Can robust standard errors also account for autocorrelation in time series data?

Yes, robust standard errors can be extended to account for autocorrelation, especially in time series or panel data contexts. This is achieved through Heteroskedasticity and Autocorrelation Consistent (HAC) standard errors, such as Newey-West standard errors. HAC estimators not only adjust for heteroskedasticity but also for serial correlation (autocorrelation) in the error terms over time. This is crucial for valid inference when errors are correlated across observations, which is common in time series models where the error at one point in time might be correlated with errors at previous time points.