I am trying to run the following two regressions to compare the coefficients on the 'iso_str' dummies. The only difference between the two is that the second one includes the variable 'shr',

1.
Code:
reg lncost ib6.iso_str i.var_str, eform(exp_coeff) baselevels
2.
Code:
reg lncost ib6.iso_str shr i.var_str, eform(exp_coeff) baselevels
When I run regression (2) above, Stata omits the 'shr' variable because of collinearity.

Then, I tried an alternative formulation of the above two regressions to see if this way I could compare their coefficients. Again, the only difference is the inclusion of the variable 'shr' in the second regression.

3.
Code:
reg lncost ib6.iso_str ibn.var_str, noconstant eform(exp_coeff) baselevels
4.
Code:
reg lncost ib6.iso_str shr ibn.var_str, noconstant eform(exp_coeff) baselevels
Notice that the outputted coefficients for the 'iso_str' dummies in (3) are identical to those in (4). However, I still can't compare 3 vs.4, as this time Stata doesn't omit the 'shr' variable in reg 4, but it omits one of the 'var_str' dummies in 4 (again, because of collinearity)..even though I used the 'ibn' command so that none would be dropped!

How can I compare the 'iso_str' coefficients outputted by these two regressions, with and without the variable 'shr'? Perhaps there is a way around the collinearity issue I am facing, e.g. rearranging my data differently?

Thank you. An excerpt of my data is below.


Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input str3 iso str5 var double(cost shr) long(iso_str var_str) float lncost
"CIV" "x1105" 11458.3333333333             49.674 1 1  9.346473
"COD" "x1105" 44083.2888217523              56.12 2 1 10.693836
"MRT" "x1105"              540             47.176 3 1  6.291569
"NGA" "x1105" 16842.1052631579             50.481 4 1  9.731637
"TGO" "x1105" 5590.76923076923             58.838 5 1  8.628872
"TZA" "x1105"            48000             66.947 6 1 10.778956
"ZAF" "x1105" 904.655301204819 34.150000000000006 7 1  6.807554
"CIV" "x1106" 10441.1764705882             49.674 1 2  9.253512
"COD" "x1106" 39391.0340285401              56.12 2 2 10.581293
"MRT" "x1106"              520             47.176 3 2  6.253829
"NGA" "x1106" 11834.3195266272             50.481 4 2  9.378759
"TGO" "x1106"  4398.8603988604             58.838 5 2  8.389101
"TZA" "x1106"            45000             66.947 6 2 10.714417
"ZAF" "x1106"  608.84493902439 34.150000000000006 7 2  6.411563
"CIV" "x1107" 12032.0855614973             49.674 1 3  9.395332
"MRT" "x1107" 463.636363636364             47.176 3 3  6.139101
"NGA" "x1107" 17391.3043478261             50.481 4 3  9.763725
"TGO" "x1107" 5015.38461538462             58.838 5 3  8.520266
"TZA" "x1107" 43636.3636363636             66.947 6 3 10.683646
"ZAF" "x1107"          984.375 34.150000000000006 7 3  6.892007
end
label values iso_str iso_str
label def iso_str 1 "CIV", modify
label def iso_str 2 "COD", modify
label def iso_str 3 "MRT", modify
label def iso_str 4 "NGA", modify
label def iso_str 5 "TGO", modify
label def iso_str 6 "TZA", modify
label def iso_str 7 "ZAF", modify
label values var_str var_str
label def var_str 1 "x1105", modify
label def var_str 2 "x1106", modify
label def var_str 3 "x1107", modify