with some missing values (that I also removed,
without any difference). This is the paste from R' dataframe.
row.names ID Year p I
1 23 1 1992 NA NA
2 22 1 1993 17.01 NA
3 21 1 1994 15.86 NA
4 20 1 1995 17.02 7.512347
5 19 1 1996 20.64 7.685104
6 18 1 1997 19.11 12.730282
7 17 1 1998 12.76 12.633871
8 16 1 1999 17.90 7.416381
9 15 1 2000 28.66 6.396114
10 14 1 2001 24.46 9.213729
11 13 1 2002 24.99 20.117159
12 12 1 2003 28.85 11.117816
13 11 1 2004 38.26 11.242638
14 10 1 2005 54.57 13.015168
15 9 1 2006 65.16 18.507212
16 8 1 2007 72.44 18.875281
17 7 1 2008 96.94 24.459170
18 6 1 2009 61.74 21.332035
19 5 1 2010 79.61 17.119038
20 4 1 2011 111.26 16.941914
21 3 1 2012 111.63 19.964875
22 2 1 2013 108.56 28.863894
23 1 1 2014 99.03 15.182615
24 45 2 1993 17.01 NA
25 44 2 1994 15.86 NA
26 43 2 1995 17.02 NA
27 42 2 1996 20.64 NA
28 41 2 1997 19.11 NA
29 40 2 1998 12.76 NA
30 39 2 1999 17.90 11.428262
31 38 2 2000 28.66 20.232613
32 37 2 2001 24.46 25.811754
33 36 2 2002 24.99 18.959958
34 35 2 2003 28.85 20.767074
35 34 2 2004 38.26 29.260406
36 33 2 2005 54.57 25.837434
37 32 2 2006 65.16 32.675618
38 31 2 2007 72.44 48.415190
39 30 2 2008 96.94 42.444435
40 29 2 2009 61.74 40.047462
41 28 2 2010 79.61 49.090816
42 27 2 2011 111.26 53.828050
43 26 2 2012 111.63 61.684020
44 25 2 2013 108.56 68.394140
45 24 2 2014 99.03 55.738584
46 76 3 1984 NA NA
47 75 3 1985 NA NA
48 74 3 1986 NA NA
49 73 3 1987 18.53 NA
50 72 3 1988 14.91 NA
51 71 3 1989 18.23 NA
52 70 3 1990 23.76 17.046268
53 69 3 1991 20.04 30.191128
54 68 3 1992 19.32 30.414108
55 67 3 1993 17.01 27.916000
56 66 3 1994 15.86 26.437651
57 65 3 1995 17.02 25.895513
58 64 3 1996 20.64 26.791996
59 63 3 1997 19.11 30.074375
60 62 3 1998 12.76 42.636103
61 61 3 1999 17.90 46.862510
62 60 3 2000 28.66 30.154079
63 59 3 2001 24.46 30.297644
64 58 3 2002 24.99 34.851205
65 57 3 2003 28.85 38.854943
66 56 3 2004 38.26 37.542447
67 55 3 2005 54.57 38.456399
68 54 3 2006 65.16 43.465535
69 53 3 2007 72.44 41.749414
70 52 3 2008 96.94 48.371262
71 51 3 2009 61.74 54.914470
72 50 3 2010 79.61 65.444964
73 49 3 2011 111.26 76.888119
74 48 3 2012 111.63 81.833602
75 47 3 2013 108.56 83.800483
76 46 3 2014 99.03 79.713947
my codes are the following:
data <- plm.data(Autoregression,index=c("ID","Year"))
Panel <- subset(data, !is.na(I) )
Are <- pgmm( I~p+lag( I , 0:1)
| lag(I, 2:99),
data = Panel, effect = "twoways", model =
"onestep")
I have tried also many other versions, including every possible number of
the lags, shorter or longer.
The error is the following :
Errore in solve.default(crossprod(WX, t(crossprod(WX, A1)))) :
Lapack routine dgesv: system is exactly singular: U[3,3] = 0
Inoltre: Warning message:
In pgmm(I ~ lag(I, 1) + p | lag(I, 2:10), Panel, effect = "twoways",
:
the first-step matrix is singular, a general inverse is used
Can you please help me? Thanks for the attention, i'll wait for an answer
Regards, Luca.
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