  We construct long-term prediction intervals for time-aggregated future values
of univariate economic time series. We propose computational adjustments of the
existing methods to improve coverage probability under a small sample
constraint. A pseudo-out-of-sample evaluation shows that our methods perform at
least as well as selected alternative methods based on model-implied Bayesian
approaches and bootstrapping. Our most successful method yields prediction
intervals for eight macroeconomic indicators over a horizon spanning several
decades.
