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I am using the command ivreg from the AER package. My data looks like this:

head(d0)

       y           x0       x1      x2       x3     x4        x5
1   0.005157174 18422880    0   four stars  GA  0.02857143  37963
2   0.005157174 18422880    0   four stars  GA  0.02857143  37963
3   0.008145795 18422880    0   two stars   GA  0.00993997  37963
4   0.004613947 22938495    0   four stars  GA  0.02857143  37963
5   0.005157174 18422880    0   four stars  GA  0.02857143  37963
6   0.008145795 18422880    0   three stars GA  0.00993997  37963

My x0 variable is endogenous, so I would like to run the following regression, instrumenting x0 with x5 :

 mod_iv <- ivreg(y~x0+x1+x2+x3|x5+x1+x2+x3,data=d0)

The command above runs well. However, when I type summary(mod_iv). I get the error message

Error in solve.default(vcov.hyp) : 
  system is computationally singular: reciprocal condition number = 9.79783e-23

It seems like this is common, as I found in this post. The interesting part is that it seems like the problem really is originated by x0. For instance, theis regression below does run correctly inside summary:

 mod_iv <- ivreg(y~x4+x1+x2+x3|x5+x1+x2+x3,data=d0)
 summary(mod_iv)

Do you know what could be causing this error?

  • see [here](https://stackoverflow.com/questions/61068583/system-is-computationally-singular-error-from-linearhypothesis-but-the-matrix-ha) – paqmo Jun 01 '22 at 01:01

0 Answers0