The Park Test is a test for heteroscedasticity. Heteroscedasticity means that the variances of the errors are not the same across a set of independent (predictor) variables. Use the Park test for heteroscedasticity if you have some variable Z that you think might explain the different variances of the residuals.May 24, 2016
What is Heteroskedasticity test?
White's Test for Heteroscedasticity is a more robust test that tests whether all the variances are equal across your data if it is not normally distributed. ... It still determines whether the variance are all equal across the data; however, the test is very general and can sometimes give false negatives.May 7, 2018
How do you do a white test?
- Estimate your model using OLS:
- Obtain the predicted Y values after estimating your model.
- Estimate the model using OLS:
- Retain the R-squared value from this regression:
- Calculate the F-statistic or the chi-squared statistic:
How do you do the Goldfeld Quandt test?
- Order the data in ascending order. ...
- Divide your data into three parts*.
- Drop the observations in the middle part.
- Run separate regression analysis on the top and bottom parts (in other words, the groups with high values of x and low values of x).
What does a Chow test do?
The Chow test tells you if the regression coefficients are different for split data sets. Basically, it tests whether one regression line or two separate regression lines best fit a split set of data.Oct 11, 2016