EDIT: for reference here are my data:

              s01           s02        s03         s04
01/01/1999  3.00E+10    121.8628    1.94E+12    1.457384
01/04/1999  3.01E+10    126.09073   1.95E+12    1.520934
01/07/1999  3.13E+10    125.06515   1.97E+12    1.527138
01/10/1999  3.21E+10    126.99142   2.00E+12    1.571251
01/01/2000  3.27E+10    126.9887    2.02E+12    1.628555
01/04/2000  3.35E+10    124.37588   2.04E+12    1.639844
01/07/2000  3.44E+10    119.11178   2.05E+12    1.633594
01/10/2000  3.49E+10    113.61613   2.06E+12    1.667029
01/01/2001  3.53E+10    106.50717   2.13E+12    1.581423
01/04/2001  3.57E+10    102.98313   2.13E+12    1.628003
01/07/2001  3.58E+10    87.99769    2.13E+12    1.615208
01/10/2001  3.64E+10    81.14929    2.14E+12    1.611063
01/01/2002  3.74E+10    87.58887    2.14E+12    1.626313
01/04/2002  3.76E+10    91.04958    2.15E+12    1.592302
01/07/2002  3.85E+10    73.95882    2.16E+12    1.574734
01/10/2002  3.88E+10    65.37162    2.16E+12    1.571639
01/01/2003  3.83E+10    63.21862    2.16E+12    1.493654
01/04/2003  3.85E+10    66.92185    2.16E+12    1.425593
01/07/2003  3.91E+10    63.98062    2.17E+12    1.430009
01/10/2003  4.12E+10    75.31742    2.18E+12    1.433381
01/01/2004  4.11E+10    86.14754    2.20E+12    1.470845
01/04/2004  4.19E+10    90.64507    2.21E+12    1.499202
01/07/2004  4.19E+10    95.21745    2.21E+12    1.487668
01/10/2004  4.28E+10    98.69023    2.22E+12    1.438778
01/01/2005  4.34E+10    103.51991   2.23E+12    1.442369
01/04/2005  4.43E+10    98.09163    2.24E+12    1.474367
01/07/2005  4.45E+10    89.34391    2.26E+12    1.463475
01/10/2005  4.57E+10    92.3905     2.27E+12    1.470589
01/01/2006  4.61E+10    100.46526   2.29E+12    1.456973
01/04/2006  4.64E+10    93.49614    2.31E+12    1.454008
01/07/2006  4.75E+10    87.41035    2.33E+12    1.471341
01/10/2006  4.76E+10    88.11269    2.35E+12    1.485422
01/01/2007  4.98E+10    85.51956    2.38E+12    1.491547
01/04/2007  4.92E+10    83.95523    2.39E+12    1.473238
01/07/2007  4.81E+10    73.64344    2.40E+12    1.470523
01/10/2007  5.02E+10    65.87211    2.42E+12    1.412875
01/01/2008  4.87E+10    64.58933    2.44E+12    1.321165
01/04/2008  4.77E+10    49.00284    2.43E+12    1.261533
01/07/2008  4.75E+10    42.66211    2.41E+12    1.258634
01/10/2008  4.57E+10    45.64976    2.37E+12    1.195684
01/01/2009  4.55E+10    45.97453    2.32E+12    1.101032
01/04/2009  4.55E+10    48.54799    2.31E+12    1.13892
01/07/2009  4.49E+10    49.28164    2.32E+12    1.147522
01/10/2009  4.49E+10    53.70312    2.33E+12    1.105827
01/01/2010  4.55E+10    61.94103    2.34E+12    1.126911
01/04/2010  4.59E+10    66.2847     2.37E+12    1.174664
01/07/2010  4.63E+10    60.00519    2.38E+12    1.19952
01/10/2010  4.63E+10    46.94403    2.39E+12    1.16393
01/01/2011  4.73E+10    52.82631    2.41E+12    1.171049
01/04/2011  4.75E+10    57.85739    2.41E+12    1.132937
01/07/2011  4.73E+10    55          2.41E+12    1.140152
01/10/2011  4.73E+10    57.66075    2.40E+12    1.166011
01/01/2012  4.72E+10    58.06121    2.40E+12    1.19852
01/04/2012  4.76E+10    61.93385    2.39E+12    1.234437
01/07/2012  4.70E+10    65.9692     2.39E+12    1.263261
01/10/2012  4.76E+10    58.12565    2.38E+12    1.23845
01/01/2013  4.68E+10    61.19564    2.37E+12    1.175077
01/04/2013  4.77E+10    63.54526    2.38E+12    1.175606
01/07/2013  4.92E+10    69.36935    2.39E+12    1.17076
01/10/2013  4.88E+10    75.67541    2.40E+12    1.189011
01/01/2014  5.06E+10    84.37443    2.41E+12    1.207956
01/04/2014  5.20E+10    82.55904    2.41E+12    1.22783
01/07/2014  5.26E+10    89.75978    2.42E+12    1.259912
01/10/2014  5.33E+10    87.11057    2.43E+12    1.267081
01/01/2015  6.47E+10    98.34575    2.46E+12    1.346294
01/04/2015  6.34E+10    100.01053   2.47E+12    1.386315
01/07/2015  6.67E+10    100.4896    2.48E+12    1.393723
01/10/2015  6.69E+10    102.76665   2.49E+12    1.386148
01/01/2016  6.65E+10    104.98214   2.50E+12    1.298074
01/04/2016  6.69E+10    101.38637   2.51E+12    1.270157
01/07/2016  6.88E+10    101.43875   2.52E+12    1.176277
01/10/2016  7.28E+10    97.10191    2.54E+12    1.151544
01/01/2017  7.09E+10    101.9       2.55E+12    1.162719

