I think so, too.
In this example the computed variance for the baths
coefficient is 2.15e-13, which seems on the big side to be
forced to zero. I think the only way to get this "right" would
be to somehow keep track of which coefficients, if any, are
assigned a definite numerical value by the restriction -- i.e.
look for rows of the R matrix that have only one non-zero
Gretl-devel mailing list
Yes, I think so, too since the std errors (and coefficients) can always be
changed by an arbitrary amount by rescaling y or x or both.
Professor of Economics