How do you read white heteroskedasticity?

Test for Heteroskedasticity with the White Test

1. Estimate your model using OLS:
2. Obtain the predicted Y values after estimating your model.
3. Estimate the model using OLS:
4. Retain the R-squared value from this regression:
5. Calculate the F-statistic or the chi-squared statistic:

Is White’s test an LM test?

Popular heteroscedasticity LM tests: – Breusch and Pagan (1979)’s LM test (BP). – White (1980)’s general test. Both tests are based on OLS residuals. The BP test is an LM test, based on the score of the log likelihood function, calculated under normality.

What is the null hypothesis of White test?

The null hypothesis for White’s test is that the variances for the errors are equal. In math terms, that’s: H0 = σ2i = σ2.

Is the White test a test of heteroskedasticity?

If no cross product terms are introduced in the White test procedure, then this is a test of pure heteroskedasticity. If cross products are introduced in the model, then it is a test of both heteroskedasticity and specification bias.

Is there white’s test for heteroscadicity in R-Cross?

According to the author of the package, it is meant to do the same test as is done in Eviews. My model looks like A~B+C. Kindly guide me what I am doing wrong. I 1st run ols for equation A~B+C, after getting results, I clicked View>Residual diagnostics>Heteroscadicity tests>White’s (with Include white cross terms) and then Press ok.

When to use homoskedasticity vs.heteroskedasticity?

Heteroskedasticity vs. Homoskedasticity When analyzing regression results, it’s important to ensure that the residuals have a constant variance. When the residuals are observed to have unequal variance, it indicates the presence of heteroskedasticity. However, when the residuals have constant variance, it is known as homoskedasticity.

Is the White test a test of specification error?

In other words, the White test can be a test of heteroskedasticity or specification error or both. If no cross product terms are introduced in the White test procedure, then this is a test of pure heteroskedasticity.