If a model is estimated using the following code:
1. bptest(p) does the Breuch Pagan test to formally check presence of heteroscedasticity. To use bptest, you will have to call lmtest library.
2. If the test is positive (low p value), you should see if any transformation of the dependent variable helps you eliminate heteroscedasticity. Also check if the right hand side of the model is okay.
3. If 2 does not work, you can use the white’s heteroscedasticity-corrected covariance matrices to make inference. Package car has a function hccm that gives you the heteroscedasticity-corrected covariance matrix (there is a similar function in package sandwich also). coeftest(p,vcov=hccm(p)) will give you the results of the tests using this matrix. Use these results instead of summary(p).