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Hi,

How do I test heteroskedasticity and distributional assumption of a probit model?

If I try to run the normality (heteroskedasticity) test in a probit model. However i get the error message: insufficient observations. But I have more than 15000 observations included in my regression. Is there another manner to test for normality?

What test did you use?

Histogram - Normality Test

I don't understand why it didn't run, unless you have a perfect fit. But this test doesn't have anything to do with heteroskedasticity and one doesn't expect the raw residuals from a Probit to be normal. After all, the LHS variable is discrete.

Sorry, I look like a bit stupid now, haha. To make myself more clear:

I need to test for heteroskedasticity if I want to use a binary> Probit model right?

However in the menu of probit, the White test is not displayed. So how do I test for heteroskedasticity?

(I thought the normality test would maybe display some more diagnostics, that's why I tried that as well)

You're asking perfectly reasonable questions! EViews doesn't have a built-in test, but if you look under Heteroskedasticity in the index of the Help system they show you how to do it.

Hey Startz, thanks a lot for showing me this feature in Eviews. I was looking up all the information in the userguides only.

I tried to take the steps, described in this help menu.

However: 'Next, the dependent variable in the test regression may be obtained as the standardized residual. Select Proc/Make Residual Series... and select Standardized Residual. We will save the series as BRMR_Y. '

This new serie only generates NA's in my case.

Later on,in the step: 'i]Then run the artificial regression by clicking on Quick/Estimate Equation..., selecting Least Squares, and entering:

brmr_y brmr_x (psi*(-xb)*fac)[/i]' I get an error message with 'unsufficient number of observations' and I think this has to do with the NA's of the BRMR_Y serie

So why do I get these NA values? How can I solve this problem?!

The NA's are probably the key, but I'm afraid I haven't the foggiest idea why you're getting them.

Hey Startz,

Does it make sense that the ordinary and generalized residual types do not give NA scores? These types work properly. ( Unfortenately I don't need those)

Do you have some more advice to find out how I got these NA scores?!

Thanks!

No idea at all

MMMM in that case I'm stuck!

Does anybody have any new insights?!

Hi there.
Could someone kindly help out this newby to eviews and econometrics please?
I want to estimate a probit model and test for heteroskedasticity of the form: σi2 = σ2z. My variables are y (a dummy variable as the dep vble), and educ and minority (another dummy variable). z = educ. I don't trust the results of the heteroskedasticity regressions I've run as the log-likehood stats are twice the amount of the normal probit model.

Appreciate any help.
Cheers

Sorry there the 2's in the form of heteroskedasticity in my previous post are squares (e.g. sigma squares).

Thanks