Bootstrap Joint Prediction Regions
University of Zurich Department of Economics Working Paper No. 64
40 Pages Posted: 1 Mar 2012 Last revised: 8 May 2013
Date Written: May 2013
Abstract
Many statistical applications require the forecast of a random variable of interest over several periods into the future. The sequence of individual forecasts, one period at a time, is called a path forecast, where the term path refers to the sequence of individual future realizations of the random variable. The problem of constructing a corresponding joint prediction region has been rather neglected in the literature so far: such a region is supposed to contain the entire future path with a prespecified probability. We develop bootstrap methods to construct joint prediction regions. The resulting regions are proven to be asymptotically consistent under a mild high-level assumption. We compare the finitesample performance of our joint prediction regions to some previous proposals via Monte Carlo simulations. An empirical application to a real data set is also provided.
Keywords: Generalized error rates, path forecast, simultaneous prediction intervals
JEL Classification: C14, C32, C53
Suggested Citation: Suggested Citation
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