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Hello,

I want to estimate a Probit-Modell but I found out, that 2 of my explanatory variables are correlated by 85%.
Those two explanatory variables are:

Dummy1
X1*Dummy1

Does this mean, that I must leave one of them out, or is there any other way?


Thank you very much!

I do have an additional question.

I wanted to test several dummy variables and interaction dummies apon their correlation. In the correlation matrix I found out, that there exist high correlations in the following cases:


Dummy1*X1 with Dummy1*X2
Dummy1*X1 with Dummy1*X3
Dummy1*X2 with Dummy1*X3

Dummy2*X1 with Dummy2*X2
Dummy2*X1 with Dummy2*X3
Dummy2*X2 with Dummy2*X3

Is it possible, that a correlation matrix does not work when using dummy variables???

Just run the probit. Multicollinearity correction is built in.

Thank you very much!

Do you know if it is usual to have the dummy variable and the interaction dummy in the same regression model ?
For exampel if I have the following explanatory variables:

X1
X2
X3
D1
D2
X1*D1
X2*D1

Or is it usual to leavy D1 and D2 as singel explanatory variables out?

Thank you very much!

Do you know if it is usual to have the dummy variable and the interaction dummy in the same regression model ?
...
Or is it usual to leavy D1 and D2 as singel explanatory variables out?

If you have the interaction, you almost always include the dummy as well.

Ok that helps!

But now I do have the case, where I left all of my original explanatory variables in and only added my interactions. Eviews can't run the regression and gives me the Error Message: "Triangular matrix too small or source Matrix asymmetric". If I leave the dummy coefficients out and only include the intercations, eviews is able to run the regression.
I don't understand the meaning of this error message. Why does the message disappera, when I exclude my dummies?
This message did not appear as I performed THE SAME Regression just on a different dependent variable.

You should check whether the different dependent variables have different sets of valid observations. Past that, you might want to post your EViews workfile and the exact commands you enter.

You should check whether the different dependent variables have different sets of valid observations.

What do you mean by different sets of valid obervations?

EViews drops NAs. One dependent variable might have different non-missing observations.

I am sorry that I can't upload my workfiles, but they are simply to huge!

I made sure, that no obeservation is missing! But I figured out that my one dummy variable is only represented twice among over 400 other observations. Can this be the problem? But if it is, I wondern why eviews is able to run the regression if I merely include the dummy OR die interaction, but can't run the regression if I include them both,

I do have a compeltely other question..
Is a coefficient of -3.18E-10 with a highly significant p-value worth mentioning? I am not sure beacuse the coefficient is so small, but on the other hand this coefficient does not represent a marginal effect...

This depends entirely on the units of measurement of the dependent and independent variables.

the dependet variable is a dummy and the explanatory variable is measured in Million Euro

Then the coefficient is probably too small to matter. Having said that, it's odd to get a significant coefficient that's so small. It's possible you have something else wrong with your model.

Can this be the case if a sample selecion bias occured? Because I do estimate an inverse Mill-Ratio of -0.09 at a 10% significance level