What is Breusch-Pagan test in Stata?

Breusch-Pagan test helps to check the null hypothesis versus the alternative hypothesis. A null hypothesis is that where the error variances are all equal (homoscedasticity), whereas the alternative hypothesis states that the error variances are a multiplicative function of one or more variables (heteroscedasticity).

How do you do a Breusch-Pagan test?

We use the following steps to perform a Breusch-Pagan test:

1. Fit the regression model.
2. Calculate the squared residuals of the model.
3. Fit a new regression model, using the squared residuals as the response values.
4. Calculate the Chi-Square test statistic X2 as n*R2new where:

How do you test for heteroskedasticity in Stata?

Figure 5: Testing for Heteroscedasticity Using the Postestimation Selector Dialog Box in Stata. Click on “Tests for heteroskedasticity” and press Launch to produce a second dialog box, “estat – Postestimation statistics for regress.” In the box at the top,”Tests for heteroskedasticity (hettest)” should be highlighted.

How do you interpret a breusch-Pagan p value?

It is a chi-squared test: the test statistic is distributed nχ2 with k degrees of freedom. If the test statistic has a p-value below an appropriate threshold (e.g. p < 0.05) then the null hypothesis of homoskedasticity is rejected and heteroskedasticity assumed.

Is Heteroscedasticity good or bad?

Heteroskedasticity has serious consequences for the OLS estimator. Although the OLS estimator remains unbiased, the estimated SE is wrong. Because of this, confidence intervals and hypotheses tests cannot be relied on. Heteroskedasticity can best be understood visually.

What is the difference between breusch Pagan and white test?

The null hypothesis for White’s test is that the variances for the errors are equal. The only different between White’s test and the Breusch-Pagan is that its auxiliary regression doesn’t include cross-terms or the original squared variables. Other than that, the steps are exactly the same.

What is the null hypothesis for the breusch Pagan test?

The null hypothesis for this test is that the error variances are all equal. The alternate hypothesis is that the error variances are not equal. More specifically, as Y increases, the variances increase (or decrease).

What does P value 2.2e 16 mean?

< 2.2e-16 as the p value would indicate a significant result, meaning that the actual p value is even smaller than 2.2e-16 (a typical threshold is 0.05, anything smaller counts as statistically significant).

How much heteroscedasticity is acceptable?

In general, a rule of thumb is that you are OK as long as the largest variance is not more than four times the lowest variance. This is a rule of thumb, so that should be taken for what it’s worth.

What is the problem with heteroscedasticity?

Specifically, heteroscedasticity is a systematic change in the spread of the residuals over the range of measured values. Heteroscedasticity is a problem because ordinary least squares (OLS) regression assumes that all residuals are drawn from a population that has a constant variance (homoscedasticity).

What is the problem with heteroskedasticity?

Heteroskedasticity has serious consequences for the OLS estimator. Although the OLS estimator remains unbiased, the estimated SE is wrong. Because of this, confidence intervals and hypotheses tests cannot be relied on. In addition, the OLS estimator is no longer BLUE.

How to calculate the Breusch Pagan test for heteroskedasticity?

Stata Tutorial: Breusch-Pagan Test for Heteroskedasticity – YouTube Using the ‘hettest’ command in Stata, how to calculate and interpret the Breusch-Pagan F-statistic and Chi-square test statistics.Link to tutorial on White t…

How to perform a Breusch Pagan test in Stata-statology?

This tutorial explains how to perform a Breusch-Pagan Test in Stata. We will use the built-in Stata dataset auto to illustrate how to perform the Breusch-Pagan Test. Step 1: Load and view the data. Step 2: Perform multiple linear regression.

What is the meaning of heteroscedasticity test in Stata?

This article focuses on another important diagnostic test, i.e. heteroscedasticity test in STATA. Heteroskedastic means “differing variance” which comes from the Greek word “hetero” (‘different’) and “skedasis” (‘dispersion’). It refers to the variance of the error terms in a regression model in an independent variable.

How to perform a white test for heteroscedasticity?

White test for heteroscedasticity. To check heteroscedasticity using White test, use the following command in STATA: estat imtest, white. The below results will appear. Figure 3: Results from the White test using STATA. Similar to the results of the Breusch-Pagan test, here too prob > chi2 = 0.000.