I am trying to model some data for a VECM in R. I have confirmed that all the variables are I(1), and I have 73 observations for each variable. My understanding is that to check for cointegration, you run a line like this on the levels data:

jo.eigen <- ca.jo(data, type = "eigen", ecdet = "const", K = 2)

However, I get an error back:

Error in solve.default(M11) : 
  system is computationally singular: reciprocal condition number = 3.8303e-22

I'm not entirely sure where to go from here. Is this happening because some of my coefficients are highly correlated? The correlation matrix is:

            gdp        emp         csi        eur
gdp  1.00000000  0.6576867 -0.09380039 -0.3140209
emp  0.65768675  1.0000000 -0.36025862 -0.5978277
csi -0.09380039 -0.3602586  1.00000000  0.6251111
eur -0.31402088 -0.5978277  0.62511111  1.0000000

Running a VAR in differences doesn't seem like the correct way forward as I have a gut feeling these variables are cointegrated. However, I can't move forward with VECM unless I have a ca.jo object.

Does anyone have any recommendations about how to move forward?

I am trying to model some data for a VECM in R. I have confirmed that all the variables are I(1), and I have 73 observations for each variable. My understanding is that to check for cointegration, you run a line like this on the levels data:

jo.eigen <- ca.jo(data, type = "eigen", ecdet = "const", K = 2)

However, I get an error back:

Error in solve.default(M11) : 
  system is computationally singular: reciprocal condition number = 3.8303e-22

I'm not entirely sure where to go from here. Is this happening because some of my coefficients are highly correlated? The correlation matrix is:

            gdp        emp         csi        eur
gdp  1.00000000  0.6576867 -0.09380039 -0.3140209
emp  0.65768675  1.0000000 -0.36025862 -0.5978277
csi -0.09380039 -0.3602586  1.00000000  0.6251111
eur -0.31402088 -0.5978277  0.62511111  1.0000000

Running a VAR in differences doesn't seem like the correct way forward as I have a gut feeling these variables are cointegrated. However, I can't move forward with VECM unless I have a ca.jo object.

Does anyone have any recommendations about how to move forward?