Article ID: | iaor201112534 |
Volume: | 30 |
Issue: | 8 |
Start Page Number: | 721 |
End Page Number: | 735 |
Publication Date: | Dec 2011 |
Journal: | Journal of Forecasting |
Authors: | Staszewska-Bystrova Anna |
Keywords: | literature survey, Statistics: bootstrap, autoregressive process |
The problem of forecasting from vector autoregressive models has attracted considerable attention in the literature. The most popular non-Bayesian approaches use either asymptotic approximations or bootstrapping to evaluate the uncertainty associated with the forecast. The practice in the empirical literature has been to assess the uncertainty of multi-step forecasts by connecting the intervals constructed for individual forecast periods. This paper proposes a bootstrap method of constructing prediction bands for forecast paths. The bands are constructed from forecast paths obtained in bootstrap replications using an optimization procedure to find the envelope of the most concentrated paths. From extensive Monte Carlo study, it is found that the proposed method provides more accurate assessment of predictive uncertainty from the vector autoregressive model than its competitors.