This is actually more like a Statistics problem: I have a dataset with two dummy variables controlling three levels. The problem is, one level does not have many observations compared with other two levels (a couple of data points compared with 1000+ points on other levels). When I run the regression, the result is bad. I have unbalanced SE and VIF. Does this kind of problem also belong to "near sigularity" problem? Does it make any difference if I code the level that lacks data (0,0) in stead of (0,1)?
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