Hello,
I used below regression formula with Binary probit method to find out interaction:
y c contribution @expand(x2,@dropfirst) @expand(x3,@dropfirst) @expand(x2,x3,@dropfirst)
X2= female, male,
X3= democratic, republican
X4= challenger, incumbent, open.
y= winning probability (binary dependent)
But the result of the regression comes out with multicollinearity. Std err, P value all become NA. It shows below:
Failure to improve likelihood (singular hessian) after 7 iterations
Coefficient covariance computed using observed Hessian
WARNING: Singular covariance  coefficients are not unique
I need to find interaction result along with keeping the variables separately in the regression. It means main effect and interaction effect both. Would you help me please?
Interaction between dummy variables
Moderators: EViews Gareth, EViews Moderator

 Nonnormality and collinearity are NOT problems!
 Posts: 3715
 Joined: Wed Sep 17, 2008 2:25 pm
Re: Interaction between dummy variables
There are a number of possibilities. One is that you need to try different starting values. As a useful diagnostic you might try running the same equation by least squares and see what happens.

 Posts: 5
 Joined: Wed Oct 27, 2021 7:19 pm
Re: Interaction between dummy variables
But least square shows 'near singular matrix'. I have found result when I did below:
y c contribution @expand(x2,@dropfirst) @expand(x3,@dropfirst)
or
y c contribution @expand(x2,x3,@dropfirst)
But when I tried y c contribution @expand(x2,@dropfirst) @expand(x3,@dropfirst) @expand(x2,x3,@dropfirst), it showed multicollinearity. I need to know  doesn't EViews show main effect and interaction effect together in case of dummy variables?
y c contribution @expand(x2,@dropfirst) @expand(x3,@dropfirst)
or
y c contribution @expand(x2,x3,@dropfirst)
But when I tried y c contribution @expand(x2,@dropfirst) @expand(x3,@dropfirst) @expand(x2,x3,@dropfirst), it showed multicollinearity. I need to know  doesn't EViews show main effect and interaction effect together in case of dummy variables?

 Nonnormality and collinearity are NOT problems!
 Posts: 3715
 Joined: Wed Sep 17, 2008 2:25 pm
Re: Interaction between dummy variables
This means you really do have perfect multicollinearity. You might want to post your EViews workfile (including the command you used) to see if anyone can spot what's going on.

 Posts: 5
 Joined: Wed Oct 27, 2021 7:19 pm
Re: Interaction between dummy variables
Workfile is here.
I tried with different different options of commands, but got the error as I mentioned below. Please have a look:
y_it c log_contribution @expand(x2,@dropfirst) @expand(x3,@dropfirst) @expand(x2,x3,@dropfirst) .
with LS, I found: near singular matrix
with Binary probit, I found: multicollinearity
y_it c log_contribution @expand(x2,@dropfirst) @expand(x3,@dropfirst) @expand(x2*x3, @dropfirst)
Both with LS and Binary probit, I found Numeric operator applied to string data in "X2*X3".
y_it c log_contribution gender party gender*party
Both with LS and Binary probit, I found: No index provided for group
y_it c log_contribution gender party ineraction1
with LS, I found: near singular matrix
with Binary probit, I found:Objective function evaluates to NA for one or more observations
I tried with different different options of commands, but got the error as I mentioned below. Please have a look:
y_it c log_contribution @expand(x2,@dropfirst) @expand(x3,@dropfirst) @expand(x2,x3,@dropfirst) .
with LS, I found: near singular matrix
with Binary probit, I found: multicollinearity
y_it c log_contribution @expand(x2,@dropfirst) @expand(x3,@dropfirst) @expand(x2*x3, @dropfirst)
Both with LS and Binary probit, I found Numeric operator applied to string data in "X2*X3".
y_it c log_contribution gender party gender*party
Both with LS and Binary probit, I found: No index provided for group
y_it c log_contribution gender party ineraction1
with LS, I found: near singular matrix
with Binary probit, I found:Objective function evaluates to NA for one or more observations
 Attachments

 data_rubayat_22.10.21.wf1
 (693.13 KiB) Downloaded 16 times

 Nonnormality and collinearity are NOT problems!
 Posts: 3715
 Joined: Wed Sep 17, 2008 2:25 pm
Re: Interaction between dummy variables
I think I know what's going on.
X2 is male or female and X3 is democrat or republican. So there are four possibilities. @expand(x2,x3,@dropfirst) plus a constant covers all four. The noninteracted dummies really are redundant. Hence, the perfect multicollinearity.
X2 is male or female and X3 is democrat or republican. So there are four possibilities. @expand(x2,x3,@dropfirst) plus a constant covers all four. The noninteracted dummies really are redundant. Hence, the perfect multicollinearity.

 Posts: 5
 Joined: Wed Oct 27, 2021 7:19 pm
Re: Interaction between dummy variables
But, if I do not put noninteracted dummies in the regression, I won't get the main effect of the variables. Please let me know doesn't EViews show main effect and interaction effect together in case of dummy variables?

 Nonnormality and collinearity are NOT problems!
 Posts: 3715
 Joined: Wed Sep 17, 2008 2:25 pm
Re: Interaction between dummy variables
This has nothing to do with EViews.
I'm not sure what you mean by main effect, separately from the interacted terms.
I'm not sure what you mean by main effect, separately from the interacted terms.

 Posts: 5
 Joined: Wed Oct 27, 2021 7:19 pm
Re: Interaction between dummy variables
Yes, main effect is separate from the interacted terms. Thanks for your time and effort.

 Nonnormality and collinearity are NOT problems!
 Posts: 3715
 Joined: Wed Sep 17, 2008 2:25 pm
Re: Interaction between dummy variables
If I understand your data, there are four cells. The interacted coefficients cover all four. There is nothing further to estimate. EViews is notifying you of a mistake.
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