Confidence intervals in econometric time series regressions suffer from notorious coveragenproblems. This is especially true when the dependence in the data is noticeable andnsample sizes are small to moderate, as is often the case in empirical studies. This papernsuggests using the studentized block bootstrap and discusses practical issues, such as thenchoice of the block size. A particular data-dependent method is proposed to automate the nmethod. As a side note, it is pointed out that symmetric confidence intervals are preferred over equal-tailed ones, since they exhibit improved coverage accuracy. The improvements in small sample performance are supported by a simulation study.