When is it crucial to use robust standard errors versus OLS standard errors?

It is crucial to use robust standard errors when you suspect or detect heteroskedasticity in your data. Formal tests like the Breusch-Pagan test or White's test can help detect heteroskedasticity. Even if the tests are borderline, using robust standard errors is generally a good practice, as they are consistent regardless of whether heteroskedasticity is present